CN105025580A - Method and device for allocating wireless resources - Google Patents

Abstract

The embodiment of the invention discloses a method and a device for allocating wireless resources. The method comprises the steps of determining an adaptive value of each sub-channel according to the speed and the position of each sub-channel after initialization, updating the speed and the position of each sub-channel according to the adaptive value of each sub-channel, and judging whether the speed and the position of each sub-channel and the total transmitting power of the sub-channels after updating meet constraint conditions or not, thereby determining to adopt the updated position and the updated speed of each sub-channel to carry out wireless resource deployment on each cell. According to the embodiment of the invention, user experience maximization is taken as a target in heterogeneous wireless resource allocation, and allocation for the wireless resources in a wireless network is realized by being combined with the QoE of each service.

Description

A kind of wireless resource allocation methods and device

Technical field

The present invention relates to wireless communication technology field, particularly a kind of wireless resource allocation methods and device.

Background technology

For wireless network wireless resource characteristic, conveniently to the management of Radio Resource, open wireless network (Open Wireless Network, OWN) arises.Open wireless network is the network frame based on SDN.

Open wireless network can compatible 3G, LTE and wlan network, the base station of 3G, LTE and the access point of WLAN by Fiber connection to open wireless server-controller.Fig. 1 is the Organization Chart of open wireless network in prior art.In Fig. 1, base station and AP pass through Intel Virtualization Technology, invent soft base station and are connected to controller, by controller, can upgrade to soft base station and manage.Controller is made up of controller operating system and the application run on an operating system.Controller carries out abstract to bottom Radio Resource and business, obtains corresponding API, and operator and developer directly utilize API monitor network and optimize.The controller of OWN has two large major functions: business QoE perception and network situation awareness.

In OWN network, data surface mainly refers to the set of a series of base station, relaying and other access nodes.Programmable data face, by reconstruct base station/access point, by the controlling functions of Access Network from decoupling zero the network equipment, and the base band signal process of base station, wireless protocols process etc. are concentrated in the baseband pool based on cloud platform and realize, realized the covering of community by remote radio.Soft base station is made up of remote radio end and baseband processing unit.The function that the signal that remote radio end realizes original base station sends and receives, realizes by general software radio peripheral hardware (Universal Software Radio Peripheral, USRP) technology; Baseband processing unit adopts the X86 hardware server of standard, carries out virtual, runs corresponding software function on a virtual machine, realize corresponding base station/access point to the processing capacity of signal to hardware server.Soft base station is communicated with controller, core net by different open interfaces.In OWN network, chain of command mainly realizes on the controller concentrated, and the controller concentrated in logic is the core component of OWN framework.The major function of controller comprises: the control of system configuration, RRM, service-aware, physical layer and mobile management.

OWN network can realize the management flexible and efficient to heterogeneous network.Based on abstract to heterogeneous network resource of control plane, this aspect will for network state and customer service demand, this aspect mainly completes the fine-grained management to heterogeneous network resource, and based on the perception to Network Situation, between heterogeneous network, realize load balancing and seamless mobile management.

But in prior art, do not provide the corresponding solution to heterogeneous wireless network and minizone cooperation Resourse Distribute.

Summary of the invention

The embodiment of the invention discloses a kind of wireless resource allocation methods and device, for realizing heterogeneous wireless network and minizone cooperation Resourse Distribute.

For achieving the above object, the embodiment of the invention discloses a kind of wireless resource allocation methods, be applied in the controller of open wireless network OWN, described method comprises:

According to the quantity N of the subchannel of each community in the heterogeneous network preset, the speed of the every sub-channels of initialization and position;

The speed of every sub-channels and position are upgraded;

Judge the speed of every sub-channels after upgrading, position and subchannel power and whether meet constraints;

When meeting, carry out network design according to the speed of the every sub-channels determined and position.

Further, the described speed to every sub-channels and position are carried out renewal and are comprised:

According to with upgrade speed and the position of every sub-channels, with the random number in [0,1], χ is Dynamic gene, is fixed value, with represent history optimal location and the global history optimal location of the l time iteration i-th sub-channels respectively, wherein:

Wherein,

h _max(A)＝max[h ₁(A),h ₂(A),h ₃(A)]， $f\left(A\right)=-\underset{K=1}{\overset{K}{\Σ}}\underset{n=1}{\overset{N}{\Σ}}{\mathrm{QoE}}_K{\mathrm{\ρ}}_n^k,$

$\begin{array}{ccc}s.t.& h_1\left(A\right)=\underset{k=1}{\overset{K}{\mathrm{\Σ}}}{\mathrm{\ρ}}_n^k-1\≤0& \∀n\\ & h_2\left(A\right)=R_{\min }-R\left(k\right)\≤0& \∀k,\\ & h_3\left(A\right)=P_{\mathrm{total}}-P_{\mathrm{lim\; it}}\≤0& \end{array}$ A is subsets of sub-channels, A _i ^li-th son

The position of channel, l is the number of times of current iteration, and f (A) is target function, be the n-th subchannel by the information of a kth CU, N is the total quantity of subchannel, and K is the total quantity of user, the adaptive value of subsets of sub-channels, minl (A _i) be the minimum value of subchannel adaptive value, atan [.] represents arc tangent, and the summation of user emission power is P _total, P _{lim it}transmitting power threshold value, the speed of each business is R (k), and rate threshold value is Rmin, QoE _kfor the QoE of a kth business.

Further, when business is web-browsing service, according to

determine QoE, wherein QoE (MOS) represents the QoE of business, measures by MOS value, being average webpage or file size is wireless connections postpone, R is the transmission speed of business;

When business is the file downloading service based on web, according to

QoE (MOS)=0.775log (R)+1.268 determines QoE, and wherein, QoE (MOS) represents the QoE of business, measures by MOS value, and R is the transmission speed of business;

When business is video traffic, the QoE of video quality is: QoE (MOS)=Q _c(MOS)-∑ d _n, wherein, QoE (MOS) represents the final mass of video sequence, d _nrepresent the mass loss relevant to the packet loss of the n-th frame video, d _ncan be determined by following formula:

d _n＝d _c,n+d _p,n

D _c,nand d _p,nrepresent the mass loss because packet loss and error propagation cause respectively, be respectively:

$d_{c,n}=\left(\frac{{\mathrm{num}}_{loss}}{{\mathrm{num}}_A}\right)\×Q_c\×{\left(\frac{{\mathrm{\σ}}_{T,n}}{a_6}\right)}^{b_6}$

$d_{p,n}=d_r\×\left(1+{\left(\frac{{\mathrm{\σ}}_{T,n}}{a_7}\right)}^{b_7}\right)$

Wherein num _aand num _lossrepresent packet total amount and the packet loss amount of n frame video respectively, a ₆, a ₇, b ₆, b ₇fixing parameter, σ _t,nrepresent the current complexity of n frame video, d _rrepresent the quality degradation of r frame reference video,

q _c(MOS) for the QoE of compressed domain video, Qc are without ginseng video quality, Qc=(α × F _q+ β × F _m+ γ × F _b+ ε) × θ, α, beta, gamma, ε, θ are constants,

F _Q＝(a×C _n+b) ^c×qp

Wherein, F _qfor quantization parameter, qp represents the mean value of quantization parameter in frame of video, and a, b and c are constant, C _nfor the feature of n frame continuous videos,

F _M＝MC _g+MC _l

Wherein, F _mfor kinematic parameter, MC _gand MC _lrepresent local motion consistency and global motion consistency respectively;

$F_B=D_B\×(1-\frac{N_m}{N_B})$

Wherein F _bfor rate parameter, D _brepresent the difference number of bit amount of calculation, total macroblock number N _brepresent, N _mfor only producing the quantity of the macro block of slight influence to video quality.

Further, described judge the speed of every sub-channels after upgrading, position and subchannel power and whether meet constraints and comprise:

Judge the speed of every sub-channels after upgrading, position and subchannel power and whether meet constraints:

$\begin{array}{ccc}s.t.& h_1\left(A\right)=\underset{k=1}{\overset{K}{\mathrm{\Σ}}}{\mathrm{\ρ}}_n^k-1\≤0& \∀n\\ & h_2\left(A\right)=R_{\min }-R\left(k\right)\≤0& \∀k,\\ & h_3\left(A\right)=P_{\mathrm{total}}-P_{\mathrm{lim\; it}}\≤0& \end{array}$ Wherein, represent whether the n-th subchannel is taken by the business of a kth user, time, illustrate that the business of a kth user takies the n-th subchannel; time, illustrate that the business of a kth user does not take the n-th subchannel, the service rate of each user is R (k), R _minfor rate threshold value, in system, the summation of user emission power is P _total, P _limitfor the transmitting power threshold value of setting.

Further, when not meeting constraints, described method also comprises:

Continue to upgrade the speed of every sub-channels and position, until the power of the speed of every sub-channels after upgrading, position and subchannel and meet constraints.

The embodiment of the invention discloses a kind of radio resource allocation apparatus, be applied in the controller of open wireless network OWN, described device comprises:

Initialization module, for the quantity N according to the subchannel of each community in the heterogeneous network preset, the speed of the every sub-channels of initialization and position;

Update module, for upgrading the speed of every sub-channels and position;

Judge distribution module, for judge the speed of every sub-channels after upgrading, position and subchannel power and whether meet constraints; When meeting, carry out network design according to the speed of the every sub-channels determined and position.

Further, described update module, specifically for basis with upgrade speed and the position of every sub-channels, with the random number in [0,1], c ₁=c ₂=2.05, χ is Dynamic gene, is fixed value, with represent history optimal location and the global history optimal location of the l time iteration i-th sub-channels respectively, wherein:

Wherein, h _max(A)=max [h ₁(A), h ₂(A), h ₃(A)], $f\left(A\right)=-\underset{K=1}{\overset{K}{\Σ}}\underset{n=1}{\overset{N}{\Σ}}{\mathrm{QoE}}_K{\mathrm{\ρ}}_n^k,$

$\begin{array}{ccc}s.t.& h_1\left(A\right)=\underset{k=1}{\overset{K}{\mathrm{\Σ}}}{\mathrm{\ρ}}_n^k-1\≤0& \∀n\\ & h_2\left(A\right)=R_{\min }-R\left(k\right)\≤0& \∀k,\\ & h_3\left(A\right)=P_{\mathrm{total}}-P_{\mathrm{lim\; it}}\≤0& \end{array}$ A is subsets of sub-channels, A _i ^lbe the position of the i-th sub-channels, l is the number of times of current iteration, and f (A) is target function, be the n-th subchannel by the information of a kth CU, N is the total quantity of subchannel, and K is the total quantity of user, the adaptive value of subsets of sub-channels, minl (A _i) be the minimum value of subchannel adaptive value, atan [.] represents arc tangent, and the summation of user emission power is P _total, P _limitthe transmitting power threshold value of setting, the speed of each business is R (k), and rate threshold value is R _min, QoE _kfor the QoE of a kth business.

Further, described update module, specifically for when business is web-browsing service, according to determine QoE, wherein QoE (MOS) represents the QoE of business, measures by MOS value, being average webpage or file size is wireless connections postpone, R is the transmission speed of business;

When business is the file downloading service based on web, determine QoE according to QoE (MOS)=0.775log (R)+1.268, wherein, QoE (MOS) represents the QoE of business, measures by MOS value, and R is the transmission speed of business;

When business is video traffic, the QoE of video quality is: QoE (MOS)=Q _c(MOS)-∑ d _n, wherein, QoE (MOS) represents the final mass of video sequence, d _nrepresent the mass loss relevant to the packet loss of the n-th frame video, d _ncan be determined by following formula:

d _n＝d _c,n+d _p,n

D _c,nand d _p,nrepresent the mass loss because packet loss and error propagation cause respectively, be respectively:

$d_{c,n}=\left(\frac{{\mathrm{num}}_{loss}}{{\mathrm{num}}_A}\right)\×Q_c\×{\left(\frac{{\mathrm{\σ}}_{T,n}}{a_6}\right)}^{b_6}$

$d_{p,n}=d_r\×\left(1+{\left(\frac{{\mathrm{\σ}}_{T,n}}{a_7}\right)}^{b_7}\right)$

Wherein num _aand num _lossrepresent packet total amount and the packet loss amount of n frame video respectively, a ₆, a ₇, b ₆, b ₇fixing parameter, σ _t,nrepresent the current complexity of n frame video, d _rrepresent the quality degradation of r frame reference video,

q _c(MOS) for the QoE of compressed domain video, Qc are without ginseng video

Quality _,qc=(α × F _q+ β × F _m+ γ × F _b+ ε) × θ, α, beta, gamma, ε, θ are constants,

F _Q＝(a×C _n+b) ^c×qp

Wherein, F _qfor quantization parameter, qp represents the mean value of quantization parameter in frame of video, and a, b and c are constant, C _nfor the feature of n frame continuous videos,

F _M＝MC _g+MC _l

Wherein, F _mfor kinematic parameter, MC _gand MC _lrepresent local motion consistency and global motion consistency respectively;

$F_B=D_B\×(1-\frac{N_m}{N_B})$

Wherein F _bfor rate parameter, D _brepresent the difference number of bit amount of calculation, total macroblock number N _brepresent, N _mfor only producing the quantity of the macro block of slight influence to video quality.

Further, described judgement distribution module, specifically for judge the speed of every sub-channels after upgrading, position and subchannel power and whether meet constraints:

$\begin{array}{ccc}s.t.& h_1\left(A\right)=\underset{k=1}{\overset{K}{\mathrm{\Σ}}}{\mathrm{\ρ}}_n^k-1\≤0& \∀n\\ & h_2\left(A\right)=R_{\min }-R\left(k\right)\≤0& \∀k,\\ & h_3\left(A\right)=P_{\mathrm{total}}-P_{\mathrm{lim\; it}}\≤0& \end{array}$ Wherein, represent that the n-th subchannel is

The no business by a kth user takies, time, illustrate that the business of a kth user takies the n-th subchannel; time, illustrate that the business of a kth user does not take the n-th subchannel, the service rate of each user is R (k), R _minfor rate threshold value, in system, the summation of user emission power is P _total, P _limitfor the transmitting power threshold value of setting.

Further, described judgement distribution module, specifically for when not meeting constraints, continues to upgrade the speed of every sub-channels and position, until the power of the speed of every sub-channels after upgrading, position and subchannel and meet constraints.

Embodiments provide a kind of wireless resource allocation methods and device, the method is according to the speed of sub-channels every after initialization in heterogeneous network and position, determine the adaptive value of every sub-channels, according to the adaptive value of every sub-channels, the speed of every sub-channels and position are upgraded, judge the speed of every sub-channels after upgrading, whether total transmitting power of position and subchannel meet constraints, thus determine to adopt the position of the every sub-channels after upgrading and speed to carry out the deployment of Radio Resource to each community.Because the embodiment of the present invention is on heterogeneous wireless Resourse Distribute, to maximize Consumer's Experience for target, combine the QoE of each business, realize in the wireless network to the distribution of Radio Resource.

Accompanying drawing explanation

In order to be illustrated more clearly in the embodiment of the present invention or technical scheme of the prior art, be briefly described to the accompanying drawing used required in embodiment or description of the prior art below, apparently, accompanying drawing in the following describes is only some embodiments of the present invention, for those of ordinary skill in the art, under the prerequisite not paying creative work, other accompanying drawing can also be obtained according to these accompanying drawings.

Fig. 1 is the Organization Chart of open wireless network in prior art;

Fig. 2 is the open wireless network of network Organization Chart of the embodiment of the present invention;

A kind of allocation of radio resources process that Fig. 3 provides for the embodiment of the present invention;

A kind of radio resource allocation apparatus structure chart that Fig. 4 provides for the embodiment of the present invention.

Embodiment

Below in conjunction with the accompanying drawing in the embodiment of the present invention, be clearly and completely described the technical scheme in the embodiment of the present invention, obviously, described embodiment is only the present invention's part embodiment, instead of whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art, not making the every other embodiment obtained under creative work prerequisite, belong to the scope of protection of the invention.

Embodiments provide a kind of wireless resource allocation methods, Fig. 2 is the open wireless network of network Organization Chart of the embodiment of the present invention.Open wireless network is the heterogeneous network converged framework for GSM, 3G, LTE and wlan network, the base station of GSM, 3G, LTE and the access point of WLAN by Fiber connection to open wireless server-novel radio resource allocation apparatus (E-WRAE).By Intel Virtualization Technology, base station and AP are virtualized into soft base station and are connected to E-WRAE, by E-WRAE, can be upgraded and be managed in virtual soft base station.E-WRAE is made up of operating system and the application run on an operating system.E-WRAE carries out abstract to bottom Radio Resource and business, obtains corresponding API, and operator and developer directly utilize API monitor network and optimize.

Wireless channel basic parameter API is the wireless channel basic parameter of 2/3/4G and WLAN, in the process of Resourse Distribute, plays an important role.E-WRAE carries out abstract at the queue scheduling of the transmitting power of the signal to noise ratio to bottom wireless channel, terminal, modulating-coding strategy, MAC layer, forms wireless channel basic parameter API.The forming process of this API belongs to prior art, does not repeat in embodiments of the present invention to this forming process.

Conveniently simple the different resource of heterogeneous network is carried out United Dispatching, the Resource Abstract of different Access Network is become the API of bandwidth by the embodiment of the present invention, and such E-WRAE just can come to carry out unified subchannel or resource block assignments to heterogeneous network fast by using the subchannel bandwidth API of heterogeneous network.By abstract function, convert the subchannel relevant parameter of different Access Network to bandwidth API.This heterogeneous network comprises WCDMA and WLAN in LTE, 3G in embodiments of the present invention.

Radio Resource in LTE network distributes to user in units of Resource Block, the bandwidth sum user number of sub carrier wave employed in this Resource Block that Resource Block can provide has direct relation, modulation system directly affects the bit number of a character, so bandwidth also has inseparable relation with modulation system.Following formula gives the parameter of Radio Resource and the relation of bandwidth in LTE:

f(cell,RB,subchannel,Modem_mode)＝B

Wherein, cell is cell index number, and RB is the quantity of Resource Block, and subcarrier is the operable number of sub carrier wave of user, and Modem_mode is the modulation system adopted, and B is the bandwidth obtained.

In wlan network, frequency domain has 13 band channels, the scope that each access point covers is called a community, and neighbor cell adopts the channel of different frequency range to avoid the interference of minizone, thus greatly improves the transmission rate of signal.Adopt OFDM technology to segment each subchannel in each band channels, obtain multiple subchannel, the bit number of each number of words transmitted in subchannel is relevant with adopted modulation system.Following formula gives the parameter of Radio Resource and the relation of bandwidth in WiFi:

f(cell,subchannel,Modem_mode)＝B

Wherein, cell is cell index number, and subchannel is the quantity of subchannel, and Modem_mode is the modulation system adopted, and B is the bandwidth obtained.

In WCDMA network, user can use identical subchannel, the information of different user is distinguished by chip, and the available bandwidth of user and chip SF have linear relation, and the bit number of each character transmitted in subchannel has inseparable relation with adopted modulation system.Following formula gives the parameter of Radio Resource and the relation of bandwidth in WCDMA network:

f(cell,subchannel,SF,Modem_mode)＝B

Wherein, cell is cell index number, and subchannel is the quantity of subchannel, and SF is the spreading factor number that user uses, and Modem_mode is the modulation system adopted, and B is the bandwidth obtained.

According to foregoing description, in heterogeneous network, determine that the Radio Resource of bandwidth is different, and the channel of wireless network has the feature of time variation and cell frequency multiplex, but all have employed subchannel when determining bandwidth in which kind of network configuration, therefore using the radio resource parameter of subchannel as heterogeneous network, the distribution of Radio Resource can be carried out.

In the wireless network, the business such as web page browsing, file download and video occupy the network traffics of 95%.QoE is an important indicator of reflection quality of service and Consumer's Experience, the business of bottom can be become QoE API by accurate algorithm abstraction.

Quality of experience and the web page loading time of web-browsing service are inversely proportional to, and the loading of webpage is more smooth, and the experience of user is better, and QoE is higher.The method of the QoE of the determination web-browsing service that the embodiment of the present invention provides is as follows:

QoE(MOS)＝5.57-1.64log(pageloadtime)

Wherein QoE (MOS) represents the QoE of business, measures by MOS value, and pageloadtime is web page loading time.Simultaneously for the feature of wireless network, web page loading time can be mapped to the transmission speed of business, therefore the QoE of web-browsing service is:

QoE(MOS)＝0.775log(R)+1.268

Wherein, being average webpage or file size is wireless connections postpone, R is the transmission speed of business.

Consumer's Experience based on the file download of web shows the strong dependence to network service speed in logarithmic mapping, and the QoE of file downloading service is:

QoE(MOS)＝0.775log(R)+1.268

Wherein, R is the transmission speed of business.

Video traffic focuses on real-time more.And when original video carries out compression and wireless transmission, video all can produce mass loss.

F _Q＝(a×C _n+b) ^c×qp

Wherein, F _qfor quantization parameter, qp represents the mean value of quantization parameter in frame of video, and a, b and c are constant, can mode by experiment determine.C _nfor the feature of n frame continuous videos.

Secondly, kinematic parameter F _mcan be broken down into global motion consistency and Movement consistency two aspect, local factor, the computing formula of kinematic parameter is as follows:

F _M＝MC _g+MC _l

Wherein, F _mfor kinematic parameter, MC _gand MC _lrepresent local motion consistency and global motion consistency respectively, kinematic parameter F _mcomputational process belong to prior art, in embodiments of the present invention design parameter in this formula is not repeated.

The parameter affecting video quality also has code rate, and code rate is subject to the impact of bandwidth.Rate parameter F _bcomputing formula as follows:

$F_B=D_B\×(1-\frac{N_m}{N_B})$

Wherein D _brepresent the difference number of bit amount of calculation, total macroblock number N _brepresent, such as, when seeing video by wireless network (such as: 4G network), total macroblock number of video in setting-up time.But, there are some macro blocks only to produce for video quality the distribution that thus slight influence equally with other macro blocks should not carry out bandwidth and distribute, N _mfor only producing the quantity of the macro block of slight influence to this video quality.

Based on above three important parameters, the known module without ginseng video quality assessment is:

Qc＝(α×F _Q+β×F _M+γ×F _B+ε)×θ

Wherein α, beta, gamma, ε, θ are constants, method by experiment can determine the span of each constant.

The QoE of video downloading service with MOS value for evaluating.Therefore, the QoE of compressed domain video is:

$Q_c\left(MOS\right)=-\frac{1}{20}{Q}_c+5$

Can be there is the situations such as packet loss, frame losing, error code in video transmission in wireless channel, these situations cause mass loss to video.Video quality can be expressed as:

QoE(MOS)＝Q _c(MOS)-∑d _n

Wherein, QoE (MOS) represents the final mass of video sequence, d _nrepresent the mass loss relevant to the packet loss of the n-th frame video.D _ncan by following equation expression:

d _n＝d _c,n+d _p,n

D _c,nand d _p,nrepresent the mass loss because packet loss and error propagation cause respectively.Can be determined by following formula respectively:

$d_{c,n}=\left(\frac{{\mathrm{num}}_{loss}}{{\mathrm{num}}_A}\right)\×Q_c\×{\left(\frac{{\mathrm{\σ}}_{T,n}}{a_6}\right)}^{b_6}$

$d_{p,n}=d_r\×\left(1+{\left(\frac{{\mathrm{\σ}}_{T,n}}{a_7}\right)}^{b_7}\right)$

Wherein num _aand num _lossrepresent packet total amount and the packet loss amount of n frame video respectively, a ₆, a ₇, b ₆, b ₇fixing parameter, σ _t,nrepresent the current complexity of n frame video, d _rrepresent the quality degradation of r frame reference video.

In open wireless network, the object of the cross-layer scheduling strategy that user oriented is experienced is the Consumer's Experience in maximization system, namely meets:

$max\underset{k=1}{\overset{K}{\Σ}}\underset{n=1}{\overset{N}{\Σ}}{\mathrm{QoE}}_k{\mathrm{\ρ}}_n^k---\left(1\right)$

Constraints comprises:

$s.t.\left\{\begin{array}{cc}\underset{k=1}{\overset{K}{\mathrm{\Σ}}}{\mathrm{\ρ}}_n^k\≤1& \∀n\\ {\mathrm{\ρ}}_n^k\∈\left\{0,1\right\}& \∀k,n\\ R\left(k\right)\≥R_{\min }& \∀k\\ P_{total}\≤P_{\lim it}& \end{array}\right.$

Wherein, represent whether the n-th subchannel is taken by the business of a kth user.For all user k and all subchannel n, can only be 0 or 1. time, illustrate that the business of a kth user takies the n-th subchannel; time, illustrate that the business of a kth user does not take the n-th subchannel.In order to ensure certain efficiency, the summation P of user emission power in system _total, the power threshold P of setting must be less than _limit.The fairness of Resourse Distribute is the important indicator of an evaluation resource dispatching strategy, must ensure the fairness of strategy in scheduling process.In order to guarantee fairness, need the speed ensureing each business can not be too low, web-browsing service and video traffic be different for the requirement of speed simultaneously, and service rate R (k) of each user must be greater than corresponding rate threshold value R _min.

According to the constraints of above-mentioned formula (1) and correspondence, in order to realize the optimization of the cross-layer scheduling that user oriented is experienced, known:

$f\left(A\right)=-\underset{K=1}{\overset{K}{\Σ}}\underset{n=1}{\overset{N}{\Σ}}{\mathrm{QoE}}_K{\mathrm{\ρ}}_n^k---\left(2\right)$

Constraints comprises:

$\begin{array}{ccc}s.t.& h_1\left(A\right)=\underset{k=1}{\overset{K}{\mathrm{\Σ}}}{\mathrm{\ρ}}_n^k-1\≤0& \∀n\\ & h_2\left(A\right)=R_{\min }-R\left(k\right)\≤0& \∀k\\ & h_3\left(A\right)=P_{\mathrm{total}}-P_{\mathrm{lim\; it}}\≤0& \end{array}$

Wherein, A is subsets of sub-channels, A _i ^lbe the position of the i-th sub-channels, l is the number of times of current iteration, upgrades and once namely thinks that iteration is once, when first calculating, iterations is 1, f (A) be canonical form under the target function of optimization problem, now need to get minf (A), be every n subchannel by the information of a kth CU, N is the total quantity of subchannel, and K is the total quantity of user.

Optimization problem under reference format, remains restricted type optimization problem, very difficult to above-mentioned formula (2) direct solution.In order to optimization problem is simplified, need restricted type problem to be converted into unconfinement type optimization problem, after constraints is transformed be:

h _max(A)＝max[h ₁(A),h ₂(A),h ₃(A)] (4)

Wherein be the adaptive value of subsets of sub-channels, this value is decided by target function, shows that whether this subchannel is nearest from target function at current time, therefore requires minimum adaptive value wherein atan [.] represents arc tangent.

Secondly, in the cross-layer scheduling optimization problem that user oriented is experienced, the distribution of subchannel only has two kinds of possibilities: occupied, unoccupied, sub-channel can only by occupied change into unoccupied, or be unoccupiedly converted into occupied, adopt the subsets of sub-channels algorithm of unconfinement type can not solve the problem of this discrete type.In subsets of sub-channels optimized algorithm, the transformation of this state is determined by the speed of subchannel, therefore, introduces the speed that the speed of continuous type is converted into discrete type by Sigmoid function, as follows:

$sig\left(v\right)=\frac{1}{1+e^{-v}}---\left(5\right)$

The position of subchannel can be converted into:

$A_i^{l+1}=\left\{\begin{array}{ccc}0& if& {\mathrm{\&eta;}}_i^l\&GreaterEqual;sig\left(v_i^{l+1}\right)\\ 1& if& {\mathrm{\&eta;}}_i^l<sig\left(v_i^{l+1}\right)\end{array}\right.$

it is equally distributed random number between the current iteration number of times l moment [0,1].Because the speed of subchannel is not a value at this moment, but the position of subchannel becomes the probability of 1 from 0 or becomes the probability of 0 from 1.Need the probable value continuous instantaneous value of speed being mapped to [0,1] by certain rule.

After carrying out above-mentioned basic preparation, subsets of sub-channels algorithm can be adopted to carry out solving of the cross-layer scheduling optimization problem of user oriented experience to it.

Embodiments provide a kind of wireless resource allocation methods, be applied in the controller of open wireless network OWN, described method comprises:

According to the quantity N of the subchannel of each community in the heterogeneous network preset, the speed of the every sub-channels of initialization and position;

The speed of every sub-channels and position are upgraded;

Judge the speed of every sub-channels after upgrading, position and subchannel power and whether meet constraints;

When meeting, carry out network design according to the speed of the every sub-channels determined and position.

The embodiment of the present invention by carrying out Resourse Distribute to each community in heterogeneous network in the controller of OWN, and is defined as the resource of each cell allocation when distributing according to the position of subchannel and speed, thus achieves the Resourse Distribute in heterogeneous network.

A kind of allocation of radio resources process that Fig. 3 provides for the embodiment of the present invention, this process comprises the following steps:

S301: according to the quantity of the subchannel of each community in the heterogeneous network preset, the speed of the every sub-channels of initialization and position.

Wherein, every sub-channels speed according to determine, the position of every sub-channels according to $A_i^{l+1}=\left\{\begin{array}{ccc}0& if& {\mathrm{\&eta;}}_i^l\&GreaterEqual;sig\left(v_i^{l+1}\right)\\ 1& if& {\mathrm{\&eta;}}_i^l<sig\left(v_i^{l+1}\right)\end{array}\right.$ Determine.

According to position and the speed of above-mentioned every sub-channels, determine the adaptive value of every sub-channels.

Wherein, the adaptive value of every sub-channels ai is every sub-channels, value determine according to above-mentioned formula (3).Subchannel has adaptive value (fitness value) in each moment of search, and adaptive value is decided by target function, it show this subchannel current time whether from target function more close to.Every sub-channels has oneself position and speed, and the speed of subchannel determines heading and the distance of this subchannel.In fact, subchannel speed and position are all virtual values out, and it cannot correspond in actual channel, and speed is the optimal speed of relative current sub-channel to optimal solution, and position is used to instruct current sub-channel and optimal solution to also have distance how far.

S302: according to with upgrade speed and the position of every sub-channels, A _i ^lbe the position of the i-th sub-channels first time iteration, with be the random number in [0,1], represent the random behavior of the l time iteration of i-th particle, χ is Dynamic gene, is fixed value.By calculating χ=0.729. with represent history optimal location and the global history optimal location of this subchannel of the l time iteration i-th sub-channels respectively, the computational methods of above-mentioned two parameters are as follows:

When upgrading the speed of every sub-channels, need to upgrade according to the feature of subchannel itself and the overall feature of subchannel group. be the feature of subchannel self, by the cognition of individuality, the speed of sub-channel upgrades; be the overall feature of subchannel group, by the cognition of the overall situation, the speed of sub-channel upgrades.

S303: judge the speed of every sub-channels after upgrading, whether total transmitting power of position and subchannel meet constraints:

$\begin{array}{ccc}s.t.& h_1\left(A\right)=\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}{\mathrm{\&rho;}}_n^k-1\&le;0& \&ForAll;n\\ & h_2\left(A\right)=R_{\min }-R\left(k\right)\&le;0& \&ForAll;k\\ & h_3\left(A\right)=P_{\mathrm{total}}-P_{\mathrm{lim\; it}}\&le;0& \end{array}$

When meeting, carry out network design according to the speed of the every sub-channels determined and position, otherwise, proceed step S302.

When carrying out step S303, according to $v_i^{l+2}=\mathrm{\&chi;}\&lsqb;v^{l+1}+c_1{\mathrm{\&zeta;}}_i^{l+1}\left(A_i^{best,l}-A_i^2\right)+c_2{\mathrm{\&zeta;}}_i^{l+1}\left(A_{swarm}^{best,l}-A_i^2\right)\&rsqb;$ With upgrade rate information and the positional information of every sub-channels, with represent history optimal location and the global history optimal location of this subchannel of the 2nd iteration i-th sub-channels respectively.

A kind of radio resource allocation apparatus structure chart that Fig. 4 provides for the embodiment of the present invention, be applied to the controller of open wireless network OWN, described device comprises:

Initialization module 41, for the quantity N according to the subchannel of each community in the heterogeneous network preset, the speed of the every sub-channels of initialization and position;

Update module 42, for upgrading the speed of every sub-channels and position;

Judge distribution module 43, for judge the speed of every sub-channels after upgrading, position and subchannel power and whether meet constraints; When meeting, carry out network design according to the speed of the every sub-channels determined and position.

Described update module 42, specifically for basis with upgrade speed and the position of every sub-channels, with the random number in [0,1], c ₁=c ₂=2.05, χ is Dynamic gene, is fixed value, with represent history optimal location and the global history optimal location of the l time iteration i-th sub-channels respectively, wherein:

Wherein, h _max(A)=max [h ₁(A), h ₂(A), h ₃(A)], $\min f\left(A\right)=-\underset{K=1}{\overset{K}{\&Sigma;}}\underset{n=1}{\overset{N}{\&Sigma;}}{\mathrm{QoE}}_K{\mathrm{\&rho;}}_n^k,$

$\begin{array}{ccc}s.t.& h_1\left(A\right)=\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}{\mathrm{\&rho;}}_n^k-1\&le;0& \&ForAll;n\\ & h_2\left(A\right)=R_{\min }-R\left(k\right)\&le;0& \&ForAll;k,\\ & h_3\left(A\right)=P_{\mathrm{total}}-P_{\mathrm{lim\; it}}\&le;0& \end{array}$ A is subsets of sub-channels, A _i ^lbe the position of the i-th sub-channels, l is the number of times of current iteration, and f (A) is target function, be the n-th subchannel by the information of a kth CU, N is the total quantity of subchannel, and K is the total quantity of user, minl (A _i) be the minimum value of subchannel adaptive value, atan [.] represents arc tangent, and the summation of user emission power is P _total, P _limittransmitting power threshold value, the speed of each business is R (k), and rate threshold value is Rmin, QoE _kfor the QoE of a kth business;

Described judgement distribution module 43, specifically for judge the speed of every sub-channels after upgrading, position and subchannel power and whether meet constraints:

$\begin{array}{ccc}s.t.& h_1\left(A\right)=\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}{\mathrm{\&rho;}}_n^k-1\&le;0& \&ForAll;n\\ & h_2\left(A\right)=R_{\min }-R\left(k\right)\&le;0& \&ForAll;k\\ & h_3\left(A\right)=P_{\mathrm{total}}-P_{\mathrm{lim\; it}}\&le;0& \end{array}$

When meeting, carry out network design according to the speed of the every sub-channels determined and position.

Described update module 42, specifically for when business is web-browsing service, according to determine QoE, wherein QoE (MOS) represents the QoE of business, measures by MOS value, being average webpage or file size is wireless connections postpone, R is the transmission speed of business.

Described update module 42, specifically for when business is the file downloading service based on web, QoE is determined according to QoE (MOS)=0.775log (R)+1.268, wherein, QoE (MOS) represents the QoE of business, measure by MOS value, R is the transmission speed of business.

Described update module 42, specifically for when business is video traffic, the QoE of video quality is: QoE (MOS)=Q _c(MOS)-∑ d _n, wherein, QoE (MOS) represents the final mass of video sequence, d _nrepresent the mass loss relevant to the packet loss of the n-th frame video, d _ncan be determined by following formula:

d _n＝d _c,n+d _p,n

D _c,nand d _p,nrepresent the mass loss because packet loss and error propagation cause respectively, be respectively:

$d_{c,n}=\left(\frac{{\mathrm{num}}_{loss}}{{\mathrm{num}}_A}\right)\&times;Q_c\&times;{\left(\frac{{\mathrm{\&sigma;}}_{T,n}}{a_6}\right)}^{b_6}$

$d_{p,n}=d_r\&times;\left(1+{\left(\frac{{\mathrm{\&sigma;}}_{T,n}}{a_7}\right)}^{b_7}\right)$

Wherein num _aand num _lossrepresent packet total amount and the packet loss amount of n frame video respectively, a ₆, a ₇, b ₆, b ₇fixing parameter, σ _t,nrepresent the current complexity of n frame video, d _rrepresent the quality degradation of r frame reference video,

q _c(MOS) for the QoE of compressed domain video, Qc are without ginseng video

Quality _,qc=(α × F _q+ β × F _m+ γ × F _b+ ε) × θ, α, beta, gamma, ε, θ are constants,

F _Q＝(a×C _n+b) ^c×qp

Wherein, F _qfor quantization parameter, qp represents the mean value of quantization parameter in frame of video, and a, b and c are constant, C _nfor the feature of n frame continuous videos,

F _M＝MC _g+MC _l

Wherein, F _mfor kinematic parameter, MC _gand MC _lrepresent local motion consistency and global motion consistency respectively;

$F_B=D_B\&times;(1-\frac{N_m}{N_B})$

Wherein F _bfor rate parameter, D _brepresent the difference number of bit amount of calculation, total macroblock number N _brepresent, N _mfor only producing the quantity of the macro block of slight influence to video quality.

Described judgement distribution module 43, specifically for when not meeting constraints, continues to upgrade the speed of every sub-channels and position, until the power of the speed of every sub-channels after upgrading, position and subchannel and meet constraints.

Embodiments provide a kind of wireless resource allocation methods and device, the method is according to the speed of sub-channels every after initialization in heterogeneous network and position, determine the adaptive value of every sub-channels, according to the adaptive value of every sub-channels, the speed of every sub-channels and position are upgraded, judge the speed of every sub-channels after upgrading, whether total transmitting power of position and subchannel meet constraints, thus determine to adopt the position of the every sub-channels after upgrading and speed to carry out the deployment of Radio Resource to each community.Because the embodiment of the present invention by carrying out Resourse Distribute to each community in heterogeneous network in the controller of OWN, and be defined as the resource of each cell allocation when distributing according to the position of subchannel and speed, thus achieve the Resourse Distribute in heterogeneous network.The embodiment of the present invention, on heterogeneous wireless Resourse Distribute, to maximize Consumer's Experience for target, combines the QoE of each business, realizes in the wireless network to the distribution of Radio Resource.

For systems/devices embodiment, because it is substantially similar to embodiment of the method, so description is fairly simple, relevant part illustrates see the part of embodiment of the method.

It should be noted that, in this article, the such as relational terms of first and second grades and so on is only used for an entity or operation to separate with another entity or operating space, and not necessarily requires or imply the relation that there is any this reality between these entities or operation or sequentially.And, term " comprises ", " comprising " or its any other variant are intended to contain comprising of nonexcludability, thus make to comprise the process of a series of key element, method, article or equipment and not only comprise those key elements, but also comprise other key elements clearly do not listed, or also comprise by the intrinsic key element of this process, method, article or equipment.When not more restrictions, the key element limited by statement " comprising ... ", and be not precluded within process, method, article or the equipment comprising described key element and also there is other identical element.

One of ordinary skill in the art will appreciate that all or part of step realized in said method execution mode is that the hardware that can carry out instruction relevant by program has come, described program can be stored in computer read/write memory medium, here the alleged storage medium obtained, as: ROM/RAM, magnetic disc, CD etc.

The foregoing is only preferred embodiment of the present invention, be not intended to limit protection scope of the present invention.All any amendments done within the spirit and principles in the present invention, equivalent replacement, improvement etc., be all included in protection scope of the present invention.

Claims (10)

1. a wireless resource allocation methods, is characterized in that, be applied in the controller of open wireless network OWN, described method comprises:

According to the quantity N of the subchannel of each community in the heterogeneous network preset, the speed of the every sub-channels of initialization and position;

The speed of every sub-channels and position are upgraded;

Judge the speed of every sub-channels after upgrading, position and subchannel power and whether meet constraints;

When meeting, carry out network design according to the speed of the every sub-channels determined and position.

2. the method for claim 1, is characterized in that, the described speed to every sub-channels and position are carried out renewal and comprised:

According to with upgrade speed and the position of every sub-channels, with the random number in [0,1], c ₁=c ₂=2.05, χ is Dynamic gene, is fixed value, with represent history optimal location and the global history optimal location of the l time iteration i-th sub-channels respectively, wherein:

Wherein,

h _max(A)＝max[h ₁(A),h ₂(A),h ₃(A)]，

$\begin{array}{ccc}s.t.& h_1\left(A\right)=\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}{\mathrm{\&rho;}}_n^k-1\&le;0& \&ForAll;n\\ & h_2\left(A\right)=R_{\min }-R\left(k\right)\&le;0& \&ForAll;k\\ & h_3\left(A\right)=P_{total}-P_{\lim it}\&le;0& \end{array},$ A is subsets of sub-channels, A _i ^lbe the position of the i-th sub-channels, l is the number of times of current iteration, and f (A) is target function, be the n-th subchannel by the information of a kth CU, N is the total quantity of subchannel, and K is the total quantity of user, and l (A) is the adaptive value of subsets of sub-channels, minl (A _i) be the minimum value of subchannel adaptive value, atan [.] represents arc tangent, and the summation of user emission power is P _total, P _{lim it}transmitting power threshold value, the speed of each business is R (k), and rate threshold value is Rmin, QoE _kfor the QoE of a kth business.

3. method as claimed in claim 2, is characterized in that, when business is web-browsing service, according to determine QoE, wherein QoE (MOS) represents the QoE of business, measures by MOS value, being average webpage or file size is wireless connections postpone, R is the transmission speed of business;

When business is the file downloading service based on web, determine QoE according to QoE (MOS)=0.775log (R)+1.268, wherein, QoE (MOS) represents the QoE of business, measures by MOS value, and R is the transmission speed of business;

When business is video traffic, the QoE of video quality is:

QoE (MOS)=Q _c(MOS)-∑ d _n, wherein, QoE (MOS) represents the final mass of video sequence, d _nrepresent the mass loss relevant to the packet loss of the n-th frame video, d _ncan be determined by following formula:

d _n＝d _c,n+d _p,n

D _c,nand d _p,nrepresent the mass loss because packet loss and error propagation cause respectively, be respectively:

$d_{c,n}=\left(\frac{{\mathrm{num}}_{loss}}{{\mathrm{num}}_A}\right)\&times;Q_c\&times;{\left(\frac{{\mathrm{\&sigma;}}_{T,n}}{a_6}\right)}^{b_6}$

$d_{p,n}=d_r\&times;\left(1+{\left(\frac{{\mathrm{\&sigma;}}_{T,n}}{a_7}\right)}^{b_7}\right)$

Wherein num _aand num _lossrepresent packet total amount and the packet loss amount of n frame video respectively, a ₆, a ₇, b ₆, b ₇fixing parameter, σ _t,nrepresent the current complexity of n frame video, d _rrepresent the quality degradation of r frame reference video,

q _c(MOS) be the QoE of compressed domain video, Q _cfor nothing ginseng video

Quality _,qc=(α × F _q+ β × F _m+ γ × F _b+ ε) × θ, α, beta, gamma, ε, θ are constants,

F _Q＝(a×C _n+b) ^c×qp

Wherein, F _qfor quantization parameter, qp represents the mean value of quantization parameter in frame of video, and a, b and c are constant, C _nfor the feature of n frame continuous videos,

F _M＝MC _g+MC _l

Wherein, F _mfor kinematic parameter, MC _gand MC _lrepresent local motion consistency and global motion consistency respectively;

$F_B=D_B\&times;(1-\frac{N_m}{N_B})$

Wherein F _bfor rate parameter, D _brepresent the difference number of bit amount of calculation, total macroblock number N _brepresent, N _mfor only producing the quantity of the macro block of slight influence to video quality.

4. the method for claim 1, is characterized in that, described judge the speed of every sub-channels after upgrading, position and subchannel power and whether meet constraints and comprise:

Judge the speed of every sub-channels after upgrading, position and subchannel power and whether meet constraints:

$\begin{array}{ccc}s.t.& h_1\left(A\right)=\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}{\mathrm{\&rho;}}_n^k-1\&le;0& \&ForAll;n\\ & h_2\left(A\right)=R_{\min }-R\left(k\right)\&le;0& \&ForAll;k\\ & h_3\left(A\right)=P_{total}-P_{\lim it}\&le;0& \end{array},$ Wherein, represent whether the n-th subchannel is taken by the business of a kth user, time, illustrate that the business of a kth user takies the n-th subchannel; time, illustrate that the business of a kth user does not take the n-th subchannel, the service rate of each user is R (k), R _minfor rate threshold value, in system, the summation of user emission power is P _total, P _{lim it}for the transmitting power threshold value of setting.

5. the method as described in any one of Claims 1 to 4, is characterized in that, when not meeting constraints, described method also comprises:

Continue to upgrade the speed of every sub-channels and position, until the power of the speed of every sub-channels after upgrading, position and subchannel and meet constraints.

6. a radio resource allocation apparatus, is characterized in that, be applied in the controller of open wireless network OWN, described device comprises:

Initialization module, for the quantity N according to the subchannel of each community in the heterogeneous network preset, the speed of the every sub-channels of initialization and position;

Update module, for upgrading the speed of every sub-channels and position;

Judge distribution module, for judge the speed of every sub-channels after upgrading, position and subchannel power and whether meet constraints; When meeting, carry out network design according to the speed of the every sub-channels determined and position.

7. device as claimed in claim 6, it is characterized in that, described update module, specifically for basis with upgrade speed and the position of every sub-channels, with the random number in [0,1], c ₁=c ₂=2.05, χ is Dynamic gene, is fixed value, with represent history optimal location and the global history optimal location of the l time iteration i-th sub-channels respectively, wherein:

Wherein, h _max(A)=max [h ₁(A), h ₂(A), h ₃(A)], $\begin{array}{ccc}s.t.& h_1\left(A\right)=\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}{\mathrm{\&rho;}}_n^k-1\&le;0& \&ForAll;n\\ & h_2\left(A\right)=R_{\min }-R\left(k\right)\&le;0& \&ForAll;k\\ & h_3\left(A\right)=P_{total}-P_{\lim it}\&le;0& \end{array},$ A is subsets of sub-channels, A _i ^lbe the position of the i-th sub-channels, l is the number of times of current iteration, and f (A) is target function, be the n-th subchannel by the information of a kth CU, N is the total quantity of subchannel, and K is the total quantity of user, and l (A) is the adaptive value of subsets of sub-channels, minl (A _i) be the minimum value of subchannel adaptive value, atan [.] represents arc tangent, and the summation of user emission power is P _total,p _{lim it}the transmitting power threshold value of setting, the speed of each business is R (k), and rate threshold value is R _min, QoE _kfor the QoE of a kth business.

8. device as claimed in claim 7, is characterized in that, described update module, specifically for when business is web-browsing service, according to determine QoE, wherein QoE (MOS) represents the QoE of business, measures by MOS value, being average webpage or file size is wireless connections postpone, R is the transmission speed of business;

When business is the file downloading service based on web, determine QoE according to QoE (MOS)=0.775log (R)+1.268, wherein, QoE (MOS) represents the QoE of business, measures by MOS value, and R is the transmission speed of business;

When business is video traffic, the QoE of video quality is: QoE (MOS)=Q _c(MOS)-∑ d _n, wherein, QoE (MOS) represents the final mass of video sequence, d _nrepresent the mass loss relevant to the packet loss of the n-th frame video, d _ncan be determined by following formula:

d _n＝d _c,n+d _p,n

D _c,nand d _p,nrepresent the mass loss because packet loss and error propagation cause respectively, be respectively:

$d_{c,n}=\left(\frac{{\mathrm{num}}_{loss}}{{\mathrm{num}}_A}\right)\&times;Q_c\&times;{\left(\frac{{\mathrm{\&sigma;}}_{T,n}}{a_6}\right)}^{b_6}$

$d_{p,n}=d_r\&times;\left(1+{\left(\frac{{\mathrm{\&sigma;}}_{T,n}}{a_7}\right)}^{b_7}\right)$

Wherein num _aand num _lossrepresent packet total amount and the packet loss amount of n frame video respectively, a ₆, a ₇, b ₆, b ₇fixing parameter, σ _t,nrepresent the current complexity of n frame video, d _rrepresent the quality degradation of r frame reference video,

q _c(MOS) be the QoE of compressed domain video, Q _cfor nothing ginseng video quality, Qc=(α × F _q+ β × F _m+ γ × F _b+ ε) × θ, α, beta, gamma, ε, θ are constants,

F _Q＝(a×C _n+b) ^c×qp

Wherein, F _qfor quantization parameter, qp represents the mean value of quantization parameter in frame of video, and a, b and c are constant, C _nfor the feature of n frame continuous videos,

F _M＝MC _g+MC _l

Wherein, F _mfor kinematic parameter, MC _gand MC _lrepresent local motion consistency and global motion consistency respectively;

$F_B=D_B\&times;(1-\frac{N_m}{N_B})$

Wherein F _bfor rate parameter, D _brepresent the difference number of bit amount of calculation, total macroblock number N _brepresent, N _mfor only producing the quantity of the macro block of slight influence to video quality.

9. the device as described in claim 6, is characterized in that, described judgement distribution module, specifically for judge the speed of the every sub-channels after upgrading, position and subchannel power and whether meet constraints:

$\begin{array}{ccc}s.t.& h_1\left(A\right)=\underset{k=1}{\overset{K}{\mathrm{\&Sigma;}}}{\mathrm{\&rho;}}_n^k-1\&le;0& \&ForAll;n\\ & h_2\left(A\right)=R_{\min }-R\left(k\right)\&le;0& \&ForAll;k\\ & h_3\left(A\right)=P_{total}-P_{\lim it}\&le;0& \end{array},$ Wherein, represent whether the n-th subchannel is taken by the business of a kth user, time, illustrate that the business of a kth user takies the n-th subchannel; time, illustrate that the business of a kth user does not take the n-th subchannel, the service rate of each user is R (k), R _minfor rate threshold value, in system, the summation of user emission power is P _total, P _{lim it}for the transmitting power threshold value of setting.

10. the device as described in any one of claim 6 ~ 9, it is characterized in that, described judgement distribution module, specifically for when not meeting constraints, continue to upgrade the speed of every sub-channels and position, until the power of the speed of every sub-channels after upgrading, position and subchannel and meet constraints.