CN112888058B - Power distribution method based on nonlinear energy acquisition in multi-relay system - Google Patents

Power distribution method based on nonlinear energy acquisition in multi-relay system Download PDF

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CN112888058B
CN112888058B CN202110067260.0A CN202110067260A CN112888058B CN 112888058 B CN112888058 B CN 112888058B CN 202110067260 A CN202110067260 A CN 202110067260A CN 112888058 B CN112888058 B CN 112888058B
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CN112888058A (en
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朱琦
潘慧芳
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Nanjing University of Posts and Telecommunications
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
    • H04W52/04—TPC
    • H04W52/18—TPC being performed according to specific parameters
    • H04W52/26—TPC being performed according to specific parameters using transmission rate or quality of service QoS [Quality of Service]
    • H04W52/267—TPC being performed according to specific parameters using transmission rate or quality of service QoS [Quality of Service] taking into account the information rate
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
    • H04W52/04—TPC
    • H04W52/38—TPC being performed in particular situations
    • H04W52/46—TPC being performed in particular situations in multi hop networks, e.g. wireless relay networks
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks

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Abstract

The invention discloses a power distribution method based on nonlinear energy acquisition in a multi-relay system, which comprises the following steps: initializing a multi-relay system; calculating the maximum broken line segment of each relay in the piecewise linear energy acquisition model, and calculating the broken line set of the energy acquisition model existing in all relays according to the maximum broken line segment; power allocation is performed for each relay in a given set of polylines. The method of the invention can not only improve the information transmission rate, but also increase the energy of energy collection, thereby effectively improving the energy efficiency, and in addition, based on the piecewise linear energy collection model, the complexity of the nonlinear energy collection model can be reduced, and the accuracy of the linear energy collection model can be improved.

Description

Power distribution method based on nonlinear energy acquisition in multi-relay system
Technical Field
The invention belongs to the technical field of communication, and particularly relates to a power distribution method based on nonlinear energy acquisition in a multi-relay system.
Background
With the increase of the number of communication terminals and the improvement of the intelligent level, services put higher requirements on system capacity, communication rate and the like, and meanwhile, the energy consumption is higher and higher. According to statistics, annual energy consumption of the information communication industry accounts for 3% of global total energy consumption, and carbon emission exceeds 2% of the global energy consumption. In order to meet the requirements of users and reduce energy consumption, a cooperative relay technology and an energy acquisition technology are developed. In the post-5G era, networks are more and more complex, and how to design a proper energy distribution strategy to achieve the purpose of improving the system performance is a problem needing further research.
The cooperative relay technology can effectively solve the problem that the signal of the edge user is weak in cellular communication, and a multi-relay mode can obtain diversity gain at a receiving end, so that the purpose of improving the system capacity is achieved. In the multi-relay mode, multiple relays can receive information sent by a source node and simultaneously forward the information to a destination node, and the destination node receives signals in a certain combination and receiving mode. Through multi-relay forwarding, the influence caused by multipath effect can be effectively overcome, and the quality of received signals is improved. Under the multi-relay cooperative forwarding mode, the target node obtains diversity gain through multi-channel signal combination, the requirement for the size of the transmission power of a single relay is reduced, and the problem that the relay transmission power is small possibly caused by an energy acquisition technology is solved. But how to maximize the energy efficiency of a multi-relay system is an urgent problem to be solved.
Disclosure of Invention
The invention aims to: in order to overcome the defects in the prior art, a power distribution method based on nonlinear energy acquisition is provided, and the energy efficiency of a multi-relay system can be maximized by jointly optimizing the relay transmitting power and the power division ratio.
The technical scheme is as follows: in order to achieve the above object, the present invention provides a power allocation method based on nonlinear energy acquisition in a multi-relay system, comprising the following steps:
s1: initializing a multi-relay system;
s2: calculating the maximum broken line segment S of each relay in the piecewise linear energy acquisition model i According to the maximum broken line segment S i Calculating energy acquisition model broken line set Segment = { s) of all relays 1 ,...,s i ,...s I }；
S3: segment = { s } at a given set of polylines 1 ,...,s i ,...s I In the method, power distribution is carried out on each relay;
the method for performing power allocation to each relay in step S3 is as follows:
a1: n represents different combination numbers of all relay broken line sets and is initialized to 0, number represents the total Number of all relay broken line sets, n = n +1, n represents different combination numbers of all relay broken line sets, and if n is less than or equal to Number, an initial value x of optimal energy efficiency is initialized * Entering the step A2; if n is more than Number, go to step A;
a2: if s is i =0, then the relay transmission power P i =0, power division ratio ρ i ＝0；
If s is i = L, the optimal relay transmitting power and power division ratio are obtained through a direct derivation method, monotonicity, a Lagrange multiplier method and a KKT condition, and the energy efficiency x is calculated;
if 0 < s i If the relay power is less than L, the optimal relay transmitting power and power division ratio are obtained through a direct derivation method, monotonicity, a Lagrange multiplier method and a Kaldo formula, and the energy efficiency x is calculated;
a3: comparing the energy efficiency x obtained in the step A2, and transmitting the optimal relay transmitting power P corresponding to the maximum value of the energy efficiency x i And optimum power split ratio ρ i Respectively updating to the optimal relay transmitting power set { P } 1 ,...,P i ,...,P I } and a set of optimal power division ratios { ρ } 1 ,...,ρ i ,...,ρ I In (j) };
a4: transmitting the power set { P } to the relay 1 ,...,P i ,...,P I } and the set of power splitting ratios { ρ 1 ,...,ρ i ,...,ρ I Substituting elements in the equation into an energy efficiency formula, and calculating to obtain the optimal energy efficiency eta n If the Dinkelbach iteration convergence condition is met, eta n -x * |＜δ 1 ，δ 1 If the iteration maximum allowable error is Dinkelbach, returning to the step A1, otherwise, enabling the initial value x of the optimal energy efficiency * ＝η n Returning to the step A2 again;
a5: comparing the energy efficiency in the optimal energy efficiency set eta to obtain a maximum eta * And the value is corresponding to obtain an optimal relay transmitting power set { P } 1 * ,...,P i * ,...,P I * And a set of optimal power division ratios [ rho ] 1 * ,...,ρ i * ,...,ρ I * H, if the two sets satisfy the fixed point iteration convergence condition | P i * -P i 0 |＜δ 2 And
Figure BDA0002904614170000021
δ 2 for fixed-point iteration maximum allowable error, the loop ends, otherwise let { P 1 0 ,...,P i 0 ,...,P I 0 }＝{P 1 * ,...,P i * ,...,P I * }，{ρ 1 0 ,...,ρ i 0 ,...,ρ I 0 }＝{ρ 1 * ,...,ρ i * ,...,ρ I * And jumping to the step A1 to continue execution, and counting = Count +1.
Further, the initializing of the multi-relay system in step S1 specifically includes: the relay set is denoted by { 1.,. I.,. I }, for a total of I, and the relay transmit power set is denoted by { P } 1 ,...,P i ,...,P I Expressed and initialized to { P } 1 0 ,...,P i 0 ,...,P I 0 }, power division ratio set by { ρ 1 ,...,ρ i ,...,ρ I Expressed and initialized to
Figure BDA0002904614170000022
Count represents the number of multi-relay joint iterations and is initialized to 0.
Further, segment = { S } in the step S1 1 ,...,s i ,...s I The calculation method of the method is as follows: suppose ρ for each relay i =1, calculating the maximum broken line segment S where each relay is located in the piecewise linear energy acquisition model i Then the set of broken lines utilized in each relay energy harvesting is Segment i ＝{0,1,...,s i ,...S i And the broken line set used for collecting all relay energy is Segment = { s = 1 ,...,s i ,...s I N represents the number of different combinations of all relay broken line sets and is initialized to 0, number represents the total number of all relay broken line sets, η = { η = [. Eta. ] 1 ,...,η n ,...,η Number Represents the optimal energy efficiency set for all relay broken line sets.
Further, if s in the step A2 i The calculation method of energy efficiency x is as follows:
power division ratio rho if relaying i i Satisfying the constraint that the received signal-to-noise ratio of the relay is larger than that of the destination node, but the constraint is to relay the secondary transmission power P i When the target function is compared with the power division ratio ρ i Irrelevant, is about the relay transmission power P i The unitary convex function can solve the optimal relay transmitting power and power division ratio by using a direct derivative method, and under the condition, the energy efficiency x is calculated;
power division ratio p if relaying i i The constraint that the receiving signal-to-noise ratio of the relay is larger than that of the destination node is satisfied, and the constraint is simultaneously to the secondary transmitting power P i The optimization problem is a multivariable convex problem, the optimal relay transmitting power and the power division ratio can be obtained by using a Lagrange multiplier method and a KKT condition, and the energy efficiency x is calculated under the condition;
power division ratio p if relaying i i The constraint that the receiving signal-to-noise ratio of the relay is smaller than that of the destination node is satisfied, and the target function centralizes secondary transmission power P i Is a monotone decreasing function, and can obtain the optimal relay transmitting power P according to the linear constraint condition i Substituting the closed solution into the original binary objective function elimination element, and obtaining the optimal power division ratio rho by using a direct derivation method and monotonicity i In this case, energy efficiency x is calculated.
Further, in the step A2, if 0 < s i L, the calculation method of the energy efficiency x comprises the following steps:
power division ratio p if relaying i i The constraint that the receiving signal-to-noise ratio of the relay is larger than that of the destination node is satisfied, and the energy cause-and-effect constraint is that the secondary transmitting power P is centered i When the target function is to the power division ratio ρ i Is a monotonically increasing function centering on secondary radiation power P i The convex function can be solved by a direct derivative method, and under the condition, the energy efficiency x is calculated;
power division ratio rho if relaying i i The constraint that the receiving signal-to-noise ratio of the relay is larger than that of the destination node is satisfied, and the constraint is that the secondary transmission power P is centered i The optimization problem is a multi-variable convex problem, the optimal relay transmitting power and the power division ratio can be obtained by using a Lagrange multiplier method and a KKT condition, the solution of a unitary cubic equation is solved by using a Kaldo formula, and under the condition, the energy efficiency x is calculated;
power division ratio rho if relaying i i The constraint that the receiving signal-to-noise ratio of the relay is larger than that of the destination node is satisfied, and the limitation of the total transmission power of the relay is to the secondary transmission power P i When the target function to power division ratio ρ i Is a monotonically increasing function centering on secondary radiation power P i The convex function can be solved by a direct derivative method, and under the condition, the energy efficiency x is calculated;
power division ratio rho if relaying i i The constraint that the receiving signal-to-noise ratio of the relay is smaller than that of the destination node is satisfied, and at the moment, the objective functionSecondary radiation power P in several pairs i Is a monotone decreasing function, and can obtain the optimal relay transmitting power P according to the linear constraint condition i Substituting the closed solution into the original binary objective function elimination element, and obtaining the optimal power division ratio rho by using a direct derivation method and monotonicity i In this case, energy efficiency x is calculated.
In the scheme of the invention, different from a single-relay system, a multi-relay system can improve the information transmission rate and increase the energy of energy acquisition, so that the energy efficiency can be effectively improved. In addition, based on the piecewise linear energy acquisition model, the complexity of the nonlinear energy acquisition model can be reduced, and the accuracy of the linear energy acquisition model can be improved.
According to the invention, under the two-hop multi-relay cooperation scene, a QoS is considered, and meanwhile, an energy efficiency maximization model is constructed based on a piecewise linear energy acquisition model. Although the method has certain complexity, in the energy acquisition relay system, the energy efficiency of a multi-relay system is higher than that of a single-relay system, and compared with a linear energy acquisition model, the method provided by the invention can obtain better performance.
Aiming at the problem of energy efficiency maximization in a multi-relay cooperative forwarding scene in a two-hop half-duplex relay system, the invention considers the energy cause and effect, the transmission rate and the multi-relay total transmitting power limitation, and jointly optimizes the relay transmitting power and the power division ratio. The method comprises the following steps: according to the method, on the premise of a nonlinear energy acquisition model, power distribution of each relay is carried out on each given energy acquisition model broken line set, energy efficiency maximization is guaranteed, and the energy acquisition model broken line set and the optimal scheme of power distribution of each relay are obtained.
Has the beneficial effects that: compared with the prior art, the invention has the following advantages:
1. the method of the invention takes the maximization of energy efficiency as an optimization target, and carries out the optimal selection of the power distribution of all relays, and the energy efficiency consists of two parts: the first part is the information transmission rate, i.e. the total rate of effective transmission from the source node to the destination node via the relay; the second part is power consumption, i.e. the difference between the power consumed by all nodes in transmitting information and the power compensated for by the relay energy harvesting.
2. Different from the traditional single relay system, the method of the invention considers the mutual cooperation among multiple relays, and the target node receives signals by using a maximum ratio combining mode, thereby obtaining diversity gain and achieving the purpose of improving the information transmission rate; the increased number of relays can also be used to reduce power consumption by using energy harvesting techniques to obtain more power available. The energy efficiency of a multi-relay system is related to the number of relays.
3. Different from the traditional linear energy acquisition model, the nonlinear energy acquisition-based power distribution method provided by the invention considers that the nonlinear energy acquisition model is replaced by the piecewise linear energy acquisition model, so that the accuracy of the linear energy acquisition model can be improved, and the complexity of the nonlinear energy acquisition model can be reduced.
Drawings
FIG. 1 is a schematic diagram of a network model of the method of the present invention;
FIG. 2 is a schematic flow diagram of the process of the present invention;
FIG. 3 is a diagram of simulation results for an energy harvesting model;
FIG. 4 is a diagram of simulation results for the number of relays;
fig. 5 is a diagram of simulation results of source node transmission power.
Detailed Description
The present invention is further illustrated by the following detailed description in conjunction with the accompanying drawings, it is to be understood that such embodiments are merely illustrative of and not restrictive on the broad invention, and that various equivalent modifications of the invention may occur to those skilled in the art upon reading the appended claims.
The invention provides a power distribution method based on nonlinear energy acquisition in a multi-relay system, wherein a model of the multi-relay system in the embodiment is shown in figure 1 and comprises a source node S, a destination node D and I relays R i And (4) forming. All the relay nodes can use the PS mode to collect energy, and the source node and the destination node can not collect energy. The PS method divides the entire relay forwarding process into two time slots: first time slot, relay node is connectedReceiving information sent by a source node, and enabling received signal power to be 1-rho i :ρ i The proportional relation of the time slot and the energy acquisition module is divided into two parts, one part enters the information processing module and decodes information, the other part enters the energy acquisition module and provides energy for information decoding of the time slot and information forwarding of the next time slot, wherein rho i Satisfying rho of 0 ≦ for power division factor i Less than or equal to 1; in the second time slot, the destination node receives the information forwarded by the relay node. Assuming that no direct link exists between the source node and the destination node, the corresponding channels of each relay are independent, wherein h i Representing the source node S to the ith relay node R i Channel gain of g i Denotes the ith relay node R i Channel gain to destination node D.
The method is based on nonlinear energy acquisition, and the problem of research is often complex and difficult to solve due to the nonlinearity of an energy acquisition model, so that the nonlinearity of the original model can be reserved to the greatest extent and the problem can be solved well by adopting a piecewise linear model. A piecewise-linear model, which can be expressed as:
Figure BDA0002904614170000051
wherein the content of the first and second substances,
Figure BDA0002904614170000052
representing the received power of the energy harvesting circuit,
Figure BDA0002904614170000053
is to be
Figure BDA0002904614170000054
A separation point divided into L +1 sections
Figure BDA0002904614170000055
a l And b l Respectively the slope and intercept of the linear function of the first segment (L is more than or equal to 0 and less than or equal to L) and satisfies a 0 ＝b 0 ＝a L ＝0，b L ＝P m 。
The method takes the maximization of energy efficiency as an optimization target, the energy efficiency is defined as the ratio of the total information transmission rate and the total power consumption of all links, and the total information transmission rate and the total power consumption are defined as follows: the total information transmission rate of all links is obtained by using a Shannon formula according to the total receiving signal-to-noise ratio of all links, wherein the total receiving signal-to-noise ratio of all links can be represented as the sum of the signal-to-noise ratios of all single links according to a maximum ratio combining criterion, and the signal-to-noise ratio of the single link is the minimum value of the receiving signal-to-noise ratio of the relay and the receiving signal-to-noise ratio of the destination node. The total power consumption comprises the transmitting power of the source node S, the power consumption of the decoding circuit of the source node and the destination node, and the relay node R i Power consumption of circuit, relay node R i And a relay node R i The power obtained is collected.
Next, the overall information transmission rate and the overall power consumption definition in the actual scene are formulated. In terms of the total information transmission rate, if
Figure BDA0002904614170000056
Denotes the ith relay node R i The signal-to-noise ratio at the receiving end,
Figure BDA0002904614170000057
is represented by R i The signal-to-noise ratio of the receiving end of the destination node in the forwarding process is defined as the total information transmission rate obtained according to the maximum ratio combination and the Shannon formula
Figure BDA0002904614170000058
In terms of total power consumption, except for the transmission power P of the source node S S Consumption power P of decoding circuit of source node and destination node C The relay node R i Power consumption P of the circuit Q And a relay node R i Transmit power P of i In addition, there is a relay node R i Power obtained by energy harvesting
Figure BDA0002904614170000061
The power consumption is supplemented, so the total power consumption can be defined as
Figure BDA0002904614170000062
In summary, the energy efficiency maximization problem in the method of the present invention can be expressed as follows:
Figure BDA0002904614170000063
Figure BDA0002904614170000064
as can be seen from the above optimized expression, the problem is a complex NP problem. The invention is solved by the following two steps:
in the first step, to simplify the summation problem, a fixed point iteration mode is adopted, and only the relay R is assumed i The power of the relay is to be distributed, other relay power distribution is known, namely, the power distribution problem of multiple relays is converted into the problem of single relay power distribution to be solved, and iterative variables are introduced for convenient representation
Figure BDA0002904614170000065
Second step, let ρ be i =1, determine
Figure BDA0002904614170000066
The maximum number of segments to which it is possible to belong, if
Figure BDA0002904614170000067
Expressing optimum energy efficiency, known from theorem, if and only if
Figure BDA0002904614170000068
When this is true, the maximum energy efficiency can be obtained. Therefore, in a given segment, the objective function can be transformed using a subtractive form, introducing a slack variable t i ＝1-ρ i The non-convex problem is converted into a convex problem, and a closed-form solution is solved. But the problem is still a maximum-minimum function problem, which can be increasedAnd decomposing the two problems into two maximization problems by adding corresponding constraint conditions, and respectively solving and then comparing to obtain the optimal.
Figure BDA0002904614170000071
Figure BDA0002904614170000072
Figure BDA0002904614170000073
Figure BDA0002904614170000074
In the optimization expressions (3) and (4), the respective constraints mean as follows: s (1) is to ensure the power division ratio [ rho ] of the relay i i S < th > satisfying a piecewise linear energy harvesting model i A segment; s (2) is to ensure energy causal limitation; s (3) is used for ensuring the limit of information transmission quality; s (4) is to ensure the receiving signal-to-noise ratio of the relay
Figure BDA0002904614170000075
And received signal-to-noise ratio of destination node
Figure BDA0002904614170000076
The minimum value of (d); s (5) is to ensure the limitation of the total transmit power of multiple relays.
Based on the optimization problem, as shown in fig. 2, a specific process of the power allocation method based on nonlinear energy acquisition provided by the invention is as follows:
1) Initialization: the relay set is denoted by { 1.,. I.,. 1., I }, total I, and the relay transmit power set is denoted by { P } 1 ,...,P i ,...,P I Is expressed and initialized to { P } 1 0 ,...,P i 0 ,...,P I 0 }，{ ρ ] for power division ratio set 1 ,...,ρ i ,...,ρ I Is expressed and initialized to
Figure BDA0002904614170000077
In addition, count represents the number of multi-relay joint iterations and is initialized to 0;
2) Suppose ρ for each relay i =1, calculating the maximum broken line segment S where each relay is located in the piecewise linear energy acquisition model i Then the set of broken lines that may be utilized in each relay energy harvesting is Segment i ＝{0,1,...,s i ,...S i The broken line set possibly utilized by all the relay energy collection is Segment = { s = {(s) } 1 ,...,s i ,...s I N represents the number of different combinations of all relay fold line sets and is initialized to 0, number represents the total number of all relay fold line sets, η = { η = [. Eta. ] 1 ,...,η n ,...,η Number Expressing the optimal energy efficiency set under the condition of all relay broken line sets;
3) Segment = { s) given 1 ,...,s i ,...s I In the method, n = n +1, if n is less than or equal to Number, initializing an optimal energy efficiency initial value x * Obtaining an optimal relay transmitting power set and an optimal power division ratio set according to the steps 4-7, and enabling the optimal energy efficiency eta to be obtained n And storing the optimal energy efficiency set eta. If n is more than Number, go to step 8;
4) If s is i =0, then the relay transmission power P i =0, power division ratio ρ i ＝0；
5) If s is i = L, then:
5.1 Power division ratio ρ if relaying i i Satisfying the constraint that the received signal-to-noise ratio of the relay is larger than that of the destination node, but the constraint is to relay the secondary transmission power P i When the target function is compared with the power division ratio ρ i Independently, with respect to the relay transmission power P i The unary convex function of (2) can be solved by a direct derivation method. In this case, energy efficiency x is calculated;
5.2 Power division ratio ρ of if i is relayed i The received signal-to-noise ratio of the relay is larger than that of the destination nodeAnd the constraint of received signal-to-noise ratio is simultaneously to the secondary transmission power P i The optimization problem is a multivariable convex problem, and the optimal relay transmitting power and the power division ratio can be obtained by using a Lagrange multiplier method and a KKT condition. In this case, energy efficiency x is calculated;
5.3 Power division ratio ρ of if i is relayed i The constraint that the receiving signal-to-noise ratio of the relay is smaller than that of the destination node is satisfied, and the target function is used for centering the secondary transmission power P i Is a monotone decreasing function, and can obtain the optimal relay transmitting power P according to the linear constraint condition i Substituting the closed solution into the original binary objective function elimination element, and obtaining the optimal power division ratio rho by using a direct derivation method and monotonicity i . In this case, the energy efficiency x is calculated;
5.4 ) comparing the energy efficiency x obtained by the above conditions, and comparing the optimal relay transmitting power P corresponding to the maximum value of the energy efficiency x i And optimum power split ratio ρ i Respectively updating to an optimal relay transmitting power set and an optimal power division ratio set;
6) If 0 < s i < L, then:
6.1 Power division ratio ρ if relaying i i The constraint that the receiving signal-to-noise ratio of the relay is larger than that of the destination node is satisfied, and the energy causal constraint is that the secondary transmitting power P is centered i When the target function is to the power division ratio ρ i Is a monotonically increasing function centering on secondary radiation power P i Is a convex function and can be solved by a direct derivation method. In this case, energy efficiency x is calculated;
6.2 Power division ratio ρ if relaying i i The constraint that the receiving signal-to-noise ratio of the relay is larger than that of the destination node is satisfied, and the constraint is simultaneously to the secondary transmitting power P i The optimization problem is a multivariable convex problem, the optimal relay transmitting power and the power division ratio can be obtained by using a Lagrange multiplier method and a KKT condition, and the solution of a unitary cubic equation is solved by using a Kaldo formula. In this case, energy efficiency x is calculated;
6.3 Power division if relaying iRatio rho i The constraint that the receiving signal-to-noise ratio of the relay is larger than that of the destination node is satisfied, and the limitation of the total transmission power of the relay is to the secondary transmission power P i When the target function to power division ratio ρ i Is a monotonically increasing function centering on secondary radiation power P i Is a convex function and can be solved by a direct derivation method. In this case, energy efficiency x is calculated;
6.4 Power division ratio ρ if relaying i i The constraint that the receiving signal-to-noise ratio of the relay is smaller than that of the destination node is satisfied, and the target function is used for centering the secondary transmission power P i Is a monotone decreasing function, and can obtain the optimal relay transmitting power P according to the linear constraint condition i Substituting the closed solution into the original binary objective function to eliminate the elements, and obtaining the optimal power division ratio rho by using a direct derivation method and monotonicity i . In this case, energy efficiency x is calculated;
6.5 ) comparing the energy efficiency x obtained by the above conditions, and comparing the optimal relay transmitting power P corresponding to the maximum value of the energy efficiency x i And an optimum power division ratio ρ i Respectively updating to an optimal relay transmitting power set and an optimal power division ratio set;
7) Transmitting the power set { P } to the relay 1 ,...,P i ,...,P I } and a set of power division ratios { ρ 1 ,...,ρ i ,...,ρ I Substituting elements in the equation into an energy efficiency formula, and calculating to obtain the optimal energy efficiency eta n If the Dinkelbach iteration convergence condition is met, returning to the step 3, otherwise, enabling the optimal energy efficiency initial value x * ＝η n And returning to the step 4;
8) Comparing the energy efficiency in the optimal energy efficiency set eta to obtain a maximum eta * The value is corresponding to obtain an optimal relay transmitting power set { P 1 * ,...,P i * ,...,P I * } and a set of optimal power division ratios { ρ } 1 * ,...,ρ i * ,...,ρ I * H, if the two sets satisfy the fixed point iteration convergence condition | P i * -P i 0 |＜δ 2 And
Figure BDA0002904614170000091
δ 2 for fixed-point iteration maximum allowable error, the loop ends, otherwise let { P 1 0 ,...,P i 0 ,...,P I 0 }＝{P 1 * ,...,P i * ,...,P I * }，{ρ 1 0 ,...,ρ i 0 ,...,ρ I 0 }＝{ρ 1 * ,...,ρ i * ,...,ρ I * And jumping to the step A1 to continue execution, and counting = Count +1.
In summary, the invention establishes a system energy efficiency maximization model based on a piecewise linear energy acquisition model under the condition of guaranteeing QoS in a two-hop multi-relay cooperative communication scene. The problem is a complex NP problem, the problem is decoupled into a single relay optimization problem, the single relay power is optimally distributed based on a Dinkelbach iterative algorithm, and the optimization problem after iterative simplification is proved to be a convex planning problem. Because the optimization problem is a maximum and minimum function problem, the problem is decomposed into two maximization problems by adding corresponding constraint conditions to respectively solve the optimal solution. For the solution of each maximization problem, different classification discussions of the polygonal lines corresponding to energy collection are respectively obtained to obtain simplified expressions of corresponding joint optimization problems, and closed solutions of optimal relay transmitting power and optimal power division ratio are obtained by utilizing mathematical methods such as monotonicity, a Lagrange multiplier method, a KKT condition and a Kaldo formula. And obtaining the optimal energy efficiency and the optimal power distribution after two layers of iteration.
In this embodiment, in order to verify the effect of the method of the present invention, a simulation experiment is performed, and the specific result is as follows:
as shown in fig. 3, the power distribution method based on the piecewise linear energy collection model is better than the literature algorithm based on the linear energy collection model in energy efficiency; in fig. 4, the energy efficiency of the power distribution method based on the piecewise linear energy acquisition model in the multi-relay system is better than that of the single-relay system; FIG. 5 is a graph of energy efficiency as a function of source node transmit power, when the source node is activePoint transmission power P S And the energy efficiency reaches the highest when the density is 18 dBm. As can be seen from the combination of the attached drawings 3, 4 and 5, the method of the invention ensures the improvement of energy efficiency under the sacrifice of time complexity.

Claims (3)

1. The power distribution method based on nonlinear energy acquisition in the multi-relay system is characterized by comprising the following steps:
s1: initializing a multi-relay system;
s2: calculating the maximum broken line segment S of each relay in the piecewise linear energy acquisition model i According to the maximum broken line segment S i Calculating the broken line set Segment = { s } of the energy collection model in the presence of all relays 1 ,...,s i ,...s I In which s i ∈{0,1,...,S i }，S i The method comprises the following steps that (1) a set of curve segments is selected from a set of curve segments, wherein L is the total number of the curve segments of a segmented linear energy acquisition model;
s3: segment = { s } at a given set of polylines 1 ,...,s i ,...s I In the method, power distribution is carried out on each relay;
the method for performing power allocation to each relay in step S3 is as follows:
a1: n represents different combination numbers of all relay broken line sets, the initialization is 0, the Number represents the total Number of all relay broken line sets, n = n +1, n represents the different combination numbers of all relay broken line sets, and if n is less than or equal to the Number, the initial value x of the optimal energy efficiency is initialized * Entering step A2; if n is more than Number, go to step A5;
a2: if s is i =0, then the relay transmission power P i =0, power division ratio ρ i ＝0；
If s is i = L, the optimal relay transmitting power and power division ratio are obtained through a direct derivation method, monotonicity, a Lagrange multiplier method and KKT conditions, and energy efficiency x is calculated;
if 0 < s i If the current value is less than L, the optimal relay transmitting power and the power division ratio are obtained through a direct derivation method, monotonicity, a Lagrange multiplier method and a Kaldo formula, and the energy efficiency x is calculated;
a3: step A2, comparing the energy efficiency x obtained in the step (2), and comparing the optimal relay transmitting power P corresponding to the maximum value of the energy efficiency x i And optimum power split ratio ρ i Respectively updating to the optimal relay transmitting power set P 1 ,...,P i ,...,P I } and a set of optimal power division ratios { ρ } 1 ,...,ρ i ,...,ρ I In (j) };
a4: transmitting the power set { P } to the relay 1 ,...,P i ,...,P I } and the set of power splitting ratios { ρ 1 ,...,ρ i ,...,ρ I Substituting the elements in the formula into an energy efficiency formula, and calculating to obtain the optimal energy efficiency eta n If the Dinkelbach iteration convergence condition is met, eta n -x * |＜δ 1 ，δ 1 If the iteration maximum allowable error is Dinkelbach, returning to the step A1, otherwise, enabling the initial value x of the optimal energy efficiency * ＝η n Returning to the step A2 again;
a5: comparing the energy efficiency in the optimal energy efficiency set eta to obtain a maximum eta * And the value is corresponding to obtain an optimal relay transmitting power set { P } 1 * ,...,P i * ,...,P I * And a set of optimal power division ratios [ rho ] 1 * ,...,ρ i * ,...,ρ I * H, if the two sets satisfy the fixed point iteration convergence condition | P i * -P i 0 |＜δ 2 And | ρ i * -ρ i 0 |＜δ 2 ，δ 2 For fixed-point iteration maximum allowable error, the loop ends, otherwise let { P 1 0 ,...,P i 0 ,...,P I 0 }＝{P 1 * ,...,P i * ,...,P I * }，{ρ 1 0 ,...,ρ i 0 ,...,ρ I 0 }＝{ρ 1 * ,...,ρ i * ,...,ρ I * Skipping to the step A1 to continue execution, wherein Count = Count +1, and Count represents the number of multi-relay joint iteration times and is initialized to 0;
if s in said step A2 i Calculation method of energy efficiency x = LThe method comprises the following steps:
power division ratio rho if relaying i i Satisfying the constraint that the received signal-to-noise ratio of the relay is greater than that of the destination node, but the constraint is that the secondary transmission power P is centered i The optimal relay transmitting power and the power division ratio are solved by using a direct derivation method under the weak constraint of (1), and under the condition, the energy efficiency x is calculated;
power division ratio p if relaying i i The constraint that the receiving signal-to-noise ratio of the relay is larger than that of the destination node is satisfied, and the constraint is that the secondary transmission power P is centered i The optimal relay transmitting power and the power division ratio are obtained by using a Lagrange multiplier method and a KKT condition, and under the condition, the energy efficiency x is calculated;
power division ratio p if relaying i i The constraint that the receiving signal-to-noise ratio of the relay is smaller than that of the destination node is satisfied, and the target function centralizes secondary transmission power P i Is a monotone decreasing function, and obtains the optimal relay transmitting power P according to the linear constraint condition i Substituting the closed solution into the original binary objective function elimination element, and obtaining the optimal power division ratio rho by using a direct derivation method and monotonicity i In this case, the energy efficiency x is calculated;
if 0 < s in said step A2 i L, the calculation method of the energy efficiency x is as follows:
power division ratio rho if relaying i i The constraint that the receiving signal-to-noise ratio of the relay is larger than that of the destination node is satisfied, and the energy cause-and-effect constraint is that the secondary transmitting power P is centered i The strong constraint of (2) is solved by a direct derivation method, and under the condition, the energy efficiency x is calculated;
power division ratio rho if relaying i i The constraint that the receiving signal-to-noise ratio of the relay is larger than that of the destination node is satisfied, and the constraint is that the secondary transmission power P is centered i The optimal relay transmitting power and the power division ratio are obtained by using a Lagrange multiplier method and a KKT condition, wherein the solution of a unitary cubic equation is solved by using a Kaldo formula, and under the condition, the energy efficiency x is calculated;
power division ratio rho if relaying i i Satisfying relayingIs greater than the received signal-to-noise ratio of the destination node, and the total relay transmit power limit is the secondary relay transmit power P i The strong constraint of (2) is solved by a direct derivation method, and under the condition, the energy efficiency x is calculated;
power division ratio rho if relaying i i The constraint that the receiving signal-to-noise ratio of the relay is smaller than that of the target node is met, and the optimal relay transmitting power P is obtained according to the linear constraint condition i Substituting the closed solution into the original binary objective function elimination element, and obtaining the optimal power division ratio rho by using a direct derivation method and monotonicity i In this case, energy efficiency x is calculated.
2. The power distribution method based on nonlinear energy harvesting in the multi-relay system according to claim 1, wherein the initialization of the multi-relay system in the step S1 specifically includes: the relay set is denoted by { 1.,. I.,. I }, with the total number I, and the relay transmit power set is denoted by { P } 1 ,...,P i ,...,P I Expressed and initialized to { P } 1 0 ,...,P i 0 ,...,P I 0 }, power division ratio set by { ρ 1 ,...,ρ i ,...,ρ I Expressed and initialized to { ρ } 1 0 ,...,ρ i 0 ,...,ρ I 0 And Count represents the number of multi-relay joint iterations and is initialized to 0.
3. The method according to claim 1, wherein Segment = { S } in step S1 1 ,...,s i ,...s I The calculation method comprises the following steps: let ρ be assumed for each relay i =1, calculating the maximum broken line segment S where each relay is located in the piecewise linear energy collection model i Then the broken line set utilized in each relay energy collection is Segment i ＝{0,1,...,s i ,...S i And the broken line set used for collecting all relay energy is Segment = { s = 1 ,...,s i ,...s I N represents all relay broken linesDifferent combinations of sets are numbered and initialized to 0, number represents the total number of all relay broken line sets, η = { η = 1 ,...,η n ,...,η Number And represents the optimal energy efficiency set under the condition of all relay broken line sets.
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