CN103269242B - A kind of uplink coordinated junction waves beam forming method based on convex optimization - Google Patents

Abstract

The cooperation communication system of the Multi-source multi-relay of multiple antennas is had for base station apparatus, the present invention proposes the technical scheme of a kind of via node beamforming weight vectors and base station end linear equalization vector combined optimization, in the hope of be not less than certain threshold value at base station received signal to noise ratio prerequisite under, make via node place minimise power consumption.Two vectors to be optimized are comprised in this optimization problem.First optimized linear equalization vector represents with via node beamforming vectors by the present invention, and then two vectorial combined optimization problems are converted into the optimization problem only comprising via node beamforming weight vectors, convex optimization is used first to try to achieve optimized beamforming weight vectors, and then according to the relation between two vectors, try to achieve optimized base station linear equalization vector, realize via node minimum power.

Description

A kind of uplink coordinated junction waves beam forming method based on convex optimization

Technical field

The invention discloses a kind of uplink coordinated beam-forming method of the Multi-source multi-relay based on convex optimization, the method belongs to radio communication, signal processing technology field.

Background technology

In the past few decades, wireless communication technology obtains significant progress, and people are also unprecedentedly surging to the demand enjoying unlimited enjoyment whenever and wherever possible.Mobile communication terminal enters into huge numbers of families, mobile communication has not been the synonym of simple voice transfer, it has become the important channel of multimedia transmission, this data rate to radio communication, reliability, spectrum efficiency are proposed higher requirement, and multiple-input and multiple-output (MIMO) system has just entered into the visual field of people under such application background.

Mimo system no doubt has the advantage of its spectral efficient and high reliability, but uses this technology to need at mobile terminal configuration multiple antennas in mobile communications, and this is infeasible for the terminal of volume and power limited.In recent years, collaboration communication obtains the concern of people, and this technology is a kind of distributed diversity antenna technology, and the single antenna that mobile subscriber can share oneself forms a virtual aerial array, and then obtains multiplexing and diversity gain by distributed signal process.

In cooperating relay Wave-packet shaping network model in the past, each node is assemble single antenna mostly, and the present invention is then the situation of considering to assemble in destination node (base station end) multiple antennas.In the model, multiple user can transmit independently data flow by junction network to multi-antenna base station simultaneously.Carry out equilibrium treatment with a weighing vector after base station end receives signal, effectively can reduce the interference between different user, improve the Signal to Interference plus Noise Ratio of receiving terminal.For this model, method in the past mainly uses the method for convex optimization by iteration, maximizes Signal to Interference plus Noise Ratio, improve systematic function, but this method computation complexity is high and be easily absorbed in local optimum.

Summary of the invention

The present invention proposes a kind of new beam-forming method in Multi-source multi-relay collaborative network, namely be not less than the prerequisite of set-point at receiving terminal Signal to Interference plus Noise Ratio under, vectorial by the linear equalization of combined optimization via node beamforming weight vectors and base station end, minimize via node power.And, based on the research to relation between relaying node beam shaping weight vector and the linear equalization vector of base station end, optimized for base station linear equalization vector is represented by beamforming weight vectors enclosed, thus the many Conditions of Vector Optimization Problem relating to via node beamforming weight vectors and base station linear equalization vector are converted into the optimization problem only having beamforming weight vectors, and then corresponding optimized linear equalization vector can be tried to achieve.The method only with once convex optimization realization, avoids iteration, and therefore, compared with the prior art, computation complexity reduces and better effects if this technology, meets the current requirement energy-conservation to green communications.

Technical solution of the present invention is as follows:

A kind of uplink coordinated junction network beam-forming method based on convex optimization, the method is based on a Multi-source multi-relay and the cooperation communication system of base station end device multiple antennas, this system is made up of the source node of multiple device single antenna, the via node of multiple device single antenna, the base station of a device multiple antennas, due to the impact of channel fading, cannot set up direct communication link between source node and multi-antenna base station, source node needs to set up communication between base station by via node network;

In communication process, multiple user and source node are simultaneously to relay node broadcasts signal, these signals are on the first hop channel aliasing after noise, be broadcast to via node group, via node is weighted with beamforming weight vectors to the received signal, then by the mode of amplification forwarding noise to multi-antenna base station broadcast singal and on the second hop channel aliasing, after multi-antenna base station receives signal, be weighted by linear equalization weight vector;

Under multi-antenna base station end received signal to noise ratio is not less than the prerequisite of set-point, make the minimise power consumption that via node is total, in concrete enforcement, optimized for base station linear equalization vector is represented by beamforming weight vectors enclosed, thus be converted into relating to above-mentioned two vectorial many Conditions of Vector Optimization Problem the optimization problem only having beamforming weight vectors, try to achieve corresponding optimized linear equalization vector after trying to achieve optimized beamforming weight vectors again, concrete steps are as follows:

The threshold value γ of step one, setting multi-antenna base station end received signal to noise ratio _k> 0 (k=1,2 ..., K), make received signal to noise ratio be not less than this threshold value;

Step 2, by channel estimating, obtain channel parameter f _k=[f _{1, k}, f _{2, k}..., f _m,k] (k=1,2 ..., K), H, determining step one select threshold value whether meet wherein p _kthe transmitted power of a kth source node, i representation unit matrix, all noises are all white Gaussian noises, and at via node place, noise power is if do not meet, get back to step one and choose less threshold value, if meet, enter step 3;

Step 3,

Use convex optimization tool, try to achieve the value of optimized w, wherein, in base station noise power be (k=1,2 ..., K), D is diagonal matrix, and wherein the element of the capable m row of m is ${\left[D\right]}_{m,m}=p_k\underset{k=1}{\overset{K}{\mathrm{\Σ}}}{\left|f_{m,k}\right|}^2+{\mathrm{\σ}}_r^2,$ | f _m,k| represent f _m,kask mould;

Step 4, the w value calculated according to step 3, calculate $g_k={({\mathrm{HW}}^H{Q}_k{\mathrm{WH}}^H+{\mathrm{\σ}}_d^{2}I)}^{-1}{\mathrm{HW}}^H{f}_k,\∀k;$

Step 5, output w and g, and set via node and base station linear equalizer respectively with it, the via node power consumption global minimization of this system can be realized.

Accompanying drawing explanation

Fig. 1: system model figure of the present invention;

Fig. 2: the workflow diagram of this method;

Fig. 3: analogous diagram.

Embodiment

For Multi-source multi-relay and the cooperation communication system of base station end device multiple antennas, the present invention proposes a kind of combined optimization method using convex optimization to realize via node place beamforming weight vectors and base station linear equalization vector, object is when received signal to noise ratio meets set-point, makes via node minimum power.The former problem of this combined optimization is non-convex, multidirectional amount, the present invention, by the contact between excavation two vectors, makes it be converted into the problem only having via node beamforming weight vectors to optimize, use convex optimization to try to achieve this vector, and then corresponding optimized linear equalization vector can be tried to achieve.

Below in conjunction with specific embodiment (but being not limited thereto example) and accompanying drawing, the present invention is further detailed.

As shown in Figure 1, consider a Multi-source multi-relay based on amplification forwarding mechanism and the cooperation communication system of base station end device multiple antennas, this system is by the source node (S) of multiple device single antenna, the via node (R) of multiple device single antenna, base station (D) composition of a device multiple antennas.Due to the decline of signal, cannot set up direct communication link between source node and base station, therefore, source node needs to set up communication between base station by via node network.Suppose that this system comprises K=3 or K=4 source node, M=8 or M=12 via node, base station apparatus has N=8 or N=12 root antenna, and the transmitted power of a kth source node is p _k, a kth source node is f to the channel parameter of m via node _k,m, the second hop channel parameter matrix is H, and all noises are all stationary white Gaussian noise, and at via node place, noise power is in base station noise power be via node weight vector is w=[w ₁, w ₂..., w _m] ^t, base station end linear equalization matrix is G=[g ₁, g ₂..., g _n].

As shown in Figure 2, the method step is as follows:

The threshold value γ of step one, setting multi-antenna base station end received signal to noise ratio _k> 0 (k=1,2 ..., K), make received signal to noise ratio be not less than this threshold value;

Step 2, by channel estimating, obtain channel parameter f _k=[f _{1, k}, f _{2, k}..., f _m,k] (k=1,2 ..., K), H, all noises are all white Gaussian noises, noise power , be all 1dBw.Whether the threshold value that determining step one is selected meets wherein i representation unit matrix.If do not meet, get back to step one and choose less threshold value, if meet, enter step 3;

Step 3, former problem can be expressed as

According to Cauchy-Schwarz inequality, the problems referred to above can change into:

And it is now, optimized $g_k=\mathrm{\ρ}\left\{{({\mathrm{HW}}^H{Q}_k{\mathrm{WH}}^H+R_d)}^{-1}{\mathrm{HW}}^H{f}_k{f}_k^H{\mathrm{WH}}^H\right\},\∀k.$ The maximal eigenvector of ρ (.) representing matrix, due to order be 1, so base station optimized linear equalization vector can be expressed as the form of closed solutions: namely base station optimized linear equalization vector g available beams shaping weight vector w enclosed represents.And then former problem uses the definition of matrix inversion theorem and positive semidefinite matrix, can be converted into:

Use convex optimization tool, try to achieve the value of optimized w, wherein W=diag (w),

(k=1,2 ..., K), D is diagonal matrix, and wherein the element of the capable m row of m is ${\left[D\right]}_{m,m}=p_k\underset{k=1}{\overset{K}{\mathrm{\Σ}}}{\left|f_{m,k}\right|}^2+{\mathrm{\σ}}_r^2,$ (m＝1,...,M)；

Step 4, the w value calculated according to step 3, calculate $g_k={({\mathrm{HW}}^H{Q}_k{\mathrm{WH}}^H+{\mathrm{\σ}}_d^{2}I)}^{-1}{\mathrm{HW}}^H{f}_k,\∀k.$

Step 5, export optimized via node beamforming weight vectors w and base station end linear equalization vector g, and set via node and base station linear equalizer respectively with it, this system can be realized when received signal to noise ratio is not less than certain threshold value, make via node minimise power consumption.The method overcoming iteration in the past uses convex optimization method to be easily absorbed in the shortcoming of local optimum, and computation complexity also decreases simultaneously, meets the requirement to real-time in radio communication.As shown in Figure 3, compared with existing method, method of the present invention is under the prerequisite meeting identical Signal to Interference plus Noise Ratio, and required power consumption is lower, more meets the requirement that green communications are energy-conservation.

Claims (1)

1. the uplink coordinated junction network beam-forming method based on convex optimization, the method is based on a Multi-source multi-relay and the cooperation communication system of base station end device multiple antennas, this system is made up of the source node of multiple device single antenna, the via node of multiple device single antenna, the base station of a device multiple antennas, due to the impact of channel fading, cannot set up direct communication link between source node and multi-antenna base station, source node needs to set up communication between base station by via node network;

In communication process, multiple user and source node are simultaneously to relay node broadcasts signal, these signals are on the first hop channel aliasing after noise, be broadcast to via node group, via node is weighted with beamforming weight vectors to the received signal, then by the mode of amplification forwarding noise to multi-antenna base station broadcast singal and on the second hop channel aliasing, after multi-antenna base station receives signal, be weighted by linear equalization weight vector;

Under multi-antenna base station end received signal to noise ratio is not less than the prerequisite of set-point, make the minimise power consumption that via node is total, in concrete enforcement, optimized for base station linear equalization vector is represented by beamforming weight vectors enclosed, thus be converted into relating to above-mentioned two vectorial many Conditions of Vector Optimization Problem the optimization problem only having beamforming weight vectors, try to achieve corresponding optimized linear equalization vector after trying to achieve optimized beamforming weight vectors again, concrete steps are as follows:

The threshold value γ of step one, setting multi-antenna base station end received signal to noise ratio _k> 0 (k=1,2 ..., K), wherein K is expressed as the number of source node, makes received signal to noise ratio be not less than this threshold value;

Step 2, by channel estimating, obtain channel parameter f _k=[f _{1, k}, f _{2, k}..., f _m,k] (k=1,2 ..., K), M is the number of via node, the second hop channel parameter matrix is $H=\left[\begin{array}{cccc}{h}_{11},& h_{12}& \mathrm{...}& h_{1N}\\ h_{21},& h_{22}& \mathrm{...}& h_{2N}\\ .& & & \\ .& & & \\ .& & & \\ h_{M1}& h_{M1}& \mathrm{...}& h_{MN}\end{array}\right],$ N is the number of antennas of base station, and whether the threshold value that determining step one is selected meets wherein p _kthe transmitted power of a kth source node, i representation unit matrix, all noises are all white Gaussian noises, and at via node place, noise power is if do not meet, get back to step one and choose less threshold value, if meet, enter step 3;

Step 3,

Wherein w=[w ₁, w ₂..., w _m] ^tfor via node weight vector,

Use convex optimization tool, try to achieve the value of optimized w, wherein W=diag (w), in base station noise power be (k=1,2 ..., K), D is diagonal matrix, and wherein the element of the capable m row of m is ${\[D\]}_{m,m}=p_k\underset{k=1}{\overset{K}{\Σ}}|f_{m,k}{|}^2+{\mathrm{\σ}}_r^2,$ | f _m,k| represent f _m,kask mould;

Step 4, according to step 3 calculate w value, in the linear balanced matrix of calculation base station correspondence $g_k={({\mathrm{HW}}^H{Q}_k{\mathrm{WH}}^H+{\mathrm{\σ}}_d^{2}I)}^{-1}{\mathrm{HW}}^H{f}_k,\∀k;$

Each vectorial g of linear equalization matrix of step 5, output w and base station end, and set via node and base station linear equalizer respectively with it, the via node power consumption global minimization of this system can be realized.