CN104581958A - Resource allocation method and device based on rate self-adaption norm - Google Patents

Abstract

The invention relates to the technical field of wireless communication, in particular to a resource allocation method and device based on a rate self-adaption norm. The method includes the steps that a sub carrier is partitioned into blocks; the signal-interference and noise ratio of each sub carrier block is estimated; according to the signal-interference and noise ratio of each sub carrier block, a modulation mode is determined according to a switching threshold value; the number of the sub carrier blocks allocated to users is determined according to the priority of the users; under the conditions that the total transmitting power of a system is fixed and the bit error rate requirement is given, the total throughout of the system is maximized, and the sub carrier blocks are allocated to the users. The method and device are based on the rate self-adaption norm, under the conditions that the total transmitting power of the system is fixed and the bit error rate requirement is given, the total throughout of the system is maximized, the sub carrier blocks are allocated to the users, and an optimal solution for simplifying a problem is effectively searched for through chaos neural power transiently generated by an NCNN.

Description

Based on resource allocation methods and the device of rate adaptation criterion

Technical field

The present invention relates to wireless communication technology field, particularly based on resource allocation methods and the device of rate adaptation criterion.

Background technology

Along with the progress in epoch and the development of broadband wireless communication technique, various wide-band mobile communication demand should be given birth to.People utilize the broadband wireless communication technique such as 3G, LTE, WIMAX and Win, each portable terminal such as smart mobile phone, panel computer etc. and network is used to carry out various information interaction and process, except realizing the business such as traditional voice, note, also comprise the broadband multimedia services such as microblogging, personal letter, terminal positioning, transceiver electronics part, game on line, music download and video request program.

In order to meet various each mobile communication demand, wireless communication technology miscellaneous emerges in an endless stream.But these technology all face a severe problem, that is exactly the main bottleneck that limited Radio Resource has become wireless communication technology development.How to utilize limited Radio Resource to provide effectively again reliably mobile broadband data become the focus that current academia and industrial circle pay close attention to jointly.

RRM is the air interface resource in management of wireless communications system, such as frequency, power and time slot etc., specifically contain Resourse Distribute, packet scheduling, call access control, Bearer Control, load balancing, the technology such as mobile management, by improving Radio Resource utilance in actual applications to the reasonable distribution of Radio Resource with scheduling, in order to effectively improve the bottleneck problem of limited Radio Resource, system generally can adopt distribution or optimized algorithm to carry out reasonably distributing and scheduling to Radio Resource, with the service quality of satisfied kind of business (Quality of Service, QoS) demand.

Outstanding allocation of radio resources and optimized algorithm are except will distributing Radio Resource, more crucially to limited Radio Resource be optimized, further raising wireless resource utility efficiency, simultaneously also can the performance of elevator system each side further, as maximize throughput, minimum power, bit error rate (Bit ErrorRate, BER) and outage probability etc., so a kind of good lifting of Radio Resource optimized algorithm to entire system performance plays vital effect.

Orthogonal frequency division multiplexi (Orthogonal Frequency Division Multiplexing, OFDM) becomes one of key technology of next generation wireless communication technology because it has the advantages such as structure is simple, cost is lower, antijamming capability is strong.More allocation of radio resources and optimisation technique is made to become more complicated because of the not exclusive on an equal basis characteristic of mutually orthogonal, each user of its subcarrier channel condition on each subcarrier.At OFDM (Orthogonal Frequency Division Multiple Access, OFDMA) in system, increasing allocation of radio resources and optimized algorithm occur thereupon, such as simulated annealing, genetic algorithm, ant group algorithm, game theory and convex optimization etc.

But, because allocation of radio resources and optimization problem are usually extremely complicated, much belong to multi-objective optimization question or a nonlinear polynomial difficult problem.Convex optimization method is also had about allocation of radio resources, take maximum system throughput as RA (the Rate Adaptive of target, rate adaptation) algorithm, the MA being target with minimization system power consumption (Margin Adaptive, She measures self adaptation) algorithm; With the maximum effectiveness resource allocation algorithm turning to target of effectiveness (utility), with the maximum efficiency resource allocation algorithm turning to target of energy efficiency (energy efficiency), iterative algorithm, and subcarrier and power joint Distribution Algorithm etc.But above-mentioned algorithm only finds the solution of suboptimum, multi-user diversity gain can not be made full use of.

In sum, there is following problem in prior art:

1) Dynamic Resource Allocation for Multimedia problem is uncertain multinomial problem (NP), adopts above-mentioned algorithm computation complexity very high or can only find suboptimal solution.2) above-mentioned algorithm can not make full use of multi-user diversity gain.

Summary of the invention

The present invention is directed to the deficiency of above technology, propose the resource allocation methods based on rate adaptation criterion and device, use noise chaotic neural network to make full use of multi-user diversity gain and find comparatively ideal feasible solution.

Resource allocation methods based on rate adaptation criterion of the present invention, comprising:

Step 301, sub-carrier carry out piecemeal;

Step 302, estimate the Signal to Interference plus Noise Ratio SINR of each block of sub-carriers, according to the SINR of each block of sub-carriers according to switching threshold determination modulation system, determine the bit number in each OFDM symbol of the subcarrier of a kth user on n-th piece;

Step 303, determine according to the priority of user the block of sub-carriers number distributing to user;

Step 304, fix in the transmitting power that system is total, under given bit error rate requirement condition, maximizing overall system throughput, is each user's allocation of subcarriers block;

Described maximization overall system throughput, for each user's allocation of subcarriers block, comprise: calculate sub carries allocation matrix according to dynamic matrix, sub-carrier allocation matrix carries out sliding-model control, according to the sub carries allocation matrix computations energy function after sliding-model control, if reach exit criteria, then exit iteration, for each user's allocation of subcarriers block, otherwise repeat above process after renewal impetus matrix.

Preferably, also comprise: step 305, be that each block of sub-carriers of determining distributes power, comprising:

$P_n={[\frac{1}{\mathrm{\θ}}-\frac{1}{{\mathrm{ESINR}}_{k,n}}]}^{+}$

Wherein, P _nrepresent the power that block of sub-carriers n distributes, [] ⁺represent and only get the value being more than or equal to 0, the value being less than 0 is set to 0, θ=-λ Nln2/B and represents water filling thresholding, for Lagrange multiplier, B is the bandwidth of a block of sub-carriers, ESINR _k,nrepresent the Signal to Interference plus Noise Ratio in user k n-th block of sub-carriers, P _tfor the transmitting power that system is total, K is number of users, and N is block of sub-carriers number.

Preferably, described sub-carrier carries out piecemeal and comprises the total number of sub-carriers T calculated in available band, the number of subcarriers M in each block of sub-carriers is divided exactly with T, the Integer N obtained is just block of sub-carriers number to be allocated, by subcarrier removal minimum for T-N × M frequency, remaining subcarrier is arranged from low to high by frequency, successively every M subcarrier is divided into a block of sub-carriers.

Preferably, described sub-carrier allocation matrix carries out sliding-model control and comprises:

$V_{k,n}=\left\{\begin{array}{ccc}1,& \mathrm{if}& V_{k,n}\≥\frac{1}{K\×N}{\mathrm{\Σ}}_{k=1}^K{\mathrm{\Σ}}_{n=1}^N{V}_{k,n}\\ 0,& & \mathrm{others}\end{array}\right.$

Wherein, K is number of users number, and N is block of sub-carriers number, V _k,nrepresent block of sub-carriers allocation matrix.

Preferably, described computation energy function comprises:

$\begin{array}{c}E=\frac{A_e}{2}\underset{k=1}{\overset{K}{\mathrm{\Σ}}}\underset{n=1}{\overset{N}{\mathrm{\Σ}}}{V}_{k,n}\frac{1}{2^{\stackrel{\‾}{b_{k,n}}}-1}+\frac{B_e}{2}\underset{k=1}{\overset{K}{\mathrm{\Σ}}}\underset{h\≠k}{\mathrm{\Σ}}\underset{n=1}{\overset{N}{\mathrm{\Σ}}}{V}_{k,n}{V}_{h,n}\\ +\frac{C_e}{2}\underset{k=1}{\overset{K}{\mathrm{\Σ}}}{(\underset{n=1}{\overset{N}{\mathrm{\Σ}}}{V}_{k,n}-C_k)}^2+\frac{D_e}{2}{(\underset{k=1}{\overset{K}{\mathrm{\Σ}}}\underset{n=1}{\overset{N}{\mathrm{\Σ}}}{V}_{k,n}-N)}^2\\ +\frac{F_e}{2}\underset{k=1}{\overset{K}{\mathrm{\Σ}}}\underset{n=1}{\overset{N}{\mathrm{\Σ}}}{V}_{k,n}(1-V_{k,n})\end{array}$

Wherein, A _e, B _e, C _e, D _eand F _efor punishment parameter, V _k,nrepresent block of sub-carriers allocation matrix, K is number of users, and N is block of sub-carriers number, for the bit number in each OFDM symbol of the subcarrier of a kth user on n-th piece, V _k,nv _h,nrepresent whether block of sub-carriers n distributes to user k and h, C simultaneously _krepresent the number distributing to the block of sub-carriers of user k.

Preferably, described exit criteria be iterations more than IN time or energy function keep less, namely the continuous energy threshold IN that is less than for more than 2 times of energy function is maximum iteration time.

Preferably, described renewal impetus matrix comprises:

$\begin{array}{c}{U}_{k,n}(t+1)={\mathrm{\λ}}_0{U}_{k,n}\left(t\right)-{\mathrm{\αA}}_{\mathrm{\ϵ}}\frac{2}{2^{\stackrel{\‾}{b^{k,n}}}-1}-{\mathrm{\αB}}_{\mathrm{\ϵ}}\underset{h\≠k}{\mathrm{\Σ}}{V}_{h,n}\left(t\right)\\ -{\mathrm{\αC}}_{\mathrm{\ϵ}}(\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{V}_{k,n}\left(t\right)-C_k)-{\mathrm{\αD}}_{\mathrm{\ϵ}}(\underset{k=1}{\overset{K}{\mathrm{\Σ}}}\underset{n=1}{\overset{N}{\mathrm{\Σ}}}{V}_{k,n}\left(t\right)-N)-{\mathrm{\αF}}_{\mathrm{\ϵ}}(\frac{1}{2}-V_{k,n}\left(t\right))\\ -Z_{k,n}\left(t\right)(V_{k,n}\left(t\right)-I_0)+Q_{k,n}\left(t\right)\end{array}$

Wherein, A _e, B _e, C _e, D _eand F _efor punishment parameter, V _k,nand V _h,nrepresent block of sub-carriers allocation matrix, U _k,nt () is dynamic matrix, K is number of users, and N is block of sub-carriers number, b _k,nfor the sign bit number of a kth user on subcarrier n, C _krepresent the number distributing to the block of sub-carriers of user k, λ ₀for interneuronal damping factor, α is the amplification coefficient of input vector, Z _k,n(t)=(1-β ₁) Z _k,n(t-1) be neuronic self-feedback connection weights weight, Q _k,n(t)=(1-β ₂) Q _k,n(t-1) be random noise, I ₀for neuronic input deviation, β ₁for the time independently neuron to be coupled damping factor, β ₂for noise simulation annealing decay factor, t is iterations.

Resource allocation device based on rate adaptation criterion of the present invention, comprising:

Subcarrier piecemeal module, carries out piecemeal for sub-carrier;

Modulation system determination module, for determining the modulation system that each block of sub-carriers is selected, according to the SINR of each block of sub-carriers according to switching threshold determination modulation system, determines the bit number in each OFDM symbol of the subcarrier of a kth user on n-th piece;

Sub-carrier assignment module, for determining according to the priority of user the block of sub-carriers number distributing to user;

Maximize overall system throughput module, fix for the transmitting power total in system, under given bit error rate requirement condition, maximizing overall system throughput, is each user's allocation of subcarriers block;

Described maximization overall system throughput module comprises further:

Dynamic matrix generation unit, for generating and renewal impetus matrix;

Sub carries allocation matrix calculation unit, for calculating block of sub-carriers allocation matrix according to dynamic matrix;

Matrix sliding-model control unit, carries out sliding-model control for sub-carrier block allocation matrix;

Energy function function calculating unit, for according to the block of sub-carriers allocation matrix computation energy function after sliding-model control;

Judging unit, if reach exit criteria for judging, then exiting iteration, is each user's allocation of subcarriers block.

Preferably, comprising sub-carrier power distribution module, for distributing power for each block of sub-carriers determined, comprising:

$P_n={[\frac{1}{\mathrm{\θ}}-\frac{1}{{\mathrm{ESINR}}_{k,n}}]}^{+}$

Wherein, P _nrepresent the power that block of sub-carriers n distributes, [] ⁺represent and only get the value being more than or equal to 0, the value being less than 0 is set to 0, θ=-λ Nln2/B and represents water filling thresholding, for Lagrange multiplier, B is the bandwidth of a block of sub-carriers, ESINR _k,nrepresent the Signal to Interference plus Noise Ratio in user k n-th block of sub-carriers, P _tfor the transmitting power that system is total, K is number of users, and N is block of sub-carriers number.

Preferably, described computation energy function comprises:

$\begin{array}{c}E=\frac{A_e}{2}\underset{k=1}{\overset{K}{\mathrm{\Σ}}}\underset{n=1}{\overset{N}{\mathrm{\Σ}}}{V}_{k,n}\frac{1}{2^{\stackrel{\‾}{b_{k,n}}}-1}+\frac{B_e}{2}\underset{k=1}{\overset{K}{\mathrm{\Σ}}}\underset{h\≠k}{\mathrm{\Σ}}\underset{n=1}{\overset{N}{\mathrm{\Σ}}}{V}_{k,n}{V}_{h,n}\\ +\frac{C_e}{2}\underset{k=1}{\overset{K}{\mathrm{\Σ}}}{(\underset{n=1}{\overset{N}{\mathrm{\Σ}}}{V}_{k,n}-C_k)}^2+\frac{D_e}{2}{(\underset{k=1}{\overset{K}{\mathrm{\Σ}}}\underset{n=1}{\overset{N}{\mathrm{\Σ}}}{V}_{k,n}-N)}^2\\ +\frac{F_e}{2}\underset{k=1}{\overset{K}{\mathrm{\Σ}}}\underset{n=1}{\overset{N}{\mathrm{\Σ}}}{V}_{k,n}(1-V_{k,n})\end{array}$

Described exit criteria be iterations more than IN time or energy function keep less, namely energy function is less than energy threshold continuous more than 2 times, and IN is maximum iteration time;

Described renewal impetus matrix comprises:

$\begin{array}{c}{U}_{k,n}(t+1)={\mathrm{\λ}}_0{U}_{k,n}\left(t\right)-{\mathrm{\αA}}_{\mathrm{\ϵ}}\frac{2}{2^{\stackrel{\‾}{b^{k,n}}}-1}-{\mathrm{\αB}}_{\mathrm{\ϵ}}\underset{h\≠k}{\mathrm{\Σ}}{V}_{h,n}\left(t\right)\\ -{\mathrm{\αC}}_{\mathrm{\ϵ}}(\underset{i=1}{\overset{N}{\mathrm{\Σ}}}{V}_{k,n}\left(t\right)-C_k)-{\mathrm{\αD}}_{\mathrm{\ϵ}}(\underset{k=1}{\overset{K}{\mathrm{\Σ}}}\underset{n=1}{\overset{N}{\mathrm{\Σ}}}{V}_{k,n}\left(t\right)-N)-{\mathrm{\αF}}_{\mathrm{\ϵ}}(\frac{1}{2}-V_{k,n}\left(t\right))\\ -Z_{k,n}\left(t\right)(V_{k,n}\left(t\right)-I_0)+Q_{k,n}\left(t\right)\end{array}$

In various above, A _e, B _e, C _e, D _eand F _efor punishment parameter, V _k,nand V _h,nrepresent block of sub-carriers allocation matrix, V _k,nv _h,nrepresent whether block of sub-carriers n distributes to user k and h, U simultaneously _k,nt () is dynamic matrix, K is number of users, and N is block of sub-carriers number, for the sign bit number of a kth user on subcarrier n, C _krepresent the number distributing to the block of sub-carriers of user k, λ ₀for interneuronal damping factor, α is the amplification coefficient of input vector, Z _k,n(t)=(1-β ₁) Z _k,n(t-1) be neuronic self-feedback connection weights weight, Q _k,n(t)=(1-β ₂) Q _k,n(t-1) be random noise, I ₀for neuronic input deviation, β ₁for the time independently neuron to be coupled damping factor, β ₂for noise simulation annealing decay factor, t is iterations.

The present invention is based on rate adaptation criterion, the transmitting power total in system is fixed, under given bit error rate requirement condition, maximizing overall system throughput, is each user's allocation of subcarriers block, and the neural power of the chaos utilizing NCNN transient state to produce is searched for effectively to the optimal solution simplifying problem.

Accompanying drawing explanation

Fig. 1 is the resource allocation methods preferred embodiment flow chart that the present invention is based on rate adaptation criterion;

Fig. 2 is another preferred embodiment flow chart of resource allocation methods that the present invention is based on rate adaptation criterion;

Fig. 3 is that to maximize overall system throughput be each user's allocation of subcarriers block preferred embodiment flow chart in the present invention;

Fig. 4 is the resource allocation device preferred embodiment structure chart that the present invention is based on rate adaptation criterion;

Fig. 5 is another preferred embodiment structure chart of resource allocation device that the present invention is based on rate adaptation criterion;

Fig. 6 is that the resource allocation device that the present invention is based on rate adaptation criterion maximizes overall system throughput module preferred embodiment structure chart;

Fig. 7 is that the present invention and prior art throughput emulate comparison diagram;

Fig. 8 is that the present invention and prior art user Mean Speed emulate comparison diagram.

Embodiment

In order to make object of the present invention, technical scheme and advantage clearly understand, below in conjunction with drawings and Examples, the present invention is described in further details.

The present invention proposes a kind of resource allocation methods based on rate adaptation criterion, and preferred embodiment flow chart as shown in Figure 1, comprising:

Step 301, sub-carrier carry out piecemeal;

Step 302, estimate the Signal to Interference plus Noise Ratio SINR of each block of sub-carriers, according to the SINR of each block of sub-carriers according to switching threshold determination modulation system, determine the bit number in each OFDM symbol of the subcarrier of a kth user on n-th piece;

Step 303, determine according to the priority of user the block of sub-carriers number distributing to user.

Step 304, fix in the transmitting power that system is total, under given bit error rate requirement condition, maximizing overall system throughput, is each user's allocation of subcarriers block; Described bit error rate requires to determine according to described modulation system; The total transmitting power of described system is base station rated power.

Described maximization overall system throughput, for each user's allocation of subcarriers block, comprise: calculate sub carries allocation matrix according to dynamic matrix, sub-carrier allocation matrix carries out sliding-model control, according to the sub carries allocation matrix computations energy function after sliding-model control, if reach exit criteria, then exit iteration, for each user's allocation of subcarriers block, otherwise repeat above process after renewal impetus matrix.

Preferably, alternately, as shown in Figure 2, comprise further:

Step 305, be that each block of sub-carriers of determining distributes power, improve systematic function further.

The present invention proposes a kind of resource allocation device based on rate adaptation criterion, and preferred embodiment structure chart, as shown in Fig. 4, Fig. 6, comprising:

Subcarrier piecemeal module, carries out piecemeal for sub-carrier

Modulation system determination module, for estimating the Signal to Interference plus Noise Ratio SINR of each block of sub-carriers, according to the SINR of each block of sub-carriers according to switching threshold determination modulation system, determines the bit number in each OFDM symbol of the subcarrier of a kth user on n-th piece;

Sub-carrier assignment module, for determining according to the priority of user the block of sub-carriers number distributing to user;

Maximize overall system throughput module, fix for the transmitting power total in system, under given bit error rate requirement condition, maximizing overall system throughput, is each user's allocation of subcarriers block;

Described maximization overall system throughput module comprises further:

Dynamic matrix generation unit, for generating and renewal impetus matrix;

Sub carries allocation matrix calculation unit, for calculating block of sub-carriers allocation matrix according to dynamic matrix;

Matrix sliding-model control unit, carries out sliding-model control for sub-carrier block allocation matrix;

Energy function function calculating unit, for according to the block of sub-carriers allocation matrix computation energy function after sliding-model control;

Judging unit, if reach exit criteria for judging, then exiting iteration, is each user's allocation of subcarriers block.

Preferably, comprise sub-carrier power distribution module further, as shown in Figure 5, for distributing power for each block of sub-carriers determined.

It should be noted that, because the inventive method and device are based on same inventive concept, for saving space, do not describe with not distinguishing adopting the execution mode of identical inventive concept in method and apparatus, in other words, embodiment described below, is described although some part is the tone to accomplish method, equally can as the embodiment of device.

Below the execution mode of each step is described in detail, provides numerous embodiments respectively.

Described sub-carrier carries out piecemeal, comprising:

M adjacent sub-carrier distributes as a block of sub-carriers by the present invention.Can make like this be by adjacent sub-carrier between correlation determine.M can select according to concrete problem, and the sum of the larger block of sub-carriers of M is less, and the flexibility that block of sub-carriers is distributed is poorer, and the multi-user diversity gain of subcarrier just can not make full use of.The sum of the less block of sub-carriers of M is less, and computation complexity is higher.In order to balance this 2 point, the present invention preferably 8 adjacent sub-carriers is divided into one group to form a block of sub-carriers, and the subcarrier simultaneously in same block of sub-carriers adopts identical modulation system.

Concrete subcarrier blocking process is as follows: first calculate the total number of sub-carriers T in available band; Secondly, divide exactly M with T, the Integer N obtained is just block of sub-carriers number to be allocated, finally, by subcarrier removal minimum for T-N × M frequency, is arranged from low to high by remaining subcarrier, successively every M subcarrier is divided into a block of sub-carriers by frequency.

The Signal to Interference plus Noise Ratio SINR of each block of sub-carriers of described estimation comprises the effective Signal to Interference plus Noise Ratio mapping mode (EESM) of estimation index:

${\mathrm{ESINR}}_{k,n}=-{\mathrm{\β}}_m\ln \left(\frac{1}{M}\underset{m=1}{\overset{M}{\mathrm{\Σ}}}\exp (-\frac{{\mathrm{SINR}}_{k,n}^m}{{\mathrm{\β}}_m})\right)---\left(1\right)$

Wherein, M is the number of subcarriers in each block of sub-carriers, ESINR _k,nthe Signal to Interference plus Noise Ratio of a kth user in the n-th block of sub-carriers, it is the Signal to Interference plus Noise Ratio on the m subcarrier of user k on block of sub-carriers n; β _mbe the Dynamic gene based on concrete modulation and coding (Modulation and Coding Scheme, MCS), under different SINR conditions, value is different, and it is according to the corresponding value of response curve in 3GPP standard.

Because the SINR of the subcarrier in same block of sub-carriers is different, the error rate that simultaneously different SINR is corresponding different, and the SINR on multiple OFDM subcarrier can be mapped to effective SINR by exponential form by EESM, therefore the present invention preferably uses EESM to calculate the effective Signal to Interference plus Noise Ratio of index reflecting whole block of sub-carriers SINR situation.

The effective Signal to Interference plus Noise Ratio of the described index according to each block of sub-carriers determines modulation system according to switching threshold, comprising:

According to the indication information of MCS, suppose there is S kind qam mode M _s(s=0,1 ..., s-1).The divided threshold value T of Signal to Interference plus Noise Ratio codomain scope _s(s=0,1 ..., s-1) and be divided into S+1 continuous print not section gap.According to ESINR _k,nvalue which interval to select corresponding modulation pattern at, this rule provides as follows:

$M_s=\left\{\begin{array}{cc}0,& {\mathrm{ESINR}}_{k,n}\&le;T_0\\ M_0,& T_0<{\mathrm{ESINR}}_{k,n}\&le;T_1\\ M_1,& T_1<{\mathrm{ESINR}}_{k,n}\&le;T_2\\ & ...\\ M_{s-1},& T_{s-1}<{\mathrm{ESINR}}_{k,n}\end{array}\right.---\left(2\right)$

T ₀it is minimum threshold value.Work as ESINR _k,n≤ T ₀time there is no corresponding modulation pattern.This means that this block can not be arranged, because its channel status is very bad.

In general, when modulation system is the integral number power of 2, the bit number in each OFDM symbol of the subcarrier of a kth user on n-th piece can be known accordingly by modulation system.

Special issue ground, due to modulation system of the present invention probably not for for 2 integral number power, preferably, determine the sign bit number of a kth user on subcarrier n in the following manner

According to above formula, the modulation system distributing to user's block of sub-carriers just can calculate after determining represent the computing that rounds up.

The described priority according to user determines the block of sub-carriers number distributing to user, comprises

In order to the fairness between the throughput of rational balance sysmte and user, all block of sub-carriers are distributed according to the service priority of user, specifically describe as follows:

C ₁:C ₂:…:C _K＝η ₁:η ₂:…:η _K(3)

Constraints: $\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}{C}_k=N---\left(4\right)$

Wherein C _kand η _krepresent respectively and distribute to the block number of user k and the priority of user k, (3) represent that the block number ratio distributing to user is consistent with the priority ratio of user, and N is total block of sub-carriers number.The priority of described user can be the grade of service, incoming call priority etc., and the type of service according to system definition is determined.

The described transmitting power total in system is fixed, under given bit error rate requirement condition, maximizing overall system throughput, is each user's allocation of subcarriers block; Described bit error rate requires to determine according to described modulation system; The total transmitting power of described system is base station rated power, and system is known.

The target of block of sub-carriers allocation optimized minimizes a nonnegative variable, and this variable is referred to as zoom factor, according to formula definition below:

$f\left(u\right)=\frac{\stackrel{\&OverBar;}{P_{k,n}}}{2^{\stackrel{\&OverBar;}{b_{k,n}}}-1}---\left(5\right)$

Wherein, be the transmitting power of block of sub-carriers, it is a normal number.Work as a block of sub-carriers time maximum, (5) obtain minimum value.So just will maximization problems be converted to the minimization problem of f (u).

(5) formula is just from the angle that single sub-carrier block distributes.In order to maximize total throughput, need to consider all block of sub-carriers distribution condition.According to analysis above, following projected resources allocation optimization problems:

$\arg \min \underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}f\left(u\right)=\arg \min \underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}\frac{\stackrel{\&OverBar;}{P_{k,n}}}{2^{\stackrel{\&OverBar;}{b_{k,n}}}-1}---\left(6\right)$

(6) formula makes total user throughput maximum thus ensures global optimum, for making the optimization problem of (6) effectively be solved, and the following condition of demand fulfillment:

$\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}{P}_{k,n}\&le;P_T$ And $P_{k,n}=M\stackrel{\&OverBar;}{P_{k,n}}$ And $\stackrel{\&OverBar;}{P_{k,n}}\&GreaterEqual;0---\left(7\right)$

$C_1\&cup;C_2...\&cup;C_K\&SubsetEqual;\{\mathrm{1,2},...,N\}---\left(8\right)$

i ≠ j and i, j ∈ 1,2 ..., K} (9)

C ₁:C ₂:…:C _K＝η ₁:η ₂:…:η _K(10)

$\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}{C}_k=N---\left(11\right)$

(7) formula is gross power P _tthe computational methods of constraint and each block of sub-carriers transmitting power; (8) formula represents that user can only distribute block of sub-carriers to be allocated, and the block of sub-carriers number summation that all users distribute can not more than N; (9) formula represents that different user can not distribute identical block of sub-carriers; (10) C in formula _kand η _krepresent respectively and distribute to the number of the block of sub-carriers of user k and the priority of user.The block of sub-carriers number needing to distribute to each user just can be calculated according to formula (10).(11) formula represents that all block of sub-carriers all will be distributed, and N is total block of sub-carriers number.

Because the power on each subcarrier is identical, in formula can be replaced by 1.

$f^{\&prime;}\left(u\right)=\frac{1}{2^{\stackrel{\&OverBar;}{b_{k,n}}}-1}---\left(12\right)$

After each user tentatively distributes total frequency resource and power on each block, the optimization problem of formula (5) is converted into a new problem above: after the block number and effective power of distributing to each user are determined, how block is distributed to the summation of user's just energy minimization zoom factor.Can describe as follows:

$\arg \min \underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}{V}_{k,n}{f}^{\&prime;}\left(u\right)=\arg \min \underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}{V}_{k,n}\frac{1}{2^{\stackrel{\&OverBar;}{b_{k,n}}}-1}---\left(13\right)$

Wherein,

$\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}{V}_{k,n}=C_k---\left(14\right)$

$\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}{V}_{k,n}=N---\left(15\right)$

$\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}{V}_{k,n}=1---\left(16\right)$

V _k,n＝{0,1} (17)

V _k,nrepresent the distribution condition of block, work as V _k,nrepresent when=1 that block n distributes to user k, otherwise V _k,n=0.Under the condition that the transmitting power of the every block of hypothesis is identical, this optimization problem is again write out in (13).Constraint (14) is the data block constraint of demand of each user.Equation (15) is overall system bandwidth restriction.Equation (16) is co-channel interference restriction.Formula (17) represents V _k,n0 or 1 can only be got.Known accordingly, block of sub-carriers allocation optimized is a typical np problem.

Although formula (10) gives the block number needing to distribute to each user, the concrete allocative decision of block is not also determined.Therefore, the target of this resource allocation algorithm how just can obtain best performance for each user resource allocation block system.

Particularly, step 304 of the present invention is fixed in the transmitting power that system is total, under given bit error rate requirement condition, maximize overall system throughput, be each user's allocation of subcarriers block, take with under type, as shown in Figure 3, comprising:

304A, dynamic matrix U is set _k,n(t) initial value

Described dynamic matrix U _k,nt matrix that () is K × N, the element in matrix is the random number between [-1,1];

304B, calculate sub carries allocation matrix according to dynamic matrix

$V_{k,n}\left(t\right)=\frac{1}{1+\exp ({-U}_{k,n}\left(t\right)\&times;u0)}---\left(18\right)$

Wherein, V _k,nt () is dynamic matrix U _k,nt sub carries allocation matrix that () calculates according to excitation function (18).Wherein, u0 is the gain factor of excitation function, and it affects the steepness of excitation function.Excitation function (18) is according to the corresponding selection of practical application, and u0 is according to the corresponding value of the excitation function selected.Preferably, in the present invention, u0 is 8.

304C, sub-carrier allocation matrix sliding-model control

Sub-carrier allocation matrix sliding-model control of the present invention refers to element (the being neuron again) V in sub carries allocation matrix _k,ndiscretely turn to 0 or 1;

Can implementation as one, described sub-carrier allocation matrix sliding-model control is:

$V_{k,n}=\left\{\begin{array}{ccc}1& \mathrm{if}& V_{k,n}\&GreaterEqual;0\\ 0& \mathrm{if}& V_{k,n}<0\end{array}\right.---\left(19\right)$

Preferably, in order to accelerate the convergence of NCNN energy function further, the average of sub carries allocation matrix element is used to upgrade sub carries allocation matrix element as threshold value, namely, being separated final output is more quickly 0 or 1, and described sub-carrier allocation matrix sliding-model control is:

$V_{k,n}=\left\{\begin{array}{ccc}1,& \mathrm{if}& V_{k,n}\&GreaterEqual;\frac{1}{K\&times;N}{\mathrm{\&Sigma;}}_{k=1}^K{\mathrm{\&Sigma;}}_{n=1}^N{V}_{k,n}\\ 0,& & \mathrm{others}\end{array}\right.---\left(20\right)$

304D, computation energy function

The present invention constructs an energy function, and comprise a target function and multiple constraints optimized, the target of allocation optimized of the present invention is minimization of energy function:

$\begin{array}{c}E=\frac{A_e}{2}f{\left(u\right)}^{*}+\frac{B_e}{2}{E}_1+\frac{C_e}{2}{E}_2+\frac{D_e}{2}{E}_3+\frac{F_e}{2}{E}_4\\ =\frac{A_e}{2}\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}{V}_{k,n}\frac{1}{2^{\stackrel{\&OverBar;}{b_{k,n}}}-1}+\frac{B_e}{2}\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}\underset{h\&NotEqual;k}{\mathrm{\&Sigma;}}\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}{V}_{k,n}{V}_{h,n}\\ +\frac{C_e}{2}\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}{(\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}{V}_{k,n}-C_k)}^2+\frac{D_e}{2}{(\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}{V}_{k,n}-N)}^2\\ +\frac{F_e}{2}\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}{V}_{k,n}(1-V_{k,n})\end{array}---\left(21\right)$

Wherein A _e, B _e, C _e, D _eand F _efor punishment parameter, be normal amount, the rule that weight coefficient is followed be all items in energy function in same magnitude, make them all can not dominate, the selection of weight coefficient be very important for each balance in energy function.

Formula (21) be five adding and, to be everyly described below to formula (21) the right:

Section 1 is optimization object function, this function by function f in formula (12) ' the summation of (u) provides.When system convergence is to a stable state, this value will obtain a minimum normal number.Although system convergence is to an optimal solution, this value is also inscrutable.In other words, this object maximizes the bit number on each symbol of all subcarriers.

The value of Section 2 represents that co-channel interference retrains.Only have all V _k,nv _h,nvalue when being 0, this value is just 0.

In the Resourse Distribute of single carrier, each subcarrier can only distribute to a user simultaneously, so just can avoid co-channel interference.Same, the block comprising several subcarrier also can only distribute a user at one time.Rule description is as follows:

$\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}\underset{h\&NotEqual;k}{\mathrm{\&Sigma;}}\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}{V}_{k,n}{V}_{h,n}---\left(22\right)$

Wherein k and h represents user, V _k,nv _h,nshow whether distribute to user k and h by block n (k is not equal to h) simultaneously.If its value is 1 (i.e. V _k,n=1 and V _h,n=1), so will disturb.On the contrary, its value is 0, just can avoid interference.

Section 3 is the block of sub-carriers number constraint of each user, and only have when the block number distributing to user equals the block number of its demand, its value is just 0.

As can be seen from formula (10)-(11), all block of system distributes according to the service priority of each user the demand meeting each user.Like this, the block number that the block constraint of demand of each user should ensure to distribute to it equals the block number of its demand.Meanwhile, this rule also can ensure the fairness between user, and expression formula is as follows:

$\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}{(\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}{V}_{k,n}-C_k)}^2---\left(23\right)$

Section 4 is the restriction of limited system resource, and only having when all block of sub-carriers numbers of distribution are N that its value is just 0, N is block of sub-carriers number.In order to make full use of the frequency resource of system, all blocks that this system provides all must be assigned to user.This rule can be described below:

Section 5 is accelerating ated test item, and it can force neuron output fast close to 0 or 1.Only have when the output of all neurons equals 0 or 1, its value is 0.

Rule description is:

$\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}{V}_{k,n}(1-V_{k,n})---\left(25\right)$

When the second to five all condition all equals zero, system can converge to a stable state.Meanwhile, E is reduced to a fixed value gradually.If all bound term exports be not equal to 0, system can not restrain.

If 304E reaches exit criteria, then by sub carries allocation Output matrix, otherwise, enter 304F;

Preferably, described exit criteria can be one of following condition:

Iterations is more than IN time, and IN is maximum iteration time, value more than 1000 times; Or energy function keeps less, namely energy function is less than energy threshold Eth continuous more than 2 times, and described energy threshold Eth determines according to the practical problem (such as minimum power, maximize throughput etc.) of sub carries allocation matrix dimension, scale and optimization.

304F, renewal impetus matrix, go to step 304B and carry out next iteration;

$\begin{array}{c}{U}_{k,n}(t+1)={\mathrm{\&lambda;}}_0{U}_{k,n}\left(t\right)-{\mathrm{\&alpha;A}}_{\mathrm{\&epsiv;}}\frac{2}{2^{\stackrel{\&OverBar;}{b^{k,n}}}-1}-{\mathrm{\&alpha;B}}_{\mathrm{\&epsiv;}}\underset{h\&NotEqual;k}{\mathrm{\&Sigma;}}{V}_{h,n}\left(t\right)\\ -{\mathrm{\&alpha;C}}_{\mathrm{\&epsiv;}}(\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{V}_{k,n}\left(t\right)-C_k)-{\mathrm{\&alpha;D}}_{\mathrm{\&epsiv;}}(\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}{V}_{k,n}\left(t\right)-N)-{\mathrm{\&alpha;F}}_{\mathrm{\&epsiv;}}(\frac{1}{2}-V_{k,n}\left(t\right))\\ -Z_{k,n}\left(t\right)(V_{k,n}\left(t\right)-I_0)+Q_{k,n}\left(t\right)\end{array}---\left(26\right)$

Z _k,n(t)＝(1-β ₁)Z _k,n(t-1) (27)

Q _k,n(t)＝(1-β ₂)Q _k,n(t-1) (28)

Definition every in formula, in table 1:

Table 1

Described 305 is that each block of sub-carriers of determining is distributed power and comprised and adopt water-filling algorithm to be that each block of sub-carriers determined distributes power, improves systematic function further, comprises

After completing block distribution, average preallocated power is undertaken reallocating by water-filling algorithm thus the throughput of further raising system in a first step.

Obtained by Lagrange multiplier:

$L=\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}B\&times;{\log }_2(1+P_n\&times;{\mathrm{ESINR}}_{k,n})+\mathrm{\&lambda;}(\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}{P}_n-P_T)---\left(29\right)$

Wherein B is the bandwidth of a block of sub-carriers, and N is the sum of block of sub-carriers, ESINR _k,nrepresent the Signal to Interference plus Noise Ratio in user k n-th block of sub-carriers, P _nrepresent the transmitting power in the n-th block of sub-carriers, λ is Lagrange multiplier, P _tfor the transmitting power that system is total, calculate local derviation can obtain

$P_n={[\frac{1}{\mathrm{\&theta;}}-\frac{1}{{\mathrm{ESINR}}_{k,n}}]}^{+}---\left(30\right)$

Here, formula (30) represents, [] ⁺represent and only get the value being more than or equal to 0, the value being less than 0 being set to 0, θ=-λ Nln2/B is water filling thresholding, can obtain the through-put power P in each block of sub-carriers by this method fast _n, further elevator system performance.

Wherein, $\mathrm{\&lambda;}=-B/\ln 2(P_T+\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}\frac{1}{{\mathrm{ESINR}}_{k,n}})---\left(31\right)$

Wherein, K is number of users, and N is block of sub-carriers number.

After calculating the transmitting power of each block of sub-carriers, just distribute for each block of sub-carriers the power P calculated accordingly _n.

For beneficial effect of the present invention is described, the present invention is in noise chaotic neural network NCNN model, and setting K × N number of neuron K user and N number of block of sub-carriers, emulate under table 2 simulation parameter is arranged.

Table 2 simulation parameter

Subcarrier spacing	15KHz
		Time slot	0.5ms
The symbolic number of every frame	7
		Number of users	6，8，10，12，14，16，18
The error rate	10 -4
		Channel model	6 independent Rayleigh multipaths
Additive white gaussian power spectral density	2×10 -3
		Modulation pattern	0，4-QAM，16-QAM，64-QAM
The byte number of every symbol	0，2，4，6
		Switching threshold	6，12，18(dB)

As long as whether as long as find a feasible solution or be no matter that a feasible solution iterative steps reaches the maximum number (being set to 1000 in this emulation) preset, iteration all terminates.

The main experimentally experience of NCNN Model Parameter is selected, and the weight coefficient in energy function is arranged according to optimization problem.

Optimum configurations is as follows: μ 0=8, α=0.05, λ ₀=0.95, I ₀=0.65, z (0)=0.8, A _e=0.5, B _e=2, C _e=5, D _e=3.5, F _e=4.

NCNN performs 1000 times in each case, and under 9 kinds of different situations, the statistics row of NCNN performance in table 3.

Table 3

K	N	β 1＝β 2	Mean iterative number of time	Justifiable rate
					8	96	0.02	125	87.2％
12	96	0.02	142	82.7％
					16	96	0.02	153	73.6％
12	48	0.02	118	88.1％

12	60	0.02	132	81.6％
					12	72	0.02	140	78.8％
12	84	0.03	129	71.3％
					12	84	0.02	135	86.3％
12	84	0.01	141	87.8％

Each neuronic initial condition is stochastic generation, to show the robustness of NCNN.It is as shown in the table, and Average Iteration step number increases with the increase of neuron scale, but the ratio of reliable solution is but in reduction.Its reason is, because K and N becomes large, the neural power that NCNN produces becomes more flexible and complicated.

Fig. 7 is the throughput emulation comparison diagram of algorithms of different, and transverse axis is average signal-to-noise ratio (Average SNR), is defined as P _t/ N ₀b, N ₀be the power spectral density of additive white Gaussian noise, the longitudinal axis is throughput of system (Throughput of system).Show the throughput of four kinds of algorithms in figure, MAX C/I (maximum subcarrier interference ratio) algorithm mean each dispatching cycle each block of sub-carriers distribute to the best user of channel quality.Therefore, its throughput is maximum.But this algorithm does not consider the fairness between user.The throughput of the throughput ratio MAX C/I algorithm of other algorithm is low is because their block distributes to user accordingly according to the service priority of user.Like this can fairness effectively between balance sysmte throughput and user.CRA algorithm algorithm obtain throughput ratio the present invention (proposed algorithm) institute carry algorithm lower be because CRA algorithm can not find optimum block allocative decision.Average power allocation algorithm (APAalgorithm) representative distributes at second step power averaging.

Result shows, APA algorithm can find optimum block to distribute, but due to it can not distribution system is total dynamically transmitting power, its throughput is still lower.As can be seen from experiment, method therefor of the present invention is fixed in the transmitting power that system is total, under given bit error rate requirement condition, the throughput obtained is better than other algorithm.And due to this algorithm assigns is block of sub-carriers, its computation complexity is lower than other algorithm.

Fig. 8 is that above four kinds of algorithm user Mean Speeds compare, transverse axis represents number of users (numbers ofusers), the longitudinal axis represents user's Mean Speed (Average user rate), and four columns at each number of users scale place from left to right represent respectively: MAX C/I algorithm, the present invention, CRA algorithm and APA algorithm.

The average user speed of four kinds of algorithms all increases with the increase of number of users as can be seen from Figure 8.MAXC/I algorithm has best performance to be send because of the user that its total selective channel condition is best, but this algorithm does not consider the fairness between user.The present invention obtains better throughput than CRA algorithm.And the capacity difference between them is apart from increasing with the increase of user.This is because the present invention relies on NCNN can make full use of user diversity gain.The capacity of APA algorithm is minimum is because it does not dynamically distribute power according to user's channel condition at that time.

The present invention has carried out further detailed description for execution mode or embodiment to the object, technical solutions and advantages of the present invention; be understood that; above lifted execution mode or embodiment are only the preferred embodiment of the present invention; not in order to limit the present invention; all any amendments made for the present invention within the spirit and principles in the present invention, equivalent replacement, improvement etc., all should be included within protection scope of the present invention.

Claims (10)

1. based on the resource allocation methods of rate adaptation criterion, it is characterized in that: comprising:

Step 301, sub-carrier carry out piecemeal;

Step 302, estimate the Signal to Interference plus Noise Ratio SINR of each block of sub-carriers, according to the SINR of each block of sub-carriers according to switching threshold determination modulation system, determine the sign bit number of a kth user on subcarrier n;

Step 303, determine according to the priority of user the block of sub-carriers number distributing to user;

Step 304, fix in the transmitting power that system is total, under given bit error rate requirement condition, maximizing overall system throughput, is each user's allocation of subcarriers block;

Described maximization overall system throughput, for each user's allocation of subcarriers block, comprise: calculate sub carries allocation matrix according to dynamic matrix, sub-carrier allocation matrix carries out sliding-model control, according to the sub carries allocation matrix computations energy function after sliding-model control, if reach exit criteria, then exit iteration, for each user's allocation of subcarriers block, otherwise repeat above process after renewal impetus matrix.

2. according to claim 1 based on the resource allocation methods of rate adaptation criterion, it is characterized in that: also comprise: step 305, be that each block of sub-carriers of determining distributes power, comprising:

$P_n={[\frac{1}{\mathrm{\&theta;}}-\frac{1}{{\mathrm{ESINR}}_{k,n}}]}^{+}$

Wherein, P _nrepresent the power that block of sub-carriers n distributes, [] ⁺represent and only get the value being more than or equal to 0, the value being less than 0 is set to 0, θ=-λ Nln2/B and represents water filling thresholding, for Lagrange multiplier, B is the bandwidth of a block of sub-carriers, ESINR _k,nrepresent the Signal to Interference plus Noise Ratio of user k in the n-th block of sub-carriers, P _tfor the transmitting power that system is total, K is number of users, and N is block of sub-carriers number.

3. according to claim 1 or 2 based on the resource allocation methods of rate adaptation criterion, it is characterized in that: described sub-carrier carries out piecemeal and comprises the total number of sub-carriers T calculated in available band, the number of subcarriers M in each block of sub-carriers is divided exactly with T, the Integer N obtained is just block of sub-carriers number to be allocated, by subcarrier removal minimum for T-N × M frequency, remaining subcarrier is arranged from low to high by frequency, successively every M subcarrier is divided into a block of sub-carriers.

4. according to claim 1 or 2 based on the resource allocation methods of rate adaptation criterion, it is characterized in that: described sub-carrier allocation matrix carries out sliding-model control and comprises:

$V_{k,n}=\left\{\begin{array}{cc}1,& \mathrm{if}{V}_{k,n}\&GreaterEqual;\frac{1}{K\&times;N}{\mathrm{\&Sigma;}}_{k=1}^K{\mathrm{\&Sigma;}}_{n=1}^N{V}_{k,n}\\ 0,& \mathrm{others}\end{array}\right.$

Wherein, K is number of users, and N is block of sub-carriers number, V _k,nrepresent block of sub-carriers allocation matrix.

5. according to claim 1 or 2 based on the resource allocation methods of rate adaptation criterion, it is characterized in that: described computation energy function comprises:

$\begin{array}{c}E=\frac{A_e}{2}\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}{V}_{k,n}\frac{1}{2^{\stackrel{\&OverBar;}{b_{k,n}}}-1}+\frac{B_e}{2}\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}\underset{h\&NotEqual;k}{\mathrm{\&Sigma;}}\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}{V}_{k,n}{V}_{h,n}\\ +\frac{C_e}{2}\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}{(\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}{V}_{k,n}-C_k)}^2+\frac{D_e}{2}{(\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}{V}_{k,n}-N)}^2\\ +\frac{F_e}{2}\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}{V}_{k,n}(1-V_{k,n})\end{array}$

Wherein, A _e, B _e, C _e, D _eand F _efor punishment parameter, V _k,nrepresent block of sub-carriers allocation matrix, N is block of sub-carriers number, and K is number of users, for the bit number in each OFDM symbol of the subcarrier of a kth user on n-th piece, V _k,nv _h,nrepresent whether block of sub-carriers n distributes to user k and h, C simultaneously _krepresent the number distributing to the block of sub-carriers of user k.

6. according to claim 1 or 2 based on the resource allocation methods of rate adaptation criterion, it is characterized in that: described exit criteria be iterations more than IN time or energy function keep less, namely energy function is less than energy threshold continuous more than 2 times, and IN is maximum iteration time.

7. according to claim 1 or 2 based on the resource allocation methods of rate adaptation criterion, it is characterized in that: described renewal impetus matrix comprises:

$\begin{array}{c}{U}_{k,n}(t+1)={\mathrm{\&lambda;}}_0{U}_{k,n}\left(t\right)-\mathrm{\&alpha;}{A}_{\mathrm{\&epsiv;}}\frac{2}{2^{\stackrel{\&OverBar;}{b^{k,n}}}-1}-\mathrm{\&alpha;}{B}_{\mathrm{\&epsiv;}}\underset{h\&NotEqual;k}{\mathrm{\&Sigma;}}{V}_{h,n}\left(t\right)\\ -\mathrm{\&alpha;}{C}_{\mathrm{\&epsiv;}}(\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{V}_{k,n}\left(t\right)-C_k)-\mathrm{\&alpha;}{D}_{\mathrm{\&epsiv;}}(\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}{V}_{k,n}\left(t\right)-N)-\mathrm{\&alpha;}{F}_{\mathrm{\&epsiv;}}(\frac{1}{2}-V_{k,n}\left(t\right))\\ -Z_{k,n}\left(t\right)(V_{k,n}\left(t\right)-I_0)+Q_{k,n}\left(t\right)\end{array}$

Wherein, A _e, B _e, C _e, D _eand F _efor punishment parameter, V _k,nand V _h,nrepresent block of sub-carriers allocation matrix, U _k,nt () is dynamic matrix, K is number of users, and N is block of sub-carriers number, for the sign bit number of a kth user on subcarrier n, C _krepresent the number distributing to the block of sub-carriers of user k, λ ₀for interneuronal damping factor, α is the amplification coefficient of input vector, Z _k,n(t)=(1-β ₁) Z _k,n(t-1) be neuronic self-feedback connection weights weight, Q _k,n(t)=(1-β ₂) Q _k,n(t-1) be random noise, I ₀for neuronic input deviation, β ₁for the time independently neuron to be coupled damping factor, β ₂for noise simulation annealing decay factor, t is iterations.

8. based on the resource allocation device of rate adaptation criterion, it is characterized in that, comprising:

Subcarrier piecemeal module, carries out piecemeal for sub-carrier;

Modulation system determination module, for estimating the Signal to Interference plus Noise Ratio SINR of each block of sub-carriers, according to the SINR of each block of sub-carriers according to switching threshold determination modulation system, determines the bit number in each OFDM symbol of the subcarrier of a kth user on n-th piece;

Sub-carrier assignment module, for determining according to the priority of user the block of sub-carriers number distributing to user;

Maximize overall system throughput module, fix for the transmitting power total in system, under given bit error rate requirement condition, maximizing overall system throughput, is each user's allocation of subcarriers block;

Described maximization overall system throughput module comprises further:

Dynamic matrix generation unit, for generating and renewal impetus matrix;

Sub carries allocation matrix calculation unit, for calculating block of sub-carriers allocation matrix according to dynamic matrix;

Matrix sliding-model control unit, carries out sliding-model control for sub-carrier block allocation matrix;

Energy function function calculating unit, for according to the block of sub-carriers allocation matrix computation energy function after sliding-model control;

Judging unit, if reach exit criteria for judging, then exiting iteration, is each user's allocation of subcarriers block.

9. according to claim 8 based on the resource allocation device of rate adaptation criterion, it is characterized in that, comprise sub-carrier power distribution module, for distributing power for each block of sub-carriers determined, comprising:

$P_n={[\frac{1}{\mathrm{\&theta;}}-\frac{1}{{\mathrm{ESINR}}_{k,n}}]}^{+}$

Wherein, P _nrepresent the power that block of sub-carriers n distributes, [] ⁺represent and only get the value being more than or equal to 0, the value being less than 0 is set to 0, θ=-λ Nln2/B and represents water filling thresholding, for Lagrange multiplier, B is the bandwidth of a block of sub-carriers, ESINR _k,nrepresent the Signal to Interference plus Noise Ratio in user k n-th block of sub-carriers, P _tfor the transmitting power that system is total, K is number of users, and N is block of sub-carriers number.

10., according to claim 8 or claim 9 based on the resource allocation device of rate adaptation criterion, it is characterized in that:

Described computation energy function comprises:

$\begin{array}{c}E=\frac{A_e}{2}\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}{V}_{k,n}\frac{1}{2^{\stackrel{\&OverBar;}{b_{k,n}}}-1}+\frac{B_e}{2}\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}\underset{h\&NotEqual;k}{\mathrm{\&Sigma;}}\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}{V}_{k,n}{V}_{h,n}\\ +\frac{C_e}{2}\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}{(\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}{V}_{k,n}-C_k)}^2+\frac{D_e}{2}{(\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}{V}_{k,n}-N)}^2\\ +\frac{F_e}{2}\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}{V}_{k,n}(1-V_{k,n})\end{array}$

Described exit criteria be iterations more than IN time or energy function keep less, namely energy function is less than energy threshold continuous more than 2 times, and IN is maximum iteration time;

Described renewal impetus matrix comprises:

$\begin{array}{c}{U}_{k,n}(t+1)={\mathrm{\&lambda;}}_0{U}_{k,n}\left(t\right)-\mathrm{\&alpha;}{A}_{\mathrm{\&epsiv;}}\frac{2}{2^{\stackrel{\&OverBar;}{b^{k,n}}}-1}-\mathrm{\&alpha;}{B}_{\mathrm{\&epsiv;}}\underset{h\&NotEqual;k}{\mathrm{\&Sigma;}}{V}_{h,n}\left(t\right)\\ -\mathrm{\&alpha;}{C}_{\mathrm{\&epsiv;}}(\underset{i=1}{\overset{N}{\mathrm{\&Sigma;}}}{V}_{k,n}\left(t\right)-C_k)-\mathrm{\&alpha;}{D}_{\mathrm{\&epsiv;}}(\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}\underset{n=1}{\overset{N}{\mathrm{\&Sigma;}}}{V}_{k,n}\left(t\right)-N)-\mathrm{\&alpha;}{F}_{\mathrm{\&epsiv;}}(\frac{1}{2}-V_{k,n}\left(t\right))\\ -Z_{k,n}\left(t\right)(V_{k,n}\left(t\right)-I_0)+Q_{k,n}\left(t\right)\end{array}$

In various above, A _e, B _e, C _e, D _eand F _efor punishment parameter, V _k,nand V _h,nrepresent block of sub-carriers allocation matrix, V _k,nv _h,nrepresent whether block of sub-carriers n distributes to user k and h, U simultaneously _k,nt () is dynamic matrix, K is number of users, and N is block of sub-carriers number, for the sign bit number of a kth user on subcarrier n, C _krepresent the number distributing to the block of sub-carriers of user k, λ ₀for interneuronal damping factor, α is the amplification coefficient of input vector, Z _k,n(t)=(1-β ₁) Z _k,n(t-1) be neuronic self-feedback connection weights weight, Q _k,n(t)=(1-β ₂) Q _k,n(t-1) be random noise, I ₀for neuronic input deviation, β ₁for the time independently neuron to be coupled damping factor, β ₂for noise simulation annealing decay factor, t is iterations.