CN105554790A - Energy efficiency optimization method in asymmetric bidirectional relay system - Google Patents

Abstract

The invention discloses an energy efficiency optimization method in an asymmetric bidirectional relay system. The method mainly solves the problem that the existing optimum power distribution method is low in energy efficiency. The technical solution comprises: obtaining the summation rate of two user devices in the asymmetric bidirectional relay system; proposing an initial optimization problem taking the maximum energy efficiency as a target; rewriting the initial optimization problem into a secondary optimization problem according to the rates of the two user devices; converting the secondary optimization problem into an inner layer optimization problem and an outer layer optimization problem, obtaining the optimum solutions of the inner layer and outer layer optimization problems; finally, obtaining the optimum power distribution of the two user devices and the relay according to the optimum solutions of the inner layer and outer layer optimization problems. According to the invention, an existing circuit consumption power model is completed; the energy efficiency optimization method is low in calculation complexity and simple in realization and can be applicable to data transmission in the asymmetric bidirectional relay system.

Description

Energy efficiency optimization method in asymmetric bidirectional relay system

Technical field

The invention belongs to mobile communication system technical field, particularly related to energy efficiency optimization method in one, can be used for asymmetric bidirectional relay system.

Background technology

Along with the rise gradually of mobile Internet, Internet of Things, the Mobile data flow of explosive growth and the equipment connection of magnanimity causes energy consumption cost constantly to rise, biological environment goes from bad to worse, green communications technology receives much concern therefrom.As the green index weighing communication system energy consumption, energy efficiency becomes current study hotspot.In order to overcome traditional relaying technique time slot waste, spectrum imitates low defect, and bidirectional relay channel TWRC is introduced into.In TWRC system, two terminal nodes realize data interaction by relaying, when via node only does amplification forwarding AF process to the signal received, two terminals can be realized the mutual timeslot number of primary information and be reduced to 2 by 4 of traditional relaying, significantly improve spectrum efficiency.

Current, in bidirectional relay system, the energy that antenna consumes when sending data is considered emphatically in the research of efficiency optimization aspect, and achieves some scientific achievements.To maximize efficiency for target, HuangR etc. are at WirelessCommunicationsandNetworkingConferenceWorkshops.F RA:IEEE, and the article " EnergyefficientdesigninAFrelaynetworkswithbidirectionala symmetrictraffic " on 2012:7-11 proposes best joint relay selection and the energy-saving scheme of power division.Meeting under user rate demand and transmission power consumption constraint, the link level energy efficiency of distributed beamforming ANC system is optimized in the article on 14thInternationalConferenceonCommunicationTechnology.Chi na:IEEE, 2012:929 – 934 such as LiQ " TradeoffBetweenEnergyEfficiencyAndSpectralEfficiencyInTw o-WayRelayNetwork ".These researchs, it is considered that traditional length is apart from transmitting scene, now send the overwhelming majority that energy accounts for system total power consumption, therefore only considering when setting up total energy consumption model to send energy consumption, ignoring circuit energy consumption.

Along with terminal density increases, the spacing of terminal room reduces gradually, and circuit energy consumption is even greater than transmission energy consumption close to transmission energy consumption, as: at sensing network, total energy consumption model must consider circuit energy consumption.WangT etc. are at IEEETransactionsonCommunications, 2013, in the point-to-point transmitting scene of short distance, circuit energy consumption is considered in article " OntheOptimumEnergyEfficiencyforFlat-fadingChannelswithRa te-dependentCircuitPower " on 61 (12): 4910 – 4921, and circuit energy consumption is modeled as two parts: namely namely static circuit energy consumption depend on the circuit energy consumption of transmission rate independent of the circuit energy consumption of transmission rate, dynamic circuit energy consumption, wherein dynamic circuit energy consumption is the convex increasing function of transmission rate.Existing circuit energy consumption model, as: constant, transmission rate linear function, be its special case.This article proposes efficiency and maximizes lower optimal power contribution scheme, but program consideration is only the transmitting scene of point-to-point straight chain.

In order to meet the different user demand different to transmission rate, realize different application, the consideration for asymmetric transmission rate requirements is indispensable.ZhouM etc. are at IEEECommunicationsLetters, 2012, article " Energy-EfficientRelaySelectionandPowerAllocationforTwo-W ayRelayChannelwithAnalogNetworkCoding " on 16 (6): 816-819 proposes and is meeting under the end-to-end minimum transmission rate condition of asymmetric bidirectional relay system, make always to transmit energy consumption minimum time relay selection strategy and power allocation scheme, although the program considers the transmitting scene of two-way link and asymmetric transmission rate, but do not consider the impact that circuit energy consumption is brought system energy efficiency, and in the short haul scene of reality, because circuit energy consumption accounts for the overwhelming majority of system total power consumption, ignore the efficiency that circuit energy consumption will have a strong impact on communication system, the sharply decline of efficiency also can cause communication link to disconnect.

Summary of the invention

The object of the invention is to the deficiency for above-mentioned prior art, propose the energy efficiency optimization method in a kind of asymmetric bidirectional relay system, to improve the efficiency of communication system, ensure the reliable link of communication link, achieve green communications.

For achieving the above object, technical scheme of the present invention comprises as follows:

(1) obtain two subscriber equipmenies A, B in asymmetric bidirectional relay system with speed R _tot(P):

(1a) the speed R of first user device A is calculated respectively _a(P) the speed R of and the second subscriber equipment B _b(P):

(1b) calculate first user device A and the second subscriber equipment B's and speed:

R _tot(P)＝R _A(P)+R _B(P)，

Wherein, P=[P _a, P _b, P _r] be transmitted power vector, P _a, P _band P _rrepresent the transmitted power of subscriber equipment A, B and relaying R respectively;

(2) the energy efficiency η of asymmetric bidirectional relay system is calculated _eE, and propose to take maximize energy efficiency as the initial optimization problem P1 of target (P):

(2a) according to two subscriber equipmenies A, B with speed R _tot(P), the energy efficiency η of computing system _eE(P)=R _tot(P)/P _tot(P);

Wherein P _tot(P)=(P _a+ P _b+ P _r)/ε+P _cfor the gross power of system, for circuitry consumes power in system, r=[R _a, R _b] be the velocity vectors of two subscriber equipmenies A, B, for the circuitry consumes power of static state, for dynamic circuitry consumes power, and ε ∈ (0,1] be power amplifier efficiency;

(2b) according to the energy efficiency η of system _eE(P), building with maximize energy efficiency is the initial optimization problem P1 of target:

Wherein R _th, _irepresent the minimum transmission rate of subscriber equipment i under unit bandwidth, P _tit is total transmit power threshold of two subscriber equipmenies A, B and relaying R;

(3) according to the speed R of two subscriber equipmenies A, B _aand R (P) _b(P), initial optimization problem P1 is rewritten as double optimization problem P2:

Wherein represent the transmitted power of subscriber equipment B, P _r(r, P _a) represent the transmitted power of relaying R, g _i=| h _i| ², represent total transmitted power of two subscriber equipmenies A, B and relaying R;

(4) double optimization problem P2 is converted into internal layer optimization problem P3_Inner and outer optimization problem P3_Outter:

Determine the independent variable optimization order of double optimization problem P2, namely first optimize the transmitted power P of first user device A _a, then optimize velocity vectors r, then obtain and the second optimization problem P2 be converted into internal layer optimization problem P3_Inner and outer optimization problem P3_Outter:

Wherein, be respectively first user device A, optimum transmit power that the second subscriber equipment B and relaying R is independent variable with velocity vectors r, for the total transmitted power of optimum being independent variable with velocity vectors r;

(5) the optimization objective function value of internal layer optimization problem P3_Inner is obtained

(5a) being the characteristic of convex programming according to internal layer optimization problem P3_Inner, by using Karush-Kuhn-Tucker condition, obtaining the transmitted power optimal solution of first user device A

(5b) will bring the formula P of step (3) respectively into _r(r, P _a), P _b(r, P _a) in, obtain relaying R, the transmitted power optimal solution of the second subscriber equipment B under internal layer optimization problem P3_Inner

(5c) the optimization objective function value of internal layer optimization problem P3_Inner is calculated according to (5a) and (5b) result

(6) the iptimum speed r of system in outer optimization problem P3_Outter is obtained ^*:

(6a) being the characteristic of nonlinear fractional programming according to outer optimization problem P3_Outter, by using nonlinear fractional programming theorem, outer optimization problem P3_Outter being converted into three suboptimization problem P4:

Wherein q is any non-negative parameter;

(6b) for any given non-negative parameter q, by convex optimization method, the optimal rate vector of three suboptimization problem P4 is obtained with optimal objective function value F ^*(q)=min{F (r, q) | r ∈ Ξ }, wherein Ξ represents the rate constraint region of three suboptimization problem P4;

(6c) F is made ^*q ()=0, obtains F ^*q the zero point of () is worth q ^*={ q|F ^*(q)=0}, q ^*be the optimum capacity efficiency value of system;

(6d) by the optimum capacity efficiency value q of system ^*bring optimal rate vector r into ^*in (q), obtain the iptimum speed r of system ^*=r ^*(q ^*);

(7) by the iptimum speed r of system ^*bring the formula of step (5) respectively into with in, obtain the optimal power contribution value of two subscriber equipmenies A, B and relaying R in system respectively with

The present invention compared with prior art has the following advantages:

The first, the circuitry consumes power module that employing of the present invention is relevant to transmission rate, has taken into full account short haul scene, and is not limited to long apart from transmitting scene, therefore applies more extensive in practical communication environment.

Second, the optimal power allocation method that the present invention proposes is compared with the optimal power contribution method ignoring circuit energy consumption with traditional constant power distribution method, the energy efficiency of system can be made maximum, effectively reduce the energy needed for unit data transfer, achieve green communications.

3rd, optimal power allocation method proposed by the invention, for common asymmetric communication business, ensure that the business demand of the asymmetric transmission rate of uplink downlink, therefore more realistic application.

Accompanying drawing explanation

Fig. 1 is the asymmetric bidirectional relay system illustraton of model that the present invention uses;

Fig. 2 is realization flow figure of the present invention;

Fig. 3 is the minimum transmission rate value R of optimal power contribution method in A → R → B direction using the inventive method, traditional constant power distribution method and ignore circuit energy consumption _{th, B}system energy efficiency comparison diagram during=2bit/s.

Fig. 4 is the minimum transmission rate value R of optimal power contribution method in A → R → B direction using the inventive method, traditional constant power distribution method and ignore circuit energy consumption _{th, B}system energy efficiency comparison diagram during=4bit/s.

Embodiment

Below in conjunction with accompanying drawing, the specific embodiment of the present invention and effect are further described.

With reference to Fig. 1, the asymmetric bidirectional relay system model that the present invention uses comprises relaying R and two subscriber equipment, i.e. first user device A and the second subscriber equipment B, each node only installs single antenna, and all works under half-duplex mode.Owing to there is serious shadow fading between two subscriber equipmenies A, B in system, straight chain channel between the two cannot be communicated, and therefore they can only utilize relaying R to carry out data interaction, and wherein, the agreement that relaying R adopts is amplification forwarding agreement.Suppose that first user device A and the channel between relaying R, the second subscriber equipment B and relaying R are all independently quasi-static flat Rayleigh fading, and path loss index is all α, then the distance between subscriber equipment i and relaying R is d _i, channel gain is h _i, wherein i ∈ { A, B}.In system, the white Gaussian noise power of all Nodes is N ₀.

Asymmetric bidirectional relay system of the present invention provides asymmetrical transmission rate QoS to ensure, for the data flow in A → R → B direction and the data flow in B → R → A direction, the minimum transmission rate that system ensures is respectively R _thBand R _thA.

With reference to Fig. 2, the present invention is according to the energy efficiency optimization method in the asymmetric bidirectional relay system of Fig. 1, and step is as follows:

Step 1, obtain two subscriber equipmenies A, B in asymmetric bidirectional relay system with speed R _tot(P).

(1a) the speed R of first user device A is calculated respectively _a(P) the speed R of and the second subscriber equipment B _b(P):

Wherein: for the signal to noise ratio of first user device A,

be the signal to noise ratio of the second subscriber equipment B,

H _arepresent the channel gain of first user device A to relaying R, h _brepresent the channel gain of the second subscriber equipment B to relaying R, N ₀for white complex gaussian noise power, G is the amplification coefficient at relaying R place, p _arepresent the transmitted power of first user device A, P _brepresent the transmitted power of the second subscriber equipment B, P _rrepresent the transmitted power of relaying R;

(1b) speed of first user device A speed with the second subscriber equipment B is added, obtains both and speed:

R _tot(P)＝R _A(P)+R _B(P)，

Wherein, P=[P _a, P _b, P _r] be transmitted power vector.

Step 2, calculates the energy efficiency η of asymmetric bidirectional relay system _eE(P).

(2a) the dynamic circuit consumed power of asymmetric bidirectional relay system is calculated:

Wherein, ξ>=0 is constant, φ (R _a, R _b) be R _a, R _bconvex increasing function, r=[R _a, R _b] be the velocity vectors of first user device A, the second subscriber equipment B;

(2b) the circuitry consumes power of asymmetric bidirectional relay system is calculated:

Wherein, for the circuitry consumes power of static state;

(2c) the gross power P of asymmetric bidirectional relay system is calculated _tot(P):

P _tot(P)＝(P _A+P _B+P _R)/ε+P _c，

Wherein, ε ∈ (0,1] be power amplifier efficiency;

(2d) by first user device A in step 1, the second subscriber equipment B with speed R _tot(P) with the gross power P of system _tot(P) be divided by, obtain the energy efficiency of system:

η _EE(P)＝R _tot(P)/P _tot(P)。

Step 3, according to the energy efficiency η of system _eE(P), building with maximize energy efficiency is the initial optimization problem P1 of target:

Wherein R _th, _irepresent the minimum transmission rate of subscriber equipment i under unit bandwidth, P _tit is total transmit power threshold of two subscriber equipmenies A, B and relaying R.

Step 4, is rewritten as double optimization problem P2 by initial optimization problem P1:

(4a) according to the speed R of first user device A and the second subscriber equipment B _aand R (P) _b(P) can obtain respectively:

The transmitted power of the second subscriber equipment B:

The transmitted power of relaying R:

Wherein,

Then with the transmitted power P of velocity vectors r and first user device A _afor total transmitted power of independent variable can be expressed as: j' ∈ { B, R};

(4b) by P _b(r, P _a), P _r(r, P _a), substitute in initial optimization problem P1, obtain double optimization problem P2:

Step 5, according to independent variable optimization order, is converted into internal layer optimization problem P3_Inner and outer optimization problem P3_Outter by double optimization problem P2.

(5a) determine the independent variable optimization order of double optimization problem P2, first optimize the transmitted power P of first user device A _a, obtain and the second optimization problem P2 be converted into internal layer optimization problem P3_Inner:

(5b) optimize velocity vectors r, obtain and the second optimization problem P2 is converted into outer optimization problem P3_Outter:

Wherein, be respectively first user device A, optimum transmit power that the second subscriber equipment B and relaying R is independent variable with velocity vectors r, for the total transmitted power of optimum being independent variable with velocity vectors r.

Step 6, obtains the optimization objective function value of internal layer optimization problem P3_Inner

(6a) being the characteristic of convex programming according to internal layer optimization problem P3_Inner, by using Karush-Kuhn-Tucker condition, being about to to P _aderivative be set to zero: obtain the transmitted power optimal solution of first user device A

(6b) will bring the formula P of step 4 respectively into _r(r, P _a), P _b(r, P _a) in, obtain respectively under internal layer optimization problem P3_Inner, the transmitted power optimal solution of relaying R with the transmitted power optimal solution of the second subscriber equipment B

(6c) by the result of calculation in (6a) and (6b) with be added, obtain the optimization objective function value of internal layer optimization problem P3_Inner

Step 7, obtains the iptimum speed r of system in outer optimization problem P3_Outter ^*.

(7a) being the characteristic of nonlinear fractional programming according to outer optimization problem P3_Outter, by using nonlinear fractional programming theorem, namely first utilizing the target function of outer optimization problem P3_Outter, definition band ginseng convex function F (r, q):

Wherein, q is any non-negative parameter, then adds the constraints in P3_Outter, outer optimization problem P3_Outter is converted into three suboptimization problem P4:

(7b) for any given non-negative parameter q, by convex optimization method, the optimal rate vector r of three suboptimization problem P4 is obtained ^*(q) and optimal objective function value F ^*(q):

Common convex optimization method has method of Lagrange multipliers, interior point method, outer point method, and this example uses method of Lagrange multipliers, and concrete equation is:

Wherein, L is Lagrangian, λ _aand λ _bfor Lagrange multiplier;

Above-mentioned equation is solved, obtains optimal rate vector r ^*(q) and optimal objective function value F ^*(q):

F ^*(q)＝min{F(r,q)|r∈Ξ}，

Wherein, Ξ is the rate constraint region of three suboptimization problem P4;

(7c) F is made ^*q ()=0, obtains F ^*q the zero point of () is worth q ^*={ q|F ^*(q)=0}, this q ^*be the optimum capacity efficiency value of system;

(7d) by the optimum capacity efficiency value q of system ^*substitute into the optimal rate vector r of step (7b) ^*in (q), obtain the iptimum speed r of system ^*=r ^*(q ^*).

Step 8, according to the iptimum speed r of system ^*, obtain the optimal power contribution value of two subscriber equipmenies A, B and relaying R.

(8a) by the iptimum speed r of system ^*substitute into the transmitted power optimal solution of first user device A in step 6 obtain the optimal power contribution value of first user device A

(8b) by the iptimum speed r of system ^*substitute into the transmitted power optimal solution of the second subscriber equipment B in step 6 obtain the optimal power contribution value of the second subscriber equipment B

(8c) by the iptimum speed r of system ^*substitute into the transmitted power optimal solution of relaying R in step 6 obtain the optimal power contribution value of relaying R

Effect of the present invention is described further by following emulation:

1) simulated conditions:

Two subscriber equipmenies A, B and relaying R are located on the same line, and are 1 by the range normalization between two subscriber equipmenies A, B, i.e. d _a+ d _b=1, d _arepresent the distance between first user device A and relaying R, d _brepresent the distance between the second subscriber equipment B and relaying R.

Suppose path loss index α=3, then the channel gain variance of two subscriber equipmenies A, B is respectively static circuit energy consumption the energy consumption of every bit rate power amplifier efficiency ε=0.35, noise power N ₀the minimum transmission rate R in=1mw, B → R → A direction _{th, A}the minimum transmission rate in=2bit/s, A → R → B direction is set to R _{th, B}=2bit/s and R _{th, B}=4bit/s two kinds of situations.

2) content and result is emulated:

Emulation 1, gets the minimum transmission rate value R in A → R → B direction _{th, B}=2bit/s, under above-mentioned simulated conditions, use the inventive method, existing constant power distribution method EPA, the existing optimal power contribution method OPA ignoring circuit energy consumption ?these three kinds of methods of Traditional, carry out emulation to the best efficiency of the normalization of asymmetric bidirectional relay system respectively to compare, result as shown in Figure 3.In Fig. 3, abscissa is the distance d between first user device A and relaying R _a, ordinate is the best efficiency of normalization of system.

Emulation 2, gets the minimum transmission rate value R in A → R → B direction _{th, B}=4bit/s, under above-mentioned simulated conditions, use the inventive method, existing constant power distribution method EPA, the existing optimal power contribution method OPA ignoring circuit energy consumption ?these three kinds of methods of Traditional, carry out emulation to the best efficiency of the normalization of asymmetric bidirectional relay system respectively to compare, result as shown in Figure 4.In Fig. 4, abscissa is the distance d between first user device A and relaying R _a, ordinate is the best efficiency of normalization of system.

As can be seen from Fig. 3 and Fig. 4, the energy efficiency of the inventive method is better than the existing energy efficiency ignoring the optimal power contribution method of circuit energy consumption, if this phenomenon shows that ignoring circuit energy consumption in wireless communication designs will bring serious performance degradation, illustrate that the inventive method is more applicable for practical communication scene; In addition, the optimum capacity efficiency under the inventive method is greater than the optimum capacity efficiency under existing two distribution methods all the time, shows the optimality that the inventive method has.

Claims (3)

1. the energy efficiency optimization method in asymmetric bidirectional relay system, comprising:

(1) obtain two subscriber equipmenies A, B in asymmetric bidirectional relay system with speed R _tot(P):

(1a) the speed R of first user device A is calculated respectively _a(P) the speed R of and the second subscriber equipment B _b(P):

(1b) calculate first user device A and the second subscriber equipment B's and speed:

R _tot(P)＝R _A(P)+R _B(P)，

Wherein, P=[P _a, P _b, P _r] be transmitted power vector, P _a, P _band P _rrepresent the transmitted power of subscriber equipment A, B and relaying R respectively;

(2) the energy efficiency η of asymmetric bidirectional relay system is calculated _eE, and propose to take maximize energy efficiency as the initial optimization problem P1 of target (P):

(2a) according to two subscriber equipmenies A, B with speed R _tot(P), the energy efficiency η of computing system _eE(P)=R _tot(P)/P _tot(P);

Wherein P _tot(P)=(P _a+ P _b+ P _r)/ε+P _cfor the gross power of system, for circuitry consumes power in system, r=[R _a, R _b] be the velocity vectors of two subscriber equipmenies A, B, for the circuitry consumes power of static state, for dynamic circuitry consumes power, and ε ∈ (0,1] be power amplifier efficiency;

(2b) according to the energy efficiency η of system _eE(P), building with maximize energy efficiency is the initial optimization problem P1 of target:

$\left(P1\right)---\begin{array}{cc}\underset{P}{\max }& \left\{{\mathrm{\η}}_{EE}\left(P\right)\right\}\\ s.t.& R_i\≥R_{th,i},\underset{j}{\Σ}{P}_j\≤P_T,P_j>0,i\∈\left\{A,B\right\},j\∈\left\{A,B,R\right\}\end{array}$

Wherein R _{th, i}represent the minimum transmission rate of subscriber equipment i under unit bandwidth, P _tit is total transmit power threshold of two subscriber equipmenies A, B and relaying R;

(3) according to the speed R of two subscriber equipmenies A, B _aand R (P) _b(P), initial optimization problem P1 is rewritten as double optimization problem P2:

$\left(P2\right)---\begin{array}{cc}\underset{P_A,R}{\max }& \frac{R_A+R_B}{P_T^{tp}\left(r,P_A\right)/\mathrm{\ϵ}+P_{T,D}^c\left(r\right)+P_S^c}\\ s.t.& R_i\≥R_{th,i},P_T^{tp}\left(r,P_A\right)\≤P_T,P_A>0,P_{j^{\′}}\left(r,P_A\right)>0,i\∈\left\{A,B\right\},j^{\′}\∈\left\{B,R\right\}.\end{array}$

Wherein represent the transmitted power of subscriber equipment B, P _r(r, P _a) represent the transmitted power of relaying R, $P_R(r,P_A)=\frac{(1-g_B/g_A){\mathrm{\α}}_A{\mathrm{\α}}_B+(g_A{\mathrm{\α}}_B+g_B{\mathrm{\α}}_A)P_A}{P_A{g}_A{g}_B-{\mathrm{\α}}_B{g}_B},$ g _i＝|h _i| ²， ${\mathrm{\α}}_i=N_0(2^{2R_i}-1),$ represent total transmitted power of two subscriber equipmenies A, B and relaying R;

(4) double optimization problem P2 is converted into internal layer optimization problem P3_Inner and outer optimization problem P3_Outter:

Determine the independent variable optimization order of double optimization problem P2, namely first optimize the transmitted power P of first user device A _a, then optimize velocity vectors r, then obtain and the second optimization problem P2 be converted into internal layer optimization problem P3_Inner and outer optimization problem P3_Outter:

$(P3\_Inner)---P_A^{*}\left(r\right)=\arg \underset{P_A}{min}\left\{P_T^{tp}\right(R_A,R_B,P_A\left)\right\}$

$\left(P3\_Outter\right)---\begin{array}{cc}\underset{R_A,R_B}{\max }& \frac{R_A+R_B}{P_T^{t^{*}}\left(r\right)/\mathrm{\ϵ}+P_{T,D}^c\left(r\right)+P_S^c}\\ s.t.& R_i\≥R_{th,i},P_T^{t^{*}}\left(r\right)\≤P_T,P_j^{*}\left(r\right)>0,i\∈\left\{A,B\right\},j\∈\left\{A,B,R\right\}.\end{array}$

Wherein, be respectively first user device A, optimum transmit power that the second subscriber equipment B and relaying R is independent variable with velocity vectors r, for the total transmitted power of optimum being independent variable with velocity vectors r;

(5) the optimization objective function value of internal layer optimization problem P3_Inner is obtained

(5a) being the characteristic of convex programming according to internal layer optimization problem P3_Inner, by using Karush-Kuhn-Tucker condition, obtaining the transmitted power optimal solution of first user device A

(5b) will bring the formula P of step (3) respectively into _r(r, P _a), P _b(r, P _a) in, obtain relaying R, the transmitted power optimal solution of the second subscriber equipment B under internal layer optimization problem P3_Inner $P_B^{*}\left(r\right)=\frac{{\mathrm{\α}}_A}{g_B}\frac{\sqrt{g_A}+\sqrt{g_B}}{\sqrt{g_A}};$

(5c) the optimization objective function value of internal layer optimization problem P3_Inner is calculated according to (5a) and (5b) result $P_T^{t*}\left(r\right)=P_A^{*}\left(r\right)+P_B^{*}\left(r\right)+P_R^{*}\left(r\right);$

(6) the iptimum speed r of system in outer optimization problem P3_Outter is obtained ^*:

(6a) being the characteristic of nonlinear fractional programming according to outer optimization problem P3_Outter, by using nonlinear fractional programming theorem, outer optimization problem P3_Outter being converted into three suboptimization problem P4:

$\left(P4\right)---\begin{array}{cc}\underset{R}{\min }& F\left(r,q\right)=q\left(P_T^{t*}\left(r\right)/\mathrm{\ϵ}+P_{T,D}^c\left(r\right)+P_{T,S}^c\right)-\left(R_A+R_B\right)\\ s.t.& R_{th,i}\≤R_i,P_T^{t*}\left(r\right)\≤P_T,i\∈\left\{A,B\right\}.\end{array}$

Wherein q is any non-negative parameter;

(6b) for any given non-negative parameter q, by convex optimization method, the optimal rate vector of three suboptimization problem P4 is obtained with optimal objective function value F ^*(q)=min{F (r, q) | r ∈ Ξ }, wherein Ξ represents the rate constraint region of three suboptimization problem P4;

(6c) F is made ^*q ()=0, obtains F ^*q the zero point of () is worth q ^*={ q|F ^*(q)=0}, q ^*be the optimum capacity efficiency value of system;

(6d) by the optimum capacity efficiency value q of system ^*bring optimal rate vector r into ^*in (q), obtain the iptimum speed r of system ^*=r ^*(q ^*);

(7) by the iptimum speed r of system ^*bring the formula of step (5) respectively into with in, obtain the optimal power contribution value of two subscriber equipmenies A, B and relaying R in system respectively with $P_R^{*}=P_R^{*}\left(r^{*}\right).$

2. the energy efficiency optimization method in asymmetric bidirectional relay system according to claim 1, wherein step (1a) calculates the speed R of first user device A respectively _a(P) the speed R of and the second subscriber equipment B _b(P),

Be calculated as follows:

$R_A\left(P\right)=\frac{1}{2}{\log }_2(1+{\mathrm{\γ}}_A),$

$R_B\left(P\right)=\frac{1}{2}{\log }_2(1+{\mathrm{\γ}}_B),$

Wherein for the signal to noise ratio of first user device A, be the signal to noise ratio of the second subscriber equipment B, h _arepresent the channel gain of first user device A to relaying R, h _brepresent the channel gain of the second subscriber equipment B to relaying R, N ₀for white complex gaussian noise power, G is the amplification coefficient at relaying R place, $G=\sqrt{P_R/\left(P_A\right|h_A{|}^2+P_B\left|h_B{|}^2\right)}.$

3. the energy efficiency optimization method in asymmetric bidirectional relay system according to claim 1, the dynamic circuit consumed power wherein in step (2) its expression is as follows:

$P_{T,D}^c\left(r\right)=\mathrm{\ξ}\mathrm{\φ}(R_A,R_B),$

Wherein ξ>=0 is constant, φ (R _a, R _b) be R _a, R _bconvex increasing function.