CN103687023A - Optimization wireless resource method based on time delay differentiated services and proportionality rate constraints - Google Patents

Abstract

The invention discloses an optimization wireless resource method based on time delay differentiated services and proportionality rate constraints. The method divides services into two types from a physical layer: a time Delay-Constraint (DC) type service and a Best-Effort (BE) type service. Specifically, the method classifies optimization resource distribution to a linearity problem. Through introducing time sharing parameters, an index-grade mixing integer program problem is converted into a convex problem for solving; a Lagrange differential is then solved on a result to obtain an optimum performance response of bandwidth, whether the result is reasonable is verified, if the result is not reasonable, a decision is modified forwards, and if the result is reasonable, other network distribution parameters are calculated. Generally speaking, the method provided by the invention overcomes the disadvantage of a conventional wireless resource management method that the fairness between service types and users are not taken into consideration, the diversified demands for quality of service (QoS) of different types of services can be satisfied, the maximization of a data transmission rate can be realized, and the system total data transmission rate is improved to the maximum.

Description

Optimization Radio Resource method based on time delay differentiated service and proportionality rate constraint

Technical field

The present invention relates to Computer Wireless Communication technical field, particularly a kind of optimization Radio Resource method based on time delay differentiated service and proportionality rate constraint in heterogeneous wireless network.

Background technology

Along with broadband wireless network is in recent years to the improving constantly of service quality (Quality of Service, QoS) demand, RRM (Radio Resource Management, RRM) becomes the emphasis of research and development.Existing type of service, such as to the highstrung speech transmission service of time delay, need to guarantee that it has certain throughput; And the of short duration time delay of some business (as Email and file download service) tolerable, so they adapt to variable transmission rate.OFDM access (orthogonal frequency division multiple access, OFDMA) technology is as a kind of air interface solution emerging in broadband network.The policy in resource management of the heterogeneous wireless network that formulation comprises OFDMA technology will be the current and following study hotspot.

In current research field, Radio Resource generally includes transmitted power and frequency bandwidth, utilizes it can dynamically distribute, process time or the frequency selectivity problem in broadband wireless fading channel.Optimal resource allocation plan in the past, do not consider the key factors such as fairness between type of service and user, thereby caused rare Radio Resource by poor efficiency distribute and utilize, in existing Resource Allocation Formula, collaborative RRM (the Joint RRM proposing based on bankruptcy strategy, JRRM) strategy, the diversity of Radio Resource and the QoS demand of seeking system load and user/service on effective distributing radio resource basis have been considered, yet, allocation of radio resources mechanism (as power and bandwidth) is being utilized collaboration diversity technology and is further meeting in the diversified qos requirement of different kinds of business, still be faced with huge challenge.

As a kind of common recognition, aspect the overall data transmission rate and user fairness of balance sysmte, the present invention is always using the constraint of user's proportionality transmission rate as equity criterion.With respect to traditional RRM strategy, the present invention, meeting outside the user rate maximization requirement of the total speed of system under user rate constrain proportions condition, can also obtain higher message transmission rate and fairness, and can solve well problem above.

Summary of the invention

The object of the invention is to provide a kind of optimization wireless resource allocation methods based on time delay differentiated service and the constraint of proportionality rate fairness, the method reduces the switching times of wireless network and the service quality (QoS) that improves Internet Transmission effectively, the method utilizes business to carry out differentiated service type to the different demands of Qos, introduce timesharing shared variable, multistep checking result of calculation, result after comprehensive is applied in resource distribution, thus the performance of raising allocation of radio resources.

The present invention is two kinds of fundamental types from physical layer by delineation of activities, and its two kinds of fundamental types are respectively: delay constraint type (Delay-Constraint, DC) business and type (Best-Effort, the BE) business of doing one's best.Pure DC system (only considering DC business), refers to and can make system emission power minimize, and can also meet each user's master data transmission rate constraint; Pure BE system (only considering BE business), refers to and can make the total speed of system reach maximization, and obey total transmit power constraint.

The present invention is that the technical scheme that its technical problem of solution is taked is: the present invention proposes a kind of optimized allocation of resources method in heterogeneous network based on OFDMA technology, the method has met the requirement of service quality under the total speed maximization of system and user's proportionality rate constraint, the method has been considered different types of service and user fairness sex factor, and re-establish the network insertion model of a kind of user's of permission multiple access access, from physical layer, by delineation of activities, it is two types: delay constraint type (Delay-Constraint, DC) business and the type (Best-Effort that does one's best, BE) business.

Heterogeneous network, carrying out when network is selected not only considering transmission rate constraint and type of service, also has resource allocation methods to meet the validity of business to qos requirement, guarantees under the restriction of business minimum speed limit, power system capacity to be maximized.By introducing user's proportionality rate constraint, be used as equity criterion, RRM planning problem is converted to linear programming problem, the mixed integer programming of index complexity is converted to the maximized target of transmission rate with BE business, meet respectively the basic transmission rate of different DC type business simultaneously, improve to greatest extent the total speed of system.The present invention has used for reference time sharing application, guaranteeing that BE type business is under the constraint of the protruding conditions of problems of gross power proportional fairness, utilize solving with gradient projection method of dual problem comprehensively to analyze BE type business and DC type business, guarantee that DC type business has minimum transmission rate request, BE type business is not having in the mode of doing one's best, to carry out transfer of data under delay constraint condition, but transfer rate is subject to proportional fairness constraint.

Method flow:

Step 1: suppose in LTE-WLAN heterogeneous network, exist M support different service types enliven multimode terminal and the available wireless access technology of N kind; In LTE network, suppose that the wireless channel between base station and terminal is the rayleigh fading channel that frequency is selected, the channel of each subcarrier is narrower, so it is flat fading; r _inbe illustrated in each OFDM symbol time interval, the transfer rate that user i obtains based on subcarrier n, its value depends on channel gain h _inwith the power P of user i based on distributing on subcarrier n _in; r _inconventionally be represented as

$r_{\mathrm{in}}={\mathrm{\β}}_0{B}_0{\log }_2(1+\frac{P_{\mathrm{in}}{\left|h_{\mathrm{in}}\right|}^2}{\mathrm{\Γ}{N}_0{B}_0})$

Wherein, N ₀be the power spectral density of additive white Gaussian noise, Γ is a constant, is known as signal to noise ratio interval;

In the WLAN of 802.11 agreements, the present invention uses for reference the method for keeping out of the way information merging in MAC head, allows user access WLAN in the mode of a kind of TDMA; All power delivery are all supposed, user i is represented as r in j WLAN _ij, equally in above formula, r _ijcan be represented as

$r_{\mathrm{ij}}={\mathrm{\β}}_j{B}_j{\log }_2(1+\frac{P_{\mathrm{ij}}{\left|h_{\mathrm{ij}}\right|}^2}{\mathrm{\Γ}{N}_0{B}_0})$

Wherein, the spectrum efficiency of provided subsystem is provided β, i.e. the validity of each subsystem;

Step 2: the difference requiring according to service delay, M MMT can be divided into two types: first kind DC type MMT, quantity is K, the minimum transmission rate request of its business is

(i=1,2 ..., K); Second Type has (M-K) individual BE type MMT, although there is no delay constraint, in the mode of doing one's best, carries out transfer of data, and transmission rate is subject to the constraint of proportionality fair play

The condition of DC type MMT and BE type MMT is expressed as:

$r_i\≥R_i^{\min },i=\mathrm{1,2},\·\·\·,K,$

r _K+1:r _k+2:...:r _M＝γ _K+1:γ _K+2:...:γ _M；

Step 3: under user's proportionality rate constraint, calculate all users' the total speed of maximum:

$\mathrm{Max}\underset{i=1}{\overset{M}{\mathrm{\Σ}}}{R}_i$

$\begin{array}{cc}\mathrm{subject\; to}& \underset{j=0}{\overset{L}{\mathrm{\Σ}}}{\mathrm{\α}}_{\mathrm{ij}}\≤1,\∀i,{\mathrm{\α}}_{\mathrm{ij}}\∈\left\{\mathrm{0,1}\right\},\∀i,j\end{array}$

$\underset{i=1}{\overset{M}{\mathrm{\Σ}}}{f}_{\mathrm{in}}\≤1,\∀n,f_{\mathrm{in}}\∈\left\{\mathrm{0,1}\right\},\∀i,n$

$\underset{i=1}{\overset{M}{\mathrm{\Σ}}}{t}_{\mathrm{ij}}\≤1,\∀j,0\≤t_{\mathrm{ij}}\≤1,\∀j,i$

$R_i=\underset{n=1}{\overset{N}{\mathrm{\Σ}}}{f}_{\mathrm{in}}{r}_{0\mathrm{in}}+\underset{j=1}{\overset{L}{\mathrm{\Σ}}}{t}_{\mathrm{ij}}{r}_{\mathrm{ij}}$

$R_i\≥R_i^{\min },\∀i=\mathrm{1,2},\·\·\·,K$

$\frac{R_i}{{\mathrm{\γ}}_i}=\frac{R_{k+1}}{{\mathrm{\γ}}_{k+1}},\∀i\∈k+1,k+2,\·\·\·,M;$

Step 4: definition ρ _ijrepresent the time frame allocation of parameters of user i in network j (wherein 1≤j≤N refers to LTE network, and N+1≤j≤N+L refers to j WLAN).And introduced a variable s _ij, make s _ij=ρ _ijp _ij.Definition α _ij=| h _ij| ²/ Γ _kn ₀b _j, and by time frame allocation of parameters ρ _ij, can be by R _ibe rewritten as

constraints is rewritten as

$R_i\≥R_i^{\min },\∀i=\mathrm{1,2},\·\·\·,K$

$\frac{R_i}{{\mathrm{\γ}}_i}=\frac{R_{K+1}}{{\mathrm{\γ}}_{K+1}},\∀i\∈K+1,K+2,\·\·\·,M$

$\underset{i=1}{\overset{M}{\mathrm{\Σ}}}\underset{j=1}{\overset{N+L}{\mathrm{\Σ}}}{s}_{\mathrm{ji}}=P_T$

$\underset{i=1}{\overset{M}{\mathrm{\Σ}}}{\mathrm{\ρ}}_{\mathrm{ij}}=1,\∀j$

$s_{\mathrm{ij}}\≥\mathrm{0,0}\≤{\mathrm{\ρ}}_{\mathrm{ij}}\≤1,\∀i,j;$

Step 5: utilize the Lagrangian of primal problem to s _ijask partial differential, then result is updated in Caro need-Ku En-Plutarch (Karush-Kuhn-Tucker, KKT) condition, can obtain

Step 6: utilize GRADIENT PROJECTION METHODS, the optimum performance response that obtains bandwidth is and the conclusion in step 5 obtains s _ij;

Step 7: consider the continuous differential expression of the dual function of primal problem, utilize gradient projection method to upgrade the non-negative Lagrange multiplier of optimization aim function, obtain suitable ρ _ijand s _ijafter, obtain the optimization solution of target function.

System of the present invention comprises:

One, system model

I. the present invention sets up LTE-WLAN heterogeneous network (3GPP-LTE, hereinafter to be referred as LTE) system model, and this model comprises the necessary factors such as network insertion and resource distribution substantially.

Heterogeneous network system model is comprised of 1 LTE network and L wlan network.Wherein, the overlay area of LTE base station and WLAN focus can be overlapping, and suppose that the overlay area of all WLAN focuses is completely inner in the overlay area of LTE.The operating frequency of WLAN and LTE is separate, does not have inter-network interference.The channel that different WLAN distribute is not overlapping, does not have interference yet.In all signal coverage areas, there are a plurality of multimode terminals, can or access separately LTE network or wlan network simultaneously.

Suppose the Two dimensional Distribution model of a LTE-WLAN heterogeneous network as shown in Figure 2.The base station of LTE network is positioned at the origin of coordinates (0,0), three fan antennas, and radius of society is 500m.Wherein, support that the radius of society of IEEE802.11a WLAN is 200m.In a LTE sector, two WLAN can partly overlap, and these two WLAN access points lay respectively at the coverage of coordinate (300,200) and (300,200).Be randomly dispersed in sector in LTE use be applicable to per family this RRM.In emulation, the present invention's hypothesis has 3 MMTS, and they are randomly dispersed in region.1 DC(

) MMT and 2 (γ ₂: γ ₃=1:1) MMT can access a plurality of wireless networks simultaneously.

II. in LTE network, the total bandwidth of system is divided into F subcarrier, and comprises M OFDM mark space in a RRM time frame.Therefore, total N=FM the Resource Block of system under total bandwidth, each Resource Block is corresponding to a subcarrier in an OFDM mark space.R _0inrepresent the transfer rate that user i obtains based on Resource Block n, wherein n=(a-1) F+b represents the Resource Block (1≤a≤M, 1≤b≤F, 1≤n≤N) of b subcarrier in a OFDM mark space.The fading coefficients of supposing all users remains unchanged in a time frame, variable in different time frames.Central controller in base station can be predicted all channel informations, and the channel information that each terminal collection is estimated, sends to base station by feedback channel, or carries out channel estimating by the up link in time division duplex (TDD) system.In feedback information substitution subcarrier and power distribution method that utilization is recovered to, allow the central controller be the different subcarrier of user assignment, and determine according to instantaneous channel input the power/bit quantity sending on each subcarrier.If the transmitting power of base station is P _t.

III. the present invention supposes that the wireless channel between base station and terminal is the rayleigh fading channel that frequency is selected.Yet the channel of each subcarrier is narrower, so it is flat fading.R _inbe illustrated in each OFDM symbol time interval, the transfer rate that user i obtains based on subcarrier n, its value depends on channel gain h _inwith the power P of user i based on distributing on subcarrier n _in.Conventionally, r _inconventionally be represented as

$r_{\mathrm{in}}={\mathrm{\β}}_0{B}_0{\log }_2(1+\frac{P_{\mathrm{in}}{\left|h_{\mathrm{in}}\right|}^2}{\mathrm{\Γ}{N}_0{B}_0})---\left(1\right)$

Here, N ₀be the power spectral density of additive white Gaussian noise, Γ is a constant, is known as signal to noise ratio interval.

In the WLAN of 802.11 agreements, the media interviews that the present invention considers are controlled (MAC) agreement and are adopted the modified model distributed coordination function based on reservation.By merging the information of keeping out of the way in MAC head, user can avoid collision conflict completely.Therefore, the present invention can allow user access WLAN in the mode of a kind of TDMA simply, and each user exclusively enjoys all bandwidth in distributed time frame.All power delivery are supposed, user i is represented as r in a ground j WLAN _ij, equally for upper, r _ijcan be represented as

$r_{\mathrm{ij}}={\mathrm{\β}}_j{B}_j{\log }_2(1+\frac{P_{\mathrm{ij}}{\left|h_{\mathrm{ij}}\right|}^2}{\mathrm{\Γ}{N}_0{B}_j})---\left(2\right)$

In formula (1) and (2), β is the validity that the invention provides each subsystem, the spectrum efficiency of the subsystem that its expression provides.

Two, mathematical modeling

I. first the present invention's modeling again, supposes in LTE-WLAN heterogeneous network, exist M support different service types enliven multimode terminal (Multi-Mode Terminal, MMT) and the available wireless access technology (RAT) of N kind.Each MMT can obtain by the mode of multiple access the Radio Resource of heterogeneous networks.Different according to the requirement of service delay, M MMT can be divided into two types: first kind DC type MMT, and quantity is K, the minimum transmission rate request of its business is

(i=1,2 ..., K); Second Type has (M-K) individual BE type MMT, there is no delay constraint, in the mode of doing one's best, carries out transfer of data, but transfer rate is subject to proportional fairness constraint.

The condition of DC and BE is expressed as:

$r_i\≥R_i^{\min },i=\mathrm{1,2},\·\·\·,K,---\left(3\right)$

r _K+1:r _k+2:...:r _M＝γ _K+1:γ _K+2:...:γ _M (4)

Here

being the minimum transmission rate constraint of DC type MMT, is the mathematical expectation of DC type MMT minimum-rate.γ _i(i=K+1, K+2 ..., M) be the fair parameter of proportionality of BE type MMT.

In II.LTE-WLAN heterogeneous network, under user's proportionality rate constraint, all users' the total speed of maximum solves as follows:

$\mathrm{Max}\underset{i=1}{\overset{M}{\mathrm{\Σ}}}{R}_i---\left(5a\right)$

$\begin{array}{cc}\mathrm{subject\; to}& \underset{j=0}{\overset{L}{\mathrm{\Σ}}}{\mathrm{\α}}_{\mathrm{ij}}\≤1,\∀i,{\mathrm{\α}}_{\mathrm{ij}}\∈\left\{\mathrm{0,1}\right\},\∀i,j\end{array}---\left(5b\right)$

$\underset{i=1}{\overset{M}{\mathrm{\Σ}}}{f}_{\mathrm{in}}\≤1,\∀n,f_{\mathrm{in}}\∈\left\{\mathrm{0,1}\right\},\∀i,n---\left(5c\right)$

$\underset{i=1}{\overset{M}{\mathrm{\Σ}}}{t}_{\mathrm{ij}}\≤1,\∀j,0\≤t_{\mathrm{ij}}\≤1,\∀j,i---\left(5d\right)$

$R_i={\mathrm{\α}}_{0i}\underset{n=1}{\overset{N}{\mathrm{\Σ}}}{f}_{\mathrm{in}}{r}_{0\mathrm{in}}+{\mathrm{\α}}_{\mathrm{ij}}\underset{j=1}{\overset{L}{\mathrm{\Σ}}}{t}_{\mathrm{ij}}{r}_{\mathrm{ij}}---\left(5e\right)$

$R_i\≥R_i^{\min },\∀i=\mathrm{1,2},\·\·\·,K---\left(5f\right)$

$\frac{R_i}{{\mathrm{\γ}}_i}=\frac{R_{k+1}}{{\mathrm{\γ}}_{k+1}},\∀i\∈k+1,k+2,\·\·\·,M---\left(5g\right)$

Wherein, j represents network index (being that j=0 is that LTE and network j (1≤j≤L) are j wlan networks).α _ijrepresent that user i selects parameter at the network of network j.F _ijfor the resource allocation parameters of user i in the Resource Block n of LTE, t _ijfor the time frame allocation of parameters of user i at j wlan network.

Wherein, formula (5b) guarantees that each user can only access single network in each RRM time frame, (5c) guarantees that the Resource Block in LTE network can only be by single CU.R _ifor the data rate of user i, (5g) represent the user data transmission rate limit of different proportion.{ γ _k+1, γ _k+2..., γ _mit is the preset value that guarantees resource fairness in distribution between different user.

III. to above-mentioned (5b) and (5c) integer constraints relax.MMT can be called by the network of a plurality of RATs parallel transmission data multiple wireless access (multi-radio access, MRA) system, and it can hold LTE and 802.11 wlan subsystems.If α _ij=1, represent that single network selects constraint to relax and can access a plurality of networks for user simultaneously.Secondly, the present invention allows a plurality of users can in LTE, share a resource element, makes a plurality of users share the same Resource Block in LTE network in the mode of FDMA.Formula (5e) is expressed as

$R_i=\underset{n=1}{\overset{N}{\mathrm{\Σ}}}{f}_{\mathrm{in}}{r}_{0\mathrm{in}}+\underset{j=1}{\overset{L}{\mathrm{\Σ}}}{t}_{\mathrm{ij}}{r}_{\mathrm{ij}}---\left(5h\right)$

0≤f wherein _ijthe part that≤1 representative of consumer i is distributed by Resource Block n.

Finally, abbreviation (5) is as follows:

$\mathrm{Max}\underset{i=1}{\overset{M}{\mathrm{\Σ}}}{R}_i---\left(6a\right)$

$\begin{array}{cc}\mathrm{subject\; to}& \underset{i=1}{\overset{M}{\mathrm{\Σ}}}{f}_{\mathrm{in}}\≤1,\∀n,0\≤f_{\mathrm{in}}\≤1,\∀i,n\end{array}---\left(6b\right)$

$\underset{i=1}{\overset{M}{\mathrm{\Σ}}}{t}_{\mathrm{ij}}\≤1,\∀j,0\≤t_{\mathrm{ij}}\≤1,\∀i,j---\left(6c\right)$

$R_i=\underset{n=1}{\overset{N}{\mathrm{\Σ}}}{f}_{\mathrm{in}}{r}_{0\mathrm{in}}+\underset{j=1}{\overset{L}{\mathrm{\Σ}}}{t}_{\mathrm{ij}}{r}_{\mathrm{ij}}---\left(6d\right)$

$R_i\≥R_i^{\min },\∀i=\mathrm{1,2},\·\·\·,K---\left(6e\right)$

$\frac{R_i}{{\mathrm{\γ}}_i}=\frac{R_{k+1}}{{\mathrm{\γ}}_{k+1}},\∀i\∈k+1,k+2,\·\·\·,M---\left(6f\right)$

The application of three, timesharing technology of sharing

I. the present invention is approximately resource element in LTE to carry out time frame distribution, i.e. OFDM-TDMA in TDMA mode.In order to reduce the complexity of this problem, the present invention, by introducing a timesharing shared variable, is converted into an Optimization Problems of Convex Functions problem.

Definition ρ _ijrepresent the time frame allocation of parameters of user i in network j (wherein 1≤j≤N refers to LTE network, and N+1≤j≤N+L refers to j WLAN).Introduced a variable s _ij, make s _ij=ρ _ijp _ij.Obviously, s _ijbe assigned to user i at the power of j subcarrier (1≤j≤N) or j WLAN (N+1≤j≤N+L).P _ijthe power that subcarrier or WLAN access point are taken by user i.

For the purpose of simple, definition α _ij=| h _ij| ²/ Γ _kn ₀b _j, represent that user i is in the efficient channel noise ratio (CNR) of subcarrier n.Therefore, R _ican be expressed as

$R_i=\underset{j=1}{\overset{N+L}{\mathrm{\Σ}}}{\mathrm{\β}}_j{B}_j{\mathrm{\ρ}}_{\mathrm{ij}}{\log }_2(1+s_{\mathrm{ij}}{\mathrm{\α}}_{\mathrm{ij}}/{\mathrm{\ρ}}_{\mathrm{ij}})---\left(7\right)$

II. by time frame allocation of parameters ρ _ij, (6) are converted to following form:

$\mathrm{Max}\underset{i=1}{\overset{M}{\mathrm{\Σ}}}{R}_i---\left(8a\right)$

$\begin{array}{cc}\mathrm{subject\; to}& R_i\≥R_i^{\min },\∀i=\mathrm{1,2},\·\·\·,K\end{array}---\left(8b\right)$

$\frac{R_i}{{\mathrm{\γ}}_i}=\frac{R_{K+1}}{{\mathrm{\γ}}_{K+1}},\∀i\∈K+1,K+2,\·\·\·,M---\left(8c\right)$

$\underset{i=1}{\overset{M}{\mathrm{\Σ}}}\underset{j=1}{\overset{N+L}{\mathrm{\Σ}}}{s}_{\mathrm{ji}}=P_T---\left(8d\right)$

$\underset{i=1}{\overset{M}{\mathrm{\Σ}}}{\mathrm{\ρ}}_{\mathrm{ij}}=1,\∀j---\left(8e\right)$

$s_{\mathrm{ij}}\≥\mathrm{0,0}\≤{\mathrm{\ρ}}_{\mathrm{ij}}\≤1,\∀i,j---\left(8f\right)$

Here P _tit is the total transmitting power from LTE base station and WLAN access point.Wherein, (8a) be f (ρ _ij, s _ij)=β _jb _jρ _ijlog ₂(1+s _ijc/ ρ _ij) summation, wherein C is normal number.

By assessment f (ρ _ij, s _ij) middle ρ _ij, s _ijhessian matrix, the present invention can prove f (ρ _ij, s _ij) be concave function, because the inequality constraints equation of (8b) is protruding equation, and (8c)-(8f) all be all affine function, the feasible zone of this optimization scheme is convex function collection.The present invention can be converted to a protruding optimization problem equation (8) thus, and in polynomial time, obtains unique optimal solution.

Four, many wireless access

I. for the optimal solution of capacity greatest problem, formula (9) has provided Lagrangian, wherein λ _j, μ, v _iand ω _iit is non-negative Lagrange multiplier.By introducing about λ _j, μ, v _iand ω _iderivative, by KKT condition, the present invention can obtain the general differential equation of two kinds of types of service:

$L(s_{\mathrm{ij}},{\mathrm{\ρ}}_{\mathrm{ij}},{\mathrm{\λ}}_j,\mathrm{\μ},v_i,{\mathrm{\ω}}_i)=\underset{i=1}{\overset{M}{\mathrm{\Σ}}}\underset{j=1}{\overset{N+L}{\mathrm{\Σ}}}{\mathrm{\β}}_j{B}_j{\mathrm{\ρ}}_{\mathrm{ij}}{\log }_2(1+\frac{s_{\mathrm{ij}}{\mathrm{\α}}_{\mathrm{ij}}}{{\mathrm{\ρ}}_{\mathrm{ij}}})+\underset{j=1}{\overset{L+N}{\mathrm{\Σ}}}{\mathrm{\λ}}_j(1-\underset{i=1}{\overset{M}{\mathrm{\Σ}}}{\mathrm{\ρ}}_{\mathrm{ij}})$

$+\mathrm{\μ}(P_T-\underset{i=1}{\overset{M}{\mathrm{\Σ}}}\underset{j=1}{\overset{N+L}{\mathrm{\Σ}}}{s}_{\mathrm{ji}})+\underset{i=1}{\overset{K}{\mathrm{\Σ}}}{v}_i(\underset{j=1}{\overset{N+L}{\mathrm{\Σ}}}{\mathrm{\β}}_j{B}_j{\mathrm{\ρ}}_{\mathrm{ij}}{\log }_2(1+\frac{s_{\mathrm{ij}}{\mathrm{\α}}_{\mathrm{ij}}}{{\mathrm{\ρ}}_{\mathrm{ij}}})-R_i^{\min })---\left(9\right)$

$+\underset{i=K+1}{\overset{M}{\mathrm{\Σ}}}{\mathrm{\ω}}_i(\underset{j=1}{\overset{N+L}{\mathrm{\Σ}}}{\mathrm{\β}}_j{B}_j{\mathrm{\ρ}}_{(K+1)j}{\log }_2(1+\frac{s_{(K+1)j}{\mathrm{\α}}_{(K+1)j}}{{\mathrm{\ρ}}_{(K+1)j}})-\frac{{\mathrm{\γ}}_{K+1}}{{\mathrm{\γ}}_i}\underset{j=1}{\overset{N+L}{\mathrm{\Σ}}}{\mathrm{\β}}_j{B}_j{\mathrm{\ρ}}_{\mathrm{ij}}{\log }_2(1+\frac{s_{\mathrm{ij}}{\mathrm{\α}}_{\mathrm{ij}}}{{\mathrm{\ρ}}_{\mathrm{ij}}})))$

$\frac{\mathrm{dL}}{d{\mathrm{\ρ}}_{\mathrm{ij}}}={\widetilde{\mathrm{\β}}}_j{B}_j{\log }_2(1+\frac{s_{\mathrm{ij}}{\mathrm{\α}}_{\mathrm{ij}}}{{\mathrm{\ρ}}_{\mathrm{ij}}})-\frac{{\widetilde{\mathrm{\β}}}_j{B}_j{\mathrm{\α}}_{\mathrm{ij}}{s}_{\mathrm{ij}}}{({\mathrm{\ρ}}_{\mathrm{ij}}+{\mathrm{\α}}_{\mathrm{ij}}{s}_{\mathrm{ij}})\ln 2}-{\mathrm{\λ}}_j\≤0---\left(10\right)$

$\frac{\mathrm{dL}}{d{s}_{\mathrm{ij}}}=\frac{{\widetilde{\mathrm{\β}}}_j{\mathrm{\α}}_{\mathrm{ij}}{\mathrm{\ρ}}_{\mathrm{ij}}}{({\mathrm{\ρ}}_{\mathrm{ij}}+{\mathrm{\α}}_{\mathrm{ij}}{s}_{\mathrm{ij}})\ln 2}-\mathrm{\μ}\≤0---\left(11\right)$

Inequality (10), (11) are ρ _ijand s _ijnecessary condition and adequate condition.

When 1≤i≤K

${\widetilde{\mathrm{\β}}}_j=(1+v_i){\mathrm{\β}}_j,i=\mathrm{1,2},\·\·\·K---\left(12\right)$

When K+1≤i≤M, have

${\widetilde{\mathrm{\β}}}_j=(1+\underset{k=K+2}{\overset{M}{\mathrm{\Σ}}}{\mathrm{\ω}}_k){\mathrm{\β}}_j,i=K+1---\left(13\right)$

${\widetilde{\mathrm{\β}}}_j=(1-{\mathrm{\ω}}_i\frac{{\mathrm{\γ}}_{K+1}}{{\mathrm{\γ}}_K}){\mathrm{\β}}_j,i=K+2,\·\·\·,M---\left(14\right)$

By inequality (10), (11), have:

${\mathrm{\ρ}}_{\mathrm{ij}}\·\frac{\mathrm{dL}}{d{\mathrm{\ρ}}_{\mathrm{ij}}}=0,---\left(15\right)$

$s_{\mathrm{ij}}\·\frac{\mathrm{dL}}{d{s}_{\mathrm{ij}}}=0.---\left(16\right)$

II. establish { ρ _ijit is a given subcarrier distribution scheme.By Lagrangian (9) to s _ijdifferentiate, then it is inner that result is updated to KKT condition (11), the present invention can obtain

$P_{\mathrm{ij}}=\frac{s_{\mathrm{ij}}}{{\mathrm{\ρ}}_{\mathrm{ij}}}={[\frac{v_i}{\mathrm{\μ}\ln 2}-\frac{1}{{\mathrm{\α}}_{\mathrm{ij}}}]}^{+}---\left(17\right)$

I=1 wherein, 2 ... K, K+1 ..., M and j=1,2 ..., L+N.Here [z] ⁺=max{z, 0}.Formula (17) represents optimal power allocation obedience standard water flood, and in addition, the power being assigned with only depends on ρ _ijtime frame.In order to obtain ρ _ijand s _ijoptimal solution, by equation (9), the present invention can obtain its dual problem and be:

D(λ _j,μ,v _i,ω _i)＝max L(s _ij,ρ _ij,λ _j,μ,v _i,ω _i) (18)

III. according to protruding case study is found, primal problem (9) and dual problem (18) thereof have strong duality.Therefore, the present invention can obtain by solving (18) optimal solution of (9).If iteration step length is selected appropriate, it is feasible utilizing GRADIENT PROJECTION METHODS to move closer to optimal solution.So the present invention adopts the optimum performance response that obtains with the following method bandwidth:

${\mathrm{\ρ}}_{\mathrm{ij}}^{k+1}={[{\mathrm{\ρ}}_{\mathrm{ij}}^k+\mathrm{\δ}\frac{\mathrm{dL}}{d{\mathrm{\ρ}}_{\mathrm{ij}}}]}^{+},\∀i,j,---\left(19\right)$

Here δ is ρ _ijconstant iteration step length, appropriate as long as step-length δ selects, ρ _ijcan converge to optimal value.Obtaining ρ _ijafter, s _ijcan try to achieve by (17).Obtain the optimal solution of Lagrange multiplier value, the present invention considers continuously differentiable dual equation.Use gradient projection method, the power division of the non-negative multiplier of trying to achieve is as follows

${\mathrm{\λ}}_j^{k+1}={[{\mathrm{\λ}}_j^k+{\mathrm{\ϵ}}_1\frac{\mathrm{dD}}{d{\mathrm{\λ}}_j^k}]}^{+}={[{\mathrm{\λ}}_j^k+{\mathrm{\ϵ}}_1(\underset{i=1}{\overset{M}{\mathrm{\Σ}}}{\mathrm{\ρ}}_{\mathrm{ij}}-1)]}^{+},---\left(21\right)$

${\mathrm{\μ}}^{k+1}={[{\mathrm{\μ}}^k+{\mathrm{\ϵ}}_2\frac{\mathrm{dD}}{\mathrm{d\μ}}]}^{+}={[{\mathrm{\μ}}^k+{\mathrm{\ϵ}}_2(\underset{i=1}{\overset{M}{\mathrm{\Σ}}}\underset{j=1}{\overset{N+L}{\mathrm{\Σ}}}{s}_{\mathrm{ji}}-P_T)]}^{+},---\left(22\right)$

$v_i^{k+1}={[v_i^k+{\mathrm{\ϵ}}_3\frac{\mathrm{dD}}{d{v}_i^k}]}^{+}={[v_i^k+{\mathrm{\ϵ}}_3(\underset{j=1}{\overset{N+L}{\mathrm{\Σ}}}{r}_{\mathrm{ij}}-R_i^{\min })],}^{+}---\left(23\right)$

${\mathrm{\ω}}_i^{k+1}={[{\mathrm{\ω}}_i^k+{\mathrm{\ϵ}}_4\frac{\mathrm{dD}}{d{\mathrm{\ω}}_i^k}]}^{+}={[{\mathrm{\ω}}_i^k+{\mathrm{\ϵ}}_4(\underset{j=1}{\overset{N+L}{\mathrm{\Σ}}}{r}_{(K+1)j}-\frac{{\mathrm{\γ}}_{K+1}}{{\mathrm{\γ}}_i}\underset{j=1}{\overset{N+L}{\mathrm{\Σ}}}{r}_{\mathrm{ij}})]}^{+},,---\left(24\right)$

Wherein

it is a vector that step-length is constant.According to alternative manner, the invention solves the optimization problem of multiple access in heterogeneous network, improve to greatest extent the total capacity of system.

Five, the Radio Resource optimum management method based on time delay differentiated service and proportionality rate constraint

For multimode terminal (MMT), i comprises as follows:

Step1: initialization: arrange

with initial value,

Iterations initial value k=0 is set;

Step2: calculate by gradient projection method

${\mathrm{\ρ}}_{\mathrm{ij}}^{k+1}={[{\mathrm{\ρ}}_{\mathrm{ij}}^k+\mathrm{\δ}\frac{\mathrm{dL}}{d{\mathrm{\ρ}}_{\mathrm{ij}}}]}^{+},\∀i,j,;$

Step3: obtain $\frac{s_{\mathrm{ij}}}{{\mathrm{\ρ}}_{\mathrm{ij}}}={[\frac{1}{\mathrm{\μ}\ln 2}-\frac{1}{{\mathrm{\α}}_{\mathrm{ij}}}]}^{+}\∀i,j,;$

For the access point in RAT j, comprise:

Step1: utilize

calculate

Step2: after renewal

be broadcast to all MMTs,

Step3：k←k+1,goto step 1)

The optimal solution that the present invention utilizes projection gradient method to seek to deal with problems (7) as basis, dual equation D (λ _j, μ, v _i, ω _i) be protruding, the method for gradient type can remove to upgrade D (λ according to the appropriate direction of search _j, μ, v _i, ω _i) and obtain D (λ simultaneously _j, μ, v _i, ω _i) minimum value, thereby guarantee that it converges to optimal solution.In general, D (λ _j, μ, v _i, ω _i) can be not micro-, its gradient does not exist.

Beneficial effect:

1, the present invention is meeting under the basic transmission rate condition of DC type business, and the message transmission rate that realizes BE type business maximizes, thereby makes the total throughput of system reach maximum.

2, the present invention, according to best allocation strategy, is easy to draw under resource proportionality fair allocat, the Radio Resources such as the acquisition bandwidth that a plurality of BE type business can be fair and power, thus reach separately corresponding message transmission rate.

Accompanying drawing explanation

Fig. 1 is system model figure of the present invention.

Fig. 2 is the simulation model figure of LTE-WLAN network of the present invention.

Fig. 3 is method flow diagram of the present invention.

Embodiment

Below in conjunction with Figure of description, the invention is described in further detail.

As shown in Figure 3, the invention provides a kind of Radio Resource optimum management method based on time delay differentiated service and proportionality rate constraint, the method comprises the steps:

Step 1: suppose in LTE-WLAN heterogeneous network, exist M support different service types enliven multimode terminal and the available wireless access technology of N kind; In LTE network, suppose that the wireless channel between base station and terminal is the rayleigh fading channel that frequency is selected, the channel of each subcarrier is narrower, so it is flat fading; r _inbe illustrated in each OFDM symbol time interval, the transfer rate that user i obtains based on subcarrier n, its value depends on channel gain h _inwith the power P of user i based on distributing on subcarrier n _in; r _inconventionally be represented as

$r_{\mathrm{in}}={\mathrm{\β}}_0{B}_0{\log }_2(1+\frac{P_{\mathrm{in}}{\left|h_{\mathrm{in}}\right|}^2}{\mathrm{\Γ}{N}_0{B}_0})$

Wherein, N ₀be the power spectral density of additive white Gaussian noise, Γ is a constant, is known as signal to noise ratio interval; In the WLAN of 802.11 agreements, user accesses WLAN in the mode of TDMA; All power delivery are all supposed, user i is represented as r in j WLAN _ij, equally in above formula, r _ijbe represented as

$r_{\mathrm{ij}}={\mathrm{\β}}_j{B}_j{\log }_2(1+\frac{P_{\mathrm{ij}}{\left|h_{\mathrm{ij}}\right|}^2}{\mathrm{\Γ}{N}_0{B}_j})$

Wherein, the spectrum efficiency of provided subsystem is provided β, i.e. the validity of each subsystem;

Step 2: the difference requiring according to service delay, M MMT can be divided into two types: first kind DC type MMT, quantity is K, the minimum transmission rate request of its business is (i=1,2 ..., K); Second Type has (M-K) individual BE type MMT, although there is no delay constraint, in the mode of doing one's best, carries out transfer of data, and transmission rate is subject to the constraint of proportionality fair play

The condition of DC type MMT and BE type MMT is expressed as:

$r_i\≥R_i^{\min },i=\mathrm{1,2},\·\·\·,K,$

r _K+1:r _k+2:...:r _M＝γ _K+1:γ _K+2:...:γ _M；

Step 3: under user's proportionality rate constraint, calculate all users' the total speed of maximum:

$\mathrm{Max}\underset{i=1}{\overset{M}{\mathrm{\Σ}}}{R}_i$

$\begin{array}{cc}\mathrm{subject\; to}& \underset{j=0}{\overset{L}{\mathrm{\Σ}}}{\mathrm{\α}}_{\mathrm{ij}}\≤1,\∀i,{\mathrm{\α}}_{\mathrm{ij}}\∈\left\{\mathrm{0,1}\right\},\∀i,j\end{array}$

$\underset{i=1}{\overset{M}{\mathrm{\Σ}}}{f}_{\mathrm{in}}\≤1,\∀n,f_{\mathrm{in}}\∈\left\{\mathrm{0,1}\right\},\∀i,n$

$\underset{i=1}{\overset{M}{\mathrm{\Σ}}}{t}_{\mathrm{ij}}\≤1,\∀j,0\≤t_{\mathrm{ij}}\≤1,\∀j,i$

$R_i=\underset{n=1}{\overset{N}{\mathrm{\Σ}}}{f}_{\mathrm{in}}{r}_{0\mathrm{in}}+\underset{j=1}{\overset{L}{\mathrm{\Σ}}}{t}_{\mathrm{ij}}{r}_{\mathrm{ij}}$

$R_i\≥R_i^{\min },\∀i=\mathrm{1,2},\·\·\·,K$

$\frac{R_i}{{\mathrm{\γ}}_i}=\frac{R_{k+1}}{{\mathrm{\γ}}_{k+1}},\∀i\∈k+1,k+2,\·\·\·,M;$

Step 4: definition ρ _ijrepresent the time frame allocation of parameters of user i in network j (wherein 1≤j≤N refers to LTE network, and N+1≤j≤N+L refers to j WLAN), and introduced a variable s _ij, make s _ij=ρ _ijp _ij, definition α _ij=| h _ij| ²/ Γ _kn ₀b _j, and by time frame allocation of parameters ρ _ij, can be by R _ibe rewritten as

constraints is rewritten as

$R_i\≥R_i^{\min },\∀i=\mathrm{1,2},\·\·\·,K$

$\frac{R_i}{{\mathrm{\γ}}_i}=\frac{R_{K+1}}{{\mathrm{\γ}}_{K+1}},\∀i\∈K+1,K+2,\·\·\·,M$

$\underset{i=1}{\overset{M}{\mathrm{\Σ}}}\underset{j=1}{\overset{N+L}{\mathrm{\Σ}}}{s}_{\mathrm{ji}}=P_T$

$\underset{i=1}{\overset{M}{\mathrm{\Σ}}}{\mathrm{\ρ}}_{\mathrm{ij}}=1,\∀j$

$s_{\mathrm{ij}}\≥\mathrm{0,0}\≤{\mathrm{\ρ}}_{\mathrm{ij}}\≤1,\∀i,j;$

Step 5: utilize the Lagrangian of primal problem to s _ijask partial differential, then result is updated in Caro need-Ku En-Plutarch (Karush-Kuhn-Tucker, KKT) condition, can obtain

Step 6: utilize GRADIENT PROJECTION METHODS, the optimum performance response that obtains bandwidth is

and the conclusion in step 5 obtains s _ij;

Step 7: consider the continuous differential expression of the dual function of primal problem, utilize gradient projection method to upgrade the non-negative Lagrange multiplier of optimization aim function, obtain suitable ρ _ijand s _ijafter, obtain the optimization solution of target function.

System of the present invention comprises:

One, system model

I. the research of the RRM mechanism under the heterogeneous network based on OFDMA technology, the present invention sets up LTE-WLAN heterogeneous network (3GPP-LTE, hereinafter to be referred as LTE) system model, and this model comprises the necessary factors such as network insertion and resource distribution substantially.

Heterogeneous network system model, as Fig. 1, is comprised of 1 LTE network and L wlan network.Wherein, the overlay area of LTE base station and WLAN focus can be overlapping, and suppose that the overlay area of all WLAN focuses is completely inner in the overlay area of LTE.The operating frequency of WLAN and LTE is separate, does not have inter-network interference.The channel that different WLAN distribute is not overlapping, does not have interference yet.In all signal coverage areas, there are a plurality of multimode terminals, can or access separately LTE network or wlan network simultaneously.

Suppose the Two dimensional Distribution model of a LTE-WLAN heterogeneous network as shown in Figure 2.The base station of LTE network is positioned at the origin of coordinates (0,0), three fan antennas, and radius of society is 500m.Wherein, support that the radius of society of IEEE802.11a WLAN is 200m.In a LTE sector, two WLAN can partly overlap, and these two WLAN access points lay respectively at the coverage of coordinate (300,200) and (300,200).Be randomly dispersed in sector in LTE use be applicable to per family this RRM.In emulation, the present invention's hypothesis has 3 MMTS, and they are randomly dispersed in region.1 DC( ) MMT and 2 (γ ₂: γ ₃=1:1) MMT can access a plurality of wireless networks simultaneously.

II. in LTE network, the total bandwidth of system is divided into F subcarrier, and comprises M OFDM mark space in a RRM time frame.Therefore, total N=FM the Resource Block of system under total bandwidth, each Resource Block is corresponding to a subcarrier in an OFDM mark space.R _0inrepresent the transfer rate that user i obtains based on Resource Block n, wherein n=(a-1) F+b represents the Resource Block (1≤a≤M, 1≤b≤F, 1≤n≤N) of b subcarrier in a OFDM mark space.The fading coefficients of supposing all users remains unchanged in a time frame, variable in different time frames.Central controller in base station can be predicted all channel informations, and the channel information that each terminal collection is estimated, sends to base station by feedback channel, or carries out channel estimating by the up link in time division duplex (TDD) system.In feedback information substitution subcarrier and power distribution method that utilization is recovered to, allow the central controller be the different subcarrier of user assignment, and determine according to instantaneous channel input the power/bit quantity sending on each subcarrier.If the transmitting power of base station is P _t.

III. the present invention supposes that the wireless channel between base station and terminal is the rayleigh fading channel that frequency is selected.Yet the channel of each subcarrier is narrower, so it is flat fading.R _inbe illustrated in each OFDM symbol time interval, the transfer rate that user i obtains based on subcarrier n, its value depends on channel gain h _inwith the power P of user i based on distributing on subcarrier n _in.Conventionally, r _inconventionally be represented as

$r_{\mathrm{in}}={\mathrm{\β}}_0{B}_0{\log }_2(1+\frac{P_{\mathrm{in}}{\left|h_{\mathrm{in}}\right|}^2}{\mathrm{\Γ}{N}_0{B}_0})---\left(1\right)$

Here, N ₀be the power spectral density of additive white Gaussian noise, Γ is a constant, is known as signal to noise ratio interval.

In the WLAN of 802.11 agreements, the media interviews that the present invention considers are controlled (MAC) agreement and are adopted the modified model distributed coordination function based on reservation.By merging the information of keeping out of the way in MAC head, user can avoid collision conflict completely.Therefore, the present invention can allow user access WLAN in the mode of a kind of TDMA simply, and each user exclusively enjoys all bandwidth in distributed time frame.All power delivery are supposed, user i is represented as r in a ground j WLAN _ij, equally for upper, r _ijcan be represented as

$r_{\mathrm{ij}}={\mathrm{\β}}_j{B}_j{\log }_2(1+\frac{P_{\mathrm{ij}}{\left|h_{\mathrm{ij}}\right|}^2}{\mathrm{\Γ}{N}_0{B}_j})---\left(2\right)$

In formula (1) and (2), β is the validity that the invention provides each subsystem, the spectrum efficiency of the subsystem that its expression provides.

Two, mathematical modeling

I. first the present invention's modeling again, supposes in LTE-WLAN heterogeneous network, exist M support different service types enliven multimode terminal (Multi-Mode Terminal, MMT) and the available wireless access technology (RAT) of N kind.Each MMT can obtain by the mode of multiple access the Radio Resource of heterogeneous networks.Different according to the requirement of service delay, M MMT can be divided into two types: first kind DC type MMT, and quantity is K, the minimum transmission rate request of its business is

(i=1,2 ..., K); Second Type has (M-K) individual BE type MMT, there is no delay constraint, in the mode of doing one's best, carries out transfer of data, but transfer rate is subject to proportional fairness constraint.

The condition of DC and BE is expressed as:

$r_i\≥R_i^{\min },i=\mathrm{1,2},\·\·\·,K,---\left(3\right)$

r _K+1:r _k+2:...:r _M＝γ _K+1:γ _K+2:...:γ _M (4)

Here

being the minimum transmission rate constraint of DC type MMT, is the mathematical expectation of DC type MMT minimum-rate.γ _i(i=K+1, K+2 ..., M) be the fair parameter of proportionality of BE type MMT.

In II.LTE-WLAN heterogeneous network, under user's proportionality rate constraint, all users' the total speed of maximum solves as follows:

$\mathrm{Max}\underset{i=1}{\overset{M}{\mathrm{\Σ}}}{R}_i---\left(5a\right)$

$\begin{array}{cc}\mathrm{subject\; to}& \underset{j=0}{\overset{L}{\mathrm{\Σ}}}{\mathrm{\α}}_{\mathrm{ij}}\≤1,\∀i,{\mathrm{\α}}_{\mathrm{ij}}\∈\left\{\mathrm{0,1}\right\},\∀i,j\end{array}---\left(5b\right)$

$\underset{i=1}{\overset{M}{\mathrm{\Σ}}}{f}_{\mathrm{in}}\≤1,\∀n,f_{\mathrm{in}}\∈\left\{\mathrm{0,1}\right\},\∀i,n---\left(5c\right)$

$\underset{i=1}{\overset{M}{\mathrm{\Σ}}}{t}_{\mathrm{ij}}\≤1,\∀j,0\≤t_{\mathrm{ij}}\≤1,\∀j,i---\left(5d\right)$

$R_i={\mathrm{\α}}_{0i}\underset{n=1}{\overset{N}{\mathrm{\Σ}}}{f}_{\mathrm{in}}{r}_{0\mathrm{in}}+{\mathrm{\α}}_{\mathrm{ji}}\underset{j=1}{\overset{L}{\mathrm{\Σ}}}{t}_{\mathrm{ij}}{r}_{\mathrm{ij}}---\left(5e\right)$

$R_i\≥R_i^{\min },\∀i=\mathrm{1,2},\·\·\·,K---\left(5f\right)$

$\frac{R_i}{{\mathrm{\γ}}_i}=\frac{R_{k+1}}{{\mathrm{\γ}}_{k+1}},\∀i\∈k+1,k+2,\·\·\·,M---\left(5g\right)$

Wherein, j represents network index (being that j=0 is that LTE and network j (1≤j≤L) are j wlan networks).α _ijrepresent that user i selects parameter at the network of network j.F _ijfor the resource allocation parameters of user i in the Resource Block n of LTE, t _ijfor the time frame allocation of parameters of user i at j wlan network.

Wherein, formula (5b) guarantees that each user can only access single network in each RRM time frame, (5c) guarantees that the Resource Block in LTE network can only be by single CU.R _ifor the data rate of user i, (5g) represent the user data transmission rate limit of different proportion.{ γ _k+1, γ _k+2..., γ _mit is the preset value that guarantees resource fairness in distribution between different user.

III. to above-mentioned (5b) and (5c) integer constraints relax.MMT can be called by the network of a plurality of RATs parallel transmission data multiple wireless access (multi-radio access, MRA) system, and it can hold LTE and 802.11 wlan subsystems.If α _ij=1, represent that single network selects constraint to relax and can access a plurality of networks for user simultaneously.Secondly, the present invention allows a plurality of users can in LTE, share a resource element, makes a plurality of users share the same Resource Block in LTE network in the mode of FDMA.Formula (5e) is expressed as

$R_i=\underset{n=1}{\overset{N}{\mathrm{\Σ}}}{f}_{\mathrm{in}}{r}_{0\mathrm{in}}+\underset{j=1}{\overset{L}{\mathrm{\Σ}}}{t}_{\mathrm{ij}}{r}_{\mathrm{ij}}---\left(5h\right)$

0≤f wherein _ijthe part that≤1 representative of consumer i is distributed by Resource Block n.

Finally, abbreviation (5) is as follows:

$\mathrm{Max}\underset{i=1}{\overset{M}{\mathrm{\Σ}}}{R}_i---\left(6a\right)$

$\begin{array}{cc}\mathrm{subject\; to}& \underset{i=1}{\overset{M}{\mathrm{\Σ}}}{f}_{\mathrm{in}}\≤1,\∀n,0\≤f_{\mathrm{in}}\≤1,\∀i,n\end{array}---\left(6b\right)$

$\underset{i=1}{\overset{M}{\mathrm{\Σ}}}{t}_{\mathrm{ij}}\≤1,\∀j,0\≤t_{\mathrm{ij}}\≤1,\∀i,j---\left(6c\right)$

$R_i=\underset{n=1}{\overset{N}{\mathrm{\Σ}}}{f}_{\mathrm{in}}{r}_{0\mathrm{in}}+\underset{j=1}{\overset{L}{\mathrm{\Σ}}}{t}_{\mathrm{ij}}{r}_{\mathrm{ij}}---\left(6d\right)$

$R_i\≥R_i^{\min },\∀i=\mathrm{1,2},\·\·\·,K---\left(6e\right)$

$\frac{R_i}{{\mathrm{\γ}}_i}=\frac{R_{k+1}}{{\mathrm{\γ}}_{k+1}},\∀i\∈k+1,k+2,\·\·\·,M---\left(6f\right)$

The application of three, timesharing technology of sharing

I. the present invention is approximately resource element in LTE to carry out time frame distribution, i.e. OFDM-TDMA in TDMA mode.In order to reduce the complexity of this problem, the present invention, by introducing a timesharing shared variable, is converted into an Optimization Problems of Convex Functions problem.

Definition ρ _ijrepresent the time frame allocation of parameters of user i in network j (wherein 1≤j≤N refers to LTE network, and N+1≤j≤N+L refers to j WLAN).Introduced a variable s _ij, make s _ij=ρ _ijp _ij.Obviously, s _ijbe assigned to user i at the power of j subcarrier (1≤j≤N) or j WLAN (N+1≤j≤N+L).P _ijthe power that subcarrier or WLAN access point are taken by user i.

For the purpose of simple, definition α _ij=| h _ij| ²/ Γ _kn ₀b _j, represent that user i is in the efficient channel noise ratio (CNR) of subcarrier n.Therefore, R _ican be expressed as

$R_i=\underset{j=1}{\overset{N+L}{\mathrm{\Σ}}}{\mathrm{\β}}_j{B}_j{\mathrm{\ρ}}_{\mathrm{ij}}{\log }_2(1+s_{\mathrm{ij}}{\mathrm{\α}}_{\mathrm{ij}}/{\mathrm{\ρ}}_{\mathrm{ij}})---\left(7\right)$

II. by time frame allocation of parameters ρ _ij, (6) are converted to following form:

$\mathrm{Max}\underset{i=1}{\overset{M}{\mathrm{\Σ}}}{R}_i---\left(8a\right)$

$\begin{array}{cc}\mathrm{subject\; to}& R_i\≥\end{array},R_i^{\min },\∀i=\mathrm{1,2},\·\·\·,K---\left(8b\right)$

$\frac{R_i}{{\mathrm{\γ}}_i}=\frac{R_{K+1}}{{\mathrm{\γ}}_{K+1}},\∀i\∈K+1,K+2,\·\·\·,M---\left(8c\right)$

$\underset{i=1}{\overset{M}{\mathrm{\Σ}}}\underset{j=1}{\overset{N+L}{\mathrm{\Σ}}}{s}_{\mathrm{ji}}=P_T---\left(8d\right)$

$\underset{i=1}{\overset{M}{\mathrm{\Σ}}}{\mathrm{\ρ}}_{\mathrm{ij}}=1,\∀j---\left(8e\right)$

$s_{\mathrm{ij}}\≥\mathrm{0,0}\≤{\mathrm{\ρ}}_{\mathrm{ij}}\≤1,\∀i,j---\left(8f\right)$

Here P _tit is the total transmitting power from LTE base station and WLAN access point.Wherein, (8a) be f (ρ _ij, s _ij)=β _jb _jρ _ijlog ₂(1+s _ijc/ ρ _ij) summation, wherein C is normal number.

By assessment f (ρ _ij, s _ij) middle ρ _ij, s _ijhessian matrix, the present invention can prove f (ρ _ij, s _ij) be concave function.Because the inequality constraints equation of (8b) is protruding equation, and (8c)-(8f) all be all affine function, the feasible zone of this optimization scheme is convex function collection.The present invention can be converted to a protruding optimization problem equation (8) thus, and in polynomial time, obtains unique optimal solution.

Four, many wireless access

I. for the optimal solution of capacity greatest problem, formula (9) has provided Lagrangian, wherein λ _j, μ, v _iand ω _iit is non-negative Lagrange multiplier.By introducing about λ _j, μ, v _iand ω _iderivative, by KKT condition, the present invention can obtain the general differential equation of two kinds of types of service:

$L(s_{\mathrm{ij}},{\mathrm{\ρ}}_{\mathrm{ij}},{\mathrm{\λ}}_j,\mathrm{\μ},v_i,{\mathrm{\ω}}_i)=\underset{i=1}{\overset{M}{\mathrm{\Σ}}}\underset{j=1}{\overset{N+L}{\mathrm{\Σ}}}{\mathrm{\β}}_j{B}_j{\mathrm{\ρ}}_{\mathrm{ij}}{\log }_2(1+\frac{s_{\mathrm{ij}}{\mathrm{\α}}_{\mathrm{ij}}}{{\mathrm{\ρ}}_{\mathrm{ij}}})+\underset{j=1}{\overset{L+N}{\mathrm{\Σ}}}{\mathrm{\λ}}_j(1-\underset{i=1}{\overset{M}{\mathrm{\Σ}}}{\mathrm{\ρ}}_{\mathrm{ij}})$

$+\mathrm{\μ}(P_T-\underset{i=1}{\overset{M}{\mathrm{\Σ}}}\underset{j=1}{\overset{N+L}{\mathrm{\Σ}}}{s}_{\mathrm{ji}})+\underset{i=1}{\overset{K}{\mathrm{\Σ}}}{v}_i(\underset{j=1}{\overset{N+L}{\mathrm{\Σ}}}{\mathrm{\β}}_j{B}_j{\mathrm{\ρ}}_{\mathrm{ij}}{\log }_2(1+\frac{s_{\mathrm{ij}}{\mathrm{\α}}_{\mathrm{ij}}}{{\mathrm{\ρ}}_{\mathrm{ij}}})-R_i^{\min })---\left(9\right)$

$+\underset{i=K+1}{\overset{M}{\mathrm{\Σ}}}{\mathrm{\ω}}_i(\underset{j=1}{\overset{N+L}{\mathrm{\Σ}}}{\mathrm{\β}}_j{B}_j{\mathrm{\ρ}}_{(K+1)j}{\log }_2(1+\frac{s_{(K+1)j}{\mathrm{\α}}_{(K+1)j}}{{\mathrm{\ρ}}_{(K+1)}})-\frac{{\mathrm{\γ}}_{K+1}}{{\mathrm{\γ}}_i}\underset{j=1}{\overset{N+L}{\mathrm{\Σ}}}{\mathrm{\β}}_j{B}_j{\mathrm{\ρ}}_{\mathrm{ij}}{\log }_2(1+\frac{s_{\mathrm{ij}}{\mathrm{\α}}_{\mathrm{ij}}}{{\mathrm{\ρ}}_{\mathrm{ij}}})))$

$\frac{\mathrm{dL}}{d{\mathrm{\ρ}}_{\mathrm{ij}}}={\widetilde{\mathrm{\β}}}_j{B}_j{\log }_2(1+\frac{s_{\mathrm{ij}}{\mathrm{\α}}_{\mathrm{ij}}}{{\mathrm{\ρ}}_{\mathrm{ij}}})-\frac{{\widetilde{\mathrm{\β}}}_j{B}_j{\mathrm{\α}}_{\mathrm{ij}}{s}_{\mathrm{ij}}}{({\mathrm{\ρ}}_{\mathrm{ij}}+{\mathrm{\α}}_{\mathrm{ij}}{s}_{\mathrm{ij}})\ln 2}-{\mathrm{\λ}}_j\≤0---\left(10\right)$

$\frac{\mathrm{dL}}{d{s}_{\mathrm{ij}}}=\frac{{\widetilde{\mathrm{\β}}}_j{\mathrm{\α}}_{\mathrm{ij}}{\mathrm{\ρ}}_{\mathrm{ij}}}{({\mathrm{\ρ}}_{\mathrm{ij}}+{\mathrm{\α}}_{\mathrm{ij}}{s}_{\mathrm{ij}})\ln 2}-\mathrm{\μ}\≤0---\left(11\right)$

Inequality (10), (11) are ρ _ijand s _ijnecessary condition and adequate condition.

When 1≤i≤K

${\widetilde{\mathrm{\β}}}_j=(1+v_i){\mathrm{\β}}_j,i=\mathrm{1,2},\·\·\·K---\left(12\right)$

When K+1≤i≤M, have

${\widetilde{\mathrm{\β}}}_j=(1+\underset{k=K+2}{\overset{M}{\mathrm{\Σ}}}{\mathrm{\ω}}_k){\mathrm{\β}}_j,i=K+1---\left(13\right)$

${\widetilde{\mathrm{\β}}}_j=(1-{\mathrm{\ω}}_i\frac{{\mathrm{\γ}}_{K+1}}{{\mathrm{\γ}}_K}){\mathrm{\β}}_j,i=K+2,\·\·\·,M---\left(14\right)$

By inequality (10), (11), have:

${\mathrm{\ρ}}_{\mathrm{ij}}\·\frac{\mathrm{dL}}{d{\mathrm{\ρ}}_{\mathrm{ij}}}=0,---\left(15\right)$

$s_{\mathrm{ij}}\·\frac{\mathrm{dL}}{d{s}_{\mathrm{ij}}}=0.---\left(16\right)$

II. establish { ρ _ijit is a given subcarrier distribution scheme.By Lagrangian (9) to s _ijdifferentiate, then it is inner that result is updated to KKT condition (11), the present invention can obtain

$P_{\mathrm{ij}}=\frac{s_{\mathrm{ij}}}{{\mathrm{\ρ}}_{\mathrm{ij}}}={[\frac{v_i}{\mathrm{\μ}\ln 2}-\frac{1}{{\mathrm{\α}}_{\mathrm{ij}}}]}^{+}---\left(17\right)$

I=1 wherein, 2 ... K, K+1 ..., M and j=1,2 ..., L+N.Here [z] ⁺=max{z, 0}.Formula (17) represents optimal power allocation obedience standard water flood, and in addition, the power being assigned with only depends on ρ _ijtime frame.In order to obtain ρ _ijand s _ijoptimal solution, by equation (9), the present invention can obtain its dual problem and be:

D(λ _j,μ,v _i,ω _i)＝maxL(s _ij,ρ _ij,λ _j,μ,v _i,ω _i) (18)

III. according to protruding case study is found, primal problem (9) and dual problem (18) thereof have strong duality.Therefore, the present invention can obtain by solving (18) optimal solution of (9).If iteration step length is selected appropriate, it is feasible utilizing GRADIENT PROJECTION METHODS to move closer to optimal solution.So the present invention adopts the optimum performance response that obtains with the following method bandwidth:

${\mathrm{\ρ}}_{\mathrm{ij}}^{k+1}={[{\mathrm{\ρ}}_{\mathrm{ij}}^k+\mathrm{\δ}\frac{\mathrm{dL}}{d{\mathrm{\ρ}}_{\mathrm{ij}}}]}^{+},\∀i,j,---\left(19\right)$

Here δ is ρ _ijconstant iteration step length, appropriate as long as step-length δ selects, ρ _ijcan converge to optimal value.Obtaining ρ _ijafter, s _ijcan try to achieve by (17).Obtain the optimal solution of Lagrange multiplier value, the present invention considers continuously differentiable dual equation.Use gradient projection method, the power division of the non-negative multiplier of trying to achieve is as follows

${\mathrm{\λ}}_j^{k+1}={[{\mathrm{\λ}}_j^k+{\mathrm{\ϵ}}_1\frac{\mathrm{dD}}{d{\mathrm{\λ}}_j^k}]}^{+}={[{\mathrm{\λ}}_j^k+{\mathrm{\ϵ}}_1(\underset{i=1}{\overset{M}{\mathrm{\Σ}}}{\mathrm{\ρ}}_{\mathrm{ij}}-1)]}^{+}---\left(21\right)$

${\mathrm{\μ}}^{k+1}={[{\mathrm{\μ}}^k+{\mathrm{\ϵ}}_2\frac{\mathrm{dD}}{\mathrm{d\μ}}]}^{+}={[{\mathrm{\μ}}^k+{\mathrm{\ϵ}}_2(\underset{i=1}{\overset{M}{\mathrm{\Σ}}}\underset{j=1}{\overset{N+L}{\mathrm{\Σ}}}{s}_{\mathrm{ji}}-P_T)]}^{+},---\left(22\right)$

$v_i^{k+1}={[v_i^k+{\mathrm{\ϵ}}_3\frac{\mathrm{dD}}{d{v}_i^k}]}^{+}={[v_i^k+{\mathrm{\ϵ}}_3(\underset{j=1}{\overset{N+L}{\mathrm{\Σ}}}{r}_{\mathrm{ij}}-R_i^{\min })]}^{+},---\left(23\right)$

${\mathrm{\ω}}_i^{k+1}={[{\mathrm{\ω}}_i^k+{\mathrm{\ϵ}}_4\frac{\mathrm{dD}}{d{\mathrm{\ω}}_i^k}]}^{+}={[{\mathrm{\ω}}_i^k+{\mathrm{\ϵ}}_4(\underset{j=1}{\overset{N+L}{\mathrm{\Σ}}}{r}_{(K+1)j}-\frac{{\mathrm{\γ}}_{K+1}}{{\mathrm{\γ}}_i}\underset{j=1}{\overset{N+L}{\mathrm{\Σ}}}{r}_{\mathrm{ij}})]}^{+},,---\left(24\right)$

Wherein

it is a vector that step-length is constant.According to alternative manner, the invention solves the optimization problem of multiple access in heterogeneous network, improve to greatest extent the total capacity of system.

Five, the Radio Resource optimum management method based on time delay differentiated service and proportionality rate constraint

For multimode terminal (MMT), i comprises as follows:

Step1: initialization: arrange

with initial value,

Iterations initial value k=0 is set;

Step2: calculate by gradient projection method

${\mathrm{\ρ}}_{\mathrm{ij}}^{k+1}={[{\mathrm{\ρ}}_{\mathrm{ij}}^k+\mathrm{\δ}\frac{\mathrm{dL}}{d{\mathrm{\ρ}}_{\mathrm{ij}}}]}^{+},\∀i,j,;$

Step3: obtain $\frac{s_{\mathrm{ij}}}{{\mathrm{\ρ}}_{\mathrm{ij}}}={[\frac{1}{\mathrm{\μ}\ln 2}-\frac{1}{{\mathrm{\α}}_{\mathrm{ij}}}]}^{+}\∀i,j,;$

For the access point in RAT j, comprise as follows:

Step1: utilize calculate

Step2: after renewal be broadcast to all MMTs,

Step3：k←k+1,goto step 1)

As shown in Figures 1 and 2, the multiple access optimal condition under distinguishing based on type of service, the optimal solution that the present invention utilizes projection gradient method to seek to deal with problems (7) as basis, because dual equation D is (λ _j, μ, v _i, ω _i) be protruding, the method for gradient type can remove to upgrade D (λ according to the appropriate direction of search _j, μ, v _i, ω _i) and obtain D (λ simultaneously _j, μ, v _i, ω _i) minimum value, thereby guarantee that it converges to optimal solution.In general, D (λ _j, μ, v _i, ω _i) can be not micro-, its gradient does not exist.

The present invention, in order to make overall system capacity maximize in multiple access allocation of radio resources problem, has also proposed a distributed decision making mode, and its complexity is the common function determining of iteration step length and initial value.Although (7) can go out convergency value by centralized Optimization Method, and can guarantee not have loss of signal, but the present invention or the first-selected distributed optimization method of using, so that each MMT does decision-making under correct synchronous renewal operation, be applied in the wireless connections between each terminal and different Access Network.

Claims (4)

1. the optimization Radio Resource method based on time delay differentiated service and proportionality rate constraint, is characterized in that, described method comprises the steps:

Step 1: suppose in LTE-WLAN heterogeneous network, exist M support different service types enliven multimode terminal and the available wireless access technology of N kind; In LTE network, suppose that the wireless channel between base station and terminal is the rayleigh fading channel that frequency is selected, the channel of each subcarrier is narrower, so it is flat fading; r _inbe illustrated in each OFDM symbol time interval, the transfer rate that user i obtains based on subcarrier n, its value depends on channel gain h _inwith the power P of user i based on distributing on subcarrier n _in; r _inconventionally be represented as

$r_{\mathrm{in}}={\mathrm{\β}}_0{B}_0{\log }_2(1+\frac{P_{\mathrm{in}}{\left|h_{\mathrm{in}}\right|}^2}{\mathrm{\Γ}{N}_0{B}_0})$

Wherein, N ₀be the power spectral density of additive white Gaussian noise, Γ is a constant, is known as signal to noise ratio interval; In the WLAN of 802.11 agreements, user accesses WLAN in the mode of TDMA; All power delivery are all supposed, user i is represented as r in j WLAN _ij, equally in above formula, r _ijbe represented as

$r_{\mathrm{ij}}={\mathrm{\β}}_j{B}_j{\log }_2(1+\frac{P_{\mathrm{ij}}{\left|h_{\mathrm{ij}}\right|}^2}{\mathrm{\Γ}{N}_0{B}_j})$

Wherein, the spectrum efficiency of provided subsystem is provided β, i.e. the validity of each subsystem;

Step 2: the difference requiring according to service delay, M MMT can be divided into two types: first kind DC type MMT, quantity is K, the minimum transmission rate request of its business is

(i=1,2 ..., K); Second Type has (M-K) individual BE type MMT, although there is no delay constraint, in the mode of doing one's best, carries out transfer of data, and transmission rate is subject to the constraint of proportionality fair play

The condition of DC type MMT and BE type MMT is expressed as:

$r_i\≥R_i^{\min },i=\mathrm{1,2},\·\·\·,K,$

r _K+1:r _k+2:...:r _M＝γ _K+1:γ _K+2:...:γ _M；

Step 3: under user's proportionality rate constraint, calculate all users' the total speed of maximum:

$\mathrm{Max}\underset{i=1}{\overset{M}{\mathrm{\Σ}}}{R}_i$

$\begin{array}{cc}\mathrm{subject\; to}& \underset{j=0}{\overset{L}{\mathrm{\Σ}}}{\mathrm{\α}}_{\mathrm{ij}}\≤1,\∀i,{\mathrm{\α}}_{\mathrm{ij}}\∈\left\{\mathrm{0,1}\right\},\∀i,j\end{array}$

$\underset{i=1}{\overset{M}{\mathrm{\Σ}}}{f}_{\mathrm{in}}\≤1,\∀n,f_{\mathrm{in}}\∈\left\{\mathrm{0,1}\right\},\∀i,n$

$\underset{i=1}{\overset{M}{\mathrm{\Σ}}}{t}_{\mathrm{ij}}\≤1,\∀j,0\≤t_{\mathrm{ij}}\≤1,\∀j,i$

$R_i=\underset{n=1}{\overset{N}{\mathrm{\Σ}}}{f}_{\mathrm{in}}{r}_{0\mathrm{in}}+\underset{j=1}{\overset{L}{\mathrm{\Σ}}}{t}_{\mathrm{ij}}{r}_{\mathrm{ij}}$

$R_i\≥R_i^{\min },\∀i=\mathrm{1,2},\·\·\·,K$

$\frac{R_i}{{\mathrm{\γ}}_i}=\frac{R_{k+1}}{{\mathrm{\γ}}_{k+1}},\∀i\∈k+1,k+2,\·\·\·,M;$

Step 4: definition ρ _ijrepresent the time frame allocation of parameters of user i in network j (wherein 1≤j≤N refers to LTE network, and N+1≤j≤N+L refers to j WLAN), and introduced a variable s _ij, make s _ij=ρ _ijp _ij, definition α _ij=| h _ij| ²/ Γ _kn ₀b _j, and by time frame allocation of parameters ρ _ij, can be by R _ibe rewritten as

constraints is rewritten as

$R_i\≥R_i^{\min },\∀i=\mathrm{1,2},\·\·\·,K$

$\frac{R_i}{{\mathrm{\γ}}_i}=\frac{R_{K+1}}{{\mathrm{\γ}}_{K+1}},\∀i\∈K+1,K+2,\·\·\·,M$

$\underset{i=1}{\overset{M}{\mathrm{\Σ}}}\underset{j=1}{\overset{N+L}{\mathrm{\Σ}}}{s}_{\mathrm{ji}}=P_T$

$\underset{i=1}{\overset{M}{\mathrm{\Σ}}}{\mathrm{\ρ}}_{\mathrm{ij}}=1,\∀j$

$s_{\mathrm{ij}}\≥\mathrm{0,0}\≤{\mathrm{\ρ}}_{\mathrm{ij}}\≤1,\∀i,j;$

Step 5: utilize the Lagrangian of primal problem to s _ijask partial differential, then result is updated in Caro need-Ku En-Plutarch (Karush-Kuhn-Tucker, KKT) condition, can obtain

Step 6: utilize GRADIENT PROJECTION METHODS, the optimum performance response that obtains bandwidth is and the conclusion in step 5 obtains s _ij;

Step 7: consider the continuous differential expression of the dual function of primal problem, utilize gradient projection method to upgrade the non-negative Lagrange multiplier of optimization aim function, obtain suitable ρ _ijand s _ijafter, obtain the optimization solution of target function.

2. a kind of optimization Radio Resource method based on time delay differentiated service and proportionality rate constraint according to claim 1, is characterized in that: described method comprises sets up LTE-WLAN heterogeneous network system model.

3. a kind of optimization Radio Resource method based on time delay differentiated service and proportionality rate constraint according to claim 1, is characterized in that, described method is by delineation of activities, to be from physical layer: delay constraint type business and the type business of doing one's best.

4. a kind of optimization Radio Resource method based on time delay differentiated service and proportionality rate constraint according to claim 3, it is characterized in that, described method is to utilize business to carry out differentiated service type to the different demands of Qos, introduce timesharing shared variable, multistep checking result of calculation, is applied to the result after comprehensive in resource distribution.

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