CN104506291B - Disturb multi-service iteration resource allocation methods in triangular crystal lattice - Google Patents
Disturb multi-service iteration resource allocation methods in triangular crystal lattice Download PDFInfo
- Publication number
- CN104506291B CN104506291B CN201410826382.3A CN201410826382A CN104506291B CN 104506291 B CN104506291 B CN 104506291B CN 201410826382 A CN201410826382 A CN 201410826382A CN 104506291 B CN104506291 B CN 104506291B
- Authority
- CN
- China
- Prior art keywords
- user
- service
- mos
- resource allocation
- subcarrier
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related
Links
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L5/00—Arrangements affording multiple use of the transmission path
- H04L5/003—Arrangements for allocating sub-channels of the transmission path
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L27/00—Modulated-carrier systems
- H04L27/26—Systems using multi-frequency codes
- H04L27/2601—Multicarrier modulation systems
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W72/00—Local resource management
- H04W72/20—Control channels or signalling for resource management
- H04W72/27—Control channels or signalling for resource management between access points
Landscapes
- Engineering & Computer Science (AREA)
- Signal Processing (AREA)
- Computer Networks & Wireless Communication (AREA)
- Mobile Radio Communication Systems (AREA)
Abstract
The present invention relates to multi-service iteration resource allocation methods in one kind interference triangular crystal lattice, belong to wireless communication technology field；Comprise the following steps：1. set up interference triangular crystal lattice model；2nd, systematic parameter is initialized, and utilizes interference triangular crystal lattice modeling base station location described in step 1；3. according to user i transmission rate RiCalculate the MOS of the useriValue；4. setting up Optimized model and Optimized model being solved using iterative algorithm, then resource allocation is carried out according to solving result.Compared with the model of traditional base station, the interference triangular crystal lattice structure that the inventive method is carried is closer in the distribution situation of real base station, therefore, it is possible to the base station location in more truly simulating actual conditions, so as to simulate the information such as more real path fading, Xinda gain, the reasonable distribution of resource is carried out using above-mentioned iteration resource allocation methods in this structure, actual demand can be more conformed to.
Description
Technical field
The present invention relates to multi-service iteration resource allocation methods in one kind interference triangular crystal lattice, belong to wireless communication technology neck
Domain.
Technical background
In recent years, people were in explosive growth to the demand of wireless data service.Handheld device has been used not only for connecing
Make a phone call there is provided main wireless service be the new business such as Online Video, file download and voice access.These are new
Type business it is also far from each other to the demand of flow, it is necessary to special instruction, since 2012, the accounting of mobile video flow
50% is had been over, this also further increases the pressure of wireless data traffic transmission, therefore, how efficiently using limited
Radio Resource become an arduous problem.
At present, the achievement in research on resource allocation algorithm has had a lot, and some of which has been related to multimedia clothes
Business.In traditional wireless resource distributing techniques field, generally using service quality (Quality of Service, QoS) this
The size of parameter weighs the excellent degree of radio resource allocation.So-called QoS, refers to that a network can utilize various basic skills
Art, the ability preferably serviced is provided for specified network service, is the critical sales index of Physical layer packet data transmission, is led to
Often it is made up of handling capacity, time delay, error code of network bottom layer etc., is all business service levels for determining users satisfaction degree
General performance.However, it can only represent the parameters such as the delay, shake and packet loss of network, the subjective feeling of user but have ignored
The characteristics of with business itself.By contrast, user experience quality (Quality if Experience, QoE) can be more directly perceived
Reflect the impression of user exactly, be more of practical significance.
Therefore, generally it regard QoE as the foundation for disposing and optimizing network structure in actual applications.Moreover, being used evaluating
During family Quality of experience (QoE), average opinion value (Mean Opinion Score, MOS) is generally quantified as.With utilizing bit
Rate and transmission rate are compared to optimize systematic function, and MOS can compare different types of service in same level, and can
To accomplish compromise well in efficiency and fairness.
The resource allocation algorithm using QoE and MOS as standard was all carried out in the case where some are preferably assumed mostly in the past, phase
The interference in situation is answered to be ignored, base station is also placed in ideal position.And in the case of reality, because cell is shunk and real
Border environment limitation, the position of base station is generally and irregular, but with randomness.Meanwhile, most widely used, optimal base station
Distributed model is the structure of traditional regular regular hexagon lattice structure either square, and both structures can ensure to reach
To maximum coverage, its simulation result will be much better than actual conditions.In addition, many traditional resource allocation algorithms are more paid close attention to
Fairness between different type service, and it is directed to the gap reduced between user's impression of trying one's best, but
This can seriously reduce the performance of total system.
The content of the invention
The purpose of the present invention be not inconsistent to solve the distribution situation of traditional base station model and real base station, existing resource point
With algorithm overall performance it is not high the problem of, it is proposed that it is a kind of based on user experience quality interference triangular crystal lattice topological structure under
Multi-service resource distribution technique, the appraisal procedure of different business is unified, and efficiently distribute limited Radio Resource.
The present invention be applied to OFDM (Orthogonal Frequency Division Multiplexing,
OFDM) system.OFDM is a kind of orthogonal subcarrier multiplexing mode, and its basic thought is：By using permission sub-channel spectra
It is overlapping, and data are transmitted using the method for the frequency division multiplexing being independent of each other parallel.The system not only the availability of frequency spectrum it is high but also
Can be effectively to anti-multipath fading effect.
Concrete scene is：Comprising N number of base station, the ofdm system of K user, wherein type of service have in p kinds, system and used
Family sum is represented by K1+K2+...+KP=K, K1Represent the number of users of the 1st kind of business of progress, K2Represent to carry out the 2nd kind of business
Number of users, K3Represent the number of users ... of the 3rd kind of business of progress, KpRepresent the user of progress pth kind business.
The purpose of the present invention is achieved through the following technical solutions：
Multi-service iteration resource allocation methods in one kind interference triangular crystal lattice, comprise the following steps：
It is as follows that step 1. sets up interference triangular crystal lattice model：
Φ=x | x=Gu+Y1+Y2}
Wherein,It is a generator matrix, η is arithmetic number；U is a bivector, wherein respectively
Individual element is integer；Y1Represent in the Voronoi units V (Gu) constituted around point Gu equally distributed two-dimensional random to
Amount；Y2Represent with (Gu+Y1) it is origin, with RadptbFor the disc area b (Gu+Y of radius1,Radptb) on equally distributed one
Individual two-dimensional random vector；RadptbRepresent disturbance radius；
Step 2. initializes systematic parameter, and utilizes interference triangular crystal lattice modeling base station location described in step 1；
Step 3. is according to user i transmission rate RiThe MOS values of the user are calculated by following formula：
Wherein,Represent under type of service m (1≤m≤p, p are type of service number), user's transmission speed
Rate is to the mapping relations of MOS values, RiThe transmission rate of the i-th (i ∈ [1, K]) individual user is represented, K represents number of users；RiIt can pass through
Following formula is calculated：
Wherein, MiUser i t easet ofasubcarriers are distributed in expression；Ri,kRepresent that i-th of user is individual in kth (k ∈ [1, M])
Transmission rate on subcarrier, M represents total sub-carrier number, and M=B/ Δs B, B represent the total bandwidth of system, and Δ B represents every height
The width of carrier wave；SINRi,kRepresent that letter of i-th of user on k-th of subcarrier adds ratio of making an uproar, its calculation formula is as follows：
Wherein, currently for i-th of user provide service be base station j (j ∈ [1, N]), Pj,kRepresent base station j in kth
Transimission power on individual subcarrier, hijRepresent from base station j to user i channel gain,Represent in subcarrier k
On all interference,Represent base station number total in noise power, N expression systems；
Step 4. is solved to following Optimized models, and carries out resource allocation according to solving result：
Preferably, Radptb=0.52 η.
Preferably, the mapping relations of transmission rate to the MOS described in step 3 are as follows：
When type of service service is speech business, its mapping relations F is：
Wherein, r represents transmission rate, and unit is kbps.
When type of service service is file downloading service, its mapping relations F is as follows：
MOSdownload=α lg (β r)
Wherein, r represents transmission rate, and α and β are adjusting parameter, and its value is real number.
Preferably, α=2.3741 and β=0.2667；
When type of service service is video traffic, its mapping relations F is as follows：
Wherein, SBR represents transmission bit rate, and FR represents frame per second, and PER represents Packet Error Ratio, a1、a2、a3、a4And a5For adjustment ginseng
Number, its value is real number.
Preferably, when video type is SM, a1、a2、a3、a4And a5Value be respectively 2.797, -0.0065,
0.2498th, 2.2073 and 7.1773.
Preferably, when video type is GW, a1、a2、a3、a4And a5Value be respectively 2.273, -0.0022,
0.3322nd, 2.4984 and -3.7433.
Preferably, when video type is RM, a1、a2、a3、a4And a5Value be respectively -0.0228, -0.0065,
0.6582nd, 10.0437 and 0.6865.
Preferably, can be carried out to Optimized model progress solution using iterative algorithm described in step 4, detailed process is such as
Under：
Step 4.1:M subcarrier is distributed into K user, and root using Round Robin algorithm (Round Robin, RR)
According to the type of service of user, the transmission rate R of each user is calculatediAnd MOSi, and by the MOS value summations of all users be
System entirety MOS values；
Step 4.2：First subcarrier is removed from system, the MOS values MOS of now each user is calculatedi；Again will be by
The subcarrier of removal distributes to each user, calculates the MOS values MOS ' of now each useri；Next MOS values twice are found
Maximum user, the i.e. maximum user of MOS values lifting are differed, (F ∈ [1, K], K represent total number of users amount) is represented with F, i.e.,First subcarrier is distributed into user F；Next, according to above-mentioned first son
The method of salary distribution of carrier wave is respectively by second subcarrier, and the 3rd subcarrier ... m-th subcarrier is respectively allocated to lifting most
Big user；Finally, now system entirety MOS values are calculated；
Step 4.3：Continuous repeat step 4.2, distributes to the maximum user of MOS values lifting, directly by each subcarrier successively
To after adjacent operation twice, the difference of overall MOS values is less than the threshold value δ of setting.
The principle to the inventive method is introduced below.
Step 1. sets up base station model
The present invention proposes a kind of new base station model --- interference triangular crystal lattice topological structure.
The base station location considered is located on two-dimentional number plane, and only allows in same position to have a base station.
, it is necessary to first define traditional triangular crystal lattice structure before introducing interference triangular crystal lattice topological structure, Φ is used1Represent, it is two dimension
The set that the point x of formula (1) is constituted is met in real plane, wherein each point represents base station putting position.
Φ1=x | x=Gu } (1)
Wherein,A generator matrix, and u is the real vector of a two dimension, and wherein each
Element is integer, and η is arithmetic number.It realizes structure as shown in fig. 2, it can be seen that triangular crystal lattice structure is the most frequently used
Hexagon base station placing structure, wherein every three adjacent base stations are in an equilateral triangle, therefore is referred to as triangular crystal lattice
Structure.
Triangular crystal lattice is not stable, but it can utilize a random vector by this lattice in Voronoi units
Model becomes stable.Voronoi units are explained as follows：
Assuming that S={ q1,q2,...,qnIt is a scatterplot collection in Euclidean plane, Voronoi diagram dissipates around each
Whole plane is divided into multiple regions (i.e. Voronoi units) by point, is made around scatterplot qiVoronoi unit V (qi) in
Arbitrfary point x meets condition：
Wherein, qjRepresent in plane different from qiScatterplot.Corresponding Voronoi diagram is as shown in Figure 1.
V (Gu) is made to represent to surround certain base station location Gu Voronoi units in plane, then this stable lattice structure
It can be expressed as meeting the set that the point x of formula (3) is constituted in two-dimentional real plane, use Φ2Represent：
Φ2=x | x=Gu+Y1} (3)
Wherein, u is the real vector of a two dimension, and wherein each element is integer, Y1Represent equally distributed in V (Gu)
The real vector of two-dimensional random, it is ensured that above-mentioned triangular crystal lattice structure is stabilization.
Finally definition interference triangular crystal lattice structure.It is in traditional hexagonal lattice architecture basics to disturb triangular crystal lattice structure
On, the random homogeneous perturbation in given range of each base station.It is exactly, using each base station as the center of circle, one to be drawn with given interference radius
Individual disk, base station can be moved on disk on any one point.Which forms interference triangular crystal lattice structure.
Make Y2Represent with (Gu+Y1) it is the center of circle, with RadptbFor the disc area b (Gu+Y of radius1,Radptb) on it is uniform
One two-dimensional random vector of distribution, RadptbRepresent disturbance radius.So interference triangular crystal lattice topological structure can be expressed as two
The set that the point x of formula (4) is constituted is met in the real plane of dimension, is represented with Φ：
Φ=x | x=Gu+Y1+Y2} (4)
Wherein, u is a bivector, and wherein each element is integer.It is brilliant using the interference triangle in foregoing description
Base station location in LF Topology structural simulation system, than traditional base station model more conform in practice base station distribution (Fig. 3 for should
The once realization of structure), resource allocation will be carried out on this basis below, actual conditions are more conformed to.
Step 2. initializes systematic parameter, and triangular crystal lattice topological structure anolog base station position is disturbed in utilization.
Each parameter such as type of service, user's number, base station number, channel parameter in system is initialized.Different
Base station location can produce different path fadings, so as to influence channel gain, therefore, using disturbing triangular crystal lattice topological structure mould
Intend base station location, more real channel conditions can be simulated by determining the positional information of base station, more conform to actual conditions.
Step 3. sets up transmission rate to MOS mapping relations.
The total bandwidth of system is expressed as B, then total sub-carrier number is represented by M=B/ Δ B, wherein Δ B is expressed as often
The width of individual subcarrier.
Make RiUser i (i ∈ [1, K]) transmission rate is represented, can be defined as：
Wherein Ri,kRepresent transmission rate of i-th of user on kth (k ∈ [1, M]) individual subcarrier, MiExpression is distributed to
User i t easet ofasubcarriers, SINRi,kRepresent that letter of i-th of user on k-th of subcarrier adds to make an uproar than (Signal to
Interference plus Noise Ration, SINR), it is assumed that currently for i-th of user provide service be base station j
(j ∈ [1, N]), it can be further represented as：
Wherein, Pj,kRepresent transimission powers of the base station j on k-th of subcarrier, hijRepresent from base station j to user i channel
Gain,All interference on sub-carrierk are represented,Represent noise power.
There are certain mapping relations, and the mapping relations corresponding to different service types between MOS and the rate of information throughput
It is different, it is assumed that the type of service of i-th of user is m (1≤m≤p, p are type of service number), then its transmission rate RiTo pair
Shown in the mapping relations such as formula (7) for answering MOS values：
Therefore, the transmission rate of each user is calculated using formula (5) and formula (6), with reference to its type of service, formula is substituted into
(7) it is the MOS that can determine that the business.As can be seen from the above equation, MOS values by type of service, base station location, customer location, make an uproar
The many factors such as sound and channel parameter influence, and disturb triangular crystal lattice topological structure more to press close to reality than traditional base station model
Border, thus the MOS values that the base station position information determined using the model is calculated are truer, the money carried out using the MOS values
Source distribution is also better able to meet real resource distribution condition, solves actual resource allocation problem.
Step 4. carries out resource allocation using iterative algorithm
Resource point point is carried out in the case of using disturbing triangular crystal lattice topological structure anolog base station position, calculating MOS values
Match somebody with somebody.
The present invention proposes a kind of resource allocation methods of iteration, can maximize the QoE of whole system, i.e., all differences
The summation of business MOS values.This optimization problem can be expressed as：
Due to the log characteristic of MOS evaluation methods, service can be ensured automatically by maximizing the summation of the MOS values of all users
Fairness between the user under different business or different channels quality.Because：Channel is allocated resources to always
The best user of situation, it is impossible to always improve MOS values to greatest extent, especially when MOS values are in of a relatively high level.
At this moment system, which will allocate resources to the not good enough user of channel conditions or those automatically, needs the larger business of stock number
Type.So, the MOS values of whole system will all have larger lifting.
In addition, many resource allocation algorithms are only for the purpose of maximum system performance, and not iterative process, this is also one
Determine to reduce accuracy in degree.MOS evaluation methods are nonlinear, therefore the sequencing of subcarrier distribution also will be to final
Allocation result produce significant impact.Especially when new subcarrier occurs, the distribution of conventional subcarrier is most likely not most
It is excellent.In summary all to consider, the present invention proposes a kind of Resource Allocation Formula of iteration, can with the MOS summations for ensureing system
To reach maximum.The realization approach of this programme is that on the sub-carrier basis distributed in the past, some is continually looked for successively
The optimum allocation of subcarrier, and this subcarrier also can temporarily distribute to the maximum user of now MOS values lifting, until whole
Untill the MOS liftings of individual system can be ignored.
Specifically resource allocation step is：
Step 4.1:M subcarrier is distributed into K user, and root using Round Robin algorithm (Round Robin, RR)
According to the type of service of user, the transmission rate R of each user is calculatediAnd MOS values.
Step 4.2：First subcarrier is removed from system, the MOS values MOS of each user is calculatedi.Now this is
Allocated total number of sub-carriers is (M-1) in system.Removed subcarrier is distributed into each user again, that is, assumes that institute is useful
This subcarrier is with the addition of per family, calculates the MOS values MOS of now each useri′.Now, the subcarrier that all users are allocated
Sum is (M+K-1).The maximum user of MOS values difference twice is found, i.e.,Now
It can determine that first subcarrier distributes to user F lifting maximums, then first subcarrier be distributed into user F.It is now whole
The sub-carrier number of system reverts to M.Then, using the above method respectively by second subcarrier, the 3rd subcarrier ... M
Individual subcarrier is respectively allocated to the maximum user of lifting, then completes once-through operation.
Step 4.3：Continuous repeat step 4.2, distributes to the maximum user of MOS values lifting, directly by each subcarrier successively
To after adjacent operation twice, the difference of overall MOS values is less than the threshold value δ of setting.This is arrived, resource allocation terminates.
Using above-mentioned iteration resource allocation methods, can in the case where each user possesses comparatively ideal preferable MOS values,
Ensure entirety MOS value highests.
Beneficial effect
Compared with the model of traditional base station, the interference triangular crystal lattice structure that the present invention is carried is closer in the distribution of real base station
Situation, therefore, it is possible to the base station location in more truly simulating actual conditions, so as to simulate more real path fading, letter
Up to information such as gains, the reasonable distribution of resource is carried out using above-mentioned iteration resource allocation methods in this structure, can more be accorded with
Close actual demand.
Brief description of the drawings
Fig. 1 is Voronoi diagram schematic diagram；
Fig. 2 is traditional triangle lattice structure schematic diagram, wherein, η=500m；
Fig. 3 disturbs the once realization of triangular crystal lattice topological structure to be proposed by the present invention, wherein disturbing radius Radptb=
0.52η；
Fig. 4 is speech business and file downloading service MOS values and transmission rate graph of a relation；
Fig. 5 is three kinds of video traffic MOS values and transmission rate graph of a relation；
Fig. 6 is the multi business resource allocation method under interference triangular crystal lattice topological structure of the invention designed in embodiment
Lower convergence rate schematic diagram；
Fig. 7 is the multi-service resource distribution side under interference triangular crystal lattice topological structure of the invention designed in embodiment
The comparison diagram of method and each user's MOS values under traditional Round Robin algorithm；
Fig. 8 is the inventive method schematic flow sheet.
Embodiment
To make the target, technical scheme and advantage of the present invention more explicit, embodiments of the invention will be entered below
The detailed description of row.The present embodiment is with the technical scheme is that instruct to carry out actual practice veritification, while giving in detail
Thin embodiment and specific operating process, but protection scope of the present invention is not only limited in examples below.
The schematic flow sheet of the inventive method is illustrated in figure 8, it is described in detail with reference to specific embodiment：
Step 1. sets up base station model
On the basis of traditional triangular crystal lattice structure (such as Fig. 2, base distance between sites are η=500m), the present invention is designed
Triangular crystal lattice topological structure is disturbed once to be realized, the position of simulation system base station, as shown in figure 3, disturbance radius Radptb=
0.52η。
Step 2. initializes systematic parameter
It is as shown in table 1 to each parameter assignment in system：
The system parameter setting of table 1
Step 3. sets up transmission rate to MOS mapping relations
The real base station position of interference triangular crystal lattice topology controlment simulation in using step 1, and in step 2
Each channel parameter of initialization, it may be determined that the information such as channel gain, transimission power, noise power, according to formula (5) (6) and
Relation between each business MOS values and transmission rate, can set up transmission rate to the mapping relations of MOS values.
Based on the assumption that three kinds of radio services are respectively speech business, video traffic and file downloading service, due to every
The MOS computational methods difference of the business of kind, it is necessary to set up the mapping relations between its transmission speed and MOS values respectively.
1) for speech business, providing its subjective quality assessment, some are difficult, therefore MOS is sampled according to a series of voices
Measure, wherein the coded system and content that measure all are different.As a result 4 discrete points are shown, are respectively
In 6.4kbs, 15.2kbps 24.6kbps and 64kbps, it can be formulated as：
Wherein, r represents transmission rate, and unit is kbps.Specific corresponding relation is as shown in Figure 4.
2) for file downloading service, subjective experience and the transmission rate of user are into logarithmic relationship, and specific formula is as follows：
MOS=α lg (β r) (9)
Assuming that the lower bound of the MOS values of file download service is 10kbps, MOS values are 1.0 in this transmission rate, and most
MOS maximums 4.5 are reached on high transfer rate 300kbps,.Then can be with according to upper bound speed and the corresponding MOS values of lower bound speed
Calculate：α=2.3741 and β=0.2667, i.e.,：
MOS=2.3471lg (0.2667r) (10)
Wherein, r represents transmission rate；
The MOS curves of speech business and file downloading service are as shown in Figure 4.
3) for video traffic, the severe degree that video type can change according to video content is divided into 3 kinds, and this three class is regarded
The Variation Features of screen content are slight change (Slight Movement, SM) respectively, moderate change (Gentle Working,
GW) and quickly (Rapid Movement, RM) is changed.Therefore type of service and network layer parameter are being considered, including
Transmission bit rate (Sender Bit Rate, SBR), frame per second (Frame Rate, FR) and Packet Error Ratio (Packet Error
Rate, PER), on the basis of the factor of these joint effect user experience values.Establish following nonlinear video traffic
MOS models：
Table 2 lists the coefficient value in three kinds of video types, and Fig. 5 is fixed on 10fps for video frame rate (FR), wrapped by mistake
Rate (PER) is equal to MOS curves when 0.01.
The coefficient value of 2 three kinds of video types of table
| SM | GW | RM | |
| a1 | 2.797 | 2.273 | -0.0228 |
| a2 | -0.0065 | -0.0022 | -0.0065 |
| a3 | 0.2498 | 0.3322 | 0.6582 |
| a4 | 2.2073 | 2.4984 | 10.0437 |
| a5 | 7.1773 | -3.7433 | 0.6865 |
The video traffic type utilized in the present embodiment is RM, according to the parameter setting in table 2, it is known that：
Step 4. carries out resource allocation using iterative algorithm
In the case of based on above-mentioned base station location, channel parameter and MOS value calculating methods, money mentioned above is utilized
Source allocative decision carries out radio resource allocation, and the subcarrier in system is distributed into each user by successive iteration, is realizing
System MOS values it is maximized simultaneously, it is ensured that the MOS's of each user is optimal, completes effective distribution of resource.
Fig. 6 illustrates the iterations curve suggested plans in the case where two sub-carrier original allocations order is different.
Abscissa represents iterations, and ordinate represents the total MOS values of system.By figure it can be seen that the convergence rate of curve is very fast,
The MOS values of whole system can reach maximum after iteration 5 to 7 times.In addition, the user of this two curves initial subcarrier point
It is entirely different with state, but finally they all converge to identical MOS values, this also demonstrates this iterative scheme right and wrong
Often stable.I.e. subcarrier can utilize the overall MOS performances of this scheme optimization under any distribution state.
Fig. 7 compares the MOS that the present invention suggests plans with each user under Round Robin algorithm two spike-type cultivars allocative decision
As a result.Wherein abscissa is Customs Assigned Number, and ordinate represents MOS values.Wherein numbering 1-8 represents file download user, numbering 9-
16 represent video user, and 17-24 then represents voice user.It can be seen that the present invention suggests plans and Round Robin algorithm phase
Than resource allocation effect has significant raising.Wherein, the MOS values of most of users, which have, is obviously lifted, only few
The MOS of number voice user has small reduction, but still keeps a level close to highest MOS values.Further, since MOS is commented
The log characteristic of valency mode, is almost on excessively poor Consumer's Experience without user, and minimum MOS values have also exceeded 3.2, and respectively
The use for planting service type is more satisfied with per family.
In summary, multi-service iteration resource allocation methods and traditional base in a kind of interference triangular crystal lattice proposed by the present invention
Analogy method of standing is compared, interference triangular crystal lattice structure can truer simulation real base station position, so as to more press close to reality
Path fading, the channel gain on border etc., make simulating scenes closer to reality, therefore simulation result is also more credible.Carried
Fast convergence rate and stability height, based on MOS evaluation methods, and while using the MOS values of maximum overall system as target, make
With each with the user experience value being satisfied with per family under business.
Above-described to specifically describe, the purpose, technical scheme and advantage benefit to invention has all been carried out further in detail
Describe in detail it is bright, should be understood that the foregoing is only the present invention specific embodiment, the guarantor being not intended to limit the present invention
Scope is protected, within the spirit and principles of the invention, any modification, equivalent substitution and improvements done etc. should be included in this
Within the protection domain of invention.
Claims (8)
1. multi-service iteration resource allocation methods in one kind interference triangular crystal lattice, it is characterised in that：Comprise the following steps：
Step 1: it is as follows to set up interference triangular crystal lattice model：
Φ=x | x=Gu+Y1+Y2}
Wherein,It is a generator matrix, η is arithmetic number；U is a bivector, wherein each element
It is integer；Y1Represent the equally distributed two-dimensional random vector in the Voronoi units V (Gu) constituted around point Gu；Y2Represent
With (Gu+Y1) it is origin, with RadptbFor the disc area b (Gu+Y of radius1,Radptb) on an equally distributed two dimension with
Machine vector；RadptbRepresent disturbance radius；
Step 2: initialization systematic parameter, and utilize interference triangular crystal lattice modeling base station location described in step one；
Step 3: according to user i transmission rate RiMean Opinion Score MOS (the Mean Opinion of the user are calculated by following formula
Score) value：
Wherein,Represent under type of service m (1≤m≤p, p are type of service number), user's transmission rate to MOS
The mapping relations of value, RiThe transmission rate of the i-th (i ∈ [1, K]) individual user is represented, K represents number of users；RiFollowing formula meter can be passed through
Calculate：
Wherein, MiUser i t easet ofasubcarriers are distributed in expression；Ri,kRepresent i-th of user in kth (k ∈ [1, M]) individual subcarrier
On transmission rate, M represents total sub-carrier number, and M=B/ Δs B, B represent the total bandwidth of system, and Δ B represents each subcarrier
Width；SINRi,kRepresent signal of i-th of user on k-th of subcarrier and interference and noise ratio SINR (Singal to
Interference plus Noise Ratio), its calculation formula is as follows：
Wherein, currently for i-th of user provide service be base station j (j ∈ [1, N]), Pj,kRepresent base station j in k-th of son
Transimission power on carrier wave, hijRepresent from base station j to user i channel gain,Represent on sub-carrierk
All interference,Represent base station number total in noise power, N expression systems；M
Step 4: being solved to following Optimized models, and resource allocation is carried out according to solving result：
2. multi-service iteration resource allocation methods in a kind of interference triangular crystal lattice according to claim 1, it is characterised in that：
Radptb=0.52 η.
3. multi-service iteration resource allocation methods in a kind of interference triangular crystal lattice according to claim 1, it is characterised in that：
The mapping relations of transmission rate to MOS described in step 3 are as follows：
When type of service service is speech business, its mapping relations F is：
Wherein, r represents transmission rate, and unit is kbps；
When type of service service is file downloading service, its mapping relations F is as follows：
MOSdownload=α lg (β r)
Wherein, α and β is adjusting parameter, and its value is real number；
When type of service service is video traffic, its mapping relations F is as follows：
Wherein, SBR represents transmission bit rate, and FR represents frame per second, and PER represents Packet Error Ratio, a1、a2、a3、 a4And a5For real number, for ginseng
Number.
4. multi-service iteration resource allocation methods in a kind of interference triangular crystal lattice according to claim 3, it is characterised in that：
α=2.3741 and β=0.2667.
5. according to multi-service iteration resource allocation methods in a kind of any described interference triangular crystal lattices of claim 3-4, it is special
Levy and be：When video type is SM, a1、a2、a3、a4And a5Value be respectively 2.797, -0.0065,0.2498,2.2073
With 7.1773.
6. according to multi-service iteration resource allocation methods in a kind of any described interference triangular crystal lattices of claim 3-4, it is special
Levy and be：When video type is GW, a1、a2、a3、a4And a5Value be respectively 2.273, -0.0022,0.3322,2.4984
With -3.7433.
7. according to multi-service iteration resource allocation methods in a kind of any described interference triangular crystal lattices of claim 3-4, it is special
Levy and be：When video type is RM, a1、a2、a3、a4And a5Value be respectively -0.0228, -0.0065,0.6582,
10.0437 with 0.6865.
8. multi-service iteration resource allocation methods in a kind of interference triangular crystal lattice according to claim 1, it is characterised in that：
Can be carried out to Optimized model progress solution using iterative algorithm described in step 4, detailed process is as follows：
Step 4.1:M subcarrier is distributed into K user using Round Robin algorithm, and according to the type of service of user, meter
Calculate the transmission rate R of each useriAnd MOSi, and the MOS value summations of all users are obtained into system entirety MOS values；
Step 4.2：First subcarrier is removed from system, the MOS values MOS of now each user is calculatedi；It will be removed again
Subcarrier distribute to each user, calculate the MOS values MOS of now each useri′；Next MOS values twice are found to differ
The maximum user F (F ∈ [1, K]) of maximum user, i.e. MOS values lifting, i.e.,Will
First subcarrier distributes to user F；Next, second son is carried respectively according to the method for salary distribution of above-mentioned first subcarrier
Ripple, the 3rd subcarrier ... m-th subcarrier is respectively allocated to the maximum user of lifting；Finally, now system is calculated overall
MOS values；
Step 4.3：Continuous repeat step 4.2, distributes to the maximum user of MOS values lifting, Zhi Daoxiang by each subcarrier successively
After adjacent operation twice, the difference of overall MOS values is less than the threshold value δ of setting.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410826382.3A CN104506291B (en) | 2014-12-25 | 2014-12-25 | Disturb multi-service iteration resource allocation methods in triangular crystal lattice |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410826382.3A CN104506291B (en) | 2014-12-25 | 2014-12-25 | Disturb multi-service iteration resource allocation methods in triangular crystal lattice |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN104506291A CN104506291A (en) | 2015-04-08 |
| CN104506291B true CN104506291B (en) | 2017-08-11 |
Family
ID=52948008
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201410826382.3A Expired - Fee Related CN104506291B (en) | 2014-12-25 | 2014-12-25 | Disturb multi-service iteration resource allocation methods in triangular crystal lattice |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104506291B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114828193B (en) * | 2022-04-19 | 2024-04-26 | 北京邮电大学 | Uplink and downlink multi-service concurrent power distribution method for wireless network and storage medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6839348B2 (en) * | 1999-04-30 | 2005-01-04 | Cisco Technology, Inc. | System and method for distributing multicasts in virtual local area networks |
| CN102083220A (en) * | 2010-10-28 | 2011-06-01 | 中国人民解放军信息工程大学 | Quality of experience index-based power distribution method and system |
| CN103327540A (en) * | 2013-07-18 | 2013-09-25 | 西安电子科技大学 | Energy-saving and anti-interference speed cracking method in cognitive heterogeneous network |
| CN103476123A (en) * | 2013-08-30 | 2013-12-25 | 西安电子科技大学 | QoE (quality of experience) support resource distribution method for LTE (long term evolution) network video service |
| CN104023383A (en) * | 2014-05-28 | 2014-09-03 | 北京邮电大学 | QoE prediction-based interference shaping method |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100029282A1 (en) * | 2008-07-31 | 2010-02-04 | Qualcomm Incorporated | Resource partitioning in heterogeneous access point networks |
-
2014
- 2014-12-25 CN CN201410826382.3A patent/CN104506291B/en not_active Expired - Fee Related
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6839348B2 (en) * | 1999-04-30 | 2005-01-04 | Cisco Technology, Inc. | System and method for distributing multicasts in virtual local area networks |
| CN102083220A (en) * | 2010-10-28 | 2011-06-01 | 中国人民解放军信息工程大学 | Quality of experience index-based power distribution method and system |
| CN103327540A (en) * | 2013-07-18 | 2013-09-25 | 西安电子科技大学 | Energy-saving and anti-interference speed cracking method in cognitive heterogeneous network |
| CN103476123A (en) * | 2013-08-30 | 2013-12-25 | 西安电子科技大学 | QoE (quality of experience) support resource distribution method for LTE (long term evolution) network video service |
| CN104023383A (en) * | 2014-05-28 | 2014-09-03 | 北京邮电大学 | QoE prediction-based interference shaping method |
Non-Patent Citations (3)
| Title |
|---|
| A QoE-Oriented Strategy for OFDMA Radio Resource Allocation Based on Min-MOS Maximization;C. Sacchi et al;《IEEE Communications Letters》;20110530;第494-496页 * |
| Spatial Stochastic Models and Metrics for the Structure of Base Stations in Cellular Networks,Wireless Communications;Guo Anjin et al;《IEEE Transactions on》;20131120;第5800-5812页 * |
| 用户体验质量（ＱｏＥ）的模型与评价方法综述;林闯等;《计算机学报》;20120115;第1-15页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN104506291A (en) | 2015-04-08 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN101026445B (en) | Wireless regional area network uplink resource distributing method and device using orthogonal frequency division multi access | |
| CN104768162B (en) | A kind of pilot tone dynamic allocation method of the extensive mimo system of multiple cell | |
| CN103338455B (en) | Communication resource allocation method, system, terminal and network side equipment | |
| CN106658514A (en) | Energy efficiency and frequency spectrum efficiency balance method for micro base station super dense disposition heterogeneous network | |
| CN110121213B (en) | Multi-service resource scheduling method and device | |
| CN106341826B (en) | The resource optimal distribution method towards wireless power private network based on virtualization technology | |
| CN102858015B (en) | Multi-service scheduling method | |
| CN108430104A (en) | A kind of method and its system of optimized for energy efficiency and resource allocation | |
| CN103338453B (en) | A kind of dynamic spectrum access method for hierarchical wireless network network and system | |
| CN102984717B (en) | The evaluation method and system of power system capacity | |
| CN104023400B (en) | For the down channel allocation method based on demand of OFDM base station systems | |
| CN104506291B (en) | Disturb multi-service iteration resource allocation methods in triangular crystal lattice | |
| Masaracchia et al. | The impact of user mobility into non-orthogonal multiple access (noma) transmission systems | |
| CN105611640B (en) | A kind of adjustable CoMP downlink user dispatching method of equitable degree | |
| CN110996326B (en) | Method for planning cluster number of MTC (machine type communication) network in resource reuse scene | |
| CN108012335A (en) | Multipath resource distribution method is virtualized under a kind of software defined network | |
| CN108377481B (en) | energy and rate sensing D2D communication spectrum resource allocation method | |
| CN117201369A (en) | Network rate determining method, device, electronic equipment and storage medium | |
| CN106851726A (en) | A kind of cross-layer resource allocation method based on minimum speed limit constraint | |
| CN107018571A (en) | The inter-cell interference restraint method and system of a kind of partial frequency multiplexing | |
| CN106793122A (en) | A kind of heterogeneous network minimizes Radio Resource safety distribution method per bit | |
| CN105516636A (en) | Heterogeneous network multi-access resource distribution method based on video communication | |
| Merlhe et al. | Dynamic cell-less radio access network meta-scheduler for high system capacity increase | |
| CN104581958A (en) | Resource allocation method and device based on rate self-adaption norm | |
| CN107801251A (en) | Three-dimensional multiple-input and multiple-output descending multi-user Transmission system dispatching method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20170811 Termination date: 20211225 |