CN103338470A - Spectrum demand forecasting method and device - Google Patents

Abstract

The invention provides a spectrum demand forecasting method and device. The method comprises the following steps: forecasting a user's service volume in a set time period in a region, and transmission rates of the service in different types of districts in the service volume in the region; forecasting the macro base station number, micro base station number and corresponding service carrying capacity thereof in different types of districts in the region according to the transmission rate, preset macro base station total number, the allocation proportion of the macro base station in different types of districts of the region; forecasting the macro base station number, micro base station number and corresponding service carrying capacity thereof in different types of districts of the region according to the transmission rate of service in different types of districts, and forecasting the using frequency spectrum of the user in the future of the region. Through the adoption of the method and device provided by the embodiment of the invention, a technical problem that the accuracy of the network spectrum demand predicting in the prior art is not high, so that the spectrum resource of the network cannot be configured reasonably is solved.

Description

Spectrum requirement Forecasting Methodology and device

Technical field

The present invention relates to communication technical field, relate in particular to a kind of spectrum requirement Forecasting Methodology and device.

Background technology

Along with the fast development of global mobile broadband communication, the data traffic of mobile communication subscriber acutely rises, and frequency is the basic resource of mobile communication development, and its demand also increases thereupon fast.For the use of make rational planning for country or telecom operators' frequency spectrum resource, national radio authorities or telecom operators need predict spectrum requirement amount and operating position that following a period of time is applied to mobile communication.

In the prior art, adopt a typical mobile communication scene, as predicting whole mobile communications network spectrum requirement by the corresponding relation of monitoring different business amount and required frequency spectrum in the city.Yet the accuracy that predicts the outcome that this Forecasting Methodology obtains is not high, can not carry out reasonable configuration to the frequency spectrum resource of network.

Summary of the invention

The invention provides a kind of spectrum requirement Forecasting Methodology and device, predict that in order to solve prior art network spectrum demand accuracy is not high, and then can not carry out the technical problem of reasonable configuration to the frequency spectrum resource of network.

On the one hand, the embodiment of the invention provides a kind of spectrum requirement Forecasting Methodology, comprising:

User's traffic carrying capacity in the following time of setting in the estimation range;

According to the distribution of traffic situation of historical time user in the described zone, determine described in the traffic carrying capacity of user in the described following time transmission rate of the business in dissimilar areas in the zone;

According to the allocation proportion in the transmission rate of the business in dissimilar areas in the zone described in the traffic carrying capacity of user in the described following time, default macro base station total number, described macro base station dissimilar areas in described zone, predict the described macro base station number in dissimilar areas in the described zone;

According to the described macro base station number in dissimilar areas in the transmission rate of the business in dissimilar areas in the zone described in the traffic carrying capacity of user in the described following time, the described zone, predict little number of base stations in dissimilar areas in the described zone;

According to the transmission rate of the business in dissimilar areas in the zone described in the traffic carrying capacity of user in the described following time, predict in the described zone service bearer ability of described macro base station and described little service in base station bearing capacity in the dissimilar areas;

Transmission rate according to the business in dissimilar areas in the zone described in the traffic carrying capacity of user in the described following time, dissimilar areas in the described zone that obtains of prediction: the service bearer ability of described macro base station number, described little number of base stations, described macro base station and described little service in base station bearing capacity, predict the frequency spectrum of user's use in the following time in described the zone in.

On the other hand, the embodiment of the invention provides a kind of spectrum requirement prediction unit, comprising: prediction module and processing module;

Described prediction module, user's traffic carrying capacity in the following time that is used for setting in the estimation range;

Described processing module is used for the distribution of traffic situation according to historical time user in the described zone, determines described in the traffic carrying capacity of user in the described following time transmission rate of the business in dissimilar areas in the zone;

Described prediction module also is used for:

According to the allocation proportion in the transmission rate of the business in dissimilar areas in the zone described in the traffic carrying capacity of user in the described following time, default macro base station total number, described macro base station dissimilar areas in described zone, predict the described macro base station number in dissimilar areas in the described zone;

According to the described macro base station number in dissimilar areas in the transmission rate of the business in dissimilar areas in the zone described in the traffic carrying capacity of user in the described following time, the described zone, predict little number of base stations in dissimilar areas in the described zone;

According to the transmission rate of the business in dissimilar areas in the zone described in the traffic carrying capacity of user in the described following time, predict in the described zone service bearer ability of described macro base station and described little service in base station bearing capacity in the dissimilar areas;

Transmission rate according to the business in dissimilar areas in the zone described in the traffic carrying capacity of user in the described following time, dissimilar areas in the described zone that obtains of prediction: the service bearer ability of described macro base station number, described little number of base stations, described macro base station and described little service in base station bearing capacity, predict the frequency spectrum of user's use in the following time in described the zone in.

Spectrum requirement Forecasting Methodology provided by the invention and device are by the transmission rate of user's business in the following time of obtaining the setting in dissimilar areas in the zone; And in this zone in the dissimilar areas: the service bearer ability of macro base station number, little number of base stations, macro base station and little service in base station bearing capacity, the frequency spectrum that the user uses in the following time in this zone of final prediction, improve prediction accuracy, and then can carry out reasonable configuration to the frequency spectrum resource of network.

Description of drawings

Fig. 1 is the flow chart of an embodiment of spectrum requirement Forecasting Methodology provided by the invention;

Fig. 2 is the flow chart of another embodiment of spectrum requirement Forecasting Methodology provided by the invention;

Fig. 3 is the structural representation of an embodiment of spectrum requirement prediction unit provided by the invention.

Embodiment

The techniques described herein may be used in the spectrum requirement prediction of various communication networks, current 2G for example, 3G communication system and next generation communication system, global system for mobile communications (GSM for example, Global System for Mobile communications), code division multiple access (CDMA, Code Division Multiple Access) system, time division multiple access (TDMA, Time Division Multiple Access) system, Wideband Code Division Multiple Access (WCDMA) (WCDMA, Wideband Code Division Multiple Access Wireless), frequency division multiple access (FDMA, Frequency Division Multiple Addressing) system, OFDM (OFDMA, Orthogonal Frequency-Division Multiple Access) system, Single Carrier Frequency Division Multiple Access (SC-FDMA) system, GPRS (GPRS, General Packet Radio Service) system, Long Term Evolution (LTE, Long Term Evolution) system, and other these type of communication systems.

Fig. 1 is the flow chart of an embodiment of spectrum requirement Forecasting Methodology provided by the invention.As shown in Figure 1, the executive agent of following steps can be the network equipment in the network, server, or is integrated in module on this network equipment or the server, chip etc.As shown in Figure 1, this spectrum requirement Forecasting Methodology specifically comprises:

S101, user's traffic carrying capacity in the following time of setting in the estimation range;

Wherein, can comprise the different areas of one or more density of population such as city, suburb, rural area in the predicted zone.Predict in this zone in the following time of setting, as one month, 1 year, the traffic carrying capacity of mobile communication business that the user uses generation during the decade, can add up by the historical traffic that in this zone, produces, analyze its variation tendency; And population trends in should the zone, this population trends carries out integrated forecasting to the aspects such as influence of Added Business amount.As taking all factors into consideration through above-mentioned each factor, determine the number of users in the following time of setting in the zone, and the average traffic carrying capacity used of each user, then the product of the traffic carrying capacity that this number of users and average each number of users can be used is as the predicted value of user's traffic carrying capacity in the following time of setting in this zone.

S102, according to the distribution of traffic situation of historical time user in this zone, determine in the traffic carrying capacity of user in the above-mentioned following time should the zone in the transmission rate of business in dissimilar areas;

Regional population in the predicted zone can comprise areas such as above-mentioned city, suburb, rural area.By the distribution of traffic situation analysis to historical time user in this zone, can be informed in the bigger urban area of the density of population, mobile communication network device is disposed comparatively perfect, and the traffic carrying capacity that the user uses in this area is also more relatively; And the suburb is less relatively because of its density of population, and the mobile communication network device deployment is rare relatively, and the traffic carrying capacity that this area produces is also less relatively; The traffic carrying capacity that the rural area produces then still less.Distribution of traffic situation according to above historical time user, user's traffic carrying capacity is distributed according to the distribution of traffic situation in dissimilar areas in this zone in the following time that prediction in the step 101 can be obtained, obtain the traffic carrying capacity in dissimilar areas in this zone, time that produces according to these traffic carrying capacitys then, obtain in the traffic carrying capacity of user in the following time transmission rate of the business in dissimilar areas in this zone.

S103, according to the transmission rate of the business in dissimilar areas in should the zone in the traffic carrying capacity of user in the following time, default macro base station total number, the allocation proportion in this macro base station dissimilar areas in this zone, predict the described macro base station number in dissimilar areas in this zone;

Wherein, the macro base station total number that should preset can be the development according to existing network in this estimation range, concrete number as the base station deployment of each department that annual operator is announced carries out statistical analysis, the macro base station number of this estimation range in the following time that prediction obtains.According to default macro base station total number, the allocation proportion in this macro base station dissimilar areas in this zone, can obtain being assigned to the macro base station number in variant type area roughly.And in the practical application scene, even between the area of same type, and since its area difference, number of users difference in the area, and also there is larger difference in the traffic carrying capacity that causes these users to use.Also will do further judgement according to the transmission rate of the business in dissimilar areas in should the zone in the traffic carrying capacity of user in the following time in this case, professional transmission rate has directly been reacted its needed macro base station total number of carrying.Therefore, passing through default macro base station total number, the allocation proportion in this macro base station dissimilar areas in this zone, after having determined general macro base station number that dissimilar areas are assigned with, according to the transmission rate of the business in dissimilar areas in should the zone in the traffic carrying capacity of user in the following time macro base station number of the each department distributed is adjusted, so that its distribution is more reasonable.For example, generally, the user's in city traffic carrying capacity is bigger with respect to the traffic carrying capacity in suburb and rural area, and therefore, both are higher in the back relatively in the allocation proportion of urban area for macro base station.And under some special screnes, less with respect to other urban area areas as certain urban area, number of users integral body is less, the transmission rate of customer service is less relatively, therefore can on the basis of original allocation proportion, suitably reduce the distribution number of macro base station, so that macro base station distributes is more reasonable between all types of areas.

S104 according to the macro base station number in dissimilar areas in the transmission rate of the business in dissimilar areas in should the zone in the traffic carrying capacity of user in the following time, this zone, predicts little number of base stations in dissimilar areas in this zone;

Consider the characteristic of traffic carrying capacity uneven distribution spatially, all exist " focus " zone to absorb most traffic carrying capacity and a small amount of professional situation of " cold spot " regional only carrying in the dissimilar areas.For " focus " zone, little base station of fixed qty can be in this zone be set in the macrocell of each macro base station correspondence.Shunt too high traffic densities by the frequency spectrum of the macro base station use of multiplexing fixed-bandwidth this little base station, thereby reduce the transmission rate of the bearer service of macro base station.

According to the size of traffic carrying capacity transmission rate of the business in dissimilar areas in this zone of user in the following time, judge whether the type area is " focus " area in the present embodiment.If the transmission rate of the type area institute loaded service is very big, approach or exceeded the maximum traffic bearing capacity of the macro base station in this area, think that then this area is " focus " area.According to the macro base station number in this hot zones, and be fixing little number of base stations of each macro base station configuration, can obtain little number of base stations in dissimilar areas in this zone.

S105 according to the transmission rate of the business in dissimilar areas in should the zone in the traffic carrying capacity of user in the following time, predicts in this zone the service bearer ability of macro base station and little service in base station bearing capacity in the dissimilar areas;

Wherein, the transmission rate that is used for bearer service that each macro base station or little base station utilize every MHz bandwidth can provide at most, this service bearer ability difference under the different network formats are provided the service bearer ability.This service bearer ability and macro base station or little base station: the transmission rate situation of spectrum efficiency, the sector number that comprises, institute's loaded service is relevant with maximum bearing load.Wherein, spectrum efficiency is in the mobile communications network, and according to the different network formats technology that adopts, the service bearer ability that operator uses the frequency spectrum of same band to provide will be provided for the spectrum efficiency numerical value that obtains, this numerical value.Transmission rate according to the business in dissimilar areas in should the zone in the traffic carrying capacity of user in the following time, and each macro base station or little base station itself: spectrum efficiency, the sector number that comprises and maximum bearing load, measurable should the zone in service bearer ability and the little service in base station bearing capacity of macro base station in the dissimilar areas.

S106, transmission rate according to the business in dissimilar areas in the zone described in the traffic carrying capacity of user in the following time, dissimilar areas in this zone of obtaining of prediction: the service bearer ability of macro base station number, little number of base stations, macro base station and little service in base station bearing capacity, predict this zone in the frequency spectrum of user's use in the following time;

Deduct the transmission rate of little base station shunting in should the zone in prediction obtains the following time in the transmission rate of the business in dissimilar areas, send the transmission rate of carrying with the macro base station that obtains dissimilar areas in this zone, then, according to the service bearer ability of each macro base station and the number of macro base station, obtain the frequency spectrum that the user uses in the following time in this zone.Wherein, the transmission rate of little base station shunting can obtain by little number of base stations, little service in base station bearing capacity and the bandwidth of distributing to little base station.

Spectrum requirement Forecasting Methodology provided by the invention is by the transmission rate of user's business in the following time of obtaining the setting in dissimilar areas in the zone; And in this zone in the dissimilar areas: the service bearer ability of macro base station number, little number of base stations, macro base station and little service in base station bearing capacity, the frequency spectrum that the user uses in the following time in this zone of final prediction, improve prediction accuracy, and then can carry out reasonable configuration to the frequency spectrum resource of network.

Fig. 2 is the flow chart of another embodiment of spectrum requirement Forecasting Methodology provided by the invention, is a kind of concrete implementation of embodiment as shown in Figure 1.As shown in Figure 2, described method specifically comprises:

S201, user's traffic carrying capacity in the following time of setting in the estimation range; The concrete implementation of this step can be referring to the corresponding contents of step 101.Because the user uses and comprises speech business and data service in the mobile communications network business, therefore in this step, also comprise voice services volume and data business volume in user's the traffic carrying capacity in the following time of setting in the estimation range.

S202 is according to T _v=M _v* 60 * K(1), with voice services volume M _vBe converted to equivalent data traffic carrying capacity T _vWherein, K is conversion coefficient;

Voice services volume and the data business volume that prediction is obtained unified to handle for convenience, voice services volume can be converted to the equivalent data traffic carrying capacity by (1) formula; Wherein, M _vFor the message minute of speech business, the unit of K are Kbps.

S203, user's traffic carrying capacity in the following time that equivalent data traffic carrying capacity and data business volume sum are defined as setting in the zone;

Voice services volume M in the following time of setting in the zone that prediction is obtained in user's the traffic carrying capacity _vBe converted to equivalent data traffic carrying capacity T _v, again with this equivalent number according to traffic carrying capacity T _vUser's traffic carrying capacity in the following time that is defined as setting in the zone with data business volume sum in the traffic carrying capacity of former prediction.So, can make subsequent step can unify to handle to this traffic carrying capacity.

At in the step 102, according to historical time user's distribution of traffic situation in the zone, determine in the traffic carrying capacity of user in the above-mentioned following time should the zone in the transmission rate of business in dissimilar areas; Present embodiment step 204～206 have provided a kind of concrete implementation.

S204, according to $\mathrm{TBH}=\frac{(T_d+T_V)\×\mathrm{DLR}\×\mathrm{BHR}}{t}---\left(2\right)$

The transmission rate TBH of downlink business when obtaining busy in the traffic carrying capacity; Wherein, T _dBe data business volume, T _VFor equivalent data traffic carrying capacity, DLR are the duration that historical time user's ratio, the BHR of downlink traffic in total traffic is historical time user's busy-hour traffic when the ratio of total traffic, t are busy in for the following time;

The traffic carrying capacity of considering the user that prediction obtains uneven distribution in time and the characteristics of the asymmetry of up-downgoing (these characteristics can with reference to obtaining after the distribution of traffic situation analysis to historical time user in this zone), in the practical application scene, can there be certain centrality in the distribution of traffic carrying capacity.Wherein, traffic carrying capacity intensity has in time then directly been reacted required amount of frequency spectrum.Present embodiment has also been considered the distribution situation of up-downgoing business in total traffic when considering traffic carrying capacity intensity in time, the final transmission rate TBH of downlink business during by busy in (2) formula computing service amount.Definition for " when hurrying " can be that the traffic carrying capacity that produces this period has exceeded set point, or certain the set time section in a day etc.

S205 is according to TBH _m=TBH * P _m* U _m(3)

The transmission rate TBH of downlink business when obtaining to hurry in the following time _mThe transmission rate of downlink business, m were regional network formats, the P that adopts when wherein, TBH was busy under all standards _mAccounting, U for user under the m network formats _mFor each user under the m network formats uses the normalized parameter of traffic carrying capacity;

Wherein, the network formats that m adopts for this estimation range, can comprise the second generation/third generation/the 4th third-generation mobile communication technology (Second-Generation/Third-Generation/Fourth-Generation, 2G/3G/4G); P _mBe the accounting among the user under all standards in this zone of the user under the m network formats; U _mFor each user under the m network formats uses the normalized parameter of traffic carrying capacity, be used for representing to belong to the professional relatively use amount of each user in the m network, for example: usually with U _3GBe made as 1, average each 3G subscription of expression uses the traffic carrying capacity of 1 unit, if U _2GAnd U _4GBe respectively a(less than 1) and b(greater than 1), then average each the 2G user of expression uses the traffic carrying capacity of a unit, on average each 4G user uses the traffic carrying capacity of b unit.

S206 is according to TBH _{M, n}=TBH _m* P _n* U _n(4)

Obtain in the following time should the zone in the transmission rate TBH of the downlink business of correspondence in the dissimilar areas _{M, n}Wherein, n is the type in area, TBH _mTransmission rate, the P of downlink business during for busy under the m network formats _nAccounting, U for user in the n type area under the m network formats _nBe that each user uses the normalized parameter of traffic carrying capacity in the area of n for the type under the m network formats;

Wherein, P _nBe specially the accounting in the number of users under all types area under this m network formats of the number of users in the n type area under the m network formats; U _nFor each user in the n type area under the m network formats uses the normalized parameter of traffic carrying capacity, this normalized parameter is used for representing the professional relatively use amount of every user at belonging under the consolidated network standard in the different regions.For example, can be with U _sBe made as 1, average each rural subscriber of expression uses the traffic carrying capacity of 1 unit, if U _uAnd U _rBe respectively c(greater than 1) and d(less than 1), then average each the city user of expression uses the traffic carrying capacity of c unit, on average each rural subscribers uses the traffic carrying capacity of d unit.

S207, according to the transmission rate of the business in dissimilar areas in should the zone in the traffic carrying capacity of user in the following time, default macro base station total number, the allocation proportion in macro base station dissimilar areas in the zone, the macro base station number in dissimilar areas in the estimation range; The concrete implementation of this step can be referring to the corresponding contents of step 103.

S208 sorts the macro base station in the same type area size according to the transmission rate of institute's loaded service, and is divided into the j group macro base station group that number equates;

Consider the characteristic of traffic carrying capacity uneven distribution spatially, all exist " focus " zone to absorb most traffic carrying capacity in the dissimilar areas, " cold spot " zone is a small amount of professional situation of carrying only, the macro base station in the same type area that in this step prediction is obtained sorts according to the size of the transmission rate of institute's loaded service, and is divided into the j group macro base station group that number equates.Judge the transmission rate of each macro base station group institute loaded service and the magnitude relationship of threshold value by subsequent step again, determine whether to dispose for each macro base station the number of little base station and configuration.

S209, according to ${\mathrm{MSN}}_n=\underset{i=1}{\overset{j}{\mathrm{\Σ}}}{\mathrm{MSN}}_{\mathrm{ni}}---\left(5\right)$

${\mathrm{MSN}}_{\mathrm{ni}}=\left\{\begin{array}{cc}{\mathrm{SN}}_{\mathrm{ni}}\&times;\mathrm{MSPS},& \frac{{\mathrm{TBH}}_n\&times;{\mathrm{TR}}_i}{{\mathrm{SN}}_{\mathrm{ni}}/{\mathrm{SD}}_n}\&GreaterEqual;G_{\mathrm{MS}}\\ 0,& \frac{{\mathrm{TBH}}_n\&times;{\mathrm{TR}}_i}{{\mathrm{SN}}_{\mathrm{ni}}/{\mathrm{SD}}_n}<G_{\mathrm{MS}}\end{array}\right.---\left(6\right),$

Type of prediction is little number of base stations MSN in the area of n _nWherein, i is 1 to j integer, MSN _NiBe little number of base stations, the SN that comprises among the i group macro base station group in the area of n for type _NiBe that the macro base station number, the MSPS that comprise among the i group macro base station group in the area of n are that type is little number of base stations, the TBH that comprises in the macrocell of each macro base station in area of n for type _nBe the corresponding transmission rate of downlink business when busy in the area of n for type, TR _iThe transmission rate of downlink business ratio, SD in the transmission rate of downlink business during correspondence busy in all types is the area of n when being i group macro base station carrying busy in area of n for type _nBe the site density of macro base station in the area of n for type, G _MSThe transmission rate density threshold value of downlink business when setting up required busy in little base station at each macro base station;

(5) in this step and (6) formula are the transmission rate density threshold value G of downlink business when whether the transmission rate distribution density spatially of downlink business is reached for each macro base station and sets up required busy in little base station when judging among each macro base station group corresponding carrying busy _MS, determine whether to set up little base station in the macrocell of each macro base station in this macro base station group, and the concrete number of setting up.If with TBH _nDifference according to the network formats at place is carried out refinement, and can also obtain so at the type under the different network formats m is little number of base stations MSN in the area of n _{M, n}Step 208～209 can be considered a kind of specific implementation of step 104.

S210 according to the transmission rate of the business in dissimilar areas in should the zone in the traffic carrying capacity of user in the following time, predicts in this zone the service bearer ability of macro base station and little service in base station bearing capacity in the dissimilar areas; The concrete implementation of this step can be referring to the corresponding contents of step 105.As to the further specifying of step 105, present embodiment has provided following scheme:

According to MaT=FE _Ma* ASN _Ma* L (7)

MiT=FE _Mi×ASN _Mi （8），

Calculate n type area respectively: the service bearer ability MaT of macro base station and little service in base station bearing capacity MiT; Wherein, Ma is the attribute-bit of macro base station, attribute-bit, the FE that Mi is little base station _MaSpectrum efficiency, ASN for macro base station _MaAverage sector number, FE for macro base station _MiSpectrum efficiency, ASN for little base station _MiFor the transmission rate of the average sector number of little base station, L downlink business when busy this regional network system the ratio in the maximum capacity value of transmission rate of energy bearer service.

S211, transmission rate according to the business in dissimilar areas in should the zone in the traffic carrying capacity of user in the following time, dissimilar areas in the zone that obtains of prediction: the service bearer ability of macro base station number, little number of base stations, macro base station and little service in base station bearing capacity, the frequency spectrum of user's use in the following time estimation range in; The concrete implementation of this step can be referring to the corresponding contents of step 106.As to the further specifying of step 106, present embodiment has provided following scheme:

According to BW _n=MAX (BW _N1, BW _N2..., BW _Nj),

${\mathrm{BW}}_{\mathrm{ni}}=\left\{\begin{array}{cc}\frac{{\mathrm{TBH}}_n\&times;{\mathrm{TR}}_i-\mathrm{MiT}\&times;B_i\&times;{\mathrm{FU}}_i\&times;{\mathrm{MSN}}_{\mathrm{ni}}}{\mathrm{MaT}\&times;{\mathrm{FU}}_n\&times;{\mathrm{SN}}_{\mathrm{ni}}}& {\mathrm{MSN}}_{\mathrm{ni}}>0\\ \frac{{\mathrm{TBH}}_n\&times;{\mathrm{TR}}_i}{\mathrm{MaT}\&times;{\mathrm{FU}}_n\&times;{\mathrm{SN}}_{\mathrm{ni}}}& {\mathrm{MSN}}_{\mathrm{ni}}=0\end{array}\right.$

Predict the frequency spectrum BW of interior user's use of following time in n type area in this zone _nWherein, j be the same type area macro base station according to carry busy the time downlink business the size of transmission rate sort, and the number, the i that are divided into the macro base station group that number equates are 1 to j integer, BW _NiBe required frequency spectrum, the TBH of i group macro base station group in the area of n for type _nFor type be n the area in busy the time downlink business transmission rate, TR _iWhen being busy in the area of n for type in the transmission rate of downlink business during i group busy ratio, the MiT of the transmission rate of downlink business be above-mentioned little service in base station bearing capacity, B _iBe corresponding bandwidth, the FU that distributes in little base station that comprises among the i group macro base station group in the area of n for type _iBe the availability of frequency spectrum, the MSN of little base station of comprising among the i group macro base station group in the area of n for type _NiBe the number of little base station of comprising among the i group macro base station group in the area of n for type, MaT is the service bearer ability of macro base station, FU _nBe the availability of frequency spectrum, the SN of macro base station in the area of n for type _NiIt is the number of macro base station among the i group macro base station group in the area of n for type.Wherein, because of FU _nThe generation of concept be because mobile communication system is used the frequency spectrum of big bandwidth usually, be applied to various geographical scenes, this can cause existing in the entire spectrum some frequency spectrum transmission performances not good, causes the situation that overall network performance descends.So, introduced this parameter of the availability of frequency spectrum in the present embodiment, be used for characterizing the performance " discount " that above factor causes.

Further, in step 207～211, can also continue according to the macro base station number under each network formats, little number of base stations, and their corresponding service bearing capacity does further division, finally obtains in the estimation range frequency spectrum that uses under the m network formats in type is the area of n of user in the following time.

Spectrum requirement Forecasting Methodology provided by the invention is by the transmission rate of user's business in the following time of obtaining the setting in dissimilar areas in the zone; And in this zone in the dissimilar areas: the service bearer ability of macro base station number, little number of base stations, macro base station and little service in base station bearing capacity, the frequency spectrum that the user uses in the following time in this zone of final prediction, improve prediction accuracy, and then can carry out reasonable configuration to the frequency spectrum resource of network.

One of ordinary skill in the art will appreciate that: all or part of step that realizes above-mentioned each method embodiment can be finished by the relevant hardware of program command.Aforesaid program can be stored in the computer read/write memory medium.This program is carried out the step that comprises above-mentioned each method embodiment when carrying out; And aforesaid storage medium comprises: various media that can be program code stored such as ROM, RAM, magnetic disc or CD.

Fig. 3 is the structural representation of an embodiment of spectrum requirement prediction unit provided by the invention.As shown in Figure 3, this spectrum requirement prediction unit can be the network equipment in the network, server, or is integrated in module on this network equipment or the server, chip etc., and can carry out the step as the spectrum requirement Forecasting Methodology among Fig. 1 embodiment.This spectrum requirement prediction unit comprises: prediction module 31 and processing module 32, wherein:

Prediction module 31, user's traffic carrying capacity in the following time that is used for setting in the estimation range;

Processing module 32 is used for the distribution of traffic situation according to historical time user in the zone, determine in the traffic carrying capacity of user in this time in future should the zone in the transmission rate of business in dissimilar areas;

This prediction module 31 also is used for:

According to the transmission rate of the business in dissimilar areas in should the zone in the traffic carrying capacity of user in the following time, default macro base station total number, the allocation proportion in macro base station dissimilar areas in the zone, predict the described macro base station number in dissimilar areas in this zone;

According to the macro base station number in dissimilar areas in the transmission rate of the business in dissimilar areas in should the zone in the traffic carrying capacity of user in the following time, this zone, predict little number of base stations in dissimilar areas in this zone;

According to the transmission rate of the business in dissimilar areas in should the zone in the traffic carrying capacity of user in the following time, predict in this zone the service bearer ability of macro base station and little service in base station bearing capacity in the dissimilar areas;

Transmission rate according to the business in dissimilar areas in should the zone in the traffic carrying capacity of user in the following time, dissimilar areas in this zone of obtaining of prediction: the service bearer ability of macro base station number, little number of base stations, macro base station and little service in base station bearing capacity, predict this zone in the frequency spectrum of user's use in the following time.

Particularly, the prediction unit of spectrum requirement shown in the present embodiment realize to following time user in certain zone to the forecasting process of required frequency spectrum be:

User's traffic carrying capacity in the following time of setting in prediction module 31 estimation ranges, this process can be referring to the corresponding contents of step 101; Processing module 32 is according to the distribution of traffic situation of historical time user in this zone, determine in the traffic carrying capacity of user in following time that prediction module 31 prediction obtains the transmission rate of the business in dissimilar areas in this zone, this process can be referring to the corresponding contents of step 102; The transmission rate of the business in dissimilar areas, default macro base station total number, the allocation proportion in this macro base station dissimilar areas in this zone in should the zone in user's the traffic carrying capacity in the following time that prediction module 31 obtains according to processing module 32, predict the described macro base station number in dissimilar areas in this zone, this process can be referring to the corresponding contents of step 103; Then, prediction module 31 is according to the macro base station number in dissimilar areas in the transmission rate of the business in dissimilar areas in should the zone in the traffic carrying capacity of user in the following time, this zone that prediction obtains, predict little number of base stations in dissimilar areas in this zone, this process can be referring to the corresponding contents of step 104; Then, prediction module 31 is according to the transmission rate of the business in dissimilar areas in should the zone in the traffic carrying capacity of user in the following time, predict in this zone the service bearer ability of macro base station and little service in base station bearing capacity in the dissimilar areas, this process can be referring to the corresponding contents of step 105; At last, prediction module 31 is according to the transmission rate of the business in dissimilar areas in should the zone in the traffic carrying capacity of user in the above-mentioned following time, dissimilar areas in this zone of obtaining of prediction: the service bearer ability of macro base station number, little number of base stations, macro base station and little service in base station bearing capacity, predict the frequency spectrum that the user uses in the following time in this zone, this process can be referring to the corresponding contents of step 106.

Spectrum requirement prediction unit provided by the invention is by the transmission rate of user's business in the following time of obtaining the setting in dissimilar areas in the zone; And in this zone in the dissimilar areas: the service bearer ability of macro base station number, little number of base stations, macro base station and little service in base station bearing capacity, the frequency spectrum that the user uses in the following time in this zone of final prediction, improve prediction accuracy, and then can carry out reasonable configuration to the frequency spectrum resource of network.

The present invention also provides the structural representation of another embodiment of spectrum requirement prediction unit.This structural representation is a kind of concrete implementation of embodiment as shown in Figure 3, can carry out the step of spectrum requirement Forecasting Methodology as shown in Figure 2.This spectrum requirement prediction unit also comprises on the basis of as shown in Figure 3 26S Proteasome Structure and Function:

Processing module 32 is used for: according to T _v=M _v* 60 * K is with voice services volume M _vBe converted to equivalent data traffic carrying capacity T _vWherein, K is conversion coefficient; User's traffic carrying capacity in the following time that equivalent data traffic carrying capacity and data business volume sum are defined as setting in the zone;

Processing module 32 also is used for basis $\mathrm{TBH}=\frac{(T_d+T_V)\&times;\mathrm{DLR}\&times;\mathrm{BHR}}{t}$

The transmission rate TBH of downlink business when obtaining busy in the above-mentioned traffic carrying capacity; Wherein, T _dBe above-mentioned data business volume, T _VFor above-mentioned equivalent data traffic carrying capacity, DLR be ratio in total traffic of above-mentioned historical time user's downlink traffic, BHR for this historical time user's busy-hour traffic at the ratio of total traffic, the t duration when busy in this time in future;

According to TBH _m=TBH * P _m* U _m

The transmission rate TBH of downlink business when obtaining to hurry in the following time _mWherein, TBH is the described transmission rate, network formats, the P that m adopts for this zone of downlink business when busy under all standards _mAccounting, U for user under this m network formats _mFor each user under this m network formats uses the normalized parameter of traffic carrying capacity;

According to TBH _{M, n}=TBH _m* P _n* U _n

Obtain in this time in future should the zone in the transmission rate TBH of corresponding downlink business in the dissimilar areas _{M, n}Wherein, n is the type in area, TBH _mTransmission rate, the P of downlink business during for busy under the m network formats _nAccounting, U for user in the n type area under this m network formats _nBe that each user uses the normalized parameter of described traffic carrying capacity in the area of n for the type under this m network formats;

Prediction module 31 is used for the macro base station in the same type area size according to the transmission rate of institute's loaded service is sorted, and is divided into the j group macro base station group that number equates;

According to ${\mathrm{MSN}}_n=\underset{i=1}{\overset{j}{\mathrm{\&Sigma;}}}{\mathrm{MSN}}_{\mathrm{ni}},$

${\mathrm{MSN}}_{\mathrm{ni}}=\left\{\begin{array}{cc}{\mathrm{SN}}_{\mathrm{ni}}\&times;\mathrm{MSPS},& \frac{{\mathrm{TBH}}_n\&times;{\mathrm{TR}}_i}{{\mathrm{SN}}_{\mathrm{ni}}/{\mathrm{SD}}_n}\&GreaterEqual;G_{\mathrm{MS}}\\ 0,& \frac{{\mathrm{TBH}}_n\&times;{\mathrm{TR}}_i}{{\mathrm{SN}}_{\mathrm{ni}}/{\mathrm{SD}}_n}<G_{\mathrm{MS}}\end{array}\right.$

Type of prediction is little number of base stations MSN in the area of n _nWherein, i is 1 to j integer, MSN _NiBe little number of base stations, the SN that comprises among the i group macro base station group in the area of n for type _NiBe that the macro base station number, the MSPS that comprise among the i group macro base station group in the area of n are that type is little number of base stations, the TBH that comprises in the macrocell of each macro base station in area of n for type _nBe the corresponding transmission rate of downlink business when busy in the area of n for type, TR _iThe transmission rate of downlink business ratio, SD in the transmission rate of downlink business during correspondence busy in all types is the area of n when being i group macro base station carrying busy in area of n for type _nBe the site density of macro base station in the area of n for type, G _MSThe transmission rate density threshold value of downlink business when setting up required busy in little base station at each macro base station;

This prediction module 31 also is used for:

According to MaT=FE _Ma* ASN _Ma* L,

MiT=FE _Mi×ASN _Mi

Calculate n type area respectively: the service bearer ability MaT of macro base station and little service in base station bearing capacity MiT; Wherein, Ma is the attribute-bit of macro base station, attribute-bit, the FE that Mi is little base station _MaSpectrum efficiency, ASN for macro base station _MaAverage sector number, FE for macro base station _MiSpectrum efficiency, ASN for little base station _MiFor the average sector number of little base station, L during by n type area busy the transmission rate of downlink business in this zone network system the ratio in the maximum capacity value of transmission rate of energy bearer service;

According to BW _n=MAX (BW _N1, BW _N2..., BW _Nj),

${\mathrm{BW}}_{\mathrm{ni}}=\left\{\begin{array}{cc}\frac{{\mathrm{TBH}}_n\&times;{\mathrm{TR}}_i-\mathrm{MiT}\&times;B_i\&times;{\mathrm{FU}}_i\&times;{\mathrm{MSN}}_{\mathrm{ni}}}{\mathrm{MaT}\&times;{\mathrm{FU}}_n\&times;{\mathrm{SN}}_{\mathrm{ni}}}& {\mathrm{MSN}}_{\mathrm{ni}}>0\\ \frac{{\mathrm{TBH}}_n\&times;{\mathrm{TR}}_i}{\mathrm{MaT}\&times;{\mathrm{FU}}_n\&times;{\mathrm{SN}}_{\mathrm{ni}}}& {\mathrm{MSN}}_{\mathrm{ni}}=0\end{array}\right.$

Predict the frequency spectrum BW of interior user's use of following time in n type area in this zone _nWherein, j be the same type area macro base station according to carry busy the time downlink business the size of transmission rate sort, and the number, the i that are divided into the macro base station group that number equates are 1 to j integer, BW _NiBe required frequency spectrum, the TBH of i group macro base station group in the area of n for type _nFor type be n the area in busy the time downlink business transmission rate, TR _iWhen being busy in the area of n for type in the transmission rate of downlink business during i group busy ratio, the MiT of the transmission rate of downlink business be little service in base station bearing capacity, B _iBe corresponding bandwidth, the FU that distributes in little base station that comprises among the i group macro base station group _iBe the availability of frequency spectrum, the MSN that i organizes the little base station that comprises among the macro base station group _NiBe the number of little base station of comprising among the i group macro base station group in the area of n for type, MaT is the service bearer ability of macro base station, FU _nBe the availability of frequency spectrum, the SN of macro base station in the area of n for type _NiIt is the number of macro base station among the i group macro base station group in the area of n for type.

Particularly, the prediction unit of spectrum requirement shown in the present embodiment is realized following time user in certain zone as follows to the forecasting process of required frequency spectrum.

User's traffic carrying capacity in the following time of setting in prediction module 31 estimation ranges; This process can be referring to the corresponding contents of step 201.

For voice services volume in the above-mentioned traffic carrying capacity, processing module 32 is according to T _v=M _v* 60 * K(1), with this voice services volume M _vBe converted to equivalent data traffic carrying capacity T _v, then, user's traffic carrying capacity in the following time that equivalent data traffic carrying capacity and data business volume sum are defined as setting in the above-mentioned zone is so that voice services volume and data business volume that prediction is obtained are unified to handle.

Processing module 32 is according to the distribution of traffic situation of historical time user in this zone, determines in the traffic carrying capacity of user in following time that prediction module 31 predictions obtain the transmission rate of the business in dissimilar areas in this zone, specifically comprises:

According to $\mathrm{TBH}=\frac{(T_d+T_V)\&times;\mathrm{DLR}\&times;\mathrm{BHR}}{t}---\left(2\right)$ The transmission rate TBH of downlink business when obtaining busy in the traffic carrying capacity; According to TBH _m=TBH * P _m* U _mThe transmission rate TBH of downlink business when (3) obtaining to hurry in the following time _mAccording to TBH _{M, n}=TBH _m* P _n* U _n(4) obtain in the following time should the zone in the transmission rate TBH of the downlink business of correspondence in the dissimilar areas _{M, n}, this implementation can be referring to the corresponding contents of step 204～206.

The transmission rate of the business in dissimilar areas, default macro base station total number, the allocation proportion in this macro base station dissimilar areas in this zone in should the zone in user's the traffic carrying capacity in the following time that prediction module 31 obtains according to processing module 32, predict the described macro base station number in dissimilar areas in this zone, this process can be referring to the corresponding contents of step 103.

Prediction module 31 is according to the macro base station number in dissimilar areas in the transmission rate of the business in dissimilar areas in should the zone in the traffic carrying capacity of user in the following time, this zone that prediction obtains, predict little number of base stations in dissimilar areas in this zone, specifically comprise:

The macro base station in the same type area size according to the transmission rate of institute's loaded service is sorted, and be divided into the j group macro base station group that number equates;

According to ${\mathrm{MSN}}_n=\underset{i=1}{\overset{j}{\mathrm{\&Sigma;}}}{\mathrm{MSN}}_{\mathrm{ni}}---\left(5\right)$

${\mathrm{MSN}}_{\mathrm{ni}}=\left\{\begin{array}{cc}{\mathrm{SN}}_{\mathrm{ni}}\&times;\mathrm{MSPS},& \frac{{\mathrm{TBH}}_n\&times;{\mathrm{TR}}_i}{{\mathrm{SN}}_{\mathrm{ni}}/{\mathrm{SD}}_n}\&GreaterEqual;G_{\mathrm{MS}}\\ 0,& \frac{{\mathrm{TBH}}_n\&times;{\mathrm{TR}}_i}{{\mathrm{SN}}_{\mathrm{ni}}/{\mathrm{SD}}_n}<G_{\mathrm{MS}}\end{array}\right.---\left(6\right),$

Type of prediction is little number of base stations MSN in the area of n _nThis process specifically can be referring to the corresponding contents of step 208～209.

Then, prediction module 31 is according to the transmission rate of the business in dissimilar areas in should the zone in the traffic carrying capacity of user in the following time, predicts in this zone the service bearer ability of macro base station and little service in base station bearing capacity in the dissimilar areas, specifically comprises:

According to MaT=FE _Ma* ASN _Ma* L (7)

MiT=FE _Mi×ASN _Mi （8），

Calculate n type area respectively: the service bearer ability MaT of macro base station and little service in base station bearing capacity MiT, this process can be referring to the corresponding contents of step 210.

At last, prediction module 31 is according to the transmission rate of the business in dissimilar areas in should the zone in the traffic carrying capacity of user in the above-mentioned following time, dissimilar areas in this zone of obtaining of prediction: the service bearer ability of macro base station number, little number of base stations, macro base station and little service in base station bearing capacity, predict the frequency spectrum that the user uses in the following time in this zone, specifically comprise:

According to BW _n=MAX (BW _N1, BW _N2..., BW _Nj),

${\mathrm{BW}}_{\mathrm{ni}}=\left\{\begin{array}{cc}\frac{{\mathrm{TBH}}_n\&times;{\mathrm{TR}}_i-\mathrm{MiT}\&times;B_i\&times;{\mathrm{FU}}_i\&times;{\mathrm{MSN}}_{\mathrm{ni}}}{\mathrm{MaT}\&times;{\mathrm{FU}}_n\&times;{\mathrm{SN}}_{\mathrm{ni}}}& {\mathrm{MSN}}_{\mathrm{ni}}>0\\ \frac{{\mathrm{TBH}}_n\&times;{\mathrm{TR}}_i}{\mathrm{MaT}\&times;{\mathrm{FU}}_n\&times;{\mathrm{SN}}_{\mathrm{ni}}}& {\mathrm{MSN}}_{\mathrm{ni}}=0\end{array}\right.$

Predict the frequency spectrum BW of interior user's use of following time in n type area in this zone _n, this process can be referring to the corresponding contents of step 211.

Further, the present embodiment shown device is in the process that realizes spectrum prediction, can also be according to the macro base station number under each network formats, little number of base stations, and their corresponding service bearing capacity does further division, finally obtains in the estimation range frequency spectrum that uses under the m network formats in type is the area of n of user in the following time.

Spectrum requirement prediction unit provided by the invention is by the transmission rate of user's business in the following time of obtaining the setting in dissimilar areas in the zone; And in this zone in the dissimilar areas: the service bearer ability of macro base station number, little number of base stations, macro base station and little service in base station bearing capacity, the frequency spectrum that the user uses in the following time in this zone of final prediction, improve prediction accuracy, and then can carry out reasonable configuration to the frequency spectrum resource of network.

It should be noted that at last: above each embodiment is not intended to limit only in order to technical scheme of the present invention to be described; Although the present invention has been described in detail with reference to aforementioned each embodiment, those of ordinary skill in the art is to be understood that: it still can be made amendment to the technical scheme that aforementioned each embodiment puts down in writing, and perhaps some or all of technical characterictic wherein is equal to replacement; And these modifications or replacement do not make the essence of appropriate technical solution break away from the scope of various embodiments of the present invention technical scheme.

Claims (12)

1. a spectrum requirement Forecasting Methodology is characterized in that, comprising:

User's traffic carrying capacity in the following time of setting in the estimation range;

According to the distribution of traffic situation of historical time user in the described zone, determine described in the traffic carrying capacity of user in the described following time transmission rate of the business in dissimilar areas in the zone;

According to the allocation proportion in the transmission rate of the business in dissimilar areas in the zone described in the traffic carrying capacity of user in the described following time, default macro base station total number, described macro base station dissimilar areas in described zone, predict the described macro base station number in dissimilar areas in the described zone;

According to the described macro base station number in dissimilar areas in the transmission rate of the business in dissimilar areas in the zone described in the traffic carrying capacity of user in the described following time, the described zone, predict little number of base stations in dissimilar areas in the described zone;

According to the transmission rate of the business in dissimilar areas in the zone described in the traffic carrying capacity of user in the described following time, predict in the described zone service bearer ability of described macro base station and described little service in base station bearing capacity in the dissimilar areas;

Transmission rate according to the business in dissimilar areas in the zone described in the traffic carrying capacity of user in the described following time, dissimilar areas in the described zone that obtains of prediction: the service bearer ability of described macro base station number, described little number of base stations, described macro base station and described little service in base station bearing capacity, predict the frequency spectrum of user's use in the following time in described the zone in.

2. method according to claim 1 is characterized in that, user's traffic carrying capacity comprises voice services volume and data business volume in the following time of setting in the described zone, after user's the traffic carrying capacity, also comprises in the following time of setting in the described estimation range:

According to T _v=M _v* 60 * K is with described voice services volume M _vBe converted to equivalent data traffic carrying capacity T _vWherein, described K is conversion coefficient;

User's traffic carrying capacity in the following time that described equivalent data traffic carrying capacity and described data business volume sum are defined as setting in the described zone.

3. according to the described method of claim 2, it is characterized in that described traffic carrying capacity according to user in the described regional historical time is determined described in the traffic carrying capacity of user in the described following time transmission rate of the business in dissimilar areas in the zone, comprising:

According to $\mathrm{TBH}=\frac{(T_d+T_V)\&times;\mathrm{DLR}\&times;\mathrm{BHR}}{t}$

The transmission rate TBH of downlink business when obtaining busy in the described traffic carrying capacity; Wherein, T _dBe described data business volume, T _VFor described equivalent data traffic carrying capacity, DLR are that described historical time user's ratio, the BHR of downlink traffic in total traffic is the duration of described historical time user's busy-hour traffic when busy in ratio, the t of total traffic are the described following time;

According to TBH _m=TBH * P _m* U _m

The transmission rate TBH of downlink business when obtaining to hurry in the described following time _mWherein, TBH under all standards described when busy transmission rate, the m of downlink business be network formats, the P that adopt in described zone _mAccounting, U for user under the described m network formats _mFor each user under the described m network formats uses the normalized parameter of traffic carrying capacity;

According to TBH _{M, n}=TBH _m* P _n* U _n

Obtain in the described following time in the described zone transmission rate TBH of the downlink business of correspondence in the dissimilar areas _{M, n}Wherein, n is the type in area, TBH _mTransmission rate, the P of downlink business during for busy under the described m network formats _nAccounting, U for user in the described n type area under the described m network formats _nBe that each user uses the normalized parameter of described traffic carrying capacity in the area of n for the described type under the described m network formats.

4. method according to claim 3, it is characterized in that, described macro base station number according to dissimilar areas in the transmission rate of the business in dissimilar areas in the zone described in the traffic carrying capacity of user in the described following time, the described zone, predict little number of base stations in dissimilar areas in the described zone, comprising:

The macro base station in the same type area size according to the transmission rate of institute's loaded service is sorted, and be divided into the j group macro base station group that number equates;

According to ${\mathrm{MSN}}_n=\underset{i=1}{\overset{j}{\mathrm{\&Sigma;}}}{\mathrm{MSN}}_{\mathrm{ni}},$

${\mathrm{MSN}}_{\mathrm{ni}}=\left\{\begin{array}{cc}{\mathrm{SN}}_{\mathrm{ni}}\&times;\mathrm{MSPS},& \frac{{\mathrm{TBH}}_n\&times;{\mathrm{TR}}_i}{{\mathrm{SN}}_{\mathrm{ni}}/{\mathrm{SD}}_n}\&GreaterEqual;G_{\mathrm{MS}}\\ 0,& \frac{{\mathrm{TBH}}_n\&times;{\mathrm{TR}}_i}{{\mathrm{SN}}_{\mathrm{ni}}/{\mathrm{SD}}_n}<G_{\mathrm{MS}}\end{array}\right.$

Type of prediction is little number of base stations MSN in the area of n _nWherein, i is 1 to j integer, MSN _NiBe little number of base stations, the SN that comprises among the i group macro base station group in the area of n for type _NiBe that the macro base station number, the MSPS that comprise among the i group macro base station group in the area of n are that type is little number of base stations, the TBH that comprises in the macrocell of each macro base station in area of n for type _nBe the corresponding transmission rate of downlink business when busy in the area of n for type, described TR _iThe transmission rate of downlink business ratio, SD in the transmission rate of downlink business during correspondence busy in all described types are the area of n when being i group macro base station carrying described busy in area of n for type _nBe the site density of macro base station in the area of n for type, G _MSThe transmission rate density threshold value of downlink business when setting up required busy in little base station at each macro base station.

5. method according to claim 4, it is characterized in that, described transmission rate according to the business in dissimilar areas in the zone described in the traffic carrying capacity of user in the described following time, predict in the described zone service bearer ability of described macro base station and described little service in base station bearing capacity in the dissimilar areas, comprising:

According to MaT=FE _Ma* ASN _Ma* L,

MiT=FE _Mi×ASN _Mi

Calculate described n type area respectively: the service bearer ability MaT of described macro base station and described little service in base station bearing capacity MiT; Wherein, Ma is the attribute-bit of described macro base station, attribute-bit, the FE that Mi is described little base station _MaSpectrum efficiency, ASN for macro base station _MaAverage sector number, FE for macro base station _MiSpectrum efficiency, ASN for little base station _MiFor the average sector number of little base station, L during by described n type area busy the transmission rate of downlink business in this zone network system the ratio in the maximum capacity value of transmission rate of energy bearer service.

6. method according to claim 5, it is characterized in that, described transmission rate according to the business in dissimilar areas in the zone described in the traffic carrying capacity of user in the described following time, dissimilar areas in the described zone that obtains of prediction: the service bearer ability of described macro base station number, described little number of base stations, described macro base station and described little service in base station bearing capacity, predict the frequency spectrum that the user uses in the following time in the described zone, comprising:

According to BW _n=MAX (BW _N1, BW _N2..., BW _Nj),

${\mathrm{BW}}_{\mathrm{ni}}=\left\{\begin{array}{cc}\frac{{\mathrm{TBH}}_n\&times;{\mathrm{TR}}_i-\mathrm{MiT}\&times;B_i\&times;{\mathrm{FU}}_i\&times;{\mathrm{MSN}}_{\mathrm{ni}}}{\mathrm{MaT}\&times;{\mathrm{FU}}_n\&times;{\mathrm{SN}}_{\mathrm{ni}}}& {\mathrm{MSN}}_{\mathrm{ni}}>0\\ \frac{{\mathrm{TBH}}_n\&times;{\mathrm{TR}}_i}{\mathrm{MaT}\&times;{\mathrm{FU}}_n\&times;{\mathrm{SN}}_{\mathrm{ni}}}& {\mathrm{MSN}}_{\mathrm{ni}}=0\end{array}\right.$

Predict the frequency spectrum BW of interior user's use of following time in described n type area in the described zone _nWherein, j be the same type area macro base station according to carry busy the time downlink business the size of transmission rate sort, and the number, the i that are divided into the macro base station group that number equates are 1 to j integer, BW _NiBe required frequency spectrum, the TBH of i group macro base station group in the area of n for type _nFor type be n the area in busy the time downlink business transmission rate, TR _iWhen being busy in the area of n for type in the transmission rate of downlink business during i group busy ratio, the MiT of the transmission rate of downlink business be little service in base station bearing capacity, B _iBe corresponding bandwidth, the FU that distributes in little base station that comprises among the i group macro base station group _iBe the availability of frequency spectrum, the MSN that i organizes the little base station that comprises among the macro base station group _NiBe the number of little base station of comprising among the i group macro base station group in the area of n for type, MaT is the service bearer ability of macro base station, FU _nBe the availability of frequency spectrum, the SN of macro base station in the area of n for type _NiIt is the number of macro base station among the i group macro base station group in the area of n for type.

7. a spectrum requirement prediction unit is characterized in that, comprising: prediction module and processing module;

Described prediction module, user's traffic carrying capacity in the following time that is used for setting in the estimation range;

Described processing module is used for the distribution of traffic situation according to historical time user in the described zone, determines described in the traffic carrying capacity of user in the described following time transmission rate of the business in dissimilar areas in the zone;

Described prediction module also is used for:

According to the allocation proportion in the transmission rate of the business in dissimilar areas in the zone described in the traffic carrying capacity of user in the described following time, default macro base station total number, described macro base station dissimilar areas in described zone, predict the described macro base station number in dissimilar areas in the described zone;

According to the described macro base station number in dissimilar areas in the transmission rate of the business in dissimilar areas in the zone described in the traffic carrying capacity of user in the described following time, the described zone, predict little number of base stations in dissimilar areas in the described zone;

According to the transmission rate of the business in dissimilar areas in the zone described in the traffic carrying capacity of user in the described following time, predict in the described zone service bearer ability of described macro base station and described little service in base station bearing capacity in the dissimilar areas;

Transmission rate according to the business in dissimilar areas in the zone described in the traffic carrying capacity of user in the described following time, dissimilar areas in the described zone that obtains of prediction: the service bearer ability of described macro base station number, described little number of base stations, described macro base station and described little service in base station bearing capacity, predict the frequency spectrum of user's use in the following time in described the zone in.

8. according to the described device of claim 7, it is characterized in that user's traffic carrying capacity comprises voice services volume and data business volume in the following time of setting in the described zone;

Described processing module also is used for after the traffic carrying capacity of user in the following time of setting in described prediction module estimation range:

According to T _v=M _v* 60 * K is with described voice services volume M _vBe converted to equivalent data traffic carrying capacity T _vWherein, described K is conversion coefficient;

User's traffic carrying capacity in the following time that described equivalent data traffic carrying capacity and described data business volume sum are defined as setting in the described zone.

9. described device according to Claim 8 is characterized in that described processing module is used for,

According to $\mathrm{TBH}=\frac{(T_d+T_V)\&times;\mathrm{DLR}\&times;\mathrm{BHR}}{t}$

The transmission rate TBH of downlink business when obtaining busy in the described traffic carrying capacity; Wherein, T _dBe described data business volume, T _VFor described equivalent data traffic carrying capacity, DLR are that described historical time user's ratio, the BHR of downlink traffic in total traffic is the duration of described historical time user's busy-hour traffic when busy in ratio, the t of total traffic are the described following time;

According to TBH _m=TBH * P _m* U _m

The transmission rate TBH of downlink business when obtaining to hurry in the described following time _mWherein, TBH under all standards described when busy transmission rate, the m of downlink business be network formats, the P that adopt in described zone _mAccounting, U for user under the described m network formats _mFor each user under the described m network formats uses the normalized parameter of traffic carrying capacity;

According to TBH _{M, n}=TBH _m* P _n* U _n

Obtain in the described following time in the described zone transmission rate TBH of the downlink business of correspondence in the dissimilar areas _{M, n}Wherein, n is the type in area, TBH _mTransmission rate, the P of downlink business during for busy under the described m network formats _nAccounting, U for user in the described n type area under the described m network formats _nBe that each user uses the normalized parameter of described traffic carrying capacity in the area of n for the described type under the described m network formats.

10. according to the described device of claim 9, it is characterized in that described prediction module is used for,

The macro base station in the same type area size according to the transmission rate of institute's loaded service is sorted, and be divided into the j group macro base station group that number equates;

According to ${\mathrm{MSN}}_n=\underset{i=1}{\overset{j}{\mathrm{\&Sigma;}}}{\mathrm{MSN}}_{\mathrm{ni}},$

${\mathrm{MSN}}_{\mathrm{ni}}=\left\{\begin{array}{cc}{\mathrm{SN}}_{\mathrm{ni}}\&times;\mathrm{MSPS},& \frac{{\mathrm{TBH}}_n\&times;{\mathrm{TR}}_i}{{\mathrm{SN}}_{\mathrm{ni}}/{\mathrm{SD}}_n}\&GreaterEqual;G_{\mathrm{MS}}\\ 0,& \frac{{\mathrm{TBH}}_n\&times;{\mathrm{TR}}_i}{{\mathrm{SN}}_{\mathrm{ni}}/{\mathrm{SD}}_n}<G_{\mathrm{MS}}\end{array}\right.$

Type of prediction is little number of base stations MSN in the area of n _nWherein, i is 1 to j integer, MSN _NiBe little number of base stations, the SN that comprises among the i group macro base station group in the area of n for type _NiBe that the macro base station number, the MSPS that comprise among the i group macro base station group in the area of n are that type is little number of base stations, the TBH that comprises in the macrocell of each macro base station in area of n for type _nBe the corresponding transmission rate of downlink business when busy in the area of n for type, described TR _iThe transmission rate of downlink business ratio, SD in the transmission rate of downlink business during correspondence busy in all described types are the area of n when being i group macro base station carrying described busy in area of n for type _nBe the site density of macro base station in the area of n for type, G _MSThe transmission rate density threshold value of downlink business when setting up required busy in little base station at each macro base station.

11., it is characterized in that described prediction module is used for according to the described device of claim 10,

According to MaT=FE _Ma* ASN _Ma* L,

MiT=FE _Mi×ASN _Mi

Calculate described n type area respectively: the service bearer ability MaT of described macro base station and described little service in base station bearing capacity MiT; Wherein, Ma is the attribute-bit of described macro base station, attribute-bit, the FE that Mi is described little base station _MaSpectrum efficiency, ASN for macro base station _MaAverage sector number, FE for macro base station _MiSpectrum efficiency, ASN for little base station _MiFor the average sector number of little base station, L during by described n type area busy the transmission rate of downlink business in this zone network system the ratio in the maximum capacity value of transmission rate of energy bearer service.

12., it is characterized in that described prediction module is used for according to the described device of claim 11,

According to BW _n=MAX (BW _N1, BW _N2..., BW _Nj),

${\mathrm{BW}}_{\mathrm{ni}}=\left\{\begin{array}{cc}\frac{{\mathrm{TBH}}_n\&times;{\mathrm{TR}}_i-\mathrm{MiT}\&times;B_i\&times;{\mathrm{FU}}_i\&times;{\mathrm{MSN}}_{\mathrm{ni}}}{\mathrm{MaT}\&times;{\mathrm{FU}}_n\&times;{\mathrm{SN}}_{\mathrm{ni}}}& {\mathrm{MSN}}_{\mathrm{ni}}>0\\ \frac{{\mathrm{TBH}}_n\&times;{\mathrm{TR}}_i}{\mathrm{MaT}\&times;{\mathrm{FU}}_n\&times;{\mathrm{SN}}_{\mathrm{ni}}}& {\mathrm{MSN}}_{\mathrm{ni}}=0\end{array}\right.$

Predict the frequency spectrum BW of interior user's use of following time in described n type area in the described zone _nWherein, j be the same type area macro base station according to carry busy the time downlink business the size of transmission rate sort, and the number, the i that are divided into the macro base station group that number equates are 1 to j integer, BW _NiBe required frequency spectrum, the TBH of i group macro base station group in the area of n for type _nFor type be n the area in busy the time downlink business transmission rate, TR _iWhen being busy in the area of n for type in the transmission rate of downlink business during i group busy ratio, the MiT of the transmission rate of downlink business be little service in base station bearing capacity, B _iBe corresponding bandwidth, the FU that distributes in little base station that comprises among the i group macro base station group _iBe the availability of frequency spectrum, the MSN that i organizes the little base station that comprises among the macro base station group _NiBe the number of little base station of comprising among the i group macro base station group in the area of n for type, MaT is the service bearer ability of macro base station, FU _nBe the availability of frequency spectrum, the SN of macro base station in the area of n for type _NiIt is the number of macro base station among the i group macro base station group in the area of n for type.

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