CN102752767B - Method for improving performance of cell edge users by using multi-objective genetic algorithm - Google Patents
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Abstract
The invention discloses a method for improving the performance of cell edge users by using a multi-objective genetic algorithm, and relates to the field of communication. The method for improving the performance of the cell edge users by using the multi-objective genetic algorithm can reduce the number of edge users to the greatest extent and greatly improve the service quality and the satisfaction degree of the users. The method comprises the following steps: enabling a base station to judge whether a user is a cell edge user or not according to measurement reports of the user; enabling the base station to determine the geographical positions of the edge users in coverage; enabling the base station to determine the base station which is in the vicinity of a cell edge user set according to the geographical positions of the edge users and the geographical position of the base station; enabling the base station to exchange information with the neighboring base station through X2; and enabling the base station to generate a coverage adjusting strategy through the multi-objective genetic algorithm according to the obtained information, and adjusting the activation and the closing of an RRU (radio remote unit), the transmission power and the declination angle and the azimuth angle of an antenna to change the coverage, thereby ensuring that users in the inter-cell overlapping region are as few as possible.
Description
Technical field
The present invention relates to the communications field, relate in particular to a kind of method of improving cellular cell marginal user performance with multi-objective genetic algorithm.
Background technology
At Long Term Evolution, (the English full name of Long Term Evolution is Long Term Evolution, be abbreviated as LTE) in system, stress the systematic function of cell edge in particular, because whether the systematic function of cell edge has determined can bring, user is stable, business impression reliably.Because LTE system uplink adopts single-carrier frequency division multiple access access, (the English full name of single-carrier frequency division multiple access access is Single Carrier-Frequency Division Multiple Access, be abbreviated as SC-FDMA), (the English full name of OFDM is Orthogonal Frequency Division Multiple Access to descending employing OFDM, be abbreviated as OFDMA) multi-access mode, its availability of frequency spectrum is close to 1, the channel frequency of junction, edge, neighbor cell may be identical, thereby to adjacent cell base station and user, can produce very strong interference the user at cell edge place.At present, the optimization that cell edge covers is mainly to realize by technology such as presence of intercell interference randomization, inter-cell interference cancellation, Inter-Cell Interference Coordination/avoidance technology (partial frequency multiplexing, soft-frequency reuse, enhancing soft-frequency reuse), resource scheduling algorithms.The < < Soft Frequency Reuse Scheme For UTRAN LTE > > (3GPP number of documents R1-050507) that for example Huawei Company proposes, the < < Inter-Cell Interference Mitigation for EURTA > > (3GPP number of documents R1-051059) that Texas Instruments proposes is to reduce presence of intercell interference by Inter-Cell Interference Coordination technology.But Chinese patent CN101420760 discloses a kind of edge customer scheduling method and device, point out that area interference randomization and interference cancellation techniques complexity are high, the poor deficiency that waits of interference suppressioning effect.Chinese patent CN 102036397A discloses a kind of resource regulating method and device of TD-LTE system, but resource scheduling algorithm is difficult to the fairness of considering frequency domain, time domain, spatial domain and power simultaneously and taking into account user.
Said method is all in the situation that not changing cell coverage area, realizes the optimization of edges cover by inter-cell interference cancellation and resource scheduling algorithm.
Summary of the invention
The object of the present invention is to provide a kind of quantity that can farthest reduce edge customer, that greatly improves user's service quality and satisfaction improves the method for cellular cell marginal user performance with multi-objective genetic algorithm.
Provided by the inventionly by the method that multi-objective genetic algorithm improves cellular cell marginal user performance, be applied to LTE system, comprise the following steps:
1) whether base station is Cell Edge User according to user's measurement report judgement user;
2) coverage inward flange user's geographical position is determined in base station;
3) base station contiguous with Cell Edge User collection, according to the geographical position of described edge customer geographical position and base station, determined in base station;
4) base station and neighbor base station are by X2 (X2 is a kind of logic interfacing of the 3G (Third Generation) Moblie technical specification 3GPP of mechanism definition) exchange message;
5) according to step 4) information that obtains, base station generates coverage by multi-objective genetic algorithm and adjusts strategy, the activation of adjusting RRU with close, transmitting power, Downtilt and azimuth, change coverage, make minizone overlapping region user as far as possible few.
In step 1) in, whether described base station is that Cell Edge User can adopt following method or similarly adjudicate user for the method for Cell Edge User according to user's measurement report judgement user:
(1) according to the quality of reception of reference signal that receives reporting of user, (the English full name of the quality of reception of reference signal is Reference Signal Receiving Quality in base station, be abbreviated as RSRQ), by certain thresholding, judge that whether user is in cell edge;
(2) according to the Reference Signal Received Power that receives reporting of user Zhe community and adjacent area, (the English full name of Reference Signal Received Power is Reference Signal Receiving Power in base station, be abbreviated as RSRP) measured value, the RSRP measured value of Dang Zhe community and when the RSRP measured value of strong adjacent area differs the threshold value that is less than setting, determine that the user is Cell Edge User, otherwise this user is Cell Center User.
In step 2) in, described base station determines that coverage inward flange user's geographical position can adopt following method or similar method for positioning user:
(1) based on satellite fix:
Adopt the geographical position of global positioning system (the English full name of global positioning system is Global Positioning System, is abbreviated as GPS) estimating user;
(2) based on signal, arrive time delay (the English full name that arrives time delay is Time of Arrival, is abbreviated as TA)/arrival angle (the English full name that arrives angle is Angle of Arrival, is abbreviated as AOA) location:
Base station is according to AOA and the TA of received user's upstream data estimating user, and according to described user's AOA and TA, determines the geographical position of described edge customer;
(3) based on signal, arrive delay inequality (it is Observed Time Difference of Arrival that signal arrives delay inequality English full name, is abbreviated as OTDOA) location:
User reports the pilot tone of at least 3 location aided rebroadcast base stations observing to arrive subscriber equipment from corresponding location aided rebroadcast base station, and (the English full name of subscriber equipment is User Equipment to base station, be abbreviated as UE) time difference OTDOA, base station adopts the geographical position of hyperbola positioning method estimating user according to the OTDOA of reporting of user.
In step 3) in, described base station definite and that Cell Edge User collection is contiguous can adopt following methods:
First to determine Cell Edge User concentrated area, then by base station location and user concentrated area, determine geographical position neighbor base station.
Described definite Cell Edge User concentrated area can comprise following methods or similar approach:
According to step 2) measured user geographical position, suppose that east longitude is for just, west longitude is for negative, north latitude is for just, south latitude is for negative, the maximum maxLon of calculation plot edge customer longitude, the minimum value minLon of longitude are, the minimum value minLat of the maximum maxLat of latitude and latitude, and the region that described maxLon, minLon, maxLat and minLat comprise is exactly the concentrated area of Cell Edge User.
In step 4) in, described base station and neighbor base station can adopt following methods by X2 exchange message:
The information such as communicate by letter by X2 interface with neighbor base station in base station, exchanging cell load.
In step 5) in, described in make minizone overlapping region user can adopt following methods less as far as possible:
Use multi-objective genetic algorithm or similar optimized algorithm and adopt strategy intelligence change base station coverage area, reduce as far as possible edge customer quantity, maximize user's network coverage quality and network capacity.
Described genetic algorithm is a kind of groups searching method, and its essential characteristic is by realizing polytropism and global search maintaining the population being comprised of potential solution between generations.Comprise the flow processs such as coding, initialization population, fitness function, selection, intersection, variation.
Described multi-objective genetic algorithm has weight coefficients changing method, paratactic selection method, arrangement back-and-forth method, selects 5 kinds of conventional methods such as function method, mixing method altogether.
Described strategy comprises the conversion of base station control RRU sleep and state of activation, RRU Downtilt, azimuth and transmitting power adjustment etc.
Described network coverage quality is assessed by indexs such as RSRP, RSRQ, guarantees user's basic coverage requirement.
Described network capacity is determined by indexs such as number of users, cell edge throughput, community average throughput, community peak throughput and single customer edge throughput, alone family average throughput and alone family peak throughputs, guarantees that most users can guarantee the stable user's impression obtaining in most scenes.
With in the situation that guaranteeing that user obtains effectively covering, user that the repeating of minizone covers is the least possible as follows for optimizing and revising the feasible Mathematical Modeling of target:
Total m community in model hypothesis net, n user, RSRP=[RSRP in formula
i,j]
n ' mfor reference signal strength matrix, wherein RSRP
i,jfor travelling carriage i receives the intensity of the reference signal of community j, vectorial P=[p
1, p
2..., p
m] m district pilots signal transmission power adjustment scheme of expression, V=[v
1, v
2..., v
m] represent the state of m cell base station, if base station in state of activation, v is 0, otherwise v is 1, θ=[θ
1, θ
2..., θ
m] be m cell-site antenna angle of declination,
for m cell-site antenna azimuth, e (x) is step function,
p
thfor thresholding, be greater than this thresholding and represent to provide effective covering.P in formula
tmin, P
tmaxbe respectively minimum and maximum transmission power that base station allows.
expression is adjusted cell transmit power according to adjusting vectorial P, and vectorial V arranges base station state, and antenna for base station angle of declination is set to q, when antenna for base station azimuth is set to j, in blind area, the number of users of weak covering.
for adjusting cell transmit power according to adjusting vectorial P, vectorial V arranges base station state, and antenna for base station angle of declination is set to θ, and antenna for base station azimuth is set to
time, in repeating the user of overlay area.
The present invention is by arranging the Remote Radio Unit (the English full name of Remote Radio Unit is Radio Remote Unit, is abbreviated as RRU) of some, and RRU is connected with baseband processor by optical fiber.By the configuration to baseband processor, the activation that can control neatly RRU with close, transmitting power, Downtilt and azimuth, in the continuity situation of ensuring coverage, realize and change flexibly overlay area, neighbor cell, make minizone overlapping region user as far as possible few, or when the somewhere time period, user distribution was inhomogeneous (office building 9:00～17:00, the busy region of 10:00～21:00 telephone traffic, market and the 19:00～23:00 such as house, restaurant, public place of entertainment are the peak periods of conversing; Campus student attends class daytime, and just can make a phone call in a large number evening, so evening, phone amount sharply rose), as long as can find sparse user area, just this region can be adjusted into minizone demarcation line, and then reach the object that reduces edge customer number.Therefore, than traditional method of improving marginal user performance, the present invention is changed and is covered the probability that has fundamentally reduced presence of intercell interference by multi-objective genetic algorithm intelligence, the load level of system is optimized, thereby improved cell edge throughput, strengthens entire system user experience.
Advantage of the present invention is that base station is controlled RRU activation and closed by optimized algorithms such as multi-objective Genetics, the strategy such as RRU transmitting power, Downtilt and azimuth adjustment intelligence changes base station coverage area, avoid region that user density is high to become the edge of neighbor cell, reduce as far as possible Cell Edge User quantity, maximize user's network coverage quality and network capacity.Traditional core concept of improving community marginal user performance method allows Cell Edge User work in different frequency, even if reducing edge customer at frequency domain quadrature, user disturbs, the present invention changes base station range by intelligence, from the angle of orthogonal space, fundamentally reduced the probability of presence of intercell interference, the load level of system is optimized, thereby improved cell edge throughput, strengthens entire system user experience.
Accompanying drawing explanation
Fig. 1 is system block diagram of the present invention.
Fig. 2 is the processing execution flow chart of one embodiment of the present invention.
Fig. 3 is multi-objective genetic algorithm flow chart of the present invention.
Fig. 4 is the base station coverage diagram before the embodiment of the present invention is optimized.
Fig. 5 is the base station coverage diagram after the embodiment of the present invention is optimized.
Embodiment
Below in conjunction with accompanying drawing, the embodiment of the present invention is described in detail.
The present invention adopts Remote Radio Unit, and (the English full name of Remote Radio Unit is Radio Remote Unit, being abbreviated as RRU) (the English full name of baseband processing unit is Base Band Unit to+baseband processing unit, be abbreviated as BBU) carry out networking, as shown in Figure 1.In Fig. 1, MME (Mobility Management Entity) is the pass key control node of 3GPP agreement LTE access network, it is responsible for the location of the UE of idle pulley, call process, comprise relaying, S-GW (Serving GateWay) is for connecting the equipment of NO.7 signaling network and IP network, S1 is a kind of logic interfacing of the 3G (Third Generation) Moblie technical specification 3GPP of mechanism definition, eNodeB is enhanced base station, a corresponding logic district of BBU, a plurality of RRU cover a logic district.
Referring to Fig. 2, it realizes unit is eNodeB, and performing step of the present invention is as follows:
(1) whether base station is Cell Edge User according to user's measurement report judgement user;
According to the Reference Signal Received Power RSRP measured value that receives reporting of user Zhe community and adjacent area, the RSRP measured value of this community and when the RSRP measured value of strong adjacent area differs the threshold value that is less than setting, determine that the user is Cell Edge User, otherwise this user is Cell Center User.
(2) geographical position of user in coverage is estimated in base station;
If Cell Edge User outnumber predetermined value, described user is positioned.
Base station is according to AOA and the TA of received user's upstream data estimating user, and according to described user's AOA and TA according to the geographical position of described edge customer.
(3) base station contiguous with Cell Edge User collection, according to the edge customer geographical position of described estimation and the geographical position of base station, determined in base station;
The user geographical position measured according to step (2), suppose that east longitude is for just, west longitude is for negative, north latitude is for just, south latitude is for negative, the maximum maxLon of calculation plot edge customer longitude, the minimum value minLon of longitude are, the minimum value minLat of the maximum maxLat of latitude and latitude, and the region that described maxLon, minLon, maxLat and minLat comprise is exactly the concentrated area of Cell Edge User.
(4) base station A communicates by letter by X2 interface with neighbor base station B, the information such as exchanging cell load;
(5) information obtaining according to step (4), the activation that RRU is adjusted by multi-objective genetic algorithm in base station with close, the strategy such as transmitting power, Downtilt and azimuth, change coverage, make minizone overlapping region user as far as possible few.
Use the optimized algorithms such as multi-objective Genetic to adopt base station to control the conversion of RRU sleep and state of activation, the strategy such as RRU transmitting power, Downtilt and azimuth adjustment intelligence changes base station coverage area, reduce as far as possible edge customer quantity, maximize user's network coverage quality and network capacity.The flow process of multi-objective genetic algorithm (paratactic selection method) as shown in Figure 3.In Fig. 3, the operations such as coding, initialization population, fitness function, selection, intersection, variation are the general terms of genetic algorithm.In this flow process, first determine scale and the maximum genetic algebra of population, then according to the coding method of appointment, carry out initialization population, then the whole individualities in Xian Jiang colony are divided into some sub-groups equably according to the number of sub-goal function, and each sub-group is distributed to a sub-target function.Each sub-goal function carries out independently Selecting operation in corresponding sub-group, select separately the individuality that some fitness are high and form a new sub-group, and then all these newly-generated sub-groups are merged into a complete colony, in this colony, carry out crossover and mutation computing, thereby generate complete colony of future generation, so constantly carry out " cut apart-and column selection-merging " operation, until meet the end condition of genetic algorithm, finally can obtain the Pareto optimal solution of multi-objective optimization question.
With reference to Fig. 4 and Fig. 5, as shown in Figure 4, base station B and base station A, C covers overlapping region and has a large number of users, although can eliminate and the interference of resource scheduling algorithm minimizing part by interference, if but according to method of the present invention, base station is used multi-objective genetic algorithm to control the conversion of RRU sleep and state of activation, RRU transmitting power, the strategy such as Downtilt and azimuth adjustment intelligence changes the coverage of base station, reduce as far as possible minizone overlapping region edge customer quantity, fundamentally eliminate the probability of presence of intercell interference, maximize user's network coverage quality and network capacity.Be embodied in the present example base station A, B, C is by the mutual exchange message of X2 interface, reduce coverage separately, make their middle overlapping regions not have user or few user's that tries one's best words, just can fundamentally solve this cell edge interference problem, improve service quality and the satisfaction of Cell Edge User.After optimization as shown in Figure 5.
Claims (3)
1. with multi-objective genetic algorithm, improve a method for cellular cell marginal user performance, it is characterized in that comprising the following steps:
1) whether base station is Cell Edge User according to user's measurement report judgement user; Whether described base station is that Cell Edge User adopts following method according to user's measurement report judgement user:
(1) base station, according to the quality of reception that receives the reference signal of reporting of user, judges that by certain thresholding whether user is in cell edge;
(2) base station is according to the Reference Signal Received Power measured value that receives reporting of user Zhe community and adjacent area, the RSRP measured value of Dang Zhe community and when the RSRP measured value of strong adjacent area differs the threshold value that is less than setting, determine that the user is Cell Edge User, otherwise this user is Cell Center User;
2) coverage inward flange user's geographical position is determined in base station;
3) base station contiguous with Cell Edge User collection, according to the geographical position of described edge customer geographical position and base station, determined in base station; Described definite base station employing following methods contiguous with Cell Edge User collection:
First to determine Cell Edge User concentrated area, then by base station location and user concentrated area, determine geographical position neighbor base station; Described definite Cell Edge User concentrated area comprises following methods:
According to step 2) measured user geographical position, suppose that east longitude is for just, west longitude is for negative, north latitude is for just, south latitude is for negative, the maximum maxLon of calculation plot edge customer longitude, the minimum value minLon of longitude are, the minimum value minLat of the maximum maxLat of latitude and latitude, and the region that described maxLon, minLon, maxLat and minLat comprise is exactly the concentrated area of Cell Edge User;
4) base station and neighbor base station are by X2 exchange message;
5) according to step 4) information that obtains, base station generates coverage by multi-objective genetic algorithm and adjusts strategy, the activation of adjusting RRU with close, transmitting power, Downtilt and azimuth, change coverage, make minizone overlapping region user as far as possible few; Describedly make minizone overlapping region user adopt less following methods as far as possible:
Use multi-objective genetic algorithm and adopt strategy intelligence to change base station coverage area, reduce as far as possible edge customer quantity, maximize user's network coverage quality and network capacity.
2. a kind of method of improving cellular cell marginal user performance with multi-objective genetic algorithm as claimed in claim 1, is characterized in that in step 2) in, described base station determines that coverage inward flange user's geographical position adopts following method:
(1) based on satellite fix:
Adopt the geographical position of global positioning system estimating user;
(2) based on signal, arrive time delay localization:
Base station is according to AOA and the TA of received user's upstream data estimating user, and according to described user's AOA and TA, determines the geographical position of described edge customer;
(3) based on signal, arrive delay inequality location:
User reports the pilot tone of at least 3 location aided rebroadcast base stations observing from corresponding location aided rebroadcast base station, to arrive the time difference OTDOA of subscriber equipment to base station, base station adopts the geographical position of hyperbola positioning method estimating user according to the OTDOA of reporting of user.
3. a kind of method of improving cellular cell marginal user performance with multi-objective genetic algorithm as claimed in claim 1, is characterized in that in step 4) in, described base station and neighbor base station adopt following methods by X2 exchange message:
Communicate by letter by X2 interface with neighbor base station in base station, exchanging cell load information.
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| JP6096142B2 (en) * | 2013-08-08 | 2017-03-15 | 株式会社Ｎｔｔドコモ | User terminal, base station, and wireless communication method |
| CN104469826A (en) * | 2013-09-13 | 2015-03-25 | 中国移动通信集团海南有限公司 | Antenna scheduling method and system |
| CN104754617B (en) * | 2013-12-30 | 2018-05-08 | 中国移动通信集团湖北有限公司 | A kind of optimization method and device of wireless network |
| CN105407474B (en) * | 2014-09-04 | 2021-01-12 | 北京三星通信技术研究有限公司 | Resource management method and base station |
| CN105024793B (en) * | 2015-06-25 | 2018-02-13 | 山东大学 | Pilot distribution method based on genetic algorithm in a kind of extensive antenna system |
| CN106358173B (en) * | 2015-07-15 | 2020-02-04 | 普天信息技术有限公司 | Method and device for determining downlink edge user |
| CN108173789A (en) * | 2016-12-07 | 2018-06-15 | 中兴通讯股份有限公司 | Disturbance restraining method and device, communication system |
| CN110536338B (en) * | 2018-05-23 | 2023-04-25 | 中国移动通信集团浙江有限公司 | Antenna parameter adjustment method and device |
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