CN105979591A - Optimal user scheduling method based on minimum effective SINR under low-power-consumption large-connection scene - Google Patents

Optimal user scheduling method based on minimum effective SINR under low-power-consumption large-connection scene Download PDF

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CN105979591A
CN105979591A CN201610273591.9A CN201610273591A CN105979591A CN 105979591 A CN105979591 A CN 105979591A CN 201610273591 A CN201610273591 A CN 201610273591A CN 105979591 A CN105979591 A CN 105979591A
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user
sinr
base station
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power consumption
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CN105979591B (en
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李国兵
欧文超
吕刚明
杜清河
任品毅
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Shanghai Lingbo Intelligent Technology Co ltd
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Xian Jiaotong University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/04—Wireless resource allocation
    • H04W72/044—Wireless resource allocation based on the type of the allocated resource
    • H04W72/0453—Resources in frequency domain, e.g. a carrier in FDMA
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/50—Allocation or scheduling criteria for wireless resources
    • H04W72/54—Allocation or scheduling criteria for wireless resources based on quality criteria
    • H04W72/542—Allocation or scheduling criteria for wireless resources based on quality criteria using measured or perceived quality
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

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  • Quality & Reliability (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
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Abstract

The invention discloses an optimal user scheduling method based on a minimum effective SINR under a low-power-consumption large-connection scene. By using the method, resources of low-power-consumption large-connection terminals are distributed reasonably; system performance is increased; and access demands of traditional FullBuffer users can be satisfied and access demands of a lot of the low-power-consumption large-connection terminals can be satisfied too. The method comprises the following steps of step1, in a multi-cell heterogeneous network where the several low-power-consumption large-connection user terminals and FullBuffer user terminals are distributed, dividing each cell into three sectors; in each sector, according to initial positions of a user and a base station, determining channel information of the user and determining the base station providing a service for the user; step2, carrying out resource distribution on a low-power-consumption large-connection user which is served by each base station according to the optimal user scheduling method based on the minimum effective SINR; and step3, distributing the residual resources of each base station to the FullBuffer users according to a polling scheduling method.

Description

Based on the user scheduling method that the effective SINR of minimum is optimum under low-power consumption big connection scene
Technical field
The invention belongs to communication technique field, relate to a kind of 5G novel scene low-power consumption big connection field Based on the effective SINR of minimum under user scheduling strategy protocol under scape, specially low-power consumption big connection scene Optimum user scheduling method.
Background technology
Mobile communication is since the eighties in 20th century is born, through the explosive growth of more than 30 years, Become the Back ground Information network connecting human society.The development of mobile communication changes people's the most deeply Life style, and become and promoted the national economic development, lifting the important of Social Informatization Level to draw Hold up.Along with 4G enters scale commercial stage, towards the year two thousand twenty and the 5th third-generation mobile communication in future (5G) global development focus has been become.
5G will solve the challenge that variation application scenarios allowance below nominal size alienation performance indications are brought, different application field The performance challenges that scape faces is different, Consumer's Experience speed, flux density, time delay, efficiency and connection Number is all likely to become the challenge index of different scene.From the main applied field of mobile Internet and Internet of Things Scape, business demand and challenge are set out, and can summarize the covering of continuous wide area, focus high power capacity, low-power consumption big Connect and highly reliable four the 5G major technique scenes of low time delay.Wherein the big connection of low-power consumption and low time delay are high Reliable scene is mainly directed towards internet of things service, is the scene newly expanded of 5G, and it is mobile logical that emphasis solves tradition Letter cannot support ground Internet of Things and vertical industry application very well.
Low-power consumption big connection scene is mainly directed towards smart city, environmental monitoring, reading intelligent agriculture, forest fire protection Deng with sensing and the data acquisition application scenarios as target, there is small data packets, low-power consumption, magnanimity connection Etc. feature.This Terminal Type has a very wide distribution, large number of, do not require nothing more than network and possess and surpass hundred billion connections Tenability, meets 1,000,000/km2Connect number density index request, but also terminal to be ensured is ultralow Power consumption and Ultra Low Cost.
In traditional cellular network, user terminal is often the single use with FullBuffer business Family, user scheduling method in this case has had a lot, and similar polling algorithm and equitable proportion are calculated Method.But in low-power consumption big connection scene, owing to type of user terminal is various, have a very wide distribution, number Measure numerous, except having the user by outdoor a lot of low-power consumption business of FullBuffer business, cause into As traditional cellular network, dividing frequency money can not be carried out with simple scheduling strategy during the distribution of row resource Source.This patent devises a kind of new user scheduling method to solve problems for this situation.
Summary of the invention
For problems of the prior art, the present invention provides under low-power consumption big connection scene based on minimum Effectively optimum for SINR user scheduling method, the resource distribution of connection terminal big to low-power consumption rationally, carries High systematic function, can not only meet the access demand of traditional F ullBuffer user, and disclosure satisfy that The access demand of a large amount of low-power consumption big connection terminals.
The present invention is to be achieved through the following technical solutions:
Based on the user scheduling method that the effective SINR of minimum is optimum under low-power consumption big connection scene, including such as Lower step,
Step 1, at distribution some low-power consumption big connection user terminal and FullBuffer user terminal Multiple cell heterogeneous network in, every community is divided into three sectors；In each sector, according to user With the channel information that the initial position of base station determines user, and determine the base station of the service of providing the user；
Step 2, the low-power consumption big connection user servicing each base station is according to based on the effective SINR of minimum Optimum user scheduling method carries out resource distribution；
Step 3, distributes to FullBuffer by the resource of each station spare with reference to the dispatching method of poll User.
Preferably, in step 1, in multiple cell heterogeneous network, each sector is distributed a macro base station and two Individual micro-base station, wherein macro base station uses the Uma channel model of ITU, and micro-base station uses the Umi of ITU Channel model.
Preferably, in step 1, determine user is provided the method serviced as follows by which base station, if distance Shi Wei base station, base station that user is nearest and user are in the coverage then user of micro-base station has this micro-base station to carry For service, the macro base station in otherwise user has sector provides service.
Preferably, in step 2, minimum effectively optimum for SINR user scheduling method specifically includes as follows Step,
Step 2.1, all low-power consumption that same base station is mated big connection user according to user to base The distance size stood is ranked up, and puts in order in same set, and represents sub-load with k Wave train number, k initial value is 1；
Step 2.2, takes out first low-power consumption big connection user from user gathers, and is arranged into Kth subcarrier, it is judged that now in kth subcarrier, whether the SINR of all users meets setting mesh Mark SINRoutRequirement, if meeting requirement, then in user being gathered, first user removes and distributes to the K subcarrier, continues step 2.2；If being unsatisfactory for requirement, then perform step 2.3；
Step 2.3, now in kth subcarrier, all users meet requirement, so acquiescence kth Subcarrier has been assigned, and makes k value add 1, continues step 2.2 until not using in user's set Family.
Further, in step 2.2, the SINR value equation below of each user represents:
SINR n = Σ k = 1 K P n | h n k | 2 b n k Σ m = 1 , m ≠ n N Σ k = 1 K P m | h m k | 2 b m k b n k + σ 2 ;
In formula, bnkRepresenting nth user and take situation on kth subcarrier, 1 represents and takies, 0 represents vacant, andbmkWith bnkSimilar, σ2Being the noise power of user, P is to launch Power, h is channel matrix.
Further, in step 2.2, SINRoutRequirement setting procedure is as follows,
Step 2.2.1, distributes at least 5 users the most on each subcarrier, adds up each use respectively The SINR value at family, obtains the sample value of SINR and makes CDF curve chart；
Step 2.2.2, intercepts corresponding point also according to the access probability of system requirements on CDF curve Record SINR, obtains target setting SINRout；
Step 2.2.3, works as SINRn>SINRoutTime, the access probability index of the big user of connection of low-power consumption meets System requirements.
Further, also include the handling capacity to FullBuffer user and low-power consumption is big connects the connecing of user Enter the statistic procedure of probability, the systematic function after judging user scheduling.
Further, the big access probability connecting user of low-power consumption is added up with the following method: calculate respectively The big SINR connecting user of each low-power consumption, the access then finding correspondence on CDF curve chart is general Rate, then statistical average obtains final access probability.
Compared with prior art, the present invention has a following useful technique effect:
The present invention is by user scheduling plan based on minimum effective SINR optimum under low-power consumption big connection scene Slightly scheme, preferential distribution low-power consumption big connection user terminal, then distributes traditional FullBuffer business User terminal, efficiently solves the resource allocation problem of a large amount of low-power consumption big connection terminal.First separate A fraction of frequency resource preferentially selects for low-power consumption big connection user, then remaining resource is distributed To FullBuffer service-user, so ensureing the handling capacity of FullBuffer business greatly While can also access substantial amounts of low-power consumption terminal, greatly enriched the multiformity of network.With legacy cellular Network dispatching method is compared, and this patent sacrifices little throughput performance and exchanged substantial amounts of user connection for Number, is ensureing connecing of the low-power consumption also ensured while throughput of system big connection user terminal to greatest extent Enter probability, optimize the systematic function of heterogeneous network.
Accompanying drawing explanation
Fig. 1 is effective SINR sample CDF curve chart in present example.
Fig. 2 is the isomerism network structure figure described in present example.
Fig. 3 is to access in present example and do not access that low-power consumption is big to be connected under user situation The throughput performance block diagram of FullBuffer user.
Fig. 4 is the big method connecting user's dividing frequency resource of low-power consumption and random assortment in present example The performance comparison figure of frequency resource method.
Detailed description of the invention
Below in conjunction with specific embodiment, the present invention is described in further detail, described in be to the present invention Explanation rather than restriction.
The present invention uses isomerism network structure figure as shown in Figure 2, and macrocell base stations is (hereinafter referred to as " grand Stand ") overlay area be traditional hexagonal honeycomb structure, microcell base station (hereinafter referred to as " micro-station ") Overlay area is circular, and is deployed in the coverage of macro base station with Poisson's point distribution mode.With per family Even it is distributed in macro station, when the micro-base station of user distance is relatively near and is in the coverage of micro-base station, uses Family is provided service by this micro-base station, is otherwise provided the user service by macro base station.Fig. 2 sets macro base station Different from the transmitting power of micro-base station, and all of micro-base station has identical transmitting power.It addition, be Improve the availability of frequency spectrum, it is considered to same band frequency resource is shared in macro base station and micro-base station as far as possible, therefore, There is co-channel interference between macro base station and micro-base station, and between micro-base station, also use identical frequency resource.
It is contemplated that there is the user terminal of two kinds of distinct characteristics in system model, a kind of is traditional The user of FullBuffer business, another kind is the user of the big connection of low-power consumption, and this equipment is to data speed Rate requires relatively low, it is only necessary to ensure minimum data interaction just, but the quantity of such user is special Many.The metric of two class users is different, and the most traditional FullBuffer user pursues handling capacity and refers to Mark, low-power consumption big connection user then pursues access quantity, represents its performance by access probability index.
In the system model that Fig. 2 describes, if the frequency resource that macro base station is identical with the employing of micro-base station, So unavoidably there is co-channel interference between them, the solid line in figure represents the signal that base station is to be transmitted, Dotted line then represents the interference signal that other base station produces, and solid arrow represents the user being provided service by macro base station The signal received, space head then represents is provided the user of service the signal received by macro base station.
For low-power consumption big connection user, the user of the big connection of the most multiple low-power consumption takies one jointly Subcarrier, this has related to the big combinatorial problem connected between user, and these combinations how have been distributed Problem to subcarrier.It is the core of whole idea for this combinatorial problem, it is assumed that we will be by N Individual user combination is assigned in maximum K subcarrier, in the hope of laying as far as possible with the fewest subcarrier Many users also make the access probability of user meet requirement, the like this SINR of user nnThe most permissible Represent with following formula:
SINR n = Σ k = 1 K P n | h n k | 2 b n k Σ m = 1 , m ≠ n N Σ k = 1 K P m | h m k | 2 b m k b n k + σ 2
In formula, bnkRepresenting nth user and take situation on kth subcarrier, 1 represents and takies, 0 table Show vacant, andbmkWith bnkSimilar, bmkRepresent m-th user at kth subcarrier On the situation that takies, σ2Being the noise power of user, P is to launch power, and h is channel matrix.Now Then have, work as SINRn>SINRoutTime, the access probability index of the big user of connection of low-power consumption meets system and wants Ask.
Due to low-power consumption big connect user pursue systematic function be access probability, the most all should The user that class user is successfully accessed accounts for the proportion of total user, it will be assumed that user reaches one relatively with speed Little threshold value then judges that user is successfully accessed, and is expressed as:
Pr{Rn<Rmin}<Prout
R in formulanRepresent low-power consumption big connection user n's and speed, RminRepresent meet the minimum of access conditions and Rate requirement, ProutRepresent the big probability connecting user's access failure of low-power consumption in environment.
Derive further:
Pr{SINRn<SINRmin}<Prout
It is equivalent to:
Pr{SINRn>SINRmin}>1-Prout
Here, due to SINRminCan not by theoretical derivation out, and in reality, also neither one is definite Minimum SINR value, so above-mentioned formula is converted by further, it is desirable to find one suitably SINR value so that ensure that use when the SINR value of user is more than this suitable SINR value when The access probability at family is more than 1-Prout, the most then have: work as SINRn>SINRoutTime, use low-power consumption big connection The access probability index at family meets system requirements.
In practical operation, SINRoutCan not be by theoretical derivation out the most suitable in order to obtain SINRoutValue, it is considered to being obtained by the method for statistics from emulation, concrete grammar is as follows:
(1) distribute at least 5 users on each subcarrier at random, add up the SINR of each user respectively Value, obtains the sample value of a large amount of SINR and makes CDF curve chart, as shown in Figure 1；
(2) on CDF curve, corresponding point record are intercepted according to the access probability of system requirements, false Determine access probability 90%, then choosing SINR value is 0.6920 i.e. SINRout=0.6920.
It is proposed that a kind of feasible low-power consumption big connection user terminals resources allocative decision, concrete steps As follows:
Step 1: all low-power consumption that same base station is mated big connection user according to user to base The distance size stood is ranked up, and puts in order in same set, and represents sub-load with k Wave train number, k initial value is 1；
Step 2: take out first low-power consumption big connection user from user gathers, and be arranged into Kth subcarrier, it is judged that now in kth subcarrier, whether all users meet requirement, wants if meeting Ask, then in user being gathered, first user removes and distributes to kth subcarrier, continues step 2； If being unsatisfactory for requirement, then jump to step 3；
Step 3: now in kth subcarrier, all users meet requirement, so acquiescence kth Subcarrier has been assigned, and makes k value add 1, continues step 2 until not having user in user's set.
FullBuffer user uses the Resource Allocation Formula of poll, according to the result statistics distributed The handling capacity of FullBuffer user and the big access probability connecting user of low-power consumption.Handle up statistics of variables side Case is with reference to conventional mode, and the big access probability connecting user of low-power consumption is added up with the following method: respectively Calculate the big SINR connecting user of each low-power consumption, then on the CDF curve chart of Fig. 1, find correspondence Access probability, then statistical average obtains final access probability.
Embodiment 1:
Simulating scenes uses the network structure shown in Fig. 2, at a traditional macrocellular hexagonal network In topology, point 3 sectors, two Pico bases are spread at random with Poisson's point distribution mode in each sector Standing, user is uniformly distributed in each sector and FullBuffer number of users is set to 10, low rate Dalian Connect number of users and be set to 40.Simultaneously, it is assumed that the same resource of frequency range is shared at macro station and micro-station, and works as user The base station closest with it is provided service, otherwise for micro-station and when being in micro-station coverage by this micro-station Being thered is provided service by the macro station of sector, user place for it, remaining simulation parameter is as shown in table 1.
Table 1 simulation parameter is arranged
Access under the most identical simulation parameter and do not access that low-power consumption is big to be connected under user situation From simulation parameter, the throughput performance block diagram of FullBuffer user, additionally learns that the low-power consumption of access is big The access probability statistical average connecting user reaches 93.61%.It can be seen that do not access low merit Consumption is big, and to connect the user's average throughput in the case of user be 10.2780bps, than access in the case of 9.4498bps is slightly larger, and after analysis reason is access low-power consumption big connection user, base station certainly will distribute Component frequency resource gives these users, and like this frequency resource of FullBuffer CU is the most corresponding Reducing causes average throughput to reduce.
Embodiment 2:
Simulation parameter is same as in Example 1, and we are the low-power consumption proposed big connection user as shown in Figure 4 The method of dividing frequency resource and the performance comparison of random assortment frequency resource method, can be obvious from figure See it is proposed that feasible program the handling capacity of FullBuffer user and low-power consumption big connection user Be better than the mode of random assortment frequency resource in the performance of access probability, with it is proposed that scheme, one Aspect can be reduced as far as the big frequency resource connected shared by user of low-power consumption and make FullBuffer The more frequency resource of CU thus obtain higher throughput performance, on the other hand can also make low merit Consumption big connection user more effectively combine, and more efficiently obtains access probability performance.

Claims (8)

1., based on the user scheduling method that the effective SINR of minimum is optimum under low-power consumption big connection scene, it is special Levy and be, comprise the steps,
Step 1, at distribution some low-power consumption big connection user terminal and FullBuffer user terminal Multiple cell heterogeneous network in, every community is divided into three sectors；In each sector, according to user With the channel information that the initial position of base station determines user, and determine the base station of the service of providing the user；
Step 2, the low-power consumption big connection user servicing each base station is according to based on the effective SINR of minimum Optimum user scheduling method carries out resource distribution；
Step 3, distributes to FullBuffer by the resource of each station spare with reference to the dispatching method of poll User.
Based on minimum effective SINR optimum under low-power consumption the most according to claim 1 big connection scene User scheduling method, it is characterised in that in step 1, in multiple cell heterogeneous network each sector distribution Having a macro base station and two micro-base stations, wherein macro base station uses the Uma channel model of ITU, micro-base Stand and use the Umi channel model of ITU.
Based on minimum effective SINR optimum under low-power consumption the most according to claim 1 big connection scene User scheduling method, it is characterised in that in step 1, determine that user is provided service by which base station Method is as follows, if the nearest Shi Wei base station, base station of distance users and user are in the coverage of micro-base station, User has this micro-base station to provide service, and the macro base station in otherwise user has sector provides service.
Based on minimum effective SINR optimum under low-power consumption the most according to claim 1 big connection scene User scheduling method, it is characterised in that in step 2, minimum effectively optimum for SINR user scheduling Method specifically includes following steps,
Step 2.1, all low-power consumption that same base station is mated big connection user according to user to base The distance size stood is ranked up, and puts in order in same set, and represents sub-load with k Wave train number, k initial value is 1；
Step 2.2, takes out first low-power consumption big connection user from user gathers, and is arranged into Kth subcarrier, it is judged that now in kth subcarrier, whether the SINR of all users meets setting mesh Mark SINRoutRequirement, if meeting requirement, then in user being gathered, first user removes and distributes to the K subcarrier, continues step 2.2；If being unsatisfactory for requirement, then perform step 2.3；
Step 2.3, now in kth subcarrier, all users meet requirement, so acquiescence kth Subcarrier has been assigned, and makes k value add 1, continues step 2.2 until not using in user's set Family.
The most according to claim 4 without minimum effectively optimum for SINR user scheduling method, it is special Levying and be, in step 2.2, the SINR value equation below of each user represents:
SINR n = &Sigma; k = 1 K P n | h n k | 2 b n k &Sigma; m = 1 , m &NotEqual; n N &Sigma; k = 1 K P m | h m k | 2 b m k b n k + &sigma; 2 ;
In formula, bnkRepresenting nth user and take situation on kth subcarrier, 1 represents and takies, 0 represents vacant, andbmkWith bnkSimilar, σ2Being the noise power of user, P is to launch Power, h is channel matrix.
The most according to claim 5 without minimum effectively optimum for SINR user scheduling method, it is special Levy and be, in step 2.2, SINRoutRequirement setting procedure is as follows,
Step 2.2.1, distributes at least 5 users the most on each subcarrier, adds up each use respectively The SINR value at family, obtains the sample value of SINR and makes CDF curve chart；
Step 2.2.2, intercepts corresponding point also according to the access probability of system requirements on CDF curve Record SINR, obtains target setting SINRout；
Step 2.2.3, works as SINRn>SINRoutTime, the access probability index of the big user of connection of low-power consumption meets System requirements.
Based on minimum effective SINR optimum under low-power consumption the most according to claim 6 big connection scene User scheduling method, it is characterised in that also include the handling capacity to FullBuffer user and low-power consumption The statistic procedure of the big access probability connecting user, the systematic function after judging user scheduling.
Based on minimum effective SINR optimum under low-power consumption the most according to claim 7 big connection scene User scheduling method, it is characterised in that low-power consumption big connect user access probability come with the following method Statistics: calculate the big SINR connecting user of each low-power consumption respectively, then find on CDF curve chart Corresponding access probability, then statistical average obtains final access probability.
CN201610273591.9A 2016-04-27 2016-04-27 Based on minimum effectively SINR optimal user scheduling method under the big connection scene of low-power consumption Expired - Fee Related CN105979591B (en)

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