A method and system for improving energy efficiency of wireless energy-carrying communication based on intelligent reflective surface

Abstract

A method and system for improving energy efficiency of wireless energy-carrying communication based on intelligent reflecting surfaces, relates to the field of wireless communication technology, and is used to solve the technical problem that traditional receiving power optimization methods cannot maximize the total receiving power. The technical points of the present invention include: establishing a total receiving power model of an energy collection receiver for wireless energy-carrying communication based on an intelligent reflecting surface; maximizing the total receiving power of the energy collection receiver as the objective function, and optimizing and solving the objective function using a quantum honey badger algorithm; specifically including: initializing quantum honey badger algorithm parameters; updating the optimal quantum position in the quantum honey badger population; determining the quantum honey badger hunger rate; evaluating the target fitness function to find a better quantum position; stopping the iteration when the number of iterations is greater than or equal to the preset maximum number of iterations, outputting the global optimal quantum position of the quantum honey badger, obtaining the position according to the mapping rule and returning the optimal fitness value. The present invention realizes the intelligent joint configuration of energy collection receivers.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technology, and in particular to a method and system for improving energy efficiency of wireless energy-carrying communications based on an intelligent reflective surface. Background Art

[0002] In recent years, with the continuous release of the potential of IoT devices, wireless power transmission (SWIPT) supporting RF transmission has become an important research direction for the future development of wireless IoT due to its advantages such as reliable communication guarantee and permanent energy supply. Smart reflective surface (IRS) consists of a large number of low-cost passive reflective units and is considered to be a competitive technology that can improve the spectrum efficiency and energy efficiency of future wireless networks. In practice, the energy harvesting receiver (EHR) requires a much higher receiving power than the information decoding receiver (IDR). Therefore, how to improve the wireless power transmission efficiency of the energy harvesting receiver is a key challenge to fundamentally improve the energy transmission efficiency of the wireless power transmission system.

[0003] Recently, through the search of existing literature, it was found that for the wireless energy communication scenario based on smart reflective surface, Ren, Hong et al. published "Transmission Design for Active RIS-Aided Simultaneous Wireless Information and Power Transfer" in "IEEE Wireless Communications Letters" (2023, vol. 12, no. 4, pp. 600-604), which proposed a weighted sum rate optimization method for wireless energy communication information decoding receiver based on smart reflective surface, but this method did not consider the optimization problem of the total received power of the wireless energy communication energy collection receiver based on smart reflective surface. Although the existing method has a certain effect on the optimization of the receiving rate, the algorithm used is still a traditional method, and the traditional algorithm has a low improvement rate and cannot guarantee the maximization of the total received power. Summary of the invention

[0004] In view of this, the present invention proposes a method and system for improving the energy efficiency of wireless energy-carrying communications based on a smart reflective surface, so as to solve the technical problem that the traditional receiving power optimization method cannot maximize the improvement of the total receiving power.

[0005] According to one aspect of the present invention, a method for improving energy efficiency of wireless energy-carrying communication based on a smart reflective surface is proposed, comprising the following steps:

[0006] Step 1: Establish a total power receiving model of a wireless energy-carrying communication energy harvesting receiver based on a smart reflective surface;

[0007] Step 2: maximizing the total power received by the energy harvesting receiver is used as the objective function, and the objective function is optimized and solved using the quantum honey badger algorithm; specifically, the following steps are included:

[0008] Step 21. Initialize the parameters of the quantum honey badger algorithm;

[0009] Step 22: Update the optimal quantum honey badger position in the quantum honey badger population;

[0010] Step 23: Determine the hunger rate of the quantum honey badger;

[0011] Step 24: Evaluate the target fitness function, and the quantum honey badger looks for a better quantum position;

[0012] Step 25: When the number of iterations is greater than or equal to the preset maximum number of iterations, stop the iteration, output the global optimal quantum position of the quantum honey badger, obtain the position according to the mapping rule and return the optimal fitness value.

[0013] Furthermore, the total power model of the wireless energy-carrying communication energy harvesting receiver in step 1 is established based on the wireless energy-carrying communication system, and the wireless energy-carrying communication system is deployed as: an intelligent reflection surface with N reflection units to assist the wireless energy-carrying communication system from an access point with M antennas to two groups of single-antenna receivers, and the two groups of receivers are information decoding receivers and energy harvesting receivers; the total power model Q of the wireless energy-carrying communication energy harvesting receiver is expressed as:

[0014]

[0015] Where i is the information decoding receiver, Γ Ι is the information decoding receiver set; ω i is the precoding vector of information decoding receiver i, Indicates that ω i Find the conjugate transpose; j is the energy harvesting receiver, q j is the energy weight of j, Γ ε is a collection of energy harvesting receivers, is the baseband equivalent channel from the smart reflector to the energy harvesting receiver j, Θ is the reflection coefficient matrix of the smart reflector, G is the channel from the access point to the smart reflector, is the baseband equivalent channel from the access point to the energy harvesting receiver j; j is the precoding vector of the energy harvesting receiver j, and H represents the conjugate transpose of the corresponding elements.

[0016] Furthermore, the specific process of step 21 includes: setting the size of the quantum honey badger population to K, searching in the D-dimensional space, and mapping the quantum position of the k-th quantum honey badger in the t-th iteration into the position: in, k=1,2,...,K,d=1,2,...,D,the specific mapping rules are: Among them, U b and L b They are the upper and lower bounds of the quantum honey badger’s search interval.

[0017] Furthermore, the specific process of step 22 includes: calculating all quantum positions according to the fitness value until the optimal quantum honey badger position at the tth iteration is The suboptimal quantum honey badger position is The formula for updating the optimal position of the quantum honey badger is: Move towards the optimal solution and the suboptimal solution, where the values ​​of λ1 and λ2 are between [0,1] and sum to 1, The selection is made via a roulette mechanism.

[0018] Furthermore, the calculation formula of the hunger rate in steps 2 and 3 is:

[0019]

[0020] Where r is a random number between [0, 1], z is a random number between [-1, 1], T is the maximum number of iterations, t represents the tth iteration; η represents a random number between [-2, 2], and ν is a preset fixed value parameter.

[0021] Furthermore, the specific steps of step 24 include:

[0022] If r1 t <p1, when hunger rate |κ t |≥1,

[0023] The d-dimensional quantum rotation angle of the quantum honey badger is updated to:

[0024] The quantum position of the quantum honey badger is updated to:

[0025] Among them, r1 t is a random number between [0,1], is a random number between [0,1], is a random number between [0,1], is the optimal quantum position of the tth generation of quantum honey badger, u d and l d are the upper and lower limits of the dth dimension of the variable, d = 1, 2, ..., D;

[0026] If r1 t ≥p1, the d-dimensional quantum rotation angle of the quantum honey badger is updated to:

[0027]

[0028] The quantum position of the quantum honey badger is updated to:

[0029]

[0030] in, C is a constant; F is a flag to change the search direction, and its value is determined by Decide, is a random number between [0,1].

[0031] According to another aspect of the present invention, a wireless energy-carrying communication energy efficiency improvement system based on a smart reflective surface is proposed, the system comprising:

[0032] A model building module configured to build a total power receiving model of a wireless energy carrying communication energy harvesting receiver based on a smart reflective surface;

[0033] The optimization solution module is configured to take maximizing the total power received by the energy collection receiver as the objective function, and optimize and solve the objective function using the quantum honey badger algorithm; specifically including: initializing the quantum honey badger algorithm parameters; updating the optimal quantum honey badger position in the quantum honey badger population; determining the hunger rate of the quantum honey badger; evaluating the target fitness function, and the quantum honey badger searches for a better quantum position; stopping the iteration when the number of iterations is greater than or equal to the preset maximum number of iterations, outputting the global optimal quantum position of the quantum honey badger, obtaining the position according to the mapping rule and returning the optimal fitness value.

[0034] Further, the total power received by the wireless energy carrying communication energy harvesting receiver in the model building module is established based on the wireless energy carrying communication system, and the wireless energy carrying communication system is deployed as: an intelligent reflection surface with N reflection units to assist the wireless energy carrying communication system from an access point with M antennas to two groups of single antenna receivers, and the two groups of receivers are information decoding receivers and energy harvesting receivers; the total power received by the wireless energy carrying communication energy harvesting receiver model Q is expressed as:

[0035]

[0036] Where i is the information decoding receiver, Γ Ι is the information decoding receiver set; ω i is the precoding vector of information decoding receiver i, Indicates that ω i Find the conjugate transpose; j is the energy harvesting receiver, q j is the energy weight of j, Γ ε is a collection of energy harvesting receivers, is the baseband equivalent channel from the smart reflector to the energy harvesting receiver j, Θ is the reflection coefficient matrix of the smart reflector, G is the channel from the access point to the smart reflector, is the baseband equivalent channel from the access point to the energy harvesting receiver j; j is the precoding vector of the energy harvesting receiver j, and H represents the conjugate transpose of the corresponding elements.

[0037] Furthermore, the specific process of initializing the quantum honey badger algorithm parameters in the optimization solution module includes: setting the quantum honey badger population size to K, searching in the D-dimensional space, and mapping the quantum position of the k-th quantum honey badger in the t-th iteration into the position: in, k=1,2,...,K,d=1,2,...,D,the specific mapping rules are: Among them, U b and L b They are the upper and lower bounds of the quantum honey badger’s search interval respectively;

[0038] The specific process of updating the optimal quantum honey badger position in the quantum honey badger population includes: calculating all quantum positions according to the fitness value until the optimal quantum honey badger position until the tth iteration is The suboptimal quantum honey badger position is The formula for updating the optimal position of the quantum honey badger is: Move towards the optimal solution and the suboptimal solution, where the values ​​of λ1 and λ2 are between [0,1] and sum to 1, The selection is made via a roulette mechanism.

[0039] Furthermore, the calculation formula of the hunger rate in the optimization solution module is:

[0040]

[0041] Where r is a random number between [0,1], z is a random number between [-1,1], T is the maximum number of iterations, t represents the tth iteration; η represents a random number between [-2,2], and ν is a preset fixed value parameter;

[0042] The specific steps of evaluating the target fitness function and the quantum honey badger finding a better quantum position include:

[0043] If r1 t <p1, when hunger rate |κ t |≥1,

[0044] The d-dimensional quantum rotation angle of the quantum honey badger is updated to:

[0045] The quantum position of the quantum honey badger is updated to:

[0046] Among them, r1 t is a random number between [0,1], is a random number between [0,1], is a random number between [0,1], is the optimal quantum position of the tth generation of quantum honey badger, u d and l d are the upper and lower limits of the dth dimension of the variable, d = 1, 2, ..., D;

[0047] If r1 t ≥p1, the d-dimensional quantum rotation angle of the quantum honey badger is updated to:

[0048]

[0049] The quantum position of the quantum honey badger is updated to:

[0050]

[0051] in, C is a constant; F is a flag to change the search direction, and its value is determined by Decide, is a random number between [0,1].

[0052] The beneficial technical effects of the present invention are:

[0053] (1) The smart reflective surface technology of the present invention can significantly improve the total received power of the wireless power communication energy harvesting receiver. The present invention establishes an intelligent reflective surface including multiple reflective units to assist the wireless power communication system from an access point with multiple antennas to two groups of single-antenna receivers, the two groups of receivers being information decoding receivers and energy harvesting receivers. Based on the wireless power communication system, a total received power model of the wireless power communication energy harvesting receiver based on the smart reflective surface is established, which significantly improves the communication energy efficiency of the wireless power communication.

[0054] (2) The present invention applies the proposed quantum honey badger algorithm to the problem of optimizing the total received power of a wireless energy-carrying communication energy harvesting receiver based on a smart reflective surface, providing a preliminary attempt to solve the problem in engineering practice. Experimental data show that the quantum honey badger algorithm has significant advantages in both search speed and search accuracy. In future work, the quantum honey badger algorithm will be more widely used in a wider range of engineering application environments due to its advantages in solving complex optimization and high-dimensional optimization problems.

[0055] (3) Based on the honey badger algorithm, quantum coding and simulated quantum rotating gate, the present invention proposes a quantum honey badger algorithm, which updates the quantum position through a cleverly designed quantum rotation angle and quantum rotating gate. The most essential feature of quantum computing is the use of the superposition and coherence of quantum states and the entanglement between quantum bits to accelerate the quantum parallelism of computing speed. In this way, the search accuracy and search speed of the newly designed algorithm are significantly improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] The present invention can be better understood by referring to the description given below in conjunction with the accompanying drawings, which together with the following detailed description are included in this specification and form a part of this specification, and are used to further illustrate the preferred embodiments of the present invention and explain the principles and advantages of the present invention.

[0057] Figure 1 It is a flow chart of a method for improving energy efficiency of wireless energy-carrying communication based on a smart reflective surface described in an embodiment of the present invention;

[0058] Figure 2 is a curve diagram showing the variation of the total received power of the method for improving energy efficiency of wireless energy-carrying communication of an intelligent reflective surface based on the present invention and the traditional honey badger algorithm with the number of iterations when M=4 and N=50 in an embodiment of the present invention;

[0059] Figure 3 It is a curve diagram showing the variation of the total received power of the method for improving energy efficiency of wireless energy-carrying communication of an intelligent reflective surface based on the traditional honey badger algorithm with the number of iterations when M=8 and N=100 in an embodiment of the present invention;

[0060] Figure 4 It is a curve diagram of the total received power of the method for improving energy efficiency of wireless energy-carrying communication of an intelligent reflective surface based on the traditional honey badger algorithm and the number of access point antennas in the embodiment of the present invention;

[0061] Figure 5 It is a curve diagram showing the variation of the total received power of the smart reflective surface wireless energy-carrying communication energy efficiency improvement method of the present invention and the traditional honey badger algorithm in an embodiment of the present invention with the number of reflective units of the smart reflective surface. DETAILED DESCRIPTION

[0062] In order to enable those skilled in the art to better understand the scheme of the present invention, exemplary implementations or embodiments of the present invention will be described below in conjunction with the accompanying drawings. Obviously, the described implementations or embodiments are only implementations or embodiments of a part of the present invention, not all of them. Based on the implementations or embodiments of the present invention, all other implementations or embodiments obtained by ordinary technicians in the field without creative work should fall within the scope of protection of the present invention.

[0063] In the first embodiment of the present invention, a method for improving energy efficiency of wireless energy-carrying communication based on a smart reflective surface is proposed. Figure 1 As shown, the method comprises the following steps:

[0064] Step 1: Establish a total power receiving model of a wireless energy-carrying communication energy harvesting receiver based on a smart reflective surface;

[0065] Step 2: maximizing the total power received by the energy harvesting receiver is used as the objective function, and the objective function is optimized and solved using the quantum honey badger algorithm; specifically, the following steps are included:

[0066] Step 21. Initialize the parameters of the quantum honey badger algorithm;

[0067] Step 22: Update the optimal quantum honey badger position in the quantum honey badger population;

[0068] Step 23: Determine the hunger rate of the quantum honey badger;

[0069] Step 24: Evaluate the target fitness function, and the quantum honey badger looks for a better quantum position;

[0070] Step 25: When the number of iterations is greater than or equal to the preset maximum number of iterations, stop the iteration, output the global optimal quantum position of the quantum honey badger, obtain the position according to the mapping rule and return the optimal fitness value.

[0071] First, step one is performed. In step one, a total power receiving model of a wireless energy-carrying communication energy harvesting receiver based on a smart reflective surface is established.

[0072] According to an embodiment of the present invention, a new wireless energy-carrying communication system assisted by a smart reflective surface is proposed, which maximizes the total power received by the energy harvesting receiver by jointly optimizing the transmit precoder at the access point and the phase shift at the smart reflective surface.

[0073] Consider a wireless network assisted by a smart reflective surface, where a smart reflective surface with N reflective units is deployed to assist a wireless energy-carrying communication system from an access point with M antennas to two sets of single-antenna receivers, which are information decoding receivers and energy harvesting receivers. The transmission signal at the access point is expressed as in and is the precoding vector for information decoding receiver i and energy harvesting receiver j, and is the information carrying signal and the energy carrying signal, Γ Ι ={1,2,...,K I} and Γ ε ={1,2,...,K E} is the information decoding receiver set and the energy harvesting receiver set. Assuming that the access point has a total transmit power budget P, then and are the baseband equivalent channels from the access point to the information decoding receiver i and from the smart reflector to the information decoding receiver i, respectively. and is the baseband equivalent channel from the access point to the energy harvesting receiver j and from the smart reflective surface to the energy harvesting receiver j. The channel from the access point to the smart reflective surface is given by express. represents the reflection coefficient matrix of the smart reflective surface, where and θ n ∈[0,2π) represent the reflection amplitude and phase shift of the nth reflection unit respectively. The signal-to-noise ratio of information decoding receiver i is in σ 2 represents the average noise power. The goal is to maximize the total power received by the energy harvesting receiver under the signal-to-noise ratio constraints of different information decoding receivers. The energy weight of the energy harvesting receiver j is given by q j represents, and H represents the conjugate transpose of the corresponding elements. The weighted total power received by all energy harvesting receivers can be expressed as:

[0074]

[0075] in

[0076] Through the above analysis, for the wireless energy-carrying communication system including the smart reflective surface, the optimization goal is set to maximize the total power received by the energy harvesting receiver, which is specifically expressed as The constraints are: SINR i ≥γ i , 0≤θ n ≤2π. The parameters to be solved to maximize the total received power are: the precoding vector ω of the information decoding receiver i i , the precoding vector υ of the energy harvesting receiver j j , the reflection coefficient matrix Θ of the smart reflection surface.

[0077] Then, step 2 is performed, in which maximizing the total power received by the energy harvesting receiver is taken as the objective function, and the objective function is optimized and solved using the quantum honey badger algorithm.

[0078] First, in step 21, the quantum honey badger algorithm parameters are initialized.

[0079] Specifically, the quantum honey badger population is assumed to consist of K quantum honey badgers, and the search space dimension of each quantum honey badger is D, which represents the dimension of the problem to be solved. The quantum position of the kth quantum honey badger of the tth generation is expressed as in k=1,2,...,K,d=1,2,...,D。According to the mapping rule, the position of the kth quantum honey badger is obtained The specific mapping rules are: Among them U d and L d Represents the upper and lower bounds of the dth dimension of the quantum honey badger's search interval.

[0080] The quantum position of each quantum honey badger corresponds to an optimization scheme for the total received power of a wireless energy-carrying communication energy harvesting receiver based on a smart reflective surface. The fitness of the k-th quantum honey badger position of the t-th generation is calculated by the fitness function (i.e., objective function) of the optimization problem of the total received power of a wireless energy-carrying communication energy harvesting receiver based on a smart reflective surface. After generating the initial quantum honey badger position, the total received power optimization problem of the wireless energy-carrying communication energy harvesting receiver based on a smart reflective surface is used as the objective function to evaluate it. Calculate the fitness of the k-th quantum honey badger position of the t-th generation, and its value also represents the fitness of the corresponding k-th quantum honey badger position of the t-th generation.

[0081] Then in step 22, the optimal quantum honey badger position in the quantum honey badger population is updated.

[0082] Specifically, after forming the initial population, the fitness of all solutions is calculated. is the optimal quantum honey badger position up to the tth generation, is the suboptimal quantum honey badger position up to the tth generation, and the optimal quantum honey badger position is calculated according to the formula Update, move towards the optimal and suboptimal solutions. Where λ1 and λ2 are parameters to be determined before the search operation, the values ​​are between 0 and 1, and the sum of the two parameters is 1. Use roulette to decide, thus obtaining the probability of selecting the best solution.

[0083] Then in steps two and three, determine the hunger rate of the quantum honey badger.

[0084] Specifically, quantum honey badgers are constantly looking for food, and if they are full, they have high energy, which allows them to walk longer distances to find food, but if they are hungry, they do not have enough energy to walk longer distances to find food next to stronger quantum honey badgers, and become aggressive when hungry. To establish a mathematical model of this behavior, the hunger rate formula is:

[0085]

[0086] where r is a random number between 0 and 1, z is a random number between -1 and 1, η is a random number between -2 and 2, and ν is a parameter that is set to a fixed value before the optimization operation.

[0087] Then in step 24, the target fitness function is evaluated and the quantum honey badger searches for a better quantum position.

[0088] Specifically, generate a random number r1 between 0 and 1 t , if r1 t <p1, when hunger rate |κ t When |≥1, the d-dimensional quantum rotation angle of the quantum honey badger is updated to in is a random number between 0 and 1, is a random number between 0 and 1, is the optimal quantum position of the tth generation of quantum honey badger, u d and l d is the upper and lower limits of the variable d-th dimension, and the quantum position of the quantum honey badger is updated to d=1,2,…,D.

[0089] If r1 t ≥p1, the d-dimensional quantum rotation angle of the quantum honey badger is updated to in T is the maximum number of iterations, C is a constant, and F is used as a flag to change the search direction. Its value is determined by Decision, among which is a random number between 0 and 1. The quantum position of the quantum honey badger is updated to

[0090] Finally, in step 25, if the number of iterations is less than the preset maximum number of iterations, set t=t+1 and return to step 22; otherwise, the iteration terminates, the global optimal quantum position of the quantum honey badger is output, the position is obtained according to the mapping rule, and the optimal fitness value is returned.

[0091] The technical effect of the present invention is further verified through experiments.

[0092] For the wireless energy-carrying communication system based on smart reflective surface, the experimental parameters are set as follows: quantum honey badger population size K = 50, density factor constant C = 2, optimized operation parameter ν = 2.5, and upper and lower limits of variables u d and l d are 100 and -100 respectively. The initial quantum position of the quantum honey badger is randomly generated in the quantum position definition domain. In order to compare the performance of the proposed quantum honey badger mechanism, the traditional honey badger algorithm is applied to solve the total power optimization problem of the energy harvesting receiver for smart reflective surface wireless energy communication as a comparison, and the population size of the two is set to the same value, the maximum number of iterations is 1000 times, and all comparison results are the average of 100 simulation experiments. The other parameter settings of the honey badger algorithm refer to [1].

[0093] Figure 2 A curve graph showing how the total received power of the method for improving the energy efficiency of wireless energy-carrying communication on an intelligent reflective surface based on the quantum honey badger algorithm and the traditional honey badger algorithm varies with the number of iterations when M=4 and N=50 are set is given.

[0094] Figure 3 The graph of the total received power versus the number of iterations of the energy efficiency improvement method of the intelligent reflective surface wireless energy communication based on the quantum honey badger algorithm and the traditional honey badger algorithm is given when M=8 and N=100. Figure 3 The simulation results show that the total received power of the quantum honey badger algorithm designed by the present invention increases with the increase of the number of access point antennas and the number of reflective elements of the intelligent reflective surface. Obviously, the quantum honey badger algorithm is significantly better than the honey badger algorithm in terms of convergence performance.

[0095] Figure 4 The curves of the total received power of the energy efficiency improvement method of the intelligent reflector wireless energy communication based on the quantum honey badger algorithm and the traditional honey badger algorithm are given. The number of base station antennas in the simulation increases from 3 to 10. Figure 4 It can be seen from the simulation test that as the number of access point antennas increases, the total received power basically maintains an upward trend, and the quantum honey badger algorithm always maintains the best performance. When the number of access point antennas is fixed, the total received power can be increased by increasing the number of reflective units of the smart reflective surface.

[0096] Figure 5 A curve diagram showing the change of the total received power of the smart reflective surface wireless energy communication energy efficiency improvement method based on the quantum honey badger algorithm and the traditional honey badger algorithm as the number of reflective units in the simulation increases from 30 to 100 is given. Figure 5It can be seen from the simulation curve that as the number of reflective units of the intelligent reflective surface increases, the total received power designed by the present invention maintains an increasing trend, and the quantum honey badger algorithm always performs best. When the number of reflective units of the intelligent reflective surface is fixed, the total received power can be increased by increasing the number of access point antennas.

[0097] Another embodiment of the present invention provides a wireless energy-carrying communication energy efficiency improvement system based on a smart reflective surface, the system comprising:

[0098] A model building module configured to build a total power receiving model of a wireless energy carrying communication energy harvesting receiver based on a smart reflective surface;

[0099] The optimization solution module is configured to take maximizing the total power received by the energy collection receiver as the objective function, and optimize and solve the objective function using the quantum honey badger algorithm; specifically including: initializing the quantum honey badger algorithm parameters; updating the optimal quantum honey badger position in the quantum honey badger population; determining the hunger rate of the quantum honey badger; evaluating the target fitness function, and the quantum honey badger searches for a better quantum position; stopping the iteration when the number of iterations is greater than or equal to the preset maximum number of iterations, outputting the global optimal quantum position of the quantum honey badger, obtaining the position according to the mapping rule and returning the optimal fitness value.

[0100] In this embodiment, preferably, the total power received model of the wireless energy carrying communication energy harvesting receiver in the model building module is established based on the wireless energy carrying communication system, and the wireless energy carrying communication system is deployed as: an intelligent reflection surface with N reflection units to assist the wireless energy carrying communication system from an access point with M antennas to two groups of single-antenna receivers, and the two groups of receivers are information decoding receivers and energy harvesting receivers; the total power received model Q of the wireless energy carrying communication energy harvesting receiver is expressed as:

[0101]

[0102] Where i is the information decoding receiver, Γ Ι is the information decoding receiver set; ω i is the precoding vector of information decoding receiver i, Indicates that ω i Find the conjugate transpose; j is the energy harvesting receiver, q j is the energy weight of j, Γ ε is a collection of energy harvesting receivers, is the baseband equivalent channel from the smart reflector to the energy harvesting receiver j, Θ = is the reflection coefficient matrix of the smart reflector, G is the channel from the access point to the smart reflector, is the baseband equivalent channel from the access point to the energy harvesting receiver j;j is the precoding vector of the energy harvesting receiver j, and H represents the conjugate transpose of the corresponding elements.

[0103] In this embodiment, preferably, the specific process of initializing the quantum honey badger algorithm parameters in the optimization solution module includes: setting the quantum honey badger population size to K, searching in the D-dimensional space, and mapping the quantum position of the k-th quantum honey badger in the t-th iteration to the position: in, k=1,2,...,K,d=1,2,...,D,the specific mapping rules are: Among them, U b and L b They are the upper and lower bounds of the quantum honey badger’s search interval respectively;

[0104] The specific process of updating the optimal quantum honey badger position in the quantum honey badger population includes: calculating all quantum positions according to the fitness value until the optimal quantum honey badger position until the tth iteration is The suboptimal quantum honey badger position is The formula for updating the optimal position of the quantum honey badger is: Move towards the optimal solution and the suboptimal solution, where the values ​​of λ1 and λ2 are between [0,1] and sum to 1, The selection is made via a roulette mechanism.

[0105] In this embodiment, preferably, the calculation formula of the hunger rate in the optimization solution module is:

[0106]

[0107] Where r is a random number between [0,1], z is a random number between [-1,1], T is the maximum number of iterations, t represents the tth iteration; η represents a random number between [-2,2], and ν is a preset fixed value parameter;

[0108] The specific steps of evaluating the target fitness function and the quantum honey badger finding a better quantum position include:

[0109] If r1 t <p1, when hunger rate |κ t |≥1,

[0110] The d-dimensional quantum rotation angle of the quantum honey badger is updated to:

[0111] The quantum position of the quantum honey badger is updated to:

[0112] Among them, r1 t is a random number between [0,1], is a random number between [0,1], is a random number between [0,1], is the optimal quantum position of the tth generation of quantum honey badger, u d and l d are the upper and lower limits of the dth dimension of the variable, d = 1, 2, ..., D;

[0113] If r1 t ≥p1, the d-dimensional quantum rotation angle of the quantum honey badger is updated to:

[0114]

[0115] The quantum position of the quantum honey badger is updated to:

[0116]

[0117] in, C is a constant; F is a flag to change the search direction, and its value is determined by Decide, is a random number between [0,1].

[0118] The functions of a wireless power-carrying communication energy efficiency improvement system based on an intelligent reflective surface in an embodiment of the present invention can be described by the aforementioned wireless power-carrying communication energy efficiency improvement method based on an intelligent reflective surface. Therefore, for the parts not described in detail in the system embodiment, please refer to the above method embodiment and will not be repeated here.

[0119] Although the present invention has been described according to a limited number of embodiments, it will be apparent to those skilled in the art, with the benefit of the above description, that other embodiments are contemplated within the scope of the invention thus described. The disclosure of the present invention is intended to be illustrative rather than restrictive of the scope of the invention, which is defined by the appended claims.

[0120] The present invention cites the following documents:

[0121] [1]Fatma A.Hashima.Honey Badger Algorithm: New metaheuristic algorithm for solving optimization problems. "Mathematics and Computers in Simulation", 2022:84-110.

Claims

1. A method for improving energy efficiency of wireless energy-carrying communication based on a smart reflective surface, characterized in that: The following steps are involved: Step 1: Establish a total power receiving model of a wireless energy-carrying communication energy harvesting receiver based on a smart reflective surface; Maximizing the total power received by the energy harvesting receiver by jointly optimizing the transmit precoder at the access point and the phase shift at the smart reflective surface; The transmission signal at the access point is represented as in and is the precoding vector for information decoding receiver i and energy harvesting receiver j, and is the information carrying signal and the energy carrying signal, Γ Ι ={1,2,...,K I } and Γ ε ={1,2,...,K E } is an information decoding receiver set and an energy harvesting receiver set; Assuming that the access point has a total transmit power budget P, then and are the baseband equivalent channels from the access point to the information decoding receiver i and from the smart reflector to the information decoding receiver i, respectively. and is the baseband equivalent channel from the access point to the energy harvesting receiver j and from the smart reflective surface to the energy harvesting receiver j. The channel from the access point to the smart reflective surface is given by express; represents the reflection coefficient matrix of the smart reflective surface, where and θ n ∈[0,2π) represent the reflection amplitude and phase shift of the nth reflection unit respectively; The signal-to-noise ratio of information decoding receiver i is in σ 2 represents the average noise power; Step 2: maximizing the total power received by the energy harvesting receiver is used as the objective function, and the objective function is optimized and solved using the quantum honey badger algorithm; specifically, the following steps are included: Step 21. Initialize the parameters of the quantum honey badger algorithm; Step 22: Update the optimal quantum honey badger position in the quantum honey badger population; Step 23: Determine the hunger rate of the quantum honey badger; Step 24: Evaluate the target fitness function, and the quantum honey badger looks for a better quantum position; Step 25: When the number of iterations is greater than or equal to the preset maximum number of iterations, stop the iteration, output the global optimal quantum position of the quantum honey badger, obtain the position according to the mapping rule and return the optimal fitness value.

2. According to claim 1, a method for improving energy efficiency of wireless energy-carrying communication based on a smart reflective surface is characterized in that: The total power model of the wireless energy-carrying communication energy harvesting receiver in step 1 is established based on the wireless energy-carrying communication system, and the wireless energy-carrying communication system is deployed as: an intelligent reflection surface with N reflection units to assist the wireless energy-carrying communication system from an access point with M antennas to two groups of single-antenna receivers, and the two groups of receivers are information decoding receivers and energy harvesting receivers; the total power model Q of the wireless energy-carrying communication energy harvesting receiver is expressed as: Where i is the information decoding receiver, Γ Ι is the information decoding receiver set; ω i is the precoding vector of information decoding receiver i, ω means i υFind the conjugate transpose of υ; j is the energy harvesting receiver, q j is the energy weight of j, Γ ε is a collection of energy harvesting receivers, is the baseband equivalent channel from the smart reflector to the energy harvesting receiver j, Θ is the reflection coefficient matrix of the smart reflector, G is the channel from the access point to the smart reflector, is the baseband equivalent channel from the access point to the energy harvesting receiver j; j is the precoding vector of the energy harvesting receiver j, and H represents the conjugate transpose of the corresponding elements.

3. The method for improving energy efficiency of wireless energy-carrying communication based on a smart reflective surface according to claim 2, characterized in that: The specific process of step 21 includes: setting the size of the quantum honey badger population to K, searching in the D-dimensional space, and mapping the quantum position of the k-th quantum honey badger in the t-th iteration into the position: in, k=1,2,...,K,d=1,2,...,D,the specific mapping rules are: Among them, U d and L d They are the upper and lower bounds of the quantum honey badger’s search interval.

4. The method for improving energy efficiency of wireless energy-carrying communication based on a smart reflective surface according to claim 3, characterized in that: The specific process of step 22 includes: calculating all quantum positions according to the fitness value until the optimal quantum honey badger position at the tth iteration is The suboptimal quantum honey badger position is The formula for updating the optimal position of the quantum honey badger is: Move towards the optimal solution and the suboptimal solution, where the values ​​of λ1 and λ2 are between [0,1] and sum to 1, The selection is made via a roulette mechanism.

5. The method for improving energy efficiency of wireless energy-carrying communication based on intelligent reflective surface according to claim 4, characterized in that: The calculation formula for the hunger rate described in steps 2 and 3 is: Where r is a random number between [0, 1], z is a random number between [-1, 1], T is the maximum number of iterations, t represents the tth iteration; η represents a random number between [-2, 2], and ν is a preset fixed value parameter.

6. The method for improving energy efficiency of wireless energy-carrying communication based on smart reflective surface according to claim 5, characterized in that: The specific steps of step 24 include: If r1 t <p1, when hunger rate |κ t |≥1, The d-dimensional quantum rotation angle of the quantum honey badger is updated to: The quantum position of the quantum honey badger is updated to: Among them, r1 t is a random number between [0,1], is a random number between [0,1], is a random number between [0,1], is the optimal quantum position of the tth generation of quantum honey badger, u d and l d are the upper and lower limits of the dth dimension of the variable, d = 1, 2, ..., D; If r1 t ≥p1, the d-dimensional quantum rotation angle of the quantum honey badger is updated to: The quantum position of the quantum honey badger is updated to: in, C is a constant; F is a flag to change the search direction, and its value is determined by Decision, r f t is a random number between [0,1].

7. A wireless energy communication energy efficiency improvement system based on intelligent reflective surface, characterized in that: include: A model building module configured to build a total power receiving model of a wireless energy carrying communication energy harvesting receiver based on a smart reflective surface; Maximizing the total power received by the energy harvesting receiver by jointly optimizing the transmit precoder at the access point and the phase shift at the smart reflective surface; The transmission signal at the access point is represented as in and is the precoding vector for information decoding receiver i and energy harvesting receiver j, and is the information carrying signal and the energy carrying signal, Γ Ι ={1,2,...,K I } and Γ ε ={1,2,...,K E } is an information decoding receiver set and an energy harvesting receiver set; Assuming that the access point has a total transmit power budget P, then and are the baseband equivalent channels from the access point to the information decoding receiver i and from the smart reflector to the information decoding receiver i, respectively. and is the baseband equivalent channel from the access point to the energy harvesting receiver j and from the smart reflective surface to the energy harvesting receiver j. The channel from the access point to the smart reflective surface is given by express; represents the reflection coefficient matrix of the smart reflective surface, where and θ n ∈[0,2π) represent the reflection amplitude and phase shift of the nth reflection unit respectively; the signal-to-noise ratio of the information decoding receiver i is in σ 2 represents the average noise power; The optimization solution module is configured to take maximizing the total power received by the energy collection receiver as the objective function, and optimize and solve the objective function using the quantum honey badger algorithm; specifically including: initializing the quantum honey badger algorithm parameters; updating the optimal quantum honey badger position in the quantum honey badger population; determining the hunger rate of the quantum honey badger; evaluating the target fitness function, and the quantum honey badger searches for a better quantum position; stopping the iteration when the number of iterations is greater than or equal to the preset maximum number of iterations, outputting the global optimal quantum position of the quantum honey badger, obtaining the position according to the mapping rule and returning the optimal fitness value.

8. The wireless energy communication energy efficiency improvement system based on intelligent reflective surface according to claim 7 is characterized in that: The total power model of the wireless energy-carrying communication energy harvesting receiver in the model building module is established based on the wireless energy-carrying communication system, and the wireless energy-carrying communication system is deployed as: an intelligent reflection surface with N reflection units to assist the wireless energy-carrying communication system from an access point with M antennas to two groups of single-antenna receivers, and the two groups of receivers are information decoding receivers and energy harvesting receivers; the total power model Q of the wireless energy-carrying communication energy harvesting receiver is expressed as: Where i is the information decoding receiver, Γ Ι is the information decoding receiver set; ω i is the precoding vector of information decoding receiver i, ω means i υFind the conjugate transpose of υ; j is the energy harvesting receiver, q j is the energy weight of j, Γ ε is a collection of energy harvesting receivers, is the baseband equivalent channel from the smart reflector to the energy harvesting receiver j, Θ is the reflection coefficient matrix of the smart reflector, G is the channel from the access point to the smart reflector, is the baseband equivalent channel from the access point to the energy harvesting receiver j; j is the precoding vector of the energy harvesting receiver j, and H represents the conjugate transpose of the corresponding elements.

9. The wireless energy communication energy efficiency improvement system based on intelligent reflective surface according to claim 8, characterized in that: The specific process of initializing the quantum honey badger algorithm parameters in the optimization solution module includes: setting the quantum honey badger population size to K, searching in the D-dimensional space, and mapping the quantum position of the k-th quantum honey badger in the t-th iteration to the position: in, k=1,2,...,K,d=1,2,...,D,the specific mapping rules are: Among them, U d and L d They are the upper and lower bounds of the quantum honey badger’s search interval respectively; The specific process of updating the optimal quantum honey badger position in the quantum honey badger population includes: calculating all quantum positions according to the fitness value until the optimal quantum honey badger position until the tth iteration is The suboptimal quantum honey badger position is The formula for updating the optimal position of the quantum honey badger is: Move towards the optimal solution and the suboptimal solution, where the values ​​of λ1 and λ2 are between [0,1] and sum to 1, The selection is made via a roulette mechanism.

10. The wireless energy communication energy efficiency improvement system based on intelligent reflective surface according to claim 9, characterized in that: The calculation formula of the hunger rate in the optimization solution module is: Where r is a random number between [0,1], z is a random number between [-1,1], T is the maximum number of iterations, t represents the tth iteration; η represents a random number between [-2,2], and ν is a preset fixed value parameter; The specific steps of evaluating the target fitness function and the quantum honey badger finding a better quantum position include: If r1 t <p1, when hunger rate |κ t |≥1, The d-dimensional quantum rotation angle of the quantum honey badger is updated to: The quantum position of the quantum honey badger is updated to: Among them, r1 t is a random number between [0,1], is a random number between [0,1], is a random number between [0,1], is the optimal quantum position of the tth generation of quantum honey badger, u d and l d are the upper and lower limits of the dth dimension of the variable, d = 1, 2, ..., D; If r1 t ≥p1, the d-dimensional quantum rotation angle of the quantum honey badger is updated to: The quantum position of the quantum honey badger is updated to: in, C is a constant; F is a flag to change the search direction, and its value is determined by Decide, is a random number between [0,1].

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