CN103259586A - Multi-hop cooperation relay beam forming method based on genetic algorithm - Google Patents

Abstract

Aimed at the problem that forming and optimization effects are poor when an existing three-hop cooperation relay beam is formed, the invention provides a method for realizing joint optimization of beam forming weight vectors in two relay groups based on a genetic algorithm. According to a multi-hop cooperation relay beam forming method based on the genetic algorithm, a received signal to noise ratio of a destination node is maximized on the premise that the total power of a relay node meets certain constraints. The optimizing problem is multi-vectorial and is difficult to realize through a common method. The multi-hop cooperation relay beam forming method based on the genetic algorithm discovers the internal relation between two vectors, the original problem is converted into the problem containing the beam forming weight vector of the first relay group, and further the two groups of globally optimum beam forming weight vectors are obtained through the genetic algorithm.

Description

A kind of multi-hop cooperating relay beam-forming method based on genetic algorithm

Technical field

The invention discloses and a kind ofly jump the beam forming technique of many junction networks based on three of genetic algorithm, belong to that signal is handled, wireless communication technology field.

Background technology

The application of wireless communication technology presents the situation of explosive growth in recent years, and people are also more and more higher to the requirement that the communication quality of radio communication and user experience.Under the limited background of frequency spectrum resource, multiple-input and multiple-output (MIMO) technology is arisen at the historic moment, and it can improve power system capacity and the availability of frequency spectrum effectively.In recent years, comprise that diversity technology such as space, time, frequency, coding are widely studied.Yet the MIMO Technology Need is settled many antennas in terminal, is subjected to the constraint of volume and power, uses the MIMO technology very difficult at portable equipment.

For effectively overcoming the above problems, a kind of technology that is called collaboration communication more and more is subject to people's attention.In fact, because wireless channel has the characteristic of broadcasting, we can be considered as the contiguous node in geographical position the set of spaced antenna, and therefore, the node that these in the radio communication close on can be by working in coordination to transmit signal.For the signal sending node, a cooperative node can be regarded a via node as.The collaboration communication technology can form virtual MIMO link between communication node.The communication technology based on user collaboration is exactly " collaboration communication ".In collaboration communication, the user can be used as via node, forms the multiple transmission link from the signal sending node to destination node, can realize the diversity gain identical with mimo system.The multiple cooperative communication strategy is studied widely, for example amplifies and transmits, deciphers and transmit, encode and transmit, select relaying etc.In above cooperative communication strategy and since amplify to transmit have realize simple, the less advantage of delaying time and being paid attention to by people.The collaboration communication model of the present invention's research also will adopt the mode of transmitting of amplifying.

The junction waves beam shaping model of double bounce is mainly tended in previous research, and in the middle of the radio communication of reality, the three relaying models of jumping also are more common, and with respect to the junction waves beam shaping model of double bounce, the three network model coverages of jumping are wider.Jump in the junction network three, comprise two via node groups, the corresponding junction waves beam shaping weight vector of each group.In order to improve communication quality, satisfy at via node under the condition of certain power constraint, the received signal to noise ratio of maximization destination node is a very significant job.Ceng You researcher was approximately the positive semidefinite problem with the problems referred to above in the past, try to achieve nearly excellent wave beam shaping weight vector with protruding optimization tool then, yet this method was absorbed in local optimum easily, and effect is not ideal enough.

Summary of the invention

The object of the present invention is to provide a kind of optimized beam-forming method at the many junction networks of three jumpings based on genetic algorithm, satisfy at via node power under the prerequisite of certain constraint, two groups of via node wave beam shaping weight vectors are carried out combined optimization, make the received signal to noise ratio maximization of destination node.In this method, based on to first group of via node with the research that concerns between wave beam shaping weight vector w and the second group of via node wave beam shaping weight vector v, one of them vector is come out with another vector representation, use genetic algorithm to realize then fully, can realize globally optimal solution.

Technical solution of the present invention is as follows:

A kind of relaying cooperative beam manufacturing process based on genetic algorithm, this method is jumped many relayings cooperation communication system based on three, this system is made up of a source node, two groups of via node groups and a destination node, and all nodes in the network all only are equipped with single antenna, because the influence of channel fading, between source node and the destination node, between source node and the second group of via node group, all can't directly set up communication link between first group of via node group and the destination node, sending node need by two via node groups set up with destination node between communicate by letter; The number that participates in the via node of collaboration communication is known, and the channel parameter of whole network model can obtain by channel estimating; In communication process, source node is to first group of via node broadcast singal, noise on the first channel aliasing of jumping, first group of via node is weighted to the received signal with wave beam shaping weight vector w, broadcast to second group of via node through second hop channel with amplifying the mode of transmitting then, after second group of via node receives signal, be weighted with another wave beam shaping weight vector v to received signal, send signal to amplify the mode of transmitting to destination node then, this signal receives at the destination node place by after the noise on the 3rd channel aliasing of jumping;

All satisfy at every group of via node under the prerequisite of certain power constraint, two groups of via node wave beam shaping weight vectors are carried out combined optimization, thereby improve the received signal to noise ratio of destination node, in concrete the enforcement, based on first group of via node with the relation between wave beam shaping weight vector w and the second group of via node wave beam shaping weight vector v, second group of via node wave beam shaping weight vector v showed with wave beam shaping weight vector w with first group of via node, the multivariable optimization problem is converted into the unitary variant optimization problem that only comprises a wave beam shaping weight vector, use genetic algorithm to realize that concrete steps are as follows then fully:

Step 1, setting first group and second group of via node power constraint separately, by channel estimating, the parameter that obtains first, second and third hop channel is respectively f, H, g;

The population of the wave beam shaping weight vector w of step 2, first group of via node of initialization, this population must be in the feasible zone of being determined by the power constraint of first group of via node, for the w that satisfies first group of via node power constraint arbitrarily, optimized second group of via node wave beam shaping weight vector v shows with w, calculate the corresponding target function value of each w in the current population, i.e. the received signal to noise ratio of destination node;

Step 3, according to above-mentioned a series of target function values, use genetic algorithm, generate the new population of w, calculate the corresponding target function value of each w in this population, and select wherein maximum target function value;

Step 4, judge whether the target function value of current maximum satisfies iterated conditional, if satisfy then repeating step three, then do not carry out step 5 if do not satisfy;

Make the w of target function maximum in step 5, the output population, and calculate corresponding optimized v, be two wave beam shaping weight vectors asking.

Preferably, first group of via node with the pass between wave beam shaping weight vector w and the second group of via node wave beam shaping weight vector v is

P wherein _RThe power constraint of representing second group of via node,

Be respectively first jumping and second and jump the noise power at via node place, Noise power D for the destination node place _RBe diagonal matrix, ${\left[D_R\right]}_{k,k}=\underset{m=1}{\overset{M}{\mathrm{\Σ}}}{\left|h_{k,m}\right|}^2({\left|f_m\right|}^2{P}_s+{\mathrm{\σ}}_T^2){\left|w_m\right|}^2+{\mathrm{\σ}}_R^2,k=\mathrm{1,2},...,K,$ K represents first group of via node number, and M represents second group of via node number.

Preferably, former optimization problem can be expressed as only comprising the unitary variant optimization problem of a wave beam shaping weight vector w, for: $\underset{w}{\max }\frac{w^H{R}_{w}w}{w^H{Q}_{w}w+{\mathrm{\σ}}_R^2{\left|\right|v^{H}g\left|\right|}^2+{\mathrm{\σ}}_T^2}$

Make

Wherein

Be diagonal matrix,

R _w=P _sF ^HH ^HG ^HVv ^HGHF, F=diag (f), G=diag (g), Q _w=H ^HG ^HVv ^HGH, $v=\sqrt{P_R}{D}_R^{-1}{(D_R^{-1/2}{Q}_v{D}_R^{-1/2}+{\mathrm{\σ}}_D^{2}I)}^{-1}{D}_R^{-1/2}\mathrm{GHw},$ I representation unit matrix, P _SExpression source node transmitted power.

Description of drawings

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

Fig. 2: the workflow diagram of this method;

Fig. 3: simulation result figure.

Embodiment

At existing three problems of jumping the poor effect that the optimizations of many junction waves beam shaping face, the present invention proposes a kind of combined optimization method of two groups of trunk group wave beams of the realization shaping weight vector based on genetic algorithm.This combined optimization problem is multidirectional amount, be difficult to realize by common method, the present invention has found the inner link between two vectors, and original problem is changed into the problem of unidirectional amount, and then uses genetic algorithm to try to achieve the wave beam shaping weight vector that can be considered global optimum.

Below in conjunction with drawings and Examples the present invention is further detailed, but is not limited thereto example.

Consider one based on three many relayings of the jumping cooperation communication systems that amplify forwarding mechanism, as shown in Figure 1, this system is by a source node (S), and two groups of via node groups and a destination node (D) are formed, and all nodes in the network all assemble single antenna.Suppose between source node and the destination node, between source node and the second group of via node group, all can't set up direct communication link between first group of trunk group and the destination node.Therefore, source node need be set up and the communicating by letter of destination node by two via node groups.Transmitted power is P _S, the number that participates in the via node of collaboration communication is known, and wherein first group of via node group comprises M=4 or M=6 via node, and second group comprises K=4 or K=6 via node, remembers that the first hop channel parameter is f=[f ₁, f ₂..., f _M] ^T, the second hop channel parameter matrix is H, the 3rd hop channel parameter is g=[g ₁, g ₂..., g _K] ^TThe first jumping via node wave beam shaping weight vector is w=[w ₁, w ₂..., w _M] ^T, the second jumping via node wave beam shaping weight vector is v=[v ₁, v ₂..., v _K] ^TAll noises are the stable Gaussian white noise, and first noise power of jumping the via node place is Second noise power of jumping the via node place is

The noise power at destination node place is

We use these two via node groups' of genetic Algorithm Design complex weighting vector, via node power are satisfied under the prerequisite of certain constraint, the maximization of destination node place received signal to noise ratio.

As Fig. 2, this method step is as follows:

Step 1, setting first are jumped and second power constraint of jumping is respectively P _TAnd P _R, utilize channel estimating, obtain f, H, g,

Step 2, initialization t=0, t represents iterations, and P (t) expression t is for the population of wave beam shaping weight vector w, and the population of the wave beam shaping weight vector w of first group of via node of initialization is P (0),

S represents the feasible zone of w, this feasible zone is determined by the power constraint of first group of via node, for the w that satisfies first group of via node power constraint arbitrarily, optimized second group of via node wave beam shaping weight vector v can show with w, and then former optimization problem can be expressed as only comprising the problem of a wave beam shaping weight vector w:

$\underset{w}{\max }\frac{w^H{R}_{w}w}{w^H{Q}_{w}w+{\mathrm{\σ}}_R^2{\left|\right|v^{H}g\left|\right|}^2+{\mathrm{\σ}}_D^2}$

Make

Wherein

Be diagonal matrix,

R _w=P _sF ^HH ^HG ^HVv ^HGHF, F=diag (f), G=diag (g), Q _w=H ^HG ^HVv ^HGH, $v=\sqrt{P_R}{D}_R^{-1}{(D_R^{-1/2}{Q}_v{D}_R^{-1/2}+{\mathrm{\σ}}_D^{2}I)}^{-1}{D}_R^{-1/2}\mathrm{GHw},$ I representation unit matrix, D _RAlso be diagonal matrix, ${\left[D_R\right]}_{k,k}=\underset{m=1}{\overset{M}{\mathrm{\Σ}}}{\left|h_{k,m}\right|}^2({\left|f_m\right|}^2{P}_s+{\mathrm{\σ}}_T^2){\left|w_m\right|}^2+{\mathrm{\σ}}_R^2,k=\mathrm{1,2},...,K,$

Calculate the corresponding target function value of each w (received signal to noise ratio of destination node) among the current population P (0), wherein Zui Da target function value is expressed as m (0);

Step 3, the value of t is updated to t+1 according to the corresponding a series of target function values of P (t-1), use genetic algorithm, generate the new population P (t) of w, calculate the corresponding target function value of each w in this population, and select wherein maximum target function value m (t).

Step 4, judge whether the target function value of current maximum satisfies iterated conditional

Make ε=0.0001, if satisfy then repeating step three, then do not carry out step 5 if do not satisfy;

Make the w of target function value maximum in step 5, the output population, and the output correspondence is optimized $v=\sqrt{P_R}{D}_R^{-1}{(D_R^{-1/2}{Q}_v{D}_R^{-1/2}+{\mathrm{\σ}}_D^{2}I)}^{-1}{D}_R^{-1/2}\mathrm{GHw},$ Be two wave beam shaping weight vectors asking.Shown in accompanying drawing 3, the signal to noise ratio of accepting that method of the present invention realizes than additive method is significantly improved, because genetic algorithm is not easy to be absorbed in local optimum, so this method can be considered global optimum.

As shown in Figure 3, compare with existent method, method of the present invention satisfies at via node under the prerequisite of certain power constraint, and attainable reception Signal to Interference plus Noise Ratio is bigger, and communication quality is better.

Claims (3)

1. relaying cooperative beam manufacturing process based on genetic algorithm, this method is jumped many relayings cooperation communication system based on three, this system is made up of a source node, two groups of via node groups and a destination node, and all nodes in the network all only are equipped with single antenna, because the influence of channel fading, between source node and the destination node, between source node and the second group of via node group, all can't directly set up communication link between first group of via node group and the destination node, sending node need by two via node groups set up with destination node between communicate by letter; The number that participates in the via node of collaboration communication is known, and the channel parameter of whole network model can obtain by channel estimating; In communication process, source node is to first group of via node broadcast singal, noise on the first channel aliasing of jumping, first group of via node is weighted to the received signal with wave beam shaping weight vector w, broadcast to second group of via node through second hop channel with amplifying the mode of transmitting then, after second group of via node receives signal, be weighted with another wave beam shaping weight vector v to received signal, send signal to amplify the mode of transmitting to destination node then, this signal receives at the destination node place by after the noise on the 3rd channel aliasing of jumping;

All satisfy at every group of via node under the prerequisite of certain power constraint, two groups of via node wave beam shaping weight vectors are carried out combined optimization, thereby improve the received signal to noise ratio of destination node, in concrete the enforcement, based on first group of via node with the relation between wave beam shaping weight vector w and the second group of via node wave beam shaping weight vector v, second group of via node wave beam shaping weight vector v showed with wave beam shaping weight vector w with first group of via node, the multivariable optimization problem is converted into the unitary variant optimization problem that only comprises a wave beam shaping weight vector, use genetic algorithm to realize that concrete steps are as follows then fully:

Step 1, setting first group and second group of via node power constraint separately, by channel estimating, the parameter that obtains first, second and third hop channel is respectively f, H, g;

The population of the wave beam shaping weight vector w of step 2, first group of via node of initialization, this population must be in the feasible zone of being determined by the power constraint of first group of via node, for the w that satisfies first group of via node power constraint arbitrarily, optimized second group of via node wave beam shaping weight vector v shows with w, calculate the corresponding target function value of each w in the current population, i.e. the received signal to noise ratio of destination node;

Step 3, according to above-mentioned a series of target function values, use genetic algorithm, generate the new population of w, calculate the corresponding target function value of each w in this population, and select wherein maximum target function value;

Step 4, judge whether the target function value of current maximum satisfies iterated conditional, if satisfy then repeating step three, then do not carry out step 5 if do not satisfy;

Make the w of target function maximum in step 5, the output population, and calculate corresponding optimized v, be two wave beam shaping weight vectors asking.

2. the relaying cooperative beam manufacturing process based on genetic algorithm as claimed in claim 1 is characterized in that: first group of via node with the pass between wave beam shaping weight vector w and the second group of via node wave beam shaping weight vector v is $v=\sqrt{P_R}{D}_R^{-1}{(D_R^{-1/2}{Q}_v{D}_R^{-1/2}+{\mathrm{\σ}}_D^{2}I)}^{-1}{D}_R^{-1/2}\mathrm{GHw},$ P wherein _RThe power constraint of representing second group of via node,

Be respectively first jumping and second and jump the noise power at via node place,

Noise power D for the destination node place _RBe diagonal matrix,

K=1,2 ..., K, K represent first group of via node number, M represents second group of via node number.

3. the relaying cooperative beam manufacturing process based on genetic algorithm as claimed in claim 1, former optimization problem can be expressed as only comprising the unitary variant optimization problem of a wave beam shaping weight vector w, for:

$\underset{w}{\max }\frac{w^H{R}_{w}w}{w^H{Q}_{w}w+{\mathrm{\σ}}_R^2{\left|\right|v^{H}g\left|\right|}^2+{\mathrm{\σ}}_T^2}$

Make w ^HD _TW≤P _T,

Wherein

Be diagonal matrix,

, R _w=P _sF ^HH ^HG ^HVv ^HGHF, F=diag (f), G=diag (g), Q _w=H ^HG ^HVv ^HGH, $v=\sqrt{P_R}{D}_R^{-1}{(D_R^{-1/2}{Q}_v{D}_R^{-1/2}+{\mathrm{\σ}}_D^{2}I)}^{-1}{D}_R^{-1/2}\mathrm{GHw},$ I representation unit matrix,

P _SExpression source node transmitted power.

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