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 the technical field of mobile communication systems, and particularly relates to an intermediate energy efficiency optimization method which can be used for an asymmetric bidirectional relay system.

Background

With the gradual rise of mobile internet and internet of things, the energy consumption cost is continuously increased and the ecological environment is gradually deteriorated due to the explosive growth of mobile data traffic and massive device connection, and thus, green communication technology is receiving attention. As a green index for measuring energy consumption of communication systems, energy efficiency is a hot research spot today. In order to overcome the defects of time slot waste and low spectrum efficiency of the traditional relay technology, a two-way relay channel TWRC is introduced. In the TWRC system, two terminal nodes realize data interaction through a relay, and when the relay performs only amplification forwarding AF processing on received signals, the number of time slots for realizing one-time information interaction of the two terminals is reduced to 2 from 4 of the traditional relay, so that the frequency spectrum efficiency is obviously improved.

Currently, in the bidirectional relay system, the energy consumption of the antenna for transmitting data is mainly considered in the research on the aspect of energy efficiency optimization, and some scientific achievements are obtained. With the goal of maximizing energy efficiency, the article "energy efficient design in afresh and telecommunications networks works, fra: IEEE,2012:7-11 by huanggr et al" proposes an optimal energy saving scheme for joint relay selection and power allocation. Under the constraints of meeting user rate requirements and transmitting energy consumption, LiQ and the like optimize the link-level energy efficiency of the distributed beamforming ANC system in an article 'Tradeoff of BetWenenergyEffeiciencyAndSpectraEnfficiciencyInTwo-WayRelayNet' on 14th International communications technology, China, IEEE,2012: 929-. These studies consider the traditional long-distance transmission scenario, where the transmission energy accounts for most of the total energy consumption of the system, so that only the transmission energy consumption is considered when building the total energy consumption model, and the circuit energy consumption is ignored.

With the increase of the terminal density, the distance between the terminals is gradually reduced, and the circuit energy consumption is close to or even larger than the transmission energy consumption, such as: in the aware network, the total energy consumption model must take into account the circuit energy consumption. WangT et al in ieee transactions on communications,2013,61(12):4910 + 4921 consider circuit power consumption in a short-range point-to-point transmission scenario and model it as two parts: static circuit power consumption, i.e. the power consumption of the circuit independent of the transmission rate, dynamic circuit power consumption, i.e. the power consumption of the circuit dependent on the transmission rate, wherein the dynamic circuit power consumption is a convex increasing function of the transmission rate. Existing circuit energy consumption models, such as: constant, linear function of transmission rate, are both special cases. The paper proposes an optimal power allocation scheme with maximized energy efficiency, but the scheme only considers a point-to-point linear chain transmission scenario.

In order to meet the requirements of different users for different transmission rates and realize different applications, the consideration of the requirement of asymmetric transmission rate is indispensable. An article "Energy-efficiency relay selection and power allocation scheme for two-way channel with analog network coding" by zhouum et al, ieee communications letters,2012,16(6):816-819 proposes a relay selection strategy and a power allocation scheme for minimizing total transmission Energy consumption under the condition of satisfying the end-to-end minimum transmission rate of an asymmetric bidirectional relay system.

Disclosure of Invention

The invention aims to provide an energy efficiency optimization method in an asymmetric bidirectional relay system aiming at the defects of the prior art, so as to improve the energy efficiency of a communication system, ensure the reliable link of a communication link and realize green communication.

In order to achieve the purpose, the technical scheme of the invention comprises the following steps:

(1) obtaining sum rate R of two user equipments A, B in asymmetric bidirectional relay system_tot(P)：

(1a) Respectively calculating the rate R of the first user equipment A_A(P) and rate R of second user equipment B_B(P)：

(1b) Calculating the sum rate of the first user equipment A and the second user equipment B:

R_tot(P)＝R_A(P)+R_B(P)，

wherein, P ═ P_A,P_B,P_R]For transmitting power vectors, P_A、P_BAnd P_RRepresents the transmit power of the user equipment A, B and relay R, respectively;

(2) calculating energy efficiency η for asymmetric two-way relay system_EE(P) and presents an initial optimization problem P1 with the goal of maximizing energy efficiency:

(2a) rate R according to the sum of two user equipments A, B_tot(P), calculating the energy efficiency η of the system_EE(P)＝R_tot(P)/P_tot(P)；

Wherein P is_tot(P)＝(P_A+P_B+P_R)/+P_cFor the total power of the system to be,for the circuits in the system to consume power, R ═ R_A,R_B]For the velocity vectors of both user devices A, B,the power is consumed for the circuits that are static,for dynamic circuit consumption power, ∈ (0, 1)]To power amplification efficiency;

(2b) energy efficiency η according to system_EE(P), constructing an initial optimization problem P1 with the goal of maximizing energy efficiency:

wherein R is_th,_iDenotes the lowest transmission rate, P, of the user equipment i per unit bandwidth_TA total transmit power threshold for both user equipment A, B and relay R;

(3) rate R according to two user equipments A, B_A(P) and R_B(P), rewriting the initial optimization problem P1 to quadratic optimization problem P2:

whereinIndicating the transmission power, P, of the user equipment B_R(r,P_A) Indicates the transmission power of the relay R and,g_i＝|h_i|²， represents the total transmit power of both user equipment A, B and relay R;

(4) converting the secondary optimization problem P2 into an Inner optimization problem P3_ Inner and an outer optimization problem P3_ Outter:

determining the argument optimization order of the quadratic optimization problem P2, i.e. first optimizing the transmission power P of the first user equipment A_AAnd then optimizing the velocity vector r, obtaining the second optimization problem P2 converted into an Inner layer optimization problem P3_ Inner and an outer layer optimization problem P3_ Outter:

wherein,respectively for the first user equipment A, the second user equipment B and the relay R, and taking the velocity vector R as the optimal transmitting power of the independent variable,the optimal total transmit power with the rate vector r as an argument;

(5) obtaining an optimal objective function value for the Inner layer optimization problem P3_ Inner

(5a) Obtaining the optimal solution of the transmitting power of the first user equipment A by using a Karush-Kuhn-Tucker condition according to the characteristic that the Inner layer optimization problem P3_ Inner is a convex plan

(5b) Will be provided withFormula P in step (3) respectively_R(r,P_A)、P_B(r,P_A) Obtaining the optimal solution of the transmission power of the relay R and the second user equipment B under the Inner layer optimization problem P3_ Inner

(5c) Calculating the optimal objective function value of the Inner layer optimization problem P3_ Inner according to the results of (5a) and (5b)

(6) Obtaining the optimal rate r of the system in the outer optimization problem P3_ Outter^*：

(6a) According to the characteristic that the outer optimization problem P3_ Outter is nonlinear fractional programming, the outer optimization problem P3_ Outter is converted into a cubic optimization problem P4 by using a nonlinear fractional programming theorem:

wherein q is any non-negative parameter;

(6b) for any given non-negative parameter q, obtaining the optimal velocity vector of the cubic optimization problem P4 by a convex optimization methodAnd an optimal objective function value F^*(q) ═ min { F (r, q) | r ∈ xi }, where xi represents the rate constraint region of the cubic optimization problem P4;

(6c) let F^*(q) is 0 to give F^*Zero point value q of (q)^*＝{q|F^*(q)＝0}，q^*The optimal energy efficiency value of the system is obtained;

(6d) determining the optimal energy efficiency value q of the system^*Bringing into the optimal velocity vector r^*(q) obtaining the optimal rate r of the system^*＝r^*(q^*)；

(7) The optimal rate r of the system^*Respectively carried over to step (5)Andin the method, optimal power allocation values of two user equipment A, B and relay R in the system are respectively obtainedAnd

compared with the prior art, the invention has the following advantages:

first, the present invention adopts a transmission rate-related circuit power consumption model, and fully considers short-range transmission scenarios rather than long-range transmission scenarios, and thus is more widely applied in practical communication environments.

Second, compared with the conventional equal power allocation method and the optimal power allocation method ignoring circuit energy consumption, the optimal power allocation method provided by the invention can maximize the energy efficiency of the system, effectively reduce the energy required by unit data transmission, and realize green communication.

Thirdly, the optimal power distribution method provided by the invention guarantees the service requirement of the asymmetric transmission rate of the uplink and the downlink aiming at the common asymmetric communication service, thereby being more in line with the practical application.

Drawings

FIG. 1 is a diagram of an asymmetric two-way relay system model used in the present invention;

FIG. 2 is a flow chart of an implementation of the present invention;

FIG. 3 is a graph of the lowest transmission rate value R in the A → R → B direction using the method of the present invention, the conventional equal power allocation method and the optimal power allocation method ignoring circuit power consumption_th,BEnergy efficiency of the system at 2bit/s is plotted against the energy efficiency of the system.

FIG. 4 is a graph of the lowest transmission rate value R in the A → R → B direction using the method of the present invention, the conventional equal power allocation method and the optimal power allocation method ignoring circuit power consumption_th,BEnergy efficiency of the system at 4bit/s is plotted.

Detailed Description

The following further describes embodiments and effects of the present invention with reference to the drawings.

Referring to fig. 1, the asymmetric bidirectional relay system model used in the present invention includes one relay R and two user equipments, i.e., a first user equipment a and a second user equipment B, each node is only installed with a single antenna, and both operate in a half-duplex mode. Due to severe shadow fading between two user equipment A, B in the systemAssuming that the channels between the first UE A and the relay R, the second UE B and the relay R are all independent quasi-static flat Rayleigh fading, and the path loss exponents are all α, the distance between the UE i and the relay R is d_iChannel gain of h_i，Whereini ∈ { A, B }. Gaussian white noise power at all nodes in the system is N₀。

The asymmetric bidirectional relay system of the invention provides asymmetric transmission rate QoS guarantee, and the minimum transmission rate guaranteed by the system is respectively R for the data flow in the A → R → B direction and the data flow in the B → R → A direction_thBAnd R_thA。

Referring to fig. 2, the energy efficiency optimization method in the asymmetric bidirectional relay system of fig. 1 according to the present invention includes the following steps:

step 1, obtaining sum rate R of two user equipments A, B in asymmetric bidirectional relay system_tot(P)。

(1a) Respectively calculating the rate R of the first user equipment A_A(P) and rate R of second user equipment B_B(P)：

Wherein:for the signal-to-noise ratio of the first user equipment a,

for the signal-to-noise ratio of the second user equipment B,

h_Adenotes the channel gain, h, of the first user equipment A to the relay R_BRepresenting the channel gain, N, of the second user equipment B to the relay R₀Complex gaussian white noise power, G is the amplification factor at the relay R,P_Aindicating the transmission power, P, of the first user equipment A_BRepresenting the transmission power, P, of the second user equipment B_RRepresents the transmission power of the relay R;

(1b) adding the rate of the first user equipment A and the rate of the second user equipment B to obtain the sum rate of the first user equipment A and the second user equipment B:

R_tot(P)＝R_A(P)+R_B(P)，

wherein, P ═ P_A,P_B,P_R]Is a transmit power vector.

Step 2, calculating the energy efficiency η of the asymmetric two-way relay system_EE(P)。

(2a) Calculating the power consumption of a dynamic circuit of the asymmetric bidirectional relay system:

wherein ξ is a constant of phi (R) and not less than 0_A,R_B) Is R_A、R_BConvex increasing function, R ═ R_A,R_B]Is a first userVelocity vectors of the device a and the second user equipment B;

(2b) calculating the circuit consumption power of the asymmetric bidirectional relay system:

wherein,consuming power for static circuits;

(2c) calculating the total power P of an asymmetric two-way relay system_tot(P)：

P_tot(P)＝(P_A+P_B+P_R)/+P_c，

Wherein epsilon (0, 1) is power amplification efficiency;

(2d) the sum rate R of the first user equipment A and the second user equipment B in the step 1 is obtained_tot(P) and total power P of the system_tot(P) performing a division to obtain the energy efficiency of the system:

η_EE(P)＝R_tot(P)/P_tot(P)。

step 3, energy efficiency η according to system_EE(P), constructing an initial optimization problem P1 with the goal of maximizing energy efficiency:

wherein R is_th,_iDenotes the lowest transmission rate, P, of the user equipment i per unit bandwidth_TA total transmit power threshold for both user equipment A, B and relay R.

Step 4, rewriting the initial optimization problem P1 into a quadratic optimization problem P2:

(4a) according to the rate R of the first user equipment A and the second user equipment B_A(P) and R_B(P) respectively obtaining:

transmission power of the second user equipment B:

transmission power of relay R:

wherein,

then at the rate vector r and the transmit power P of the first user equipment a_AThe total transmit power as an argument may be expressed as:j'∈{B,R}；

(4b) will P_B(r,P_A)，P_R(r,P_A)，And substituting the initial optimization problem P1 to obtain a secondary optimization problem P2:

and 5, converting the secondary optimization problem P2 into an Inner layer optimization problem P3_ Inner and an outer layer optimization problem P3_ Outter according to the independent variable optimization sequence.

(5a) Determining the independent variable optimization order of the quadratic optimization problem P2 by first optimizing the transmission of the first user equipment APower P_AObtaining a second optimization problem P2 transformed into an Inner layer optimization problem P3_ Inner:

(5b) optimizing the rate vector r to obtain a second optimization problem P2 transformed into an outer optimization problem P3_ Outter:

wherein,respectively for the first user equipment A, the second user equipment B and the relay R, and taking the velocity vector R as the optimal transmitting power of the independent variable,is the optimal total transmit power with the rate vector r as argument.

Step 6, obtaining the optimal objective function value of the Inner layer optimization problem P3_ Inner

(6a) According to the characteristic that the Inner layer optimization problem P3_ Inner is convex programming, by using the Karush-Kuhn-Tucker condition, the method is to sayTo P_AIs set to zero:obtaining the optimal solution of the transmitting power of the first user equipment A

(6b) Will be provided withFormula P in step 4_R(r,P_A)、P_B(r,P_A) Respectively obtaining the optimal solution of the transmission power of the relay R under the Inner layer optimization problem P3_ InnerAnd the optimum solution of the transmission power of the second user equipment B

(6c) Comparing the calculation results in (6a) and (6b)Andadding to obtain the optimal objective function value of the Inner optimization problem P3_ Inner

Step 7, obtaining the optimal rate r of the system in the outer optimization problem P3_ Outer^*。

(7a) According to the characteristic that the outer optimization problem P3_ Outter is nonlinear fractional programming, a convex function F (r, q) with parameters is defined by using the nonlinear fractional programming theorem, namely an objective function of the outer optimization problem P3_ Outter is firstly utilized:

wherein q is any non-negative parameter, then adding a constraint condition in P3_ Outter, and converting the outer layer optimization problem P3_ Outter into a cubic optimization problem P4:

(7b) for any given non-negative parameter q, obtaining the optimal velocity vector r of the cubic optimization problem P4 by a convex optimization method^*(q) and the optimal objective function value F^*(q)：

Common convex optimization methods include a lagrange multiplier method, an inner point method and an outer point method, the lagrange multiplier method is used in the example, and the specific equation is as follows:

wherein L is a Lagrangian function, λ_AAnd λ_BIs a lagrange multiplier;

solving the equation to obtain the optimal velocity vector r^*(q) and the optimal objective function value F^*(q)：

F^*(q)＝min{F(r,q)|r∈Ξ}，

Wherein xi is a rate constraint region of the cubic optimization problem P4;

(7c) let F^*(q) is 0 to give F^*Zero point value q of (q)^*＝{q|F^*(q) ═ 0}, where q is equal to^*The optimal energy efficiency value of the system is obtained;

(7d) determining the optimal energy efficiency value q of the system^*Substituting the optimal rate vector of step (7b)r^*(q) obtaining the optimal rate r of the system^*＝r^*(q^*)。

Step 8, according to the optimal speed r of the system^*The optimal power allocation values for the two user equipments A, B and the relay R are obtained.

(8a) The optimal rate r of the system^*Substituting the optimal solution of the transmission power of the first user equipment A in the step 6Obtaining the optimal power distribution value of the first user equipment A

(8b) The optimal rate r of the system^*Substituting the optimal solution of the transmission power of the second user equipment B in the step 6Obtaining the optimal power distribution value of the second user equipment B

(8c) The optimal rate r of the system^*Substituting into the optimal solution of the transmission power of the relay R in the step 6Obtaining the optimal power distribution value of the relay R

The effects of the present invention can be further illustrated by the following simulations:

1) simulation conditions are as follows:

the two ues A, B are located on the same line with the relay R, and connect the two ues a,The distance between B is normalized to 1, i.e. d_A+d_B＝1，d_ADenotes the distance between the first user equipment A and the relay R, d_BIndicating the distance between the second user equipment B and the relay R.

Assuming that the path loss exponent α is 3, the channel gain variances of the two user equipments A, B are respectively Static circuit power consumptionEnergy consumption per bit ratePower amplification efficiency of 0.35, noise power N₀1mw, lowest transmission rate R in B → R → A direction_th,AThe lowest transmission rate in the a → R → B direction is set to R2 bit/s_th,B2bit/s and R_th,BTwo cases of 4 bit/s.

2) Simulation content and results:

simulation 1, taking the lowest transmission rate value R of the A → R → B direction_th,BUnder the above simulation conditions, the normalized optimal energy efficiency of the asymmetric bidirectional relay system is simulated and compared by using three methods, namely the method of the present invention, the conventional equal power allocation method EPA, and the conventional optimal power allocation method OPA-Traditional which ignores circuit energy consumption, and the result is shown in fig. 3. In fig. 3, the abscissa represents the distance d between the first ue a and the relay R_AAnd the ordinate is the normalized optimal energy efficiency of the system.

Simulation 2, taking the lowest transmission rate value R of the A → R → B direction_th,BUnder the simulation condition, the method of the invention, the existing equal power distribution method EPA and the existing optimal neglecting the circuit energy consumption are usedThe results of simulation comparison of the normalized optimal energy efficiency of the asymmetric bidirectional relay system by the three methods of the power distribution method OPA-Traditional are shown in fig. 4. In fig. 4, the abscissa represents the distance d between the first ue a and the relay R_AAnd the ordinate is the normalized optimal energy efficiency of the system.

As can be seen from fig. 3 and 4, the energy efficiency of the method of the present invention is superior to that of the existing optimal power allocation method which ignores the circuit energy consumption, and this phenomenon indicates that if the circuit energy consumption is ignored in the wireless communication design, severe performance degradation will be brought, which indicates that the method of the present invention is more suitable for the actual communication scenario; in addition, the optimal energy efficiency under the method is always higher than that under the two existing distribution methods, and the optimality of the method is shown.

Claims (3)

1. The energy efficiency optimization method in the asymmetric bidirectional relay system comprises the following steps:

(1) obtaining sum rate R of two user equipments A, B in asymmetric bidirectional relay system_tot(P)：

(1a) Respectively calculating the rate R of the first user equipment A_A(P) and rate R of second user equipment B_B(P)：

(1b) Calculating the sum rate of the first user equipment A and the second user equipment B:

R_tot(P)＝R_A(P)+R_B(P)，

wherein, P ═ P_A,P_B,P_R]For transmitting power vectors, P_A、P_BAnd P_RRepresents the transmit power of the user equipment A, B and relay R, respectively;

(2) calculating energy efficiency η for asymmetric two-way relay system_EE(P) and presents an initial optimization problem P1 with the goal of maximizing energy efficiency:

(2a) rate R according to the sum of two user equipments A, B_tot(P), calculating the energy efficiency η of the system_EE(P)＝R_tot(P)/P_tot(P)；

Wherein P is_tot(P)＝(P_A+P_B+P_R)/+P_cFor the total power of the system to be,for the circuits in the system to consume power, R ═ R_A,R_B]For the velocity vectors of both user devices A, B,the power is consumed for the circuits that are static,for dynamic circuit consumption power, ∈ (0, 1)]To power amplification efficiency;

(2b) energy efficiency η according to system_EE(P), constructing an initial optimization problem P1 with the goal of maximizing energy efficiency:

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

wherein R is_th,iDenotes the lowest transmission rate, P, of the user equipment i per unit bandwidth_TA total transmit power threshold for both user equipment A, B and relay R;

(3) rate R according to two user equipments A, B_A(P) and R_B(P), rewriting the initial optimization problem P1 to quadratic optimization problem P2:

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

whereinIndicating the transmission power, P, of the user equipment B_R(r,P_A) Indicates the transmission power of the relay R and, $P_R(r,P_A)=\frac{(1-g_B/g_A){\mathrm{\α}}_A{\mathrm{\α}}_B+(g_A{\mathrm{\α}}_B+g_B{\mathrm{\α}}_A)P_A}{P_A{g}_A{g}_B-{\mathrm{\α}}_B{g}_B},$ g_i＝|h_i|²， ${\mathrm{\α}}_i=N_0(2^{2R_i}-1),$ represents the total transmit power of both user equipment A, B and relay R;

(4) converting the secondary optimization problem P2 into an Inner optimization problem P3_ Inner and an outer optimization problem P3_ Outter:

determining the argument optimization order of the quadratic optimization problem P2, i.e. first optimizing the transmission power P of the first user equipment A_AAnd then optimizing the velocity vector r, obtaining the second optimization problem P2 converted into an Inner layer optimization problem P3_ Inner and an outer layer 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,respectively for the first user equipment A, the second user equipment B and the relay R, and taking the velocity vector R as the optimal transmitting power of the independent variable,the optimal total transmit power with the rate vector r as an argument;

(5) obtaining an optimal objective function value for the Inner layer optimization problem P3_ Inner

(5a) Obtaining the optimal solution of the transmitting power of the first user equipment A by using a Karush-Kuhn-Tucker condition according to the characteristic that the Inner layer optimization problem P3_ Inner is a convex plan

(5b) Will be provided withFormula P in step (3) respectively_R(r,P_A)、P_B(r,P_A) Obtaining the optimal solution of the transmission power of the relay R and the second user equipment B under the Inner 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) Calculating the optimal objective function value of the Inner layer optimization problem P3_ Inner according to the results of (5a) and (5b) $P_T^{t*}\left(r\right)=P_A^{*}\left(r\right)+P_B^{*}\left(r\right)+P_R^{*}\left(r\right);$

(6) Obtaining the optimal rate r of the system in the outer optimization problem P3_ Outter^*：

(6a) According to the characteristic that the outer optimization problem P3_ Outter is nonlinear fractional programming, the outer optimization problem P3_ Outter is converted into a cubic optimization problem P4 by using a nonlinear fractional programming theorem:

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

wherein q is any non-negative parameter;

(6b) for any given non-negative parameter q, obtaining the optimal velocity vector of the cubic optimization problem P4 by a convex optimization methodAnd an optimal objective function value F^*(q) ═ min { F (r, q) | r ∈ xi }, where xi represents the rate constraint region of the cubic optimization problem P4;

(6c) let F^*(q) is 0 to give F^*Zero point value q of (q)^*＝{q|F^*(q)＝0}，q^*The optimal energy efficiency value of the system is obtained;

(6d) determining the optimal energy efficiency value q of the system^*Bringing into the optimal velocity vector r^*(q) obtaining the optimal rate r of the system^*＝r^*(q^*)；

(7) The optimal rate r of the system^*Respectively carried over to step (5)Andin the method, optimal power allocation values of two user equipment A, B and relay R in the system are respectively obtainedAnd $P_R^{*}=P_R^{*}\left(r^{*}\right).$

2. the energy efficiency optimizing method in an asymmetric bidirectional relay system according to claim 1, wherein the step (1a) calculates the rate R of the first user equipment A respectively_A(P) and rate R of second user equipment B_B(P)，

Calculated according to the following formula:

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

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

whereinFor the signal-to-noise ratio of the first user equipment a,is the signal-to-noise ratio, h, of the second user equipment B_ATo representChannel gain, h, of first user equipment A to relay R_BRepresenting the channel gain, N, of the second user equipment B to the relay R₀Complex gaussian white noise power, G is the amplification factor at the relay R, $G=\sqrt{P_R/\left(P_A\right|h_A{|}^2+P_B\left|h_B{|}^2\right)}.$

3. the method for energy efficiency optimization in an asymmetric bidirectional relay system as in claim 1, wherein the dynamic circuit in step (2) consumes powerIt has the following expression:

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

wherein ξ is a constant equal to or greater than 0, phi (R)_A,R_B) Is R_A、R_BA convex increasing function.