WO2017039521A1

WO2017039521A1 - Systems and methods for performing node deployment in an enclosure

Info

Publication number: WO2017039521A1
Application number: PCT/SE2016/050824
Authority: WO
Inventors: Gunther Auer
Original assignee: Telefonaktiebolaget Lm Ericsson (Publ)
Priority date: 2015-09-04
Filing date: 2016-09-01
Publication date: 2017-03-09

Abstract

Systems and methods for performing node deployment are provided. In one exemplary embodiment, a computer-implemented method of determining where in an enclosure to place individual radio nodes for collectively providing radio coverage in the enclosure may include, for each of multiple candidate locations in the enclosure, obtaining (503) an interference metric reflecting an extent of interference at that location. Also, the method may include determining (505) to tentatively place an initial radio node at one of the candidate locations. Further, for each of one or more iterations, the method may include identifying (511) which one of obtained enclosure- wide coverage metrics for each of the multiple candidate locations in the enclosure reflects the greatest extent of radio coverage that would be collectively provided across the enclosure and determining (515) whether to tentatively place the additional radio node at the candidate location for which the identified enclosure-wide coverage metric was obtained.

Description

SYSTEMS AND METHODS FOR PERFORMING NODE DEPLOYMENT IN AN

ENCLOSURE

RELATED APPLICATIONS

This application claims priority to U.S. Provisional Patent Application Serial No. 62/214905, filed September 4, 2015, which is hereby incorporated in its entirety as if fully set forth herein.

FIELD OF DISCLOSURE

The present disclosure relates generally to the field of communications, and more specifically to performing node deployment in an enclosure.

BACKGROUND

Small cells are low-powered radio access nodes that operate in licensed and unlicensed spectrum. They are smaller compared to high-powered radio access nodes (i.e., macro cell), which may have a transmission range of a few tens of kilometers. With mobile operators struggling to support the growth in mobile data traffic, small cells are a vital element to 3G and LTE data offloading, and many mobile network operators see small cells as vital to managing LTE Advanced (LTE-A) spectrum more efficiently, compared to only using macro cells.

In indoor environments with poor macro coverage or high capacity demand (e.g., enterprise customers, busy public indoor locations, or the like), dedicated indoor base stations need to be deployed. These indoor small cells will provide coverage, boost capacity and offload the existing macro network. This leads to small cells in congested hot spot areas, such as enterprise buildings, train stations, airports, shopping malls, stadiums, exhibition centers, and the like.

Different variants of indoor small cells exist. Femto and pico base stations create small cells where each transmit and receive point constitutes its own cell. Femto and pico base stations may also be referred to as standalone small cells. Cells with multiple distributed transmission points (TPs) and receiving points (RPs) have been used to cover signal dead spots or to increase system capacity. They are useful in indoor environments with complex floor plans (i.e., inner walls, elevator shafts, or the like), which will cause many signal dead spots (i.e., coverage holes). The signal processing of the small cells is typically carried out at a central unit (CU), which includes signal generation on the downlink as well as signal combining and detection on the uplink. One cell is composed of N_n0de radio nodes, and one CU may serve up to N_ceii cells. An example of one such small cell having four radio nodes 101-104, with each radio node 101-104 containing one TP and/or one RP is shown in FIG. 1. Further, the received signals such as from a wireless device 107 (i.e., UE) are combined at a CU 105.

FIG. 2 illustrates a building 200 of indoor small cells with one digital unit (DU) 203 connected to four indoor radio units (IRUs) 205-208 on a floor 201 of the building 200, with each IRU 205-208 having one common public radio interface (CPRI) link 209-212 and serving four radio nodes (e.g., radio dots) 213-216 using LAN cables 217 in a star topology. Ericsson's Radio Dot System (RDS) is based on a similar architecture shown in FIG. 2, where radio nodes are called radio dots and the combining of the signals received at distributed regional processors (RPs) is performed in the IRU. For a distributed antenna system (DAS), a base station performs the signal generation including baseband and RF. The RF signal is then distributed to the TPs and RPs using a coaxial cable.

For the floor 201 of the building 200, a downlink baseband signal is generated in the DU 203. The downlink signal is sent to the IRU 205 over a CPRI link 209. At the IRU 205, the downlink signal is transformed to an analog waveform and sent to the radio nodes 213-216 over the LAN cables 217. At the radio nodes 213-216, the downlink signal is radiated over the wireless channel to a wireless device (e.g., UEs) typically located on the floor 201 . For the same floor 201 , an uplink signal transmitted from a wireless device typically located on the floor 201 will be received by all radio nodes (e.g., radio points (RPs)) 213-216 with all received uplink signal being sent via the LAN cables 217 to the IRU 205 for further processing. The IRU 205 will receive all of the received uplink signals, combine them into a combined uplink signal, digitize the combined uplink signal, and send the digitized combined uplink signal to the DU 203 for baseband processing such as demodulation, detection, channel estimation, decoding, etc.

One DU typically contains multiple baseband processors (BBPs), and is capable of supporting multiple IRUs. For the example in FIG. 2, one DU contains four BBPs, and serves four IRUs, and each IRU serves four dots.

Mobile devices are served by one cell of a base station. In order to associate mobile devices to their serving base station a cell selection procedure is carried out. Moreover, to support mobility the cell selection needs to be continuously updated to support hand-overs to other cells. Cell selection is mobile communication standard specific, but the fundamental principles are common to all 3GPP based mobile communication standards, such as LTE and WCDMA.

To facilitate cell selection, the base stations emit a known reference signal with fixed power. The mobile device measures the strength of the reference signal and reports back to the base station. Initially, the mobile device is assigned to the base station with the strongest reference signal. To facilitate handover from one cell to another, reference signal measurements are periodically updated. If the reference signal from a candidate cell exceeds that of the serving cell by x dB, where x is referred to as the handover margin, a handover procedure is triggered.

In LTE, a downlink subframe contains common reference symbols (CRS), which are known to the receiver and used as a reference signal for cell selection. In particular, the mobile device measures the reference signal received power (RSRP), which is the received signal strength of one LTE subcarrier, defined as:

RSRP = 30- PZ.+ 10 log₁₀ -^- Equation (1 )

^sc

where RSRP is in dBm, PL denotes the pathloss in decibels (dB), P denotes the base station transmit power in Watts, and N_sc accounts for the number of subcarriers. For WCDMA, the reference signal measured at the mobile is referred to reference signal code power (RSCP).

In order to ensure that indoor users are served by the in-building system, a dominance requirement is typically imposed. Dominance is said to be achieved if the RSRP of the inbuilding system is dB stronger than that of the macro layer in d% of the floor area of a building. Typical values for the dominance D are between three and ten decibels (3 to 10 dB), while the percentage of the floor area for which dominance need to be achieved is typically d = 95%.

Methods commonly used to assess signal levels of macro radio nodes inside a building include the fixed macro signal level method and the walk test measurement method. Macro radio nodes are those radio nodes located outside the building.

Further, a signal level of a macro radio node may also be referred to as a macro signal level. The fixed macro signal level method requires the macro signal level to be set according to a pre-defined value throughout the building. For LTE, this could be an RSRP between -95 dBm (weak macro) to -75dBm (strong macro). The walk test measurement method requires a person to walk through the building to take

measurements of the macro signal levels at a number of locations inside the building. In order to describe the macro signal levels inside a building more accurately, an indoor propagation model is applied. Some commonly used propagation models include the loss-per-meter model and the Keenan-Motley channel model.

The loss-per-meter model is a basic indoor propagation model, which is applicable when no detailed indoor floorplans are available. The indoor pathloss (in dB) is expressed by the free space pathloss plus an excess loss, which describes attenuations of the radio waves penetrating through walls as well as reflections or diffractions by obstacles. While walls and obstacles are not explicitly modeled, the attenuation associated with walls and obstacles are expressed by a loss per meter degradation on the excess loss. The pathloss for the loss-per-meter model is given by:

PL(d) = FSPL(d) Ld [dB] Equation (2) where the constant L with unit [dB/m] accounts for the excess loss and is set according to the building type. For open landscape floorplans, a typical value is L = 0.2 dB/m; for closed office areas, L = 0.6 dB/m; and for residential buildings, L = 0.8 dB/m. The free space loss (FSPL) in Equation (2) is in the form:

Equation (3)

where f_c is the carrier frequency and c is the speed of light. The distance, d, denotes the Euclidian distance between the transmitter and receiver.

The Keenan-Motley channel model is widely used, but requires the location of the interior walls, as well as their respective wall attenuation. The pathloss for the Keenan-Motley channel model is given by:

PL(d) = FSPL(d) Wk [dB] Equation (4)

The constant W with unit [dB] accounts for the penetration loss of the interior walls, and k denotes the number of walls that are crossed between the transmitter and receiver. Further, if walls have different wall losses, then W becomes different for each wall type.

For most indoor deployments, stringent requirements on the dominance of the indoor system are set, such as demanding that the small cell signal exceed the macro cell signal by 6 to 8 dB at 95% of the building floor area. Setting a fixed macro signal level of x dBm throughout the building fails to acknowledge the fact that the macro signal levels are impinged by the outer walls and decay as they traverse deeper inside the building. Hence, a fixed macro signal level inherently leads to an overprovisioning of the indoor system. An accurate estimate of the macro signal levels may facilitate indoor deployments with fewer nodes, which in turn reduces cost of the indoor system.

Furthermore, state of the art tools for designing indoor systems, such as iBwave, rely on manual labor to place TPs in a building. This requires a skilled person to manually place TPs in the building and test whether the tested TP locations achieve the desired coverage target of the indoor system. The manual placement of nodes may possibly need to be repeated multiple times. This is a time consuming task. In order to scale the design of an inbuilding system to the increased number of small cell indoor deployments that is envisaged in the coming years, a more efficient procedure for node deployment is needed. Accordingly, there is a need for improved techniques for node deployment in an enclosure. In addition, other desirable features and characteristics of the present disclosure will become apparent from the subsequent detailed description and embodiments, taken in conjunction with the accompanying figures and the foregoing technical field and background.

The Background section of this document is provided to place embodiments of the present disclosure in technological and operational context, to assist those of skill in the art in understanding their scope and utility. Unless explicitly identified as such, no statement herein is admitted to be prior art merely by its inclusion in the Background section.

SUMMARY

The following presents a simplified summary of the disclosure in order to provide a basic understanding to those of skill in the art. This summary is not an extensive overview of the disclosure and is not intended to identify key or critical elements of embodiments of the disclosure or to delineate the scope of the disclosure. The sole purpose of this summary is to present some concepts disclosed herein in a simplified form as a prelude to the more detailed description that is presented later.

Briefly described, embodiment of the present disclosure relate to systems and methods for performing node deployment. According to one aspect, a method of determining where in an enclosure to place individual radio nodes for collectively providing radio coverage in the enclosure may include, for each of multiple candidate locations in the enclosure, obtaining a location-specific interference metric reflecting an extent of interference at that location. Further, the method may include determining to tentatively place an initial radio node at one of the candidate locations. For each of one or more iterations, the method may include, for each of the multiple candidate locations in the enclosure, obtaining an enclosure-wide coverage metric reflecting an extent of radio coverage that would be collectively provided across the enclosure by any tentatively placed nodes in combination with an additional radio node, if the additional radio node were to be placed at that candidate location. Also, for each of the one or more iterations, the method may include identifying which one of the enclosure-wide coverage metrics reflects the greatest extent of radio coverage that would be

collectively provided across the enclosure and determining whether to tentatively place the additional radio node at the candidate location for which the identified enclosure- wide coverage metric was obtained.

According to another aspect, for each of the one or more iterations, the method may include obtaining a location-specific coverage metric for each enclosure-wide location reflecting an extent of radio coverage that would be provided at that enclosure- wide location, if the additional radio node were to be placed at that candidate location, in view of the interference metric obtained for that enclosure-wide location;

According to another aspect, for each of the one or more iterations, the method may include re-determining at which of the candidate locations to place each of one or more radio nodes that were tentatively placed in a previous iteration, after determining at which candidate location to tentatively place the additional radio node.

According to another aspect, the method may include performing the one or more iterations until tentative placement of an additional radio node achieves a defined extent of collective radio coverage in the enclosure.

According to another aspect, the method may include performing the one or more iterations until tentative placement of an additional radio node fails to achieve a defined improvement in the extent of collective radio coverage in the enclosure.1 .

According to another aspect, a device for determining where in an enclosure to place individual radio nodes for collectively providing radio coverage in the enclosure may include a memory configured to store data and computer-executable instructions and a processor operatively coupled to the memory. For each of multiple candidate locations in the enclosure, the processor and memory may be configured to obtain a location-specific interference metric reflecting an extent of interference at that location. Further, the processor and memory may be configured to determine to tentatively place an initial radio node at one of the candidate locations. For each of one or more iterations, the processor and memory may be configured to, for each of the multiple candidate locations in the enclosure, obtain an enclosure-wide coverage metric reflecting an extent of radio coverage that would be collectively provided across the enclosure by any tentatively placed nodes in combination with an additional radio node, if the additional radio node were to be placed at that candidate location. For each of the one or more iterations, the processor and memory may be configured to identify which one of the enclosure-wide coverage metrics reflects the greatest extent of radio coverage that would be collectively provided across the enclosure and determine whether to tentatively place the additional radio node at the candidate location for which the identified enclosure-wide coverage metric was obtained.

According to another aspect, a non-transitory computer-readable medium encoded with a computer program, the computer program comprising computer- executable instructions that when executed by a processor causes the processor to perform operations, wherein the operations may be configured to, for each of multiple candidate locations in the enclosure, obtain a location-specific interference metric reflecting an extent of interference at that location. Further, the operations may be configured to determine to tentatively place an initial radio node at one of the candidate locations. For each of one or more iterations, the operations may be configured to, for each of the multiple candidate locations in the enclosure, obtain an enclosure-wide coverage metric reflecting an extent of radio coverage that would be collectively provided across the enclosure by any tentatively placed nodes in combination with an additional radio node, if the additional radio node were to be placed at that candidate location. Also, for each of the one or more iterations, the operations may be configured to identify which one of the enclosure-wide coverage metrics reflects the greatest extent of radio coverage that would be collectively provided across the enclosure and to determine whether to tentatively place the additional radio node at the candidate location for which the identified enclosure-wide coverage metric was obtained.

According to another aspect, a computer-implemented method of performing transmission node deployment in an enclosure may include receiving a plurality of signal level measurements corresponding to one or more interfering nodes. Each signal level measurement may be determined at one of a plurality of measurement locations in the enclosure. Further, the method may include estimating a plurality of coverage areas in the enclosure by an enclosure node. Each coverage area may correspond to the enclosure node being positioned at one of a plurality of candidate placement locations. Also, the method may include selecting, using the plurality of signal level

measurements, one of the plurality of coverage areas that in combination with a collective coverage area of one or more other enclosure nodes provides a maximum collective coverage area in the enclosure to obtain a selected coverage area. In addition, the method may include outputting an indication of one of the plurality of candidate placement locations in the enclosure that corresponds to the selected coverage area for use in positioning the enclosure node.

According to another aspect, a device for performing transmission node deployment in an enclosure may include a memory configured to store data and computer-executable instructions and a processor operatively coupled to the memory. The processor and the memory may be configured to receive a plurality of signal level measurements corresponding to one or more interfering nodes. Each signal level measurement may be determined at one of a plurality of measurement locations in the enclosure. Further, the processor and the memory may be configured to estimate a plurality of coverage areas in the enclosure by an enclosure node. Each coverage area may correspond to the enclosure node being positioned at one of a plurality of candidate placement locations. Also, the processor and the memory may be configured to select, using the plurality of signal level measurements, one of the plurality of coverage areas that in combination with a collective coverage area of one or more other enclosure nodes provides a maximum collective coverage area in the enclosure to obtain a selected coverage area. In addition, the processor and the memory may be configured to output an indication of one of the plurality of candidate placement locations in the enclosure that corresponds to the selected coverage area for use in positioning the enclosure node.

According to another aspect, a non-transitory computer-readable medium encoded with a computer program, the computer program comprising computer- executable instructions that when executed by a processor causes the processor to perform operations, wherein the operations may be configured to receive a plurality of signal level measurements corresponding to one or more interfering nodes. Each signal level measurement may be determined at one of a plurality of measurement locations in the enclosure. Further, the operations may be configured to estimate a plurality of coverage areas in the enclosure by an enclosure node. Each coverage area may correspond to the enclosure node being positioned at one of a plurality of candidate placement locations. Also, the operations may be configured to select, using the plurality of signal level measurements, one of the plurality of coverage areas that in combination with a collective coverage area of one or more other enclosure nodes provides a maximum collective coverage area in the enclosure to obtain a selected coverage area. In addition, the operations may be configured to output an indication of one of the plurality of candidate placement locations in the enclosure that corresponds to the selected coverage area for use in positioning the enclosure node.

According to another aspect, a computer-implemented method of predicting a signal level in an enclosure may include receiving a plurality of perimeter signal level measurements corresponding to one or more macro radio nodes. Each perimeter signal level measurement may be determined near an outer perimeter in the enclosure. Further, the method may include, for each of the plurality of perimeter signal level measurements, predicting a composite pathloss at a certain location in the enclosure. The composite pathloss may correspond to one of the macro radio nodes. Also, the method may include selecting one of the composite pathlosses that has a minimum composite pathloss at the certain location in the enclosure. In addition, the method may include determining the signal level at the certain location using the selected composite pathloss and outputting an indication of the signal level at the certain location in the enclosure.

According to another aspect, the plurality of coverage areas are associated with downlink transmission by the enclosure node.

According to another aspect, at least one of the one or more interfering nodes are located outside of the enclosure.

According to another aspect, at least one of the one or more interfering nodes are located in the enclosure.

According to another aspect, for each coverage area, the method may include determining a plurality of signal level estimates for one of the plurality of candidate placement locations. Further, each signal level estimate may be determined at one of a plurality of estimate locations in the enclosure.

According to another aspect, the method may include determining a dominance of the enclosure using the plurality of signal level measurements and the maximum collective coverage area. Further, the method may include outputting an indication of the signal level at the certain location in the enclosure responsive to determining that the dominance of the enclosure is less than a dominance threshold.

According to another aspect, the method may include determining a coverage gain of the selected coverage area using the selected coverage area and the collective coverage area. Further, the method may include outputting an indication of the signal level at the certain location in the enclosure responsive to determining that the coverage gain is at least a coverage gain threshold.

According to another aspect, a computer-implemented method of determining where in an enclosure to place individual radio nodes for collectively providing radio coverage in the enclosure may include determining a location-specific interference metric for each enclosure-wide location. The interference metric may reflect an extent of interference at that location. Further, the method may include determining to tentatively place an initial radio node at one of multiple candidate locations selected from the enclosure-wide locations. For each of one or more iterations, the method may include performing the following steps. First, the method may include obtaining a location-specific coverage metric for each enclosure-wide location reflecting an extent of radio coverage that would be provided at that location if the additional radio node were to be placed at that location, in view of the interference metric obtained for that location. Second, for each of the multiple candidate locations in the enclosure, the method may include obtaining an enclosure-wide coverage metric based on the interference metric and the coverage metric for each enclosure-wide location. The enclosure-wide coverage metric may reflect an extent of radio coverage that would be collectively provided across the enclosure by any tentatively placed nodes in combination with an additional radio node, if the additional radio node were to be placed at that candidate location. Third, the method may include identifying which one of the enclosure-wide coverage metrics reflects the greatest extent of radio coverage that would be

collectively provided across the enclosure. Fourth, the method may include determining to tentatively place the additional radio node at the candidate location for which the identified enclosure-wide coverage metric was obtained.

According to another aspect, a device for determining where in an enclosure to place individual radio nodes for collectively providing radio coverage in the enclosure may include a memory configured to store data and computer-executable instructions and a processor operatively coupled to the memory. The processor and the memory may be configured to determine a location-specific interference metric for each enclosure-wide location, wherein the interference metric reflects an extent of interference at that location. Further, the processor and the memory may be configured to determine to tentatively place an initial radio node at one of multiple candidate locations selected from the enclosure-wide locations. For each of one or more iterations, the processor and the memory may be configured to perform the following steps. First, the processor and the memory may be configured to obtain a location- specific coverage metric for each enclosure-wide location reflecting an extent of radio coverage that would be provided at that enclosure-wide location, if the additional radio node were to be placed at that candidate location, in view of the interference metric obtained for that enclosure-wide location. Second, for each of the multiple candidate locations in the enclosure, the processor and the memory may be configured to obtain an enclosure-wide coverage metric based on the interference metric and the coverage metric for each enclosure-wide location. The enclosure-wide coverage metric may reflect an extent of radio coverage that would be collectively provided across the enclosure by any tentatively placed nodes in combination with an additional radio node, if the additional radio node were to be placed at that candidate location. Third, the processor and memory may be configured to identify which one of the enclosure-wide coverage metrics reflects the greatest extent of radio coverage that would be collectively provided across the enclosure. Fourth, the processor and memory may be configured to determine to tentatively place the additional radio node at the candidate location for which the identified enclosure-wide coverage metric was obtained.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure is illustrated by way of examples, embodiments and the like and is not limited by the accompanying figures, in which like reference numbers indicate similar elements. Elements in the figures are illustrated for simplicity and clarity and have not necessarily been drawn to scale. The figures along with the detailed description are incorporated and form part of the specification and serve to further illustrate examples, embodiments and the like, and explain various principles and advantages, in accordance with the present disclosure, where:

FIG. 1 illustrates a structure of distributed small cells with pooled baseband.

FIG. 2 illustrates a structure of indoor small cells with one digital unit connected to four IRUs. FIGs. 3A-3F illustrate one embodiment of a method of performing node deployment in an enclosure in accordance with various aspects as described herein.

FIG. 4 illustrates an example of performing node deployment in an enclosure in accordance with various aspects as described herein.

FIG. 5 provides a flowchart of one embodiment of a method of performing node deployment in an enclosure in accordance with various aspects as described herein.

FIG. 6 provides a flowchart of one embodiment of a method of performing node deployment in an enclosure in accordance with various aspects as described herein.

FIG. 7 provides an example of predicting signal levels in an enclosure in accordance with various aspects as described herein.

FIG. 8 shows predicted signal levels throughout the enclosure of FIG. 7.

FIG. 9 provides a flowchart of one embodiment of a method of predicting signal levels in an enclosure in accordance with various aspects as described herein.

FIG. 10 illustrates one embodiment of a device for performing node deployment in an enclosure in accordance with various aspects as described herein.

FIG. 11 illustrates one embodiment of a device in accordance with various aspects as described herein.

FIG. 12 illustrates one embodiment of a device for predicting macro signal levels in an enclosure in accordance with various aspects as described herein. DETAILED DESCRIPTION

In this disclosure, systems and methods for node deployment in an enclosure are provided. For example, instead of placing radio nodes manually in an enclosure, the Automatic Node Deployment (AND) algorithm, as described herein under various embodiments, places one or more radio nodes autonomously in the enclosure and without the need for human interaction. Further, location-specific interference metrics of a macro cell layer for a radio node located outside the enclosure and location-specific signal strengths of a small cell layer for a radio node located inside the enclosure may be required to perform the AND algorithm. A radio node may be a TP, an RP, a radio dot, a radio point (RP), an access point (AP), a network node, a base station, a pico base station, a nano base station, the like, or any combination thereof. An interference metric may include a signal strength, a power level, a signal-to-interference ratio (SIR), a signal-to-interference-plus-noise ratio (SINR), a carrier to noise-and-interference ration (CNIR), a Reference Signal Received Power (RSRP), a Received Signal Code Power (RSCP), the like, or any combination thereof. The embodiments described herein may apply to other wireless communication standards such as LTE and

WCDMA. For instance, these embodiments may apply to LTE by using RSRP or to WCDMA by using RSCP. The small cell layer is associated with signals transmitted by one or more radio nodes located in the enclosure. Further, the macro cell layer is associated with signals transmitted by one or more radio nodes located outside of the enclosure.

The AND algorithm may include measuring location-specific interference metrics of the macro cell layer in the enclosure. Further, the AND algorithm may include placing a first radio node in the enclosure to provide coverage of the small cell layer in the enclosure. The coverage of the small cell layer may describe the area within the enclosure where the signal strength of the strongest signal transmitted from one of the radio nodes in the enclosure (i.e., small radio node) exceeds the signal strength of the strongest signal transmitted from one of the radio nodes outside the enclosure (i.e., macro radio node). For each possible radio node candidate location in the enclosure, the AND method may include determining an enclosure-wide coverage metric representing the collective coverage of the small cell layer by the radio nodes in the enclosure. In one example, the coverage of the small cell layer may be the area in the enclosure where a location-specific signal strength of the small cell layer from one or more cells of a radio node located in the enclosure exceeds a maximum location- specific interference metric of the macro cell layer from one cell of a radio node located outside the enclosure plus a dominance requirement. A dominance of the enclosure is achieved when the location-specific signal strength of the small cell layer exceeds the location-specific interference metric of the macro cell layer plus the dominance requirement throughout the enclosure. Further, the AND algorithm may include placing each radio node in the enclosure so that the coverage of the small cell layer is maximized in the enclosure. After a new radio node is placed, the AND algorithm may include determining a location for each previously deployed radio node that maximizes the enclosure-wide coverage metric. In addition, the AND algorithm may include determining that a termination criteria is met such as when the dominance of the enclosure is achieved, a new radio node fails to add a minimum coverage gain to the small cell layer, a certain minimum or maximum number of radio nodes have been deployed, a defined extent of collective radio coverage in the enclosure, or the like. A defined extent of collective radio coverage in the enclosure may be 70%, 80%, 90%, 95%, 98% or the like of collective radio coverage of the enclosure by the radio nodes in the enclosure.

The AND algorithm is further described with reference to the enclosure 300a-f (e.g., a floor of a building) depicted in FIGs. 3A-3F with various aspects as described herein. In FIG. 3A, a location 301a of a first radio node that maximizes the enclosure- wide coverage metric is shown. Further, location-specific interference metrics for the macro cell layer are plotted for the enclosure 300a. The interference metrics for the macro cell layer are represented in FIGs. 3A-3F as a continuum of colors, as described by legends 331 a-d. The interference metrics for the macro cell layer may be calculated from the pathloss (PL) of a signal transmitted by a radio node outside the enclosure such as by the use of Equation (1 ).

The coverage of the small cell layer 321 b-e is represented by the color black in FIGs. 3B-3E and indicates locations in the enclosure 300b-e where the small cell signal strength from one of the radio nodes in the enclosure exceeds the macro cell interference metric from one of the radio nodes outside the enclosure plus the dominance requirement.

In FIG. 3B, a location 303b of a second radio node is determined by identifying which one of the enclosure-wide coverage metrics reflects the greatest extent of radio coverage that would be collectively provided by the first and second radio nodes across the enclosure. Hence, the locations 301 b and 303b of the respective first and second radio nodes collectively maximize the coverage of the small cell layer 321 b in the enclosure 300b.

After the second radio node is located at the location 303b, FIG. 3C shows the coverage of the small cell layer 321 c in the enclosure 300c after determining, for each possible location of the first and second radio nodes in the enclosure 300c, respective locations 301 c and 303c that collectively maximize the enclosure-wide coverage metric. In other words, due to deploying the second radio node, the location 301 a of the first radio node may not be optimal and may be re-located in the enclosure at the new location 301c, followed by re-locating the second radio node from the location 303a to the new location 303c, until the locations 301 c and 303c collectively maximize the coverage of the small cell layer 321 c in the enclosure 300c. The iterations associated with re-locating each radio node may be repeated until no further gain in the enclosure- wide coverage metric is achieved. After re-locating the first and second radio nodes to collectively maximize the enclosure-wide coverage metric, FIG. 3D shows determining a location 305d of a third radio node followed by re-locating the first, second and third radio nodes to collectively maximize the enclosure-wide coverage metric, using the iterative process previously described. The steps of successively adding radio nodes and performing this iterative process may be repeated until a termination criterion is met such as when the dominance of the enclosure is achieved, a new radio node fails to add a minimum coverage gain to the small cell layer, a certain minimum or maximum number of radio nodes have been deployed, or the like.

FIGs. 3E-3F show that full coverage of the small cell layer in the enclosure is achieved using five radio nodes.

FIG. 4 illustrates an example application of the AND algorithm in accordance with various aspects as described herein. The AND algorithm may require measuring or determining signal strength samples (e.g., RSRP for LTE) for both macro and small cell layers in an enclosure 400. In general, the received signal strength, R, may be expressed as a function of the (x,y) Cartesian coordinates as R{x,y) . One means of representing R{x,y) may be to regularly sample the enclosure (e.g., floor area). On each floor, signal strength samples 403 (i.e., the grey dots in FIG. 4) may be taken such as every n meters on the x and y-axes of an enclosure 401. In FIG. 4, the enclosure 401 is a floor plan in an office building. The thick lines, such as indicated by reference 405, represent thick walls (e.g., brick or concrete walls). The thin lines, such as indicated by reference 407, represent thin walls (e.g., dry walls). The signal strength samples 403 may be determined in a portion of or throughout the enclosure 401. In one example, the signal strength samples may be determined uniformly throughout the enclosure 401. In another example, the signal strength samples may be determined irregularly throughout the enclosure 401. In yet another example, the signal strength samples may be measured along the perimeter of the enclosure and then used to estimate signal strength samples in the remainder of the enclosure 401. Further, the signal strength samples may have a higher sampling density (i.e., less distance between signal strength samples) in areas of the enclosure 401 that are of more importance such as high-traffic areas.

The coverage of the small cell layer may describe the area within an enclosure (e.g., building) where the signal strength of the strongest signal transmitted from one of the radio nodes in the enclosure (i.e., small radio node) exceeds the signal strength of the strongest signal transmitted from one of the radio nodes outside the enclosure (i.e., macro radio node). The coverage of the macro cell layer by the strongest signal transmitted from one of the macro radio nodes may be described as follows:

M(x,y) = max (l 0 log₁₀(fi_m (x, y))) [dBm] Equation (5) where R_m (x, y) denotes a location-specific interference metric at location (x,y) of macro radio node m. For LTE, 1 0 log₁₀(ft_m (x,y)) is given by the RSRP calculation of

Equation (1 ). In one instance, the interference metric of a macro radio node may be determined from walk test measurements in the enclosure (e.g., building floor), where snapshots of M(x, y) are taken at selected enclosure locations (x,y) . If walk test measurements are not available, M(x, y) may be set to a pre-defined value. A typical range of values for M(x,y) may be -95 dBm (i.e., weak macro radio node) to -75 dBm

(i.e., strong macro radio node).

For the small cell signal strength (i.e., the signal strength of the small cell layer), stand-alone radio nodes in the enclosure such as pico and femto base stations and distributed antenna systems (DAS) may be distinguished. For stand-alone radio nodes, the small cell signal strength at location (x, y) of the enclosure may be given by the strongest signal that may be transmitted by one of the small cell radio nodes (i.e., radio node inside the enclosure) as follows:

S(x, y) = max (l 0 log₁₀(fl, (x,y))) [dBm] Equation (6) where R_t x,y) denotes the small cell signal strength (e.g., RSRP) at location (x,y) of small cell radio node /^'. For DAS, the small cell signal strength at location (x,y) is the sum of the signals emitted by the TPs that belong to one cell such as follows:

Equation (7)

An enclosure location (x,y) may be covered by the small cell layer if the following condition is met:

S(x, y) > M(x,y) + D Equation (8) where D is the dominance requirement as previously described.

The enclosure-wide coverage metric may be represented by >^_ov as derived by Equations (9) and (10). cov

Equation (9)

[0, elsewhere 4ov =∑cov (x,y) x y Equation (10) where AxAy is the area covered by one enclosure location (x, y) .

In another embodiment, the AND algorithm may include the following steps:

Step (1 ): Determine signal strengths of the macro cell layer (x,y) as described by Equation (5);

Step (2): Place new small radio node: for each candidate small cell location in the enclosure, determine the small cell coverage area, i.e. the area where Equation (8) is true;

• for each candidate small radio node location (x, y) , determine the

small cell signal level S(x,y) according to Equations (6) and (7) for respective stand-alone small cells and DAS; and

• place the new small radio node so that the coverage area of the small cell layer, ,_ov , in Equation (10), is maximized;

Step (3): Perform iteration loop: after a new small radio node is placed, repeat Step (2) above for already deployed nodes; · this involves a loop over all deployed nodes;

• at instance k of the loop, one small radio node is replaced so that the location of the radio node n, is moved such that S(x, y) is maximized.

Note that according to Equations (6) and (7), S(x,y) is the aggregated signal strength of the small cell layer, i.e. the joint coverage area of all deployed small radio nodes; and

• when one small radio node has been moved, than the location of the other small radio nodes may no longer be optimal, in the sense that A_cov is maximized. Hence, the iteration loop may be repeated as long as no further coverage gain is achieved. The coverage gain from iteration k→ k + 1 is denoted by AA = A_cm [k 1) -A_cov- k) ; and

Step (4): Terminate the AND algorithm if:

• full indoor dominance is achieved, i.e. A_cov represents coverage of the floor; and

• adding a new small radio node fails to add a minimum coverage gain AA to the small cell layer.

In another embodiment, there may be candidate radio node locations that achieve approximately the same coverage area, A_cm . In this case, an alternative metric that allows choosing the most appropriate node location may be desirable. One such metric is the geometry-based sum-rate achieved by the enclosure deployment. For this metric, the geometry may be calculated at enclosure location (x,y) as follows:

G(x,y) Equation (1 1 )

where N₀ denotes thermal noise. Given the geometry, the sum-rate may be approximated by the truncated Shannon bound, which is in the form:

∑iog₂(50i), 10log₁₀ (G(x,y)) > 30de

∑iog₂d -¾£¾ ^ 0e^B 10k>g₁₀ (G(x,y)) 30dB Equation (12) x —,y a ⁰¹

0, 1 0 log_l0 (G(x,y)) < -1 0o©

Provided that A_cov is similar for multiple candidate small radio node locations, the small radio node location that maximizes C in Equation (12) may be selected as the new small radio node location.

In another embodiment, the AND algorithm may converge to a local maximum for A_cm . To avoid this, the order of replacing the radio nodes in Step (3) of the AND algorithm, as described above, may be modified. For example, the order of radio nodes may be randomly selected in the iteration loop. In another example, the radio nodes may be sorted in reverse order with respect to the distance the radio nodes were moved in the previous iteration. This means that radio nodes that have not been moved in the previous iteration will be the first to be replaced in the current iteration. This allows those radio nodes to adjust their location, which are potentially affected by the movement of adjacent radio nodes.

In another embodiment, a gradient-based optimization algorithm may

automatically place radio nodes in an enclosure so that the coverage of the small cell layer is maximized. Further, this optimization algorithm may be complemented by another algorithm that maximizes the geometry- based sum-rate of the small cell deployment.

FIG. 5 provides a flowchart of one embodiment of a method 500 of performing node deployment in an enclosure in accordance with various aspects as described herein. In FIG. 5, the method 500 may start, for instance, at block 501 where it, for each of multiple candidate locations in the enclosure, may include performing the step at block 503 of obtaining a location-specific interference metric reflecting an extent of interference at that location. At block 505, the method 500 may include determining to tentatively place an initial radio node at one of the candidate locations. At block 507, for each of one or more iterations, the method 500 may include performing the steps at blocks 509, 511 , 513 and 515. At block 509, for each of the multiple candidate locations in the enclosure, the method 500 may include performing the step of block 511 of obtaining an enclosure-wide coverage metric reflecting an extent of radio coverage that would be collectively provided across the enclosure by any tentatively placed nodes in combination with an additional radio node, if the additional radio node were to be placed at that candidate location. At block 513, the method 500 may include identifying which one of the enclosure-wide coverage metrics reflects the greatest extent of radio coverage that would be collectively provided across the enclosure. At block 515, the method 500 may include determining to tentatively place the additional radio node at the candidate location for which the identified enclosure-wide coverage metric was obtained.

FIG. 6 provides a flowchart of one embodiment of a method 600 of performing node deployment in an enclosure in accordance with various aspects as described herein. In FIG. 6, the method 600 may start, for instance, at block 601 where it may include receiving a plurality of signal level measurements corresponding to one or more interfering nodes. Each signal level measurement may be determined at one of a plurality of measurement locations in the enclosure. At block 603, the method 600 may include estimating a plurality of coverage areas in the enclosure by an enclosure node. Each coverage area may correspond to the enclosure node being positioned at one of a plurality of candidate placement locations. At block 605, the method 600 may include selecting, using the plurality of signal level measurements, one of the plurality of coverage areas that in combination with a collective coverage area of one or more other enclosure nodes provides a maximum collective coverage area in the enclosure to obtain a selected coverage area. At block 607, the method 600 may include outputting an indication of one of the plurality of candidate placement locations in the enclosure that corresponds to the selected coverage area for use in positioning the enclosure node.

In another embodiment, by having more accurate knowledge of the macro signal level inside a building a more realistic indoor system may be deployed. This may potentially result in fewer radio nodes that are deployed in a given venue, while still meeting the required level of dominance.

FIG. 7 provides an example of predicting signal levels in an enclosure 700.

Instead of assuming fixed macro signal levels over the entire enclosure (e.g., floor area of a building), the signal levels from macro radio nodes may be determined at locations near or at the outer perimeter 701-704 of the enclosure 700 (e.g., inside the outer walls of a building). For instance, the macro signal levels at the outer perimeter 701-704 may be measured signal levels. Further, the macro signal levels at the outer perimeter 701- 704 may be used as reference points for determining macro signal levels in the enclosure 700. Using the determined signal levels at the perimeter 701 -704, indoor propagation models may be used to determine the macro signal levels at other locations in the enclosure 700.

The basic principle of the macro signal level prediction is explained with the aid of the floorplan depicted in FIG. 7. In this example, a strong macro cell signal is measured on the outer wall 701 of the eastern side of the building 700 with 10 dB stronger signal levels than on the remaining outer walls 702-704. The macro cell signal strength at the indoor location 705 (i.e., marked with the green dot in FIG. 7) may be derived by calculating the excess loss from a number of wall reference locations 711- 714 to the green dot.

FIG. 8 shows determined signal levels throughout the enclosure 700 of FIG. 7, which is described as reference 800 in FIG. 8. In FIG. 8, macro signal levels determined at the outer perimeter of the enclosure 800 are used to determine macro signal levels for indoor locations. As shown, the macro pathloss gets weaker when moving deeper inside the enclosure 800 (e.g., building). Moreover, higher macro pathlosses may be observed inside rooms, especially those surrounded by thicker walls such as those indicated by references 805-808 (also indicated in red in FIG. 8).

In the example floorplan of the building in FIG. 8, outer walls of the building are indicated by references 801 -804 (as indicated by thick black lines in FIG. 8). Further, reference 805 provides an example of a thick interior wall such as brick or concrete (as indicated as thick red lines in FIG. 8), and reference 807 provides an example of a thin interior wall such as a dry wall (as indicated by thin black lines in FIG. 8). In the example of FIG. 8, a strong macro cell signal is impinging from the eastern side of the building (i.e., closest to the outer wall 801 ) with 1 0 dB stronger signal levels than on the remaining outer walls. The macro cell signal strength at the indoor location 705

(marked with the green dot in FIG. 7) is derived by calculating the excess loss from the four wall reference locations 711 -714 to the indoor location 705. That candidate pathloss is selected as macro pathloss, which yields the minimum composite pathloss.

In another embodiment, for LTE, the pathloss is related to RSRP according to Equation (1 ). Provided that the transmit power P and the number of subcarriers N_sc are fixed, there is a one-to-one relationship between pathloss and RSRP. Hence, if the macro pathloss is known, it is straight forward to determine the RSRP and vice versa.

In this embodiment, the macro cell signal prediction method may include setting the signal level at the outer perimeters of the building, just inside the outer walls.

Further, the method may include calculating the composite pathloss of the macro cell signal from the wall reference points to other indoor locations further inside the building, denoted by coordinates (x_u,y_u) . The method may include selecting the macro pathloss for position (x_u,y_u) , which gives the minimum composite pathloss. Also, the method may include setting the signal levels at the wall reference locations.

Furthermore, this method may use a priori knowledge of the macro signal levels inside the building near the outer walls. The macro RSRP at the wall reference point with coordinates (x_w,y_w) may be denoted by RSRP_wall (x_w,y_w) . Hence, the pathloss between the macro radio node and the wall reference point may be given as: PLvau Equation (13)

In Equation (1 3), due to the distance dependency of the free space loss, the pathloss is separated into free space pathloss and the excess pathloss.

The macro radio node (e.g., macro base station) with the strongest RSRP at (x_w, y_w) is deployed at a distance, d_out , away from the building of interest. If d_out is not known, then a default value may be assigned (e.g., d_out = 100 meters, 1000 meters, or the like). When the macro cell signal propagates from the macro radio node to the wall reference point, the outer walls of the building are penetrated as well as some possible obstacles on the way. This is captured in the outer excess loss, which is given by: Equation (14)

where FSPL(d_out) accounts for the free space pathloss of distance d_t out ^■

Given the outer excess loss, X_out, derived in Equation (14) above, the pathloss candidate of the macro cell signal impinging from wall point (x_w,y_w) may be expressed as:

PL_w (x_i,y = FSPL(d_0Ut d_in) ^X_out(x_w,y_w) Equation (15)

In Equation (1 5), the term FSPL(d_0Ut + d_jn) includes the free space loss from the macro radio node to the wall reference point and further to the indoor location at ( ,,/,)■ The inner excess loss, X_{jn w} , from the locations indicated by (x_w,y_w) to (x,,y,) is determined by an appropriate indoor channel model, as previously described. For instance, for the Keenan-Motley channel model of Equation (3), the inner excess loss yields X_in,w = Wk .

The number of wall reference points that should be used to calculate Equation (15) may be a design parameter. For instance, at least one wall reference point from each side of the building is used.

The final step is to select the minimum pathloss from all wall points as expressed by: PL(x_i, y_i) = m u_w PL_w (x_i,y_i) Equation (16)

Given Equation (16), the macro RSRP may be determined by evaluating

Equation (1 ).

If measurements from a walk test are available, the way-points where

measurement samples are taken may not always coincide with the outer perimeters of the building. If so, the pathloss at the wall reference point may be determined from the measurement point . Starting from Equation (14), the outer excess loss may be determined by solving the following:

Equation (17) where PL(x_s, y_s) denotes the pathloss measured at the measurement way-point.

The inner excess loss x_{jn s} from the measurement point to the wall reference point may be determined by invoking an indoor channel model, in line with the methods previously described. Then the pathloss at the wall reference point may be calculated by transforming Equation (14) as follows: PL_wall (x_w,y_w) = FSPL(d_0Ut) + X_0Ut (x_w,y_w) Equation (18)

In determining PL_wall (x_w, y_w) , the macro signal level may be calculated on all indoor positions in the same way as previously described.

Similar to the macro pathloss calculations, PL_wall (x_w,y_w) may be determined at various wall reference points. Then the wall reference point that provides the minimum pathloss may be selected.

In another embodiment, a method may include applying known indoor

propagation models to derive a more accurate representation of the macro signal levels inside a building.

FIG. 9 provides a flowchart of one embodiment of a method 900 of predicting signal levels in an enclosure in accordance with various aspects as described herein. In FIG. 9, the method 900 may start, for instance, at block 901 where it may include receiving a plurality of perimeter signal level measurements corresponding to one or more macro radio nodes. Each perimeter signal level measurement may be determined near an outer perimeter in an enclosure. At block 903, the method 900 may include, for each of the plurality of perimeter signal level measurements, predicting a composite pathloss at a certain location in the enclosure. The composite pathloss may correspond to one of the macro radio nodes and may include at least one of a free space loss, an outer excess loss and an inner excess loss. At block 905, the method 900 may include selecting one of the composite pathlosses that has a minimum composite pathloss at the certain location. At block 907, the method 900 may include determining a signal level at the certain location using the selected composite pathloss. At block 909, the method 900 may include outputting an indication of the signal level at the certain location.

FIG. 10 illustrates one embodiment of a device 1000 for performing node deployment in accordance with various aspects as described herein. In FIG. 10, the device 1000 may be configured to include a wireless receiver 1001 , a signal level measurement circuit 1003, a measurement location circuit 1005, a GPS receiver 1007, an estimation circuit 1009, a selection circuit 1011 , and an output circuit 1013. The wireless receiver 1001 may be any component or collection of components that allows receiving a signal on a wireless connection. The signal level measurement circuit 1003 may be operationally coupled to the receiver and may receive signals from the wireless receiver 1001. Further, the signal level measurement circuit 1003 may be any component or collection of components that performs a measurement of a level of a received signal to obtain a signal level measurement. The GPS receiver 1007 may be any component or collection of components that allows receiving a GPS signal to determine a location of the device 1000. The measurement location circuit 1005 may be operationally coupled to the GPS receiver 1007 and the signal level measurement circuit 1003. Also, the measurement location circuit 1005 may be any component or collection of components that allows associating a signal level measurement with a location of the device 1000 when the signal level measurement was performed.

In FIG. 10, the estimation circuit 1009 may be any component or collection of components that allows estimating a plurality of coverage areas in an enclosure by an enclosure node. In one example, the GPS receiver 1007 may be used to define a perimeter of the enclosure. The selection circuit 1011 may be operationally coupled to the measurement location circuit 1005 and the estimation circuit 1009. Also, the selection circuit 1011 may be any component or collection of components that allows selecting, using signal level measurements, one of the plurality of coverage areas that in combination with a collective coverage area of one or more other enclosure nodes provides a maximum collective coverage area in the enclosure to obtain a selected coverage area. The selection circuit 1011 may output an indication of one of the plurality of candidate placement locations in the enclosure that corresponds to the selected coverage area for use in positioning the enclosure node.

FIG. 11 illustrates another embodiment of a device 1100 in accordance with various aspects as described herein. In some instances, the device 1100 may be referred to as a terminal, a cellular phone, a personal digital assistant (PDA), a smartphone, a wireless phone, an organizer, a handheld computer, a desktop computer, a laptop computer, a tablet computer, an appliance, or the like. In other instances, the device 1100 may be a set of hardware components. In FIG. 11 , the device 1100 may be configured to include a processor 1101 that is operatively coupled to an input/output interface 1105, a radio frequency (RF) interface 1109, a network connection interface 1111 , a random access memory (RAM) 1117, a read only memory (ROM) 1119, a storage medium 1121 , an operating system 1123, an application program 1125, data 1127, a communication subsystem 1131 , a power source 1133, another component, or any combination thereof. Specific devices may utilize all of the components shown in FIG. 11 , or only a subset of the components, and levels of integration may vary from device to device. Further, specific devices may contain multiple instances of a component, such as multiple processors, memories,

transceivers, transmitters, receivers, etc.

In FIG. 11 , the processor 1101 may be configured to process computer instructions and data. The processor 1101 may be configured as any sequential state machine operative to execute machine instructions stored as machine-readable computer programs in the memory, such as one or more hardware-implemented state machines (e.g., in discrete logic, FPGA, ASIC, etc.); programmable logic together with appropriate firmware; one or more stored-program, general-purpose processors, such as a microprocessor or Digital Signal Processor (DSP), together with appropriate software; or any combination of the above. For example, the processor 1101 may include two computer processors. In one definition, data is information in a form suitable for use by a computer. It is important to note that a person having ordinary skill in the art will recognize that the subject matter of this disclosure may be implemented using various operating systems or combinations of operating systems.

In the current embodiment, the input/output interface 1105 may be configured to provide a communication interface to an input device, output device, or input and output device. The device 1100 may be configured to use an output device via the input/output interface 1105. A person of ordinary skill will recognize that an output device may use the same type of interface port as an input device. For example, a USB port may be used to provide input to and output from the device 1100. The output device may be a speaker, a sound card, a video card, a display, a monitor, a printer, an actuator, an emitter, a smartcard, another output device, or any combination thereof. The device 1100 may be configured to use an input device via the input/output interface 1105 to allow a user to capture information into the device 1100. The input device may include a mouse, a trackball, a directional pad, a trackpad, a presence-sensitive input device, a display such as a presence-sensitive display, a scroll wheel, a digital camera, a digital video camera, a web camera, a microphone, a sensor, a smartcard, and the like. The presence-sensitive input device may include a digital camera, a digital video camera, a web camera, a microphone, a sensor, or the like to sense input from a user. The presence-sensitive input device may be combined with the display to form a presence- sensitive display. Further, the presence-sensitive input device may be coupled to the processor. The sensor may be, for instance, an accelerometer, a gyroscope, a tilt sensor, a force sensor, a magnetometer, an optical sensor, a proximity sensor, another like sensor, or any combination thereof. For example, the input device 1115 may be an accelerometer, a magnetometer, a digital camera, a microphone, and an optical sensor.

In FIG. 11 , the RF interface 1109 may be configured to provide a communication interface to RF components such as a transmitter, a receiver, and an antenna. The network connection interface 1111 may be configured to provide a communication interface to a network 1143a. The network 1143a may encompass wired and wireless communication networks such as a local-area network (LAN), a wide-area network (WAN), a computer network, a wireless network, a telecommunications network, another like network or any combination thereof. For example, the network 1143a may be a Wi-Fi network. The network connection interface 1111 may be configured to include a receiver and a transmitter interface used to communicate with one or more other nodes over a communication network according to one or more communication protocols known in the art or that may be developed, such as Ethernet, TCP/IP, SONET, ATM, or the like. The network connection interface 1111 may implement receiver and transmitter functionality appropriate to the communication network links (e.g., optical, electrical, and the like). The transmitter and receiver functions may share circuit components, software or firmware, or alternatively may be implemented separately. In this embodiment, the RAM 1117 may be configured to interface via the bus 1102 to the processor 1101 to provide storage or caching of data or computer instructions during the execution of software programs such as the operating system, application programs, and device drivers. In one example, the device 1100 may include at least one hundred and twenty-eight megabytes (128 Mbytes) of RAM. The ROM

1119 may be configured to provide computer instructions or data to the processor 1101. For example, the ROM 1119 may be configured to be invariant low-level system code or data for basic system functions such as basic input and output (I/O), startup, or reception of keystrokes from a keyboard that are stored in a non-volatile memory. The storage medium 1121 may be configured to include memory such as RAM, ROM, programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), magnetic disks, optical disks, floppy disks, hard disks, removable cartridges, flash drives. In one example, the storage medium 1121 may be configured to include an operating system 1123, an application program 1125 such as a web browser application, a widget or gadget engine or another application, and a data file 1127.

In FIG. 11 , the processor 1101 may be configured to communicate with a network 1143b using the communication subsystem 1131 . The network 1143a and the network 1143b may be the same network or networks or different network or networks. The communication subsystem 1131 may be configured to include one or more transceivers used to communicate with the network 1143b. For example, the communication subsystem 1131 may be configured to include one or more transceivers used to communicate with one or more remote transceivers of a radio access network (RAN) according to one or more communication protocols known in the art or that may be developed, such as IEEE 802.xx, CDMA, WCDMA, GSM, LTE, UTRAN, WiMax, or the like. Each transceiver may implement transmitter or receiver functionality appropriate to the RAN links (e.g., frequency allocations and the like). Further, the transmitter and receiver functions of each transceiver may share circuit components, software or firmware, or alternatively may be implemented separately.

In the current embodiment, the communication functions of the communication subsystem 1131 may include data communication, voice communication, multimedia communication, short-range communications such as Bluetooth, near-field

communication, location-based communication such as the use of the global positioning system (GPS) to determine a location, another like communication function, or any combination thereof. For example, the communication subsystem 1131 may include cellular communication, Wi-Fi communication, Bluetooth communication, and GPS communication. The network 1143b may encompass wired and wireless

communication networks such as a local-area network (LAN), a wide-area network (WAN), a computer network, a wireless network, a telecommunications network, another like network or any combination thereof. For example, the network 1143b may be a cellular network, a Wi-Fi network, and a near-field network. The power source 1133 may be configured to provide an alternating current (AC) or direct current (DC) power to components of the device 1100.

In FIG. 11 , the storage medium 1121 may be configured to include a number of physical drive units, such as a redundant array of independent disks (RAID), a floppy disk drive, a flash memory, a USB flash drive, an external hard disk drive, thumb drive, pen drive, key drive, a high-density digital versatile disc (HD-DVD) optical disc drive, an internal hard disk drive, a Blu-Ray optical disc drive, a holographic digital data storage (HDDS) optical disc drive, an external mini-dual in-line memory module (DIMM) synchronous dynamic random access memory (SDRAM), an external micro-DIMM SDRAM, a smartcard memory such as a subscriber identity module or a removable user identity (SIM/RUIM) module, other memory, or any combination thereof. The storage medium 1121 may allow the device 1100 to access computer-executable instructions, application programs or the like, stored on transitory or non-transitory memory media, to off-load data, or to upload data. An article of manufacture, such as one utilizing a communication system may be tangibly embodied in storage medium 1121 , which may comprise a computer-readable medium.

The functionality of the methods described herein may be implemented in one of the components of the device 1100 or partitioned across multiple components of the device 1100. Further, the functionality of the methods described herein may be implemented in any combination of hardware, software or firmware. In one example, the communication subsystem 1131 may be configured to include any of the

components described herein. Further, the processor 1101 may be configured to communicate with any of such components over the bus 1102. In another example, any of such components may be represented by program instructions stored in memory that when executed by the processor 1101 performs the corresponding functions described herein. In another example, the functionality of any of such components may be partitioned between the processor 1101 and the communication subsystem 1131. In another example, the non-computative-intensive functions of any of such components may be implemented in software or firmware and the computative-intensive functions may be implemented in hardware.

FIG. 12 illustrates one embodiment of a device 1200 for predicting macro signal levels in an enclosure in accordance with various aspects as described herein. In FIG. 12, the device 1200 may be configured to include a wireless receiver 1201 , a signal level measurement circuit 1203, a measurement location circuit 1205, a GPS receiver 1207, a prediction circuit 1209, a selection circuit 1211 , and a signal level calculator circuit 1213. The wireless receiver 1201 may be any component or collection of components that allows receiving a signal on a wireless connection. The signal level measurement circuit 1203 may be operationally coupled to the receiver and may receive signals from the wireless receiver 1201. Further, the signal level measurement circuit 1203 may be any component or collection of components that performs a measurement of a level of a received signal to obtain a signal level measurement. The GPS receiver 1207 may be any component or collection of components that allows receiving a GPS signal to determine a location of the device 1200. The measurement location circuit 1205 may be operationally coupled to the GPS receiver 1207 and the signal level measurement circuit 1203. Also, the measurement location circuit 1205 may be any component or collection of components that allows associating a signal level measurement with a location of the device 1200 when the signal level

measurement was performed.

In FIG. 12, the prediction circuit 1209 may be any component or collection of components that allows, for each of a plurality of perimeter signal level measurements, predicting a composite pathloss at a certain location in the enclosure. Further, the composite pathloss may correspond to one of the macro radio nodes. Also, the composite pathloss may include at least one of a free space loss, an outer excess loss and an inner excess loss. The selection circuit 1211 may be any component or collection of components that allows selecting one of the composite pathlosses that has a minimum composite pathloss at the certain location. The signal level calculator circuit 1213 may be any component or collection of components that allows determining a signal level at the certain location using the selected composite pathloss. Further, the signal level calculator circuit 1213 may output an indication of the signal level at the certain location. While some of the embodiments described herein are directed to LTE, application of the subject matter described herein may be directed to other wireless communication systems such as WDMA. For instance, the RSRP parameter used in LTE may be replaced by the RSCP parameter used in WCDMA.

ABBREVIATIONS:

Abbreviations Description

BBP baseband processing

CPRI common public radio interface

CU central unit

DL downlink

DU digital unit

IF intermediate frequency

IRU indoor radio unit

LTE long term evolution

OFDM orthogonal frequency division multiplexing

RB resource block

RE resource element

RP receiving point

RS reference signal

RSCP reference signal code power

RSRP reference signal received power

RU radio unit

SC-FDMA single-carrier frequency-division multiple-access

SINR signal-to-interference plus noise-ratio

TP transmission point

UE user equipment

UL uplink WCDMA wideband code division multiple access

ADDENDUM A: AUTOMATIC NODE DEPLOYMENT ALGORITHM

A.1 . BACKGROUND

Small cells are low-powered radio access nodes that operate in licensed and unlicensed spectrum. They are "small" compared to a mobile macro-cell, which may have a range of a few tens of kilometers. With mobile operators struggling to support the growth in mobile data traffic, small cells are a vital element to 3G and LTE data offloading, and many mobile network operators see small cells as vital to managing LTE Advanced spectrum more efficiently, compared to using just macro-cells.

In indoor environments with poor macro coverage and/or high capacity demand (enterprise customers, busy public indoor locations), dedicated indoor base stations need to be deployed. These indoor small cells will provide coverage, boost capacity and offload the existing macro network. This creates small cells in congested hot spot areas, such as enterprise buildings, train stations, airports, shopping malls, stadiums and exhibition centers.

Different variants of indoor small cells exist. Femto and pico base stations create small cells where each transmit and receiving point constitutes an own cell. Femto and pico base station are referred to as standalone small cells in the remainder of this document. Cells with multiple distributed transmission points (TPs) and receiving points (RPs) have been used to cover signal dead spots or to increase the system capacity. They are useful in indoor environments with complex floor plans, including inner walls and elevator shafts, which will cause many signal dead spots (or coverage holes). The signal processing of the small cells is assumed to be carried out at a central unit (CU), which includes signal generation on the downlink as well as signal combining and detection on the uplink. One cell is composed of N_n0de nodes, and one CU may serve up to N_ceii cells. An example of one such small cell with 4 nodes, each node, containing one TP and one RP is shown in FIG. 1 . Ericsson's Radio Dot System (RDS) is based on a similar architecture shown in FIG. 2, where nodes are called radio dots and the combining of the signals received at distributed RPs is performed in the indoor radio unit (IRU). For a distributed antenna system (DAS) a base station performs the signal generation including baseband and RF. The RF signal is then distributed to the TPs and RPs with a coaxial cable. On the downlink, the transmitted baseband signal is generated in the DU. The transmit signal stream is sent to the IRU over a CPRI link. At the IRU the signal is transformed to an analog waveform and sent to the TPs over a LAN cable. At the TPs the signal is radiated over the wireless channel to the UEs. On the uplink the signal transmitted from one UE will be received by all RPs, and the received signals of RPs will be sent through LAN cables to the IRU for further processing. Inside the IRU, the received signals will be combined, digitalized by the analog-to-digital (A/D) converter, and the resulting digital samples will be sent through the CPRI link to the DU, where all baseband processing (BBP) is carried out, such as (de)modulation, detection, channel estimation, decoding, etc.

One DU usually contains multiple BBPs, and is capable of supporting multiple IRUs. For the example in FIG. 2, one DU contains 4 BBPs, and serves 4 IRUs, and each IRU serves 4 dots.

FIG. 1 shows a structure of distributed small cells with pooled baseband. In FIG. 1 , each node n,, i=1 ,... ,4, contains a transmit point (TP) and receive point (RP). The received signals are combined in the central unit (CU).

FIG. 2 shows a structure of indoor small cells, with one digital unit which is connected to 4 IRUs, each with one CPRI link, and each IRU serves 4 dots using LAN cables in a star topology.

A.1 .1 . Cell selection

Mobile terminals are served by one cell of a base station. In order to associate mobiles to their serving base station a cell selection procedure is carried out. Moreover, to support mobility the cell selection needs to be continuously updated so to support hand-overs to other cells. Cell selection is standard specific, but the fundamental principles are common to all 3GPP based mobile communication standards, such as LTE and WCDMA.

To facilitate cell selection, the base stations emits a known reference signal with fixed power. The mobile measures the strength of the reference signal and reports back to the base. Initially, the mobile is assigned to the base station with the strongest reference signal. To facilitate handover from one cell to another, reference signal measurements are periodically updated. If the reference signal from a candidate cell exceeds that of the serving cell by x dB, where x is referred to as the handover margin, a handover procedure is triggered. In LTE a downlink subframe contains common reference symbols (CRS), which are known to the receiver and used as reference signal for cell selection. In particular, the mobile measures the reference signal received power (RSRP), which is the received signal strength of one LTE subcarrier, defined as RSRP = 30 - PL + 10 log₁₀ P/N_sc [dBm] Equation (A.1 )

Where PL denotes the pathloss in dB, P denotes the base station transmit power in Watts and N_sc accounts for the number of subcarriers.

For WCDMA the reference signal measured at the mobile is referred to reference signal code power (RSCP). While the discussion in this IvD is mainly referring to LTE and RSRP as a metric for the reference signal, a person skilled in the art will

acknowledge that this disclosure is applicable to other mobile communications systems in a straightforward way.

A.1 .2. Dominance

In order to ensure that indoor users are served by the inbuildng system, a dominance requirement is typically imposed. Dominance is said to be achieved if the RSRP of the inbuilding system is D dB stronger than that of the macro layer in d% of the floor area of a building. Typical values for the dominance D are between 3 and 10 dB, while the percentage of the floor area for which dominance need to be achieved is typically d=95%.

A.2. SOME OF THE PROBLEMS WITH EXISTING SOLUTIONS

State of the art tools for designing indoor systems, such as iBwave, rely on manual labor to place transmission points (TPs) in a building. This requires a skilled person to manually place TPs in the building and test whether the tested TP locations achieve the desired coverage target of the indoor system. The manual placement of nodes may possibly need to be repeated multiple times. This is a time consuming task. In order to scale the design of an inbuilding system to the increased number of small cell indoor deployments that is envisaged in the coming years, a more efficient procedure for node deployment is needed.

A.3. BRIEF SUMMARY

Instead of placing nodes manually we propose an automatic node deployment

(AND) algorithm that places the nodes autonomously, without the need for human interactions. All that is needed is the RSRP values of the small cell and macro layers. The AND algorithm is briefly outlined in the following:

1 . Generate signal levels of the macro layer.

2. Place new node: For each possible small cell location, determine the small cell coverage area, i.e. the area where the RSRP of the small cell signal exceeds the macro signal + the dominance requirement. Place the new node such that the coverage area of the small cell layer is maximized.

3. Iteration: after a new node is placed, repeat step 2 for already deployed

nodes.

4. Terminate if:

• full indoor dominance is achieved

• new node fails to add minimum coverage gain to small cell layer

The working principle of the AND algorithm is explained by means of the example floor depicted in FIG. 3.

• In FIG. 3A the macro signal pathloss is plotted for an example floor. The macro RSRP can be calculated from the pathloss PL by RSRP = 1 0 logio(P/N_sc) +30 - PL.

• The node location for the first node that maximizes indoor coverage is shown in FIG. 3A.

• In FIG. 3B a 2^nd node is added, such that the coverage area of the small cell layer (i.e. joint coverage of nodes 1 and 2, is maximized.

• FIG. 3C shows the small cell coverage area after the iteration step. That is, due to the additional 2^nd node, the location of the 1 ^st node was no longer optimal. Hence, the 1 ^st node is placed again. After that the 2^nd node is placed again, and so on. The iterations of replacing the already placed nodes is repeated until no further gain in small cell coverage is achieved.

• In FIG. 3D, a 3^rd node has been added, and the iteration step for all 3 nodes is carried out.

• The steps of successively adding nodes and the iteration step are repeated until the termination criterion is met. In FIG. 3E, full coverage of the small cell layer is achieved with 5 nodes.

FIG. 3 shows working principle of the AND algorithm. Nodes are iteratively placed in the floor, shown as dots. The colors on the plots refer to the pathloss of the macro signal. Floor locations shaded in dark grey mark locations where the small cell RSRP exceeds the macro RSRP.

A.4. SOME ADVANTAGES

To date, all available indoor small cell design tools rely on humans to place the transmission points in the building. By automatically deploying nodes, the cost can be reduced and the time between planning and deployment of an indoor system can be substantially shortened. This is envisaged as a fundamental pre-requisite to facilitate the envisaged growth in of small cells in the coming years.

A.5. DETAILED DESCRI PTION Unless otherwise stated, the following discussion applies to embodiments for deploying LTE based systems. However, application to WCDMA (and any other wireless transmission standard) is possible in a straightforward way, by replacing RSRP with the corresponding RSCP values.

A prerequisite for auto node deployment (AND) are samples of the signal strength (i.e. RSRP for LTE) for both the macro and the small cell layers on the floor of interest. In general, the received signal strength R may be expressed as a function of the (x,y) coordinates, R(x,y). One means of representing R(x,y) is to regularly sample the floor area. On each floor equidistant samples are taken every n meters on the x and y-axes on the horizontal plane. In FIG. 4, a floor plan of an office building is shown. Grey points represent samples, with one sample for n=1 meter on the 2D plane. Thick black lines represent outer contours of the building, red lines are thick walls (brick or concrete) and think black lines represent thin walls (dry walls).

Sampling of the floor area within a building may also be performed irregularly, e.g. a higher sampling density (less distance between adjacent samples) in corridor areas, rooms, or areas of specific interest.

A.5.1 . Defining the small cell coverage area

The small cell coverage area describes the area within a building where the signal strength of the strongest indoor small cell signal, denoted by R,{x,y) exceeds the signal strength of the strongest macro server given by

M(x,y) = max(10 log₁₀(R_m(x,y))) [dBm] Equation (A.2) where ft_m(x,y) denotes the macro RSRP at location (x,y) of macro server m. For LTE, 10

is given by the RSRP in Equation (A.1 ).The macro signal level may be determined from walk test measurements, where snapshots of M(x,y) are taken at selected building locations (x,y). If walk test measurements are not available M(x,y) may be set to a pre-defined value. Typical values for M(x,y) are -95 dBm (weak macro) to -75 dBm (strong macro). For the small cell signal strength we distinguish between stand-alone small cells, such as pico and femto base stations, and distributed antenna systems (DAS). For stand-alone small cells the small cell signal strength at location (x,y) is given by the strongest small cell server

S(x,y) = max(1 0 log₁₀(Fti (x,y))) [dBm] Equation (A.3) where f?,(x,y) denotes the small cell RSRP at location (x,y) of pico /. For a DAS the small cell signal strength at location (x,y) is the sum of the signals emitted by the TPs that belong to one cell

S(x,y) = 10 logjoCZi Rt(x, y)) [dBm] Equation (A.4)

A building location (x,y) is said to be covered by the small cell layer if the following condition is met

S(x,y) > M(x,y) + D Equation (A.5) where D is the dominance requirement. cov( , y) = (_{0 ;} ^yJ _e|_sewner ^J Equation (A.6)

Acov =∑_{x y} cov(x, y) - Ax - Ay Equation (A.7) where Ax^■ Ay is the area covered by one building location (x,y), i.e. the distance between two adjacent sampling points on the considered building floor.

A.5.2. Auto node deployment algorithm

The AND algorithm is composed of the following steps:

1 . Generate signal levels of the macro layer M(x,y) in Equation (A.2).

2. Place new node: For each possible small cell location, determine the small cell coverage area, i.e. the area where condition Equation (A.5) is true.

• For each potential node location (x,y), determine the small cell signal level S(x,y) according to Equation (A.3) and Equation (A.4), for standalone small cells and DAS, respectively. • Place the new node such that the coverage area of the small cell layer, Acov in Equation (A.7), is maximized.

3. Iteration: after a new node is placed, repeat step 2 for already deployed

nodes.

· This involves a loop over all deployed nodes

• At instance k of the loop, one node is replaced. That means, the

location of the node n, is moved such that S(x,y) is maximized. Note that according to Equation (A.3) and Equation (A.4), S(x,y) is the aggregated signal strength of the small cell layer, i.e. the joint

coverage area of all deployed nodes.

• When one node has been moved, than the location of the other nodes may no longer be optimal, in the sense that A_cov is maximized. Hence, the iteration loop may be repeated as long as no further coverage gain is achieved. The coverage gain from iteration k - k+1 is denoted by AA = A_C0V(k+1 ) - A_cov(k).

4. Terminate if:

• Full indoor dominance is achieved, i.e. A_cov approaches the floor area

• New node fails to add minimum coverage gain ΔΑ to the small cell

layer

A.5.3. Geometry based metric

There may be candidate node locations that achieve approximately the same coverage area A_cov. In this case, an alternative metric that allows choosing the most appropriate node location is desirable. One such metric is the geometry based sumrate achieved by the indoor deployment. For this metric, we calculate the geometry at building location (x,y) as follows

^C ^> = (Σ,.,Ε^ ,^, Equation (A.8) where N_Q denotes thermal noise. Given the geometry, the sumrate can be approximated by the truncated Shannon bound, which is in the form

( ∑*_,y log₂(501) 10 log₁₀(G(x,y)) > 30 dB

C = \∑x,y \OQ₂ (l + G(x, y)/a) ; -10 dB < 10 log₁₀(G(x, y)) < 30 dBEquation (A.9) ( 0 10 log₁₀(G(x,y)) < -10 dB Provided that A_cov is similar for multiple candidate node locations, the node location that maximizes C in Equation (A.9) is selected as the new node.

A.5.4. Sorting nodes in the iteration step

The AND algorithm is an iterative gradient based optimization algorithm, which is inherently suboptimal. Hence, AND may get stuck in a local maximum for A_00v. In order to avoid AND converging to a local optimum, the order of replacing the nodes in the iteration step 3 of Section A.5.2 may be modified.

• One possibility is to randomly choose the order of nodes in the iteration loop

• One further embodiment is to sort the nodes in reverse order with respect to the distance the nodes were moved in the previous iteration k-1 . This means that nodes that have not been moved in iteration k-1 , will be the first to be replaced in iteration k. This allows those nodes to adjust their location, which are potentially affected by the movement of adjacent nodes.

In one example, a gradient based optimization algorithm is proposed that automatically places nodes in a building, such that the coverage area of the small cell layer is maximized. The coverage based utility may be complemented by a utility that maximizes the geometry based sumrate of the small cell deployment.

ADDENDUM B: PREDICTING MACRO SIGNAL LEVELS IN INDOOR

ENVIRONMENTS

B.1 . BACKGROUND:

Since spectrum is a scarce and expensive resource, small cells are typically co- channel deployed with the existing macro network. This means that the small cells operate in the same band as the macro network, given rise to interference between the small cell and macro layers. In indoor environments with poor macro coverage and/or high capacity demand (enterprise customers, busy public indoor locations), dedicated indoor base stations need to be deployed. These indoor small cells will provide coverage, boost capacity and offload the existing macro network. This creates small cells in congested hot spot areas, such as enterprise buildings, train stations, airports, shopping malls, stadiums and exhibition centers.

Different variants of indoor small cells exist. Femto and pico base stations create small cells where each transmit and receiving point constitutes an own cell. Femto and pico base station are referred to as standalone small cells in the remainder of this document. Cells with multiple distributed transmission points (TPs) and receiving points (RPs) have been used to cover signal dead spots or to increase the system capacity. They are useful in indoor environments with complex floor plans, including inner walls and elevator shafts, which will cause many signal dead spots (or coverage holes). The signal processing of the small cells is assumed to be carried out at a central unit (CU), which includes signal generation on the downlink as well as signal combining and detection on the uplink. One cell is composed of Nnode nodes, and one CU may serve up to Ncell cells. An example of one such small cell with 4 nodes, each node, containing one TP and one RP is shown in FIG. 1. Ericsson's Radio Dot System (RDS) is based on a similar architecture shown in FIG. 2, where nodes are called radio dots and the combining of the signals received at distributed RPs is performed in the indoor radio unit (IRU). For a distributed antenna system (DAS) a base station performs the signal generation including baseband and RF. The RF signal is then distributed to the TPs and RPs with a coaxial cable.

On the downlink, the transmitted baseband signal is generated in the DU. The transmit signal stream is sent to the IRU over a CPRI link. At the IRU the signal is transformed to an analog waveform and sent to the TPs over a LAN cable. At the TPs the signal is radiated over the wireless channel to the UEs. On the uplink the signal transmitted from one UE will be received by all RPs, and the received signals of RPs will be sent through LAN cables to the IRU for further processing. Inside the IRU, the received signals will be combined, digitalized by the analog-to-digital (A/D) converter, and the resulting digital samples will be sent through the CPRI link to the DU, where all baseband processing (BBP) is carried out, such as (de)modulation, detection, channel estimation, decoding, etc. One DU usually contains multiple BBPs, and is capable of supporting multiple IRUs. For the example in FIG. 2, one DU contains 4 BBPs, and serves 4 IRUs, and each IRU serves 4 dots.

B.1 .1 . Cell selection

To facilitate cell selection, the base stations emits a known reference signal with fixed power. The mobile measures the strength of the reference signal and reports back to the base. Initially, the mobile is assigned to the base station with the strongest reference signal. To facilitate handover from one cell to another, reference signal measurements are periodically updated. If the reference signal from a candidate cell exceeds that of the serving cell by x dB, where x is referred to as the handover margin, a handover procedure is triggered.

In LTE a downlink subframe contains common reference symbols (CRS), which are known to the receiver and used as reference signal for cell selection. In particular, the mobile measures the reference signal received power (RSRP), which is the received signal strength of one LTE subcarrier, defined as

RSRP = 30 - PL + 10 log₁₀(P/N_sc) [dBm] Equation (B.1 ) where PL denotes the pathloss in dB, P denotes the base station transmit power in Watts and N_sc accounts for the number of subcarriers.

For WCDMA the reference signal measured at the mobile is referred to reference signal code power (RSCP). While the discussion in this IvD is mainly referring to LTE and RSRP as a metric for the reference signal, a person skilled in the art will acknowledge that this disclosure is applicable to other mobile communications systems in a straightforward way.

B.1 .2. Dominance

B.1 .3. Setting the macro signal levels:

To date, two methods are commonly used to assess the macro signal levels inside a building:

• Fixed macro signal level: the macro level is set according to a pre-defined value throughout the building. For LTE, this could be an RSRP between -95 dBm (weak macro) to -75dBm (strong macro)

• Walk test measurements: a person walks through the building and takes measurements of the macro signal levels at a number of locations inside the building

B.1 .4. Indoor channel modeling:

In order to describe the macro signal levels inside a building more accurately, some indoor propagation model is needed. In the following, two commonly used propagation models are briefly introduced. However, we emphasize that for the subject of this disclosure, any indoor propagation model may be used.

B.1 .4.1 . Loss per meter model:

This is the most basic indoor propagation model, which is applicable when no detailed indoor floorplans are available. The indoor pathloss (in dB) is expressed by the free space pathloss plus an excess loss, which describes attenuations of the radio waves penetrating through walls, as well as reflections/diffractions by obstacles. Walls and obstacles are not explicitly modeled; rather the attenuation is expressed by a loss per meter degradation on the excess loss. The pathloss for the loss per meter model is given by: PL(d) = FSPL(d) + L^■ d [dB] Equation (B.2) where the constant L with unit [dB/m] accounts for the excess loss and is set according to the building type. For open landscape floorplans a typical value is L = 0.2 dB/m, while for closed office areas L = 0.6 dB/m and for residential buildings L = 0.8 dB/m. The free space loss in Equation (B.2) is in the form

FSPL(d) = 20 log₁₀ (^π^ά) [dB] where f_c is the carrier frequency and c is the speed of light. The distance d denotes the Euclidian distance between the transmitter and receiver.

B.1 .4.2. Keenan-Motley channel model:

The Keenan-Motley channel model (such as described in J. M. Keenan and A. J.

Motley, "Radio coverage in buildings," British telecom technology Journal 8.1 (1990), pgs. 19-24) is widely used, but requires the location of the interior walls, as well as their respective wall attenuation. The pathloss for the Keenan-Motley channel model is given by:

PL(d) = FSPL(d) + W - k [dB] Equation (B.3)

The constant W with unit [dB] accounts for the penetration loss of the interior walls, and k denotes the number of walls that are crossed between the transmitter and receiver. Clearly, if walls have different wall losses, then w becomes different for each wall type.

B.2. SOME PROBLEMS WITH EXISTING SOLUTIONS

For most indoor deployments, stringent requirements on the dominance of the indoor system are set, such as demanding the small cell signal to exceed the macro signal by 6 to 8 dB at 95% of the building floor area. Setting a fixed macro signal level of x dBm throughout the building fails to acknowledge the fact that the macro signal levels are impinge from the outer walls and decay as they traverse deeper inside the building. Hence, a fixed macro signal level inherently leads to an overprovisioning of the indoor system. An accurate estimate of the macro signal levels may facilitate indoor

deployments with fewer nodes, which in turn reduces cost of the indoor system.

B.3. BRIEF SUMMARY

Instead of assuming fixed macro signal levels over the entire floor area, we propose to set the signal levels from the macro network at the location just inside the outer walls of the building. These wall locations are used as reference points. Starting from the outer perimeters of the building, indoor propagation models are used to determine the macro signal levels at all floor locations.

The basic principle of the macro signal level prediction is explained with the aid of the floorplan depicted in FIG. 7. It is assumed that there is a strong macro signal impinging from the eastern side of the building with 10 dB stronger signal levels than on the remaining outer walls. The macro signal strength at the indoor location marked with the green dot in FIG. 7 can be derived by calculating the excess loss from a number of wall reference locations to the green dot. Then that candidate pathloss is selected, which gives the minimum composite pathloss.

Repeating the calculations for all indoor locations, the macro signal levels are obtained as shown in FIG. 8. It is seen that the macro pathloss gets weaker when moving deeper inside the building. Moreover, higher macro pathlosses are observed inside rooms, especially those surrounded by thick walls (marked in red).

FIG. 7 shows an example floorplan of an office floor. Thick black lines represent outer contours of the building, red lines are thick walls (brick or concrete) and think black lines represent thin walls (dry walls). It is assumed that there is a strong macro signal impinging from the eastern side of the building with 10 dB stronger signal levels than on the remaining outer walls. The macro signal strength at the indoor location marked with the green dot is derived by calculating the excess loss from the 4 wall reference locations to the green dot marked with blue arrows. That candidate pathloss is selected as macro pathloss, which yields the minimum composite pathloss. FIG. 8 shows predicted macro signal pathloss for the floor plan of FIG. 7.

B.4. SOME ADVANTAGES OF THE PROPOSED SOLUTION

By having more accurate knowledge of the macro signal level inside a building a more realistic indoor system may be deployed. This may potentially result in fewer nodes that are deployed in a given venue, while still meeting the required level of dominance.

B.5. DETAILED DESCRIPTION

Unless otherwise stated, the following discussion applies to embodiments for deploying LTE based systems. However, application to WCDMA (and any other wireless transmission standard) is possible in a straightforward way, by replacing RSRP with the corresponding RSCP values.

For LTE, the pathloss is related to RSRP according to Equation (B.1 ), that is: RSRP = 30 - PL + 10 log₁₀(P/N_sc), [dBm]

Provided that the transmit power and the number of subcarriers N_sc are fixed, there is a one to one relationship between pathloss and RSRP. Hence, if the macro pathloss is known, it is straight forward to determine the RSRP and vice versa.

As outlined in Section B.3, the macro signal prediction comprises the following steps

• set the signal level at the outer perimeters of the building, just inside the outer walls

• calculate the composite pathloss of the macro signal from the wall reference points to other indoor locations further inside the building denoted by coordinates (x_u,y_u)

• select the macro pathloss for position (x_u,y_u), which gives the minimum

composite pathloss

B.5.1 . Set the signal levels at the wall reference locations

We assume that we have some a priori knowledge on the macro signal levels inside the building near the outer walls. Let the macro RSRP at the wall reference point with coordinates (x_w,y_w) be denoted by RSRP_waii(Xw,yw)- For convenience this can be translated to a pathloss between the macro base station and the wall reference point

PLwall(Xwjyw ) = 30 - RSRP_Waii(Xw,Vw) +10 log₁₀(P/N_sc) Equation (B.4) The pathloss divides into free space pathloss and the excess loss. We

emphasize the importance of separating the pathloss into free space loss and excess loss, due to the distance dependency of the free space loss.

The macro base station with the strongest RSRP at (x_w,yw) is mounted at a distance d_out away from the building of interest. If d_out is not known, then a default value e.g. d_out = 100 m may be chosen. When the macro signal propagates from the base station to the wall reference point, the outer walls of the building are penetrated as well as some possible obstacles on the way. This is captured in the outer excess loss, which is given by

Xout(Xwjyw) PLwall(Xwiyw ) - FSPL(doui) Equation (B.5)

= 30 - RSRP_waii(Xw,yw) - FSPL(d_out) +10 log₁₀(P/N_sc)

where FSPL(d_out) accounts for the free space pathloss of distance d_out- B.5.2. Path loss between wall reference points and indoor locations of interest

Given the outer excess loss, X_out, derived in Equation (B.5), the pathloss candidate of the macro signal impinging from wall point (x_w,y_w) can be expressed as

PI_w(Xi,yi) = FSPL(dout+din) + X_out(Xw,yw) + Xin.w Equation (B.6) In Equation (B.6) the term FSPL(d_out+di_n) comprises the free space loss from the macro base to the wall reference point and further to the indoor location at (χ,,Υί). The inner excess loss Xi_n,_w from (x_w,yw) to (χ,,γ,) is determined by an appropriate indoor channel model, as described in Section B.1 .4. For the Keenan-Motley channel model in Equation (B.3), the inner excess loss yields X_in,_w = kW.

The number of wall reference points that should be used to calculate Equation

(B.6) is a design parameter. There should be at least one wall reference point from each side of the building.

B.5.3. Determine the macro pathloss

The final step is to select the minimum pathloss from all wall points by finding the minimum:

PLO^y;) = min_w Pl^O^y;) Equation (B.7)

Given Equation (B.7), it is straightforward to calculate the macro RSRP by evaluating Equation (B.1 ).

B.5.4. Using walk test data

If measurements from a walk test are available, the way-points where

measurements samples are taken are not always taken close to the outer perimeters of the building. In this case, it is necessary to trace back the signal from the measurement point to the wall reference point. Starting from Equation (B.6), the outer excess loss can be determined by solving

Xout (Xw,yw ) = FSPL(doui+d_in) + Xin.s - PL(x_s,y_s) Equation (B.8) where PL(x_s,y_s) denotes the pathloss measured at the measurement way-point. The inner excess loss Xi_n,_s from the measurement point to the wall reference point may be determined by invoking an indoor channel model, in line with the methods described in Section B.5.2. Then the pathloss as the wallpoint can be calculated by transforming Equation (B.5) as follows

PLwaii(Xw,yw) = FSPL(d_out) + Xout( w,y_w) Equation (B.9) With PL_waii(x_m,y_w) the macro signal level can be calculated on all indoor positions in the same way as described in Sections B.5.2 and B.5.3.

In analogy to the macro pathloss calculations, it is possible to calculate Lwaii(Xw,yw) at various wall reference points. Then that wall point is selected that gives the minimum pathloss.

In one exemplary embodiment, a method may include applying known indoor propagation models to derive a more accurate representation of the macro signal levels inside a building.

In one exemplary embodiment, a method of determining where in an enclosure to place individual radio nodes for collectively providing radio coverage in the enclosure may include, for each of multiple candidate locations in the enclosure, obtaining an interference metric reflecting an extent of interference at that location. Further, the method may include determining to tentatively place an initial radio node at one of the candidate locations. For each of one or more iterations, the method may include, for each of the multiple candidate locations in the enclosure, obtaining an enclosure-wide coverage metric reflecting an extent of radio coverage that would be collectively provided across the enclosure by any tentatively placed nodes in combination with an additional radio node, if the additional radio node were to be placed at that candidate location. Also, for each of the one or more iterations, the method may include identifying which one of the enclosure-wide coverage metrics reflects the greatest extent of radio coverage that would be collectively provided across the enclosure and determining whether to tentatively place the additional radio node at the candidate location for which the identified enclosure-wide coverage metric was obtained.

In another exemplary embodiment, for each of the one or more iterations, the method may include obtaining a location-specific coverage metric reflecting an extent of radio coverage that would be provided at that location if the additional radio node were to be placed at that location, in view of the interference metric obtained for that location.

In another exemplary embodiment, for each of the one or more iterations, the method may include re-determining at which of the candidate locations to place each of one or more radio nodes that were tentatively placed in a previous iteration, after determining at which candidate location to tentatively place the additional radio node. In another exemplary embodiment, the method may include performing said one or more iterations until tentative placement of an additional radio node achieves a defined extent of collective radio coverage in the enclosure.

In another exemplary embodiment, the method may include performing said one or more iterations until tentative placement of an additional radio node fails to achieve a defined improvement in the extent of collective radio coverage in the enclosure.

In one exemplary embodiment, a device for determining where in an enclosure to place individual radio nodes for collectively providing radio coverage in the enclosure may include a memory configured to store data and computer-executable instructions and a processor operatively coupled to the memory. For each of multiple candidate locations in the enclosure, the processor and memory may be configured to obtain an interference metric reflecting an extent of interference at that location. Further, the processor and memory may be configured to determine to tentatively place an initial radio node at one of the candidate locations. For each of one or more iterations, the processor and memory may be configured to, for each of the multiple candidate locations in the enclosure, obtain an enclosure-wide coverage metric reflecting an extent of radio coverage that would be collectively provided across the enclosure by any tentatively placed nodes in combination with an additional radio node, if the additional radio node were to be placed at that candidate location. For each of the one or more iterations, the processor and memory may be configured to identify which one of the enclosure-wide coverage metrics reflects the greatest extent of radio coverage that would be collectively provided across the enclosure and determine whether to tentatively place the additional radio node at the candidate location for which the identified enclosure-wide coverage metric was obtained.

In one exemplary embodiment, a non-transitory computer-readable medium encoded with a computer program, the computer program comprising computer- executable instructions that when executed by a processor causes the processor to perform operations, wherein the operations may be configured to, for each of multiple candidate locations in the enclosure, obtain an interference metric reflecting an extent of interference at that location. Further, the operations may be configured to determine to tentatively place an initial radio node at one of the candidate locations. For each of one or more iterations, the operations may be configured to, for each of the multiple candidate locations in the enclosure, obtain an enclosure-wide coverage metric reflecting an extent of radio coverage that would be collectively provided across the enclosure by any tentatively placed nodes in combination with an additional radio node, if the additional radio node were to be placed at that candidate location. Also, for each of the one or more iterations, the operations may be configured to identify which one of the enclosure-wide coverage metrics reflects the greatest extent of radio coverage that would be collectively provided across the enclosure and to determine whether to tentatively place the additional radio node at the candidate location for which the identified enclosure-wide coverage metric was obtained.

In one exemplary embodiment, a computer-implemented method of performing transmission node deployment in an enclosure may include receiving a plurality of signal level measurements corresponding to one or more interfering nodes. Each signal level measurement may be determined at one of a plurality of measurement locations in the enclosure. Further, the method may include estimating a plurality of coverage areas in the enclosure by an enclosure node. Each coverage area may correspond to the enclosure node being positioned at one of a plurality of candidate placement locations. Also, the method may include selecting, using the plurality of signal level

In another exemplary embodiment, the plurality of coverage areas may be associated with downlink transmission by the enclosure node.

In another exemplary embodiment, at least one of the one or more interfering nodes may be located outside of the enclosure.

In another exemplary embodiment, at least one of the one or more interfering nodes may be located in the enclosure.

In another exemplary embodiment, the method may include estimating the plurality of coverage areas in the enclosure by the enclosure node includes for each coverage area by determining a plurality of signal level estimates for one of the plurality of candidate placement locations. Further, each signal level estimate may be

determined at one of a plurality of estimate locations in the enclosure. In another exemplary embodiment, the method may include determining a dominance of the enclosure using the plurality of signal level measurements and the maximum collective coverage area. Further, the method may include outputting the indication of the one of the plurality of candidate placement locations in the enclosure that corresponds to the selected coverage area for use in positioning the enclosure node responsive to determining that the dominance of the enclosure is less than a dominance threshold.

In another exemplary embodiment, the method may include determining a coverage gain of the selected coverage area using the selected coverage area and the collective coverage area. Also, the method may including outputting the indication of the one of the plurality of candidate placement locations in the enclosure that corresponds to the selected coverage area for use in positioning the enclosure node responsive to determining that the coverage gain is at least a coverage gain threshold.

In one exemplary embodiment, a device for performing transmission node deployment in an enclosure may include a memory configured to store data and computer-executable instructions and a processor operatively coupled to the memory. The processor and the memory may be configured to receive a plurality of signal level measurements corresponding to one or more interfering nodes. Each signal level measurement may be determined at one of a plurality of measurement locations in the enclosure. Further, the processor and the memory may be configured to estimate a plurality of coverage areas in the enclosure by an enclosure node. Each coverage area may correspond to the enclosure node being positioned at one of a plurality of candidate placement locations. Also, the processor and the memory may be configured to select, using the plurality of signal level measurements, one of the plurality of coverage areas that in combination with a collective coverage area of one or more other enclosure nodes provides a maximum collective coverage area in the enclosure to obtain a selected coverage area. In addition, the processor and the memory may be configured to output an indication of one of the plurality of candidate placement locations in the enclosure that corresponds to the selected coverage area for use in positioning the enclosure node.

In one exemplary embodiment, a non-transitory computer-readable medium encoded with a computer program, the computer program comprising computer- executable instructions that when executed by a processor causes the processor to perform operations, wherein the operations may be configured to receive a plurality of signal level measurements corresponding to one or more interfering nodes. Each signal level measurement may be determined at one of a plurality of measurement locations in the enclosure. Further, the operations may be configured to estimate a plurality of coverage areas in the enclosure by an enclosure node. Each coverage area may correspond to the enclosure node being positioned at one of a plurality of candidate placement locations. Also, the operations may be configured to select, using the plurality of signal level measurements, one of the plurality of coverage areas that in combination with a collective coverage area of one or more other enclosure nodes provides a maximum collective coverage area in the enclosure to obtain a selected coverage area. In addition, the operations may be configured to output an indication of one of the plurality of candidate placement locations in the enclosure that corresponds to the selected coverage area for use in positioning the enclosure node.

In one exemplary embodiment, a computer-implemented method of predicting a signal level in an enclosure may include receiving a plurality of perimeter signal level measurements corresponding to one or more macro nodes. Each perimeter signal level measurement may be determined near an outer perimeter in the enclosure. Further, the method may include, for each of the plurality of perimeter signal level

measurements, predicting a composite pathloss at a certain location in the enclosure. The composite pathloss may correspond to one of the macro nodes. Also, the method may include selecting one of the composite pathlosses that has a minimum composite pathloss at the certain location in the enclosure. In addition, the method may include determining the signal level at the certain location using the selected composite pathloss and outputting an indication of the signal level at the certain location in the enclosure.

The previous detailed description is merely illustrative in nature and is not intended to limit the present disclosure, or the application and uses of the present disclosure. Furthermore, there is no intention to be bound by any expressed or implied theory presented in the preceding field of use, background, summary, or detailed description. The present disclosure provides various examples, embodiments and the like, which may be described herein in terms of functional or logical block elements. The various aspects described herein are presented as methods, devices (or

apparatus), systems, or articles of manufacture that may include a number of

components, elements, members, modules, nodes, peripherals, or the like. Further, these methods, devices, systems, or articles of manufacture may include or not include additional components, elements, members, modules, nodes, peripherals, or the like.

Furthermore, the various aspects described herein may be implemented using standard programming or engineering techniques to produce software, firmware, hardware (e.g., circuits), or any combination thereof to control a computing device to implement the disclosed subject matter. It will be appreciated that some embodiments may be comprised of one or more generic or specialized processors such as

microprocessors, digital signal processors, customized processors and field

programmable gate arrays (FPGAs) and unique stored program instructions (including both software and firmware) that control the one or more processors to implement, in conjunction with certain non-processor circuits, some, most, or all of the functions of the methods, devices and systems described herein. Alternatively, some or all functions could be implemented by a state machine that has no stored program instructions, or in one or more application specific integrated circuits (ASICs), in which each function or some combinations of certain of the functions are implemented as custom logic circuits. Of course, a combination of the two approaches may be used. Further, it is expected that one of ordinary skill, notwithstanding possibly significant effort and many design choices motivated by, for example, available time, current technology, and economic considerations, when guided by the concepts and principles disclosed herein will be readily capable of generating such software instructions and programs and ICs with minimal experimentation.

The term "article of manufacture" as used herein is intended to encompass a computer program accessible from any computing device, carrier, or media. For example, a computer-readable medium may include: a magnetic storage device such as a hard disk, a floppy disk or a magnetic strip; an optical disk such as a compact disk (CD) or digital versatile disk (DVD); a smart card; and a flash memory device such as a card, stick or key drive. Additionally, it should be appreciated that a carrier wave may be employed to carry computer-readable electronic data including those used in transmitting and receiving electronic data such as electronic mail (e-mail) or in accessing a computer network such as the Internet or a local area network (LAN). Of course, a person of ordinary skill in the art will recognize many modifications may be made to this configuration without departing from the scope or spirit of the subject matter of this disclosure. Throughout the specification and the embodiments, the following terms take at least the meanings explicitly associated herein, unless the context clearly dictates otherwise. Relational terms such as "first" and "second," and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. The term "or" is intended to mean an inclusive "or" unless specified otherwise or clear from the context to be directed to an exclusive form. Further, the terms "a," "an," and "the" are intended to mean one or more unless specified otherwise or clear from the context to be directed to a singular form. The term "include" and its various forms are intended to mean including but not limited to. References to "one

embodiment," "an embodiment," "example embodiment," "various embodiments," and other like terms indicate that the embodiments of the disclosed technology so described may include a particular function, feature, structure, or characteristic, but not every embodiment necessarily includes the particular function, feature, structure, or characteristic. Further, repeated use of the phrase "in one embodiment" does not necessarily refer to the same embodiment, although it may. The terms "substantially," "essentially," "approximately," "about" or any other version thereof, are defined as being close to as understood by one of ordinary skill in the art, and in one non-limiting embodiment the term is defined to be within 10%, in another embodiment within 5%, in another embodiment within 1 % and in another embodiment within 0.5%. A device or structure that is "configured" in a certain way is configured in at least that way, but may also be configured in ways that are not listed.

Claims

CLAIMS What is claimed is:

1 . A computer-implemented method of determining where in an enclosure to place individual radio nodes for collectively providing radio coverage in the enclosure, comprising:

for each of multiple candidate locations in the enclosure, obtaining an

interference metric reflecting an extent of interference at that location; determining to tentatively place an initial radio node at one of the candidate

locations; and

for each of one or more iterations:

for each of the multiple candidate locations in the enclosure, obtaining an enclosure-wide coverage metric reflecting an extent of radio coverage that would be collectively provided across the enclosure by any tentatively placed nodes in combination with an additional radio node, if the additional radio node were to be placed at that candidate location;

identifying which one of the enclosure-wide coverage metrics reflects the greatest extent of radio coverage that would be collectively provided across the enclosure; and

determining to tentatively place the additional radio node at the candidate location for which the identified enclosure-wide coverage metric was obtained.

2. The method of claim 1 , further comprising, for each of the one or more iterations, obtaining a location-specific coverage metric for each enclosure-wide location reflecting an extent of radio coverage that would be provided at that enclosure-wide location, if the additional radio node were to be placed at that candidate location, in view of the interference metric obtained for that enclosure-wide location;

3. The method of claim 1 , further comprising, for each of the one or more iterations, re-determining at which of the candidate locations to place each of one or more radio nodes that were tentatively placed in a previous iteration, after determining at which candidate location to tentatively place the additional radio node.

4. The method of any of claims 1 -2, further comprising performing said one or more iterations until tentative placement of an additional radio node achieves a defined extent of collective radio coverage in the enclosure.

5. The method of any of claims 1 -2, further comprising performing said one or more iterations until tentative placement of an additional radio node fails to achieve a defined improvement in the extent of collective radio coverage in the enclosure.

6. A device for determining where in an enclosure to place individual radio nodes for collectively providing radio coverage in the enclosure, comprising:

a memory configured to store data and computer-executable instructions;

a processor operatively coupled to the memory, wherein the processor and

memory are configured to:

for each of multiple candidate locations in the enclosure, obtain an

interference metric reflecting an extent of interference at that location;

determine to tentatively place an initial radio node at one of the candidate locations; and

for each of one or more iterations:

for each of the multiple candidate locations in the enclosure, obtain an enclosure-wide coverage metric reflecting an extent of radio coverage that would be collectively provided across the enclosure by any tentatively placed nodes in combination with an additional radio node, if the additional radio node were to be placed at that candidate location;

identify which one of the enclosure-wide coverage metrics reflects the greatest extent of radio coverage that would be collectively provided across the enclosure; and determine to tentatively place the additional radio node at the candidate location for which the identified enclosure-wide coverage metric was obtained.

7. A non-transitory computer-readable medium encoded with a computer program, the computer program comprising computer-executable instructions that when executed by a processor causes the processor to perform operations, wherein the operations are configured to:

for each of multiple candidate locations in the enclosure, obtain an interference metric reflecting an extent of interference at that location; determine to tentatively place an initial radio node at one of the candidate

locations; and

for each of one or more iterations:

identify which one of the enclosure-wide coverage metrics reflects the greatest extent of radio coverage that would be collectively provided across the enclosure; and

determine to tentatively place the additional radio node at the candidate location for which the identified enclosure-wide coverage metric was obtained.

8. A computer-implemented method of performing transmission node deployment in an enclosure, comprising:

receiving a plurality of signal level measurements corresponding to one or more interfering nodes, wherein each signal level measurement is determined at one of a plurality of measurement locations in the enclosure;

estimating a plurality of coverage areas in the enclosure by an enclosure node, wherein each coverage area corresponds to the enclosure node being positioned at one of a plurality of candidate placement locations;

selecting, using the plurality of signal level measurements, one of the plurality of coverage areas that in combination with a collective coverage area of one or more other enclosure nodes provides a maximum collective coverage area in the enclosure to obtain a selected coverage area; and outputting an indication of one of the plurality of candidate placement locations in the enclosure that corresponds to the selected coverage area for use in positioning the enclosure node.

9. The method of claim 8, wherein the plurality of coverage areas are associated with downlink transmission by the enclosure node.

10. The method of claim 8, wherein at least one of the one or more interfering nodes are located outside of the enclosure.

1 1 . The method of claim 8, wherein at least one of the one or more interfering nodes are located in the enclosure.

12. The method of claim 8, wherein estimating the plurality of coverage areas in the enclosure by the enclosure node includes for each coverage area:

determining a plurality of signal level estimates for one of the plurality of

candidate placement locations, wherein each signal level estimate is determined at one of a plurality of estimate locations in the enclosure.

13. The method of claim 8, further comprising:

determining a dominance of the enclosure using the plurality of signal level measurements and the maximum collective coverage area; and wherein outputting is responsive to determining that the dominance of the

enclosure is less than a dominance threshold.

14. The method of claim 8, further comprising:

determining a coverage gain of the selected coverage area using the selected coverage area and the collective coverage area; and

wherein outputting is responsive to determining that the coverage gain is at least a coverage gain threshold.

15. A device for performing transmission node deployment in an enclosure, comprising:

a memory configured to store data and computer-executable instructions;

a processor operatively coupled to the memory, wherein the processor and

memory are configured to:

receive a plurality of signal level measurements corresponding to one or more interfering nodes, wherein each signal level measurement is determined at one of a plurality of measurement locations in the enclosure;

estimate a plurality of coverage areas in the enclosure by an enclosure node, wherein each coverage area corresponds to the enclosure node being positioned at one of a plurality of candidate placement locations;

select, using the plurality of signal level measurements, one of the

plurality of coverage areas that in combination with a collective coverage area of one or more other enclosure nodes provides a maximum collective coverage area in the enclosure to obtain a selected coverage area; and

output an indication of one of the plurality of candidate placement

locations in the enclosure that corresponds to the selected coverage area for use in positioning the enclosure node.

16. A non-transitory computer-readable medium encoded with a computer program, the computer program comprising computer-executable instructions that when executed by a processor causes the processor to perform operations, wherein the operations are configured to:

select, using the plurality of signal level measurements, one of the plurality of coverage areas that in combination with a collective coverage area of one or more other enclosure nodes provides a maximum collective coverage area in the enclosure to obtain a selected coverage area; and output an indication of one of the plurality of candidate placement locations in the enclosure that corresponds to the selected coverage area for use in positioning the enclosure node.

17. A computer-implemented method of predicting a signal level in an enclosure, comprising:

receiving a plurality of perimeter signal level measurements corresponding to one or more macro radio nodes, wherein each perimeter signal level measurement is determined near an outer perimeter in the enclosure; for each of the plurality of perimeter signal level measurements, predicting a composite pathloss at a certain location in the enclosure, wherein the composite pathloss corresponds to one of the macro radio nodes;

selecting one of the composite pathlosses that has a minimum composite

pathloss at the certain location in the enclosure;

determining the signal level at the certain location using the selected composite pathloss; and

outputting an indication of the signal level at the certain location in the enclosure.

18. The method of claim 17, wherein the composite signal includes at least one of a free space loss, an outer excess loss and an inner excess loss.

19. A device for predicting a signal level in an enclosure, comprising:

a memory configured to store data and computer-executable instructions;

a processor operatively coupled to the memory, wherein the processor and

memory are configured to:

receive a plurality of perimeter signal level measurements corresponding to one or more macro radio nodes, wherein each perimeter signal level measurement is determined near an outer perimeter in the enclosure;

for each of the plurality of perimeter signal level measurements, predict a composite pathloss at a certain location in the enclosure, wherein the composite pathloss corresponds to one of the macro radio nodes;

select one of the composite pathlosses that has a minimum composite pathloss at the certain location in the enclosure;

determine the signal level at the certain location using the selected

composite pathloss; and

output an indication of the signal level at the certain location in the

enclosure.

20. A non-transitory computer-readable medium encoded with a computer program, the computer program comprising computer-executable instructions that when executed by a processor causes the processor to perform operations, wherein the operations are configured to:

receive a plurality of perimeter signal level measurements corresponding to one or more macro radio nodes, wherein each perimeter signal level measurement is determined near an outer perimeter in the enclosure; for each of the plurality of perimeter signal level measurements, predict a

composite pathloss at a certain location in the enclosure, wherein the composite pathloss corresponds to one of the macro radio nodes;

determine the signal level at the certain location using the selected composite pathloss; and

output an indication of the signal level at the certain location in the enclosure.

21 . A computer-implemented method of determining where in an enclosure to place individual radio nodes for collectively providing radio coverage in the enclosure, comprising:

determining a location-specific interference metric for each enclosure-wide

location, wherein the interference metric reflects an extent of

interference at that location;

determining to tentatively place an initial radio node at one of multiple candidate locations selected from the enclosure-wide locations; and for each of one or more iterations:

obtaining a location-specific coverage metric for each enclosure-wide location reflecting an extent of radio coverage that would be provided at that enclosure-wide location, if the additional radio node were to be placed at that candidate location, in view of the interference metric obtained for that enclosure-wide location; for each of the multiple candidate locations in the enclosure, obtaining an enclosure-wide coverage metric based on the interference metric and the coverage metric for each enclosure-wide location, wherein the enclosure-wide coverage metric reflects an extent of radio coverage that would be collectively provided across the enclosure by any tentatively placed nodes in combination with an additional radio node, if the additional radio node were to be placed at that candidate location;

determining to tentatively place the additional radio node at the

candidate location for which the identified enclosure-wide coverage metric was obtained.

22. The method of claim 21 , further comprising, for each of the one or more iterations, re-determining at which of the candidate locations to place each of one or more radio nodes that were tentatively placed in a previous iteration, after determining at which candidate location to tentatively place the additional radio node.

23. The method of any of claims 21 -22, further comprising performing said one or more iterations until tentative placement of an additional radio node achieves a defined extent of collective radio coverage in the enclosure.

24. The method of any of claims 21 -22, further comprising performing said one or more iterations until tentative placement of an additional radio node fails to achieve a defined improvement in the extent of collective radio coverage in the enclosure.

25. A device for determining where in an enclosure to place individual radio nodes for collectively providing radio coverage in the enclosure, comprising:

a memory configured to store data and computer-executable instructions;

a processor operatively coupled to the memory, wherein the processor and

memory are configured to:

determine a location-specific interference metric for each enclosure-wide location, wherein the interference metric reflects an extent of interference at that location;

determine to tentatively place an initial radio node at one of multiple candidate locations selected from the enclosure-wide locations; and for each of one or more iterations:

obtain a location-specific coverage metric for each enclosure-wide location reflecting an extent of radio coverage that would be provided at that enclosure-wide location, if the additional radio node were to be placed at that candidate location, in view of the interference metric obtained for that enclosure-wide location;

for each of the multiple candidate locations in the enclosure, obtain an enclosure-wide coverage metric based on the interference metric and the coverage metric for each enclosure-wide location, wherein the enclosure-wide coverage metric reflects an extent of radio coverage that would be collectively provided across the enclosure by any tentatively placed nodes in combination with an additional radio node, if the additional radio node were to be placed at that candidate location;

determine to tentatively place the additional radio node at the

26. A non-transitory computer-readable medium encoded with a computer program, the computer program comprising computer-executable instructions that when executed by a processor causes the processor to perform operations, wherein the operations are configured to:

determine a location-specific interference metric for each enclosure-wide

location, wherein the interference metric reflects an extent of

interference at that location;