Wireless energy supply electric power communication network coverage enhancement method and system

Abstract

The invention relates to the technical field of intelligent power grids, in particular to a wireless energy supply electric power communication network coverage enhancement method and system, and the method comprises the steps: configuring a full duplex hybrid access point by an FD-WPCN model, integrating multiple transmitting and receiving antenna arrays, and achieving the synchronization of downlink energy transmission and uplink information receiving. Energy and information transmission is optimized through a beam forming technology, and an expected total energy expression collected by a user in a downlink is derived. And further deriving a user traversal rate formula based on the energy collection characteristics. Under the constraint of maximizing the minimum rate of all users, an energy distribution optimization problem is established, and an optimal closed-form solution of energy distribution is obtained through mathematical derivation. According to the solution, fair optimization of energy coverage among users can be realized, and the overall energy efficiency and communication reliability of the system are improved. The model is suitable for a wireless power supply communication network scene, provides theoretical support for resource allocation, and has remarkable application value.

Description

Technical Field

[0001] This invention relates to the field of smart grid technology, and specifically to a method and system for enhancing the coverage of wireless power supply communication networks. Background Technology

[0002] The rapid development of smart grids and IoT has made power communication networks increasingly important, requiring support for a large number of battery-powered devices in complex environments. Due to the high cost and complexity of battery replacement, Wireless Power Communication Networks (WPCNs) have been introduced to provide power via radio frequency signals. However, the power of devices in WPCNs is limited by radio frequency power, propagation distance, and channel fading. As the number of devices increases, the power of edge devices becomes insufficient, leading to a decrease in power and information coverage, and affecting grid stability.

[0003] Existing solutions use multi-antenna beamforming technology to concentrate radio frequency energy in a specific direction, thereby improving the energy harvesting capability of edge devices and thus improving coverage. Energy and information transmission mostly adopt half-duplex (HD) mode, while some attempts are made to use full-duplex (FD) mode to improve spectrum utilization, in an attempt to alleviate the energy and information coverage problem.

[0004] In smart grid operation, without considering the optimization of energy and information coverage in the Power Supply Communication Network (WPCN), all devices will face insufficient energy supply, especially edge devices. In existing technologies, energy and information transmission typically employ half-duplex (HD) mode, which cannot simultaneously transmit energy and receive information, leading to wasted spectrum resources and limited coverage performance. Furthermore, while full-duplex (FD) mode can improve spectrum utilization, downlink energy transmission can cause self-interference with uplink information reception, severely impacting system performance. These problems make it difficult for edge devices to collect sufficient energy, thus affecting the rate and stability of information transmission, ultimately reducing the operational efficiency and reliability of the power grid system. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a method and related equipment for enhancing the coverage of wireless power supply communication networks, which addresses the shortcomings of the prior art and solves the technical problem of reduced coverage caused by the energy QoS limitation of current wireless power supply communication network equipment.

[0006] The objective of this invention is achieved through the following technical solutions: In a first aspect, the present invention provides a method for enhancing coverage of a wireless power supply communication network, comprising: Construct a multi-user MIMO FD-WPCN model, in which a full-duplex hybrid access point is configured. The hybrid access point is equipped with several transmit antennas and receive antennas for transmitting downlink energy to multiple single-antenna users and receiving uplink information. Using beamforming technology to transmit downlink energy to users and receive uplink information, the expected total energy collected by each user on the downlink is determined; The user's traversal rate is derived based on the total collected energy. Under the constraint of maximizing the minimum rate of all users, the energy allocation is optimized based on the traversal rate to obtain the optimal closed-form solution for energy allocation. Based on the optimal closed-form solution, energy is allocated to each user to optimize the energy coverage among users.

[0007] As a further improvement of the present invention, in the FD-WPCN model, the hybrid access point receives uplink information from the user through the uplink channel matrix, and the hybrid access point transmits downlink energy to the user through the downlink channel matrix. The uplink channel matrix is ​​as follows:

[0008] The downlink channel matrix is ​​as follows:

[0009] In the formula, For the uplink channel matrix, This represents the small-scale fading channel matrix of the uplink channel. Let K be the K-order diagonal matrix of the uplink channel. This is the downlink channel matrix. This represents the small-scale fading channel matrix of the downlink channel. Let be the K-order diagonal matrix of the downlink channel.

[0010] As a further improvement of the present invention, before communication, the user sends a pilot sequence of a set length to the hybrid access point in the FD-WPCN model, and estimates the uplink channel matrix and downlink channel matrix based on the pilot sequence; Interference signals in the uplink and downlink channel matrices under full-duplex mode are suppressed by radio frequency domain self-interference cancellation technology.

[0011] As a further improvement of the present invention, the communication process of the FD-WPCN model includes: Using beamforming technology, all users receive downlink energy from the downlink channel of the hybrid access point, and the downlink energy is collected to obtain the expected total energy; the energy used for uplink transmission information in the predicted total energy is collected from the k+1th time period of the previous transmission time slot to the current transmission time slot.

[0012] As a further improvement of the present invention, the expected total energy collected by each user on the downlink is determined, and the expected total energy is expressed as:

[0013] in,

[0014] In the formula, For the energy expected to be collected on the user's downlink, For the expected total energy, For energy conversion efficiency, This refers to the downlink transmission power. This is the transpose of the uplink and downlink channel vectors of the k-th user. The duration of a single time period. For downlink beamforming vectors, For expectation operators.

[0015] As a further improvement of the present invention, the user's traversal rate is:

[0016] In the formula, The duration of a single time period. As expected, For signal-to-interference-plus-noise ratio.

[0017] As a further improvement of the present invention, the hybrid access point employs maximum ratio combining technology when receiving uplink information to detect the radio frequency (RF) signal in the user's uplink received information and maximize the power of the detected RF signal, wherein the RF signal is:

[0018] In the formula, This refers to the radio frequency signal in the uplink information. This refers to the downlink transmission power. This is the transpose of the self-interference channel matrix. For downlink power transmission cells, For downlink beamforming vectors, This is the uplink noise vector at the hybrid access point. Uplink transmission power for users, It is the square of the magnitude of the uplink channel vector. For uplink transmission cells, the expected total energy of the uplink transmission power and the duration of k time periods are obtained.

[0019] As a further improvement of the present invention, the maximization of minimum fairness constraint is as follows:

[0020] In the formula, For the energy allocation optimization function, Let k be the traversal rate. Let K be the power allocation coefficient for user k, where K is the total number of users.

[0021] As a further improvement of the present invention, the closed-form solution for the energy allocation optimization is:

[0022]

[0023]

[0024] In the formula, The optimal power allocation factor is... The number of transmitting antennas, For the total number of users, For the composite channel quality of the k-th user, The duration of a single time period. This is the optimal approximate solution for the k-th user. For fixed parameters of the environment and equipment, For energy conversion efficiency, For the downlink transmission power of the hybrid access point, The background noise power at the user receiver. This is a variable used to eliminate self-interference.

[0025] In a second aspect, the present invention provides a wireless power supply communication network coverage enhancement system, comprising: The channel construction module constructs a multi-user MIMO FD-WPCN model. The FD-WPCN model is configured with a full-duplex hybrid access point. The hybrid access point is equipped with several transmit antennas and receive antennas for transmitting downlink energy to multiple single-antenna users and receiving uplink information. The energy harvesting module uses beamforming technology to transmit downlink energy to users and receive uplink information, and determines the expected total energy collected by each user on the downlink. The user rate derivation module derives the user's traversal rate based on the total collected energy. The energy optimization module optimizes energy allocation based on the traversal rate under the constraint of maximizing the minimum rate of all users, and obtains the optimal closed-form solution for energy allocation. Based on the optimal closed-form solution, energy is allocated to each user to optimize the energy coverage among users.

[0026] The beneficial effects of this invention are as follows: This invention provides a method for enhancing the coverage of a wireless power communication network. It constructs an FD-WPCN model with a full-duplex hybrid access point configured with multiple user MIMO. This access point has several transmit and receive antennas for downlink energy transmission and uplink information reception to multiple single-antenna users. Therefore, during communication, beamforming technology is used to determine the expected total energy collected by each user on the downlink. Based on this total energy, the traversal rate of the user is derived. Under the constraint of maximizing the minimum rate of all users, energy allocation is optimized based on the traversal rate to obtain the optimal closed-form solution for energy allocation. Based on this optimal closed-form solution, energy is allocated to each user. Through the synergistic effect of the above model construction, energy acquisition, rate derivation, and energy allocation optimization, the technical problem of energy coverage optimization among users is solved, achieving optimization of energy coverage among users and ensuring optimal energy allocation under the constraint of maximizing the minimum rate of all users. Attached Figure Description

[0027] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0028] Figure 1 This is a schematic flowchart of the wireless power supply communication network coverage enhancement method in an embodiment of the present invention; Figure 2 This is a graph showing the relationship between the uplink information coverage probability of FD-WPCN and the average user distance in an embodiment of the present invention; Figure 3 This is a graph showing the relationship between downlink energy coverage probability and the number of antennas for the FD-WPCN in an embodiment of the present invention; Figure 4 This is a graph showing the relationship between the FD-WPCN user rate and total rate and the number of antennas in an embodiment of the present invention; Figure 5 This is a graph showing the relationship between FD-WPCN user rate and total rate and the number of users in an embodiment of the present invention; Detailed Implementation To make the objectives and technical solutions of this invention clearer and easier to understand, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. The specific embodiments described herein are for illustrative purposes only and are not intended to limit the invention.

[0029] The technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings and specific embodiments. The described embodiments are only some embodiments of the present invention, and not all embodiments.

[0030] Example 1 like Figure 1 As shown, this embodiment provides a method for enhancing the coverage of a wireless power communication network, mainly including: constructing a multi-user MIMO FD-WPCN model; wherein, the FD-WPCN model is configured with a full-duplex hybrid access point, and the hybrid access point is equipped with several transmit antennas and receive antennas for transmitting downlink energy and receiving uplink information to multiple single-antenna users; during the communication process of the FD-WPCN model, beamforming technology is used to transmit downlink energy and receive uplink information to users, and the expected total energy collected by each user on the downlink is determined; based on the collected total energy, the traversal rate of the user is derived; under the constraint of maximizing the minimum rate of all users, the energy allocation is optimized based on the traversal rate to obtain the optimal closed-form solution for energy allocation, and the energy is allocated to each user based on the optimal closed-form solution to achieve optimization of energy coverage among users. In this embodiment, an FD-WPCN model of multi-user MIMO is constructed by configuring a full-duplex hybrid access point (which has several transmit and receive antennas). Beamforming technology is used to transmit downlink energy and receive uplink information from the hybrid access point to multiple single-antenna users. The expected total energy collected by each user on the downlink is determined, and the ergodic rate of the user is derived based on this total energy. Under the constraint of maximizing the minimum rate of all users, the energy allocation is optimized based on the ergodic rate to obtain the optimal closed-form solution for energy allocation. The energy is then allocated to each user according to the optimal closed-form solution. This embodiment achieves optimization of energy coverage among users, ensuring that, under the premise of meeting the requirement of maximizing the minimum rate of all users, the energy acquisition of each user is more reasonable through optimal energy allocation, thereby improving the balance and effectiveness of energy coverage among users in the FD-WPCN model.

[0031] Furthermore, in the FD-WPCN model, the hybrid access point receives uplink information from the user through the uplink channel matrix, and transmits downlink energy to the user through the downlink channel matrix; wherein, the uplink channel matrix is:

[0032] The downlink channel matrix is ​​as follows:

[0033] In the formula, For the uplink channel matrix, This represents the small-scale fading channel matrix of the uplink channel. Let K be the K-order diagonal matrix of the uplink channel. This is the downlink channel matrix. This represents the small-scale fading channel matrix of the downlink channel. Let be the K-order diagonal matrix of the downlink channel.

[0034] Before communication, in the FD-WPCN model, the user sends a pilot sequence of a set length to the hybrid access point, and estimates the uplink channel matrix and downlink channel matrix based on the pilot sequence. Interference signals in the uplink and downlink channel matrices of the full-duplex mode are suppressed by radio frequency domain self-interference cancellation technology. Accurate estimation of the uplink and downlink channel matrices is achieved using pilot sequences, while the radio frequency domain self-interference cancellation technology effectively suppresses interference signals in full-duplex mode, ensuring the stability and reliability of FD-WPCN model communication.

[0035] Furthermore, the communication process of the FD-WPCN model includes: utilizing beamforming technology, all users receive downlink energy from the downlink channel of the hybrid access point, collect the downlink energy to obtain the expected total energy; the energy used for uplink transmission information in the predicted total energy is collected from the (k+1)th time period of the previous transmission time slot to the current transmission time slot. In this embodiment, the uplink transmission power of the uplink channel is also calculated based on the predicted total energy, and the downlink transmission power is also calculated.

[0036] Furthermore, the expected total energy collected by each user on the downlink is determined, and the expected total energy is expressed as:

[0037] in,

[0038] In the formula, For the energy expected to be collected on the user's downlink, For the expected total energy, For energy conversion efficiency, This refers to the downlink transmission power. This is the transpose of the uplink and downlink channel vectors of the k-th user. The duration of a single time period. For downlink beamforming vectors, For expectation operators.

[0039] The user's traversal rate is:

[0040] In the formula, The duration of a single time period. As expected, For signal-to-interference-plus-noise ratio.

[0041] Furthermore, the hybrid access point employs maximum ratio combining technology when receiving uplink information to detect the radio frequency (RF) signal in the user's uplink received information and maximize the power of the detected RF signal. The RF signal is:

[0042] In the formula, This refers to the radio frequency signal in the uplink information. This refers to the downlink transmission power. This is the transpose of the self-interference channel matrix. For downlink power transmission cells, For downlink beamforming vectors, This is the uplink noise vector at the hybrid access point. Uplink transmission power for users, It is the square of the magnitude of the uplink channel vector. For uplink transmission cells, the expected total energy of the uplink transmission power and the duration of k time periods are obtained.

[0043] Furthermore, the minimum fairness constraint is maximized as follows:

[0044] In the formula, For the energy allocation optimization function, Let k be the traversal rate. Let K be the power allocation coefficient for user k, where K is the total number of users.

[0045] Furthermore, the closed-form solution for energy allocation optimization is:

[0046]

[0047]

[0048] In the formula, The optimal power allocation factor is... The number of transmitting antennas, For the total number of users, For the composite channel quality of the k-th user, The duration of a single time period. This is the optimal approximate solution for the k-th user. For fixed parameters of the environment and equipment, For energy conversion efficiency, For the downlink transmission power of the hybrid access point, The background noise power at the user receiver. This is a variable used to eliminate self-interference.

[0049] Example 2 This embodiment provides a specific implementation method for enhancing the coverage of a wireless power supply communication network, including the following specific implementation steps.

[0050] This embodiment uses a wireless power supply communication network in a certain community as an example for illustration. First, a model system scenario based on multi-user MIMO (Multiple-Input Multiple-Output) FD-WPCN (Full Duplex-Wireless Powered Communication Network) is established.

[0051] In this embodiment, the user is equipped with multiple transmitting antennas and multiple receiving antennas, providing full-duplex functionality. A full-duplex hybrid access point (HAP) connects to the user via the equipped antennas. One transmitting antenna and One receiving antenna, simultaneously transmitting to A single-antenna user (denoted as) The system transmits energy downlink and receives information uplink. In embodiments of the present invention, the operating mode of a single-antenna user is to collect energy first and then transmit it. It is assumed that a single-antenna user can only collect energy from the RF (radio frequency) signal transmitted by the HAP, and then use the collected energy to transmit information to the HAP in the uplink.

[0052] In traditional WPCN systems, a time slot is typically divided into two phases, WET and WIT, respectively. In the FD model of this embodiment, a time slot with a duration of... The time slots are divided into Each time period is denoted as Assume all time periods have the same duration, i.e., for all k, the following holds true: Without loss of generality, we assume... Single-antenna users Information is transmitted during the k-th time period, and energy is collected during the other K time periods. Furthermore, the 0th time period is dedicated to WET (Weighted Equipping), ensuring the system functions correctly even with only one user.

[0053] It's important to note that full-duplex means that communication nodes (such as base stations) can simultaneously transmit and receive signals on the same frequency band. A time slot is the basic unit of time resource allocated to data transmission or control signals. WET refers to the Downlink Control Phase, a phase in wireless communication used to transmit control information and downlink data. WIT refers to the Uplink Transmission Phase. These two phases are used for uplink data transmission and control information transmission, respectively.

[0054] In the FD-WPCN model, the HAP employs multi-antenna technology to communicate with multiple single-antenna users. Specifically, it defines... and ,in, This is the downlink channel matrix from the HAP's transmit antenna array to K users. Let be the uplink channel matrix from the K users to the HAP's receive antenna array.

[0055] Among them, the downlink channel matrix To be represented as:

[0056] Uplink channel matrix for:

[0057] In the formula, For the downlink small-scale fading channel matrix, , For the uplink small-scale fading channel matrix, The elements of the small-scale fading channel matrix follow an independent and identically distributed (i.i.d.) pattern. Complex Gaussian distribution. and These are K-order diagonal matrices corresponding to the uplink and downlink channels, respectively.

[0058] The k-th diagonal elements of the K-order diagonal matrix are:

[0059]

[0060] in, and These represent the path loss for downlink and uplink, respectively.

[0061] In this embodiment, using , , and They represent , , and The k-th column represents the uplink and downlink channel vectors of the k-th user, respectively.

[0062] Therefore, all single-antenna users send a pilot sequence of length L to the full-duplex HAP before power transmission begins.

[0063] By utilizing these pilot sequences, full-duplex HAP estimates the uplink channel matrix. and downlink channel matrix Assuming perfect channel estimation, then we have , .

[0064] In the FD-WPCN model, the transmit power of the HAP is much greater than the signal power received by the HAP, which leads to severe self-interference (SI). Due to the close proximity of the transmit and receive antennas, the propagation delay is very small. Furthermore, compared to traditional full-duplex uplink and downlink information systems, the downlink radio frequency energy signal transmitted in FD-WPCN does not contain information and is simpler in form. Therefore, it is assumed that the line-of-sight (LoS) component in the self-interference signal is effectively eliminated through radio frequency domain self-interference cancellation (SIC) technology. The remaining self-interference channel components are denoted as... This represents a Rayleigh fading channel. The elements are independent and identically distributed, and follow a certain distribution. Complex Gaussian distribution, where It is defined as the self-interference cancellation capability of the FD-WPCN system.

[0065] Before uplink information transmission, single-antenna users Energy will first be harvested from the radio frequency signal. The energy used for WET is harvested from the (k+1)th period of the previous transmission time slot to the (k-1)th period of the current transmission time slot. Since users do not need to demodulate the WET signal, it is assumed that all users share the same energy transmission cells in WET. ,in .exist During this period, users Signals received on the downlink It can be represented as:

[0066] in This is the downlink transmit power of the HAP. Here is the downlink beamforming vector. The downlink beamforming vector is expressed as:

[0067] in It is a power allocation vector The k-th element represents the HAP pair. The power allocation weights satisfy .

[0068] Ignoring the energy harvested from ambient noise and other user uplink WIT signals, therefore, Any time segment The expected energy collected can be expressed as:

[0069] in It refers to the user's energy conversion efficiency.

[0070] To simplify the analysis, assume a large-scale fading coefficient. It remains constant between time slots. The expected energy collected by each user in each time slot. depending on Therefore, it is also a constant value. Each user will collect energy during the K time periods preceding the WIT phase, therefore, The expected total energy stored for WIT is denoted as . , can be represented as:

[0071] The downlink energy coverage probability is defined as the probability that the received energy is greater than a threshold. The probability of can be expressed as:

[0072] like If all of it is used for uplink information transmission, then the uplink transmission power is... It can be represented as

[0073] In the k-th time period, Energy collected during the WET period is used to transmit information uplink to the HAP. During this period, the uplink signal received by the HAP can be represented as

[0074] in yes exist The cells transmitted during the period satisfy . It is at HAP A noise vector whose elements are independently and identically distributed and follow a complex Gaussian distribution. .

[0075] Because a TDMA (Time Division Multiple Access) transmission model is used, only one user uploads information at a time. Assume that the HAP uses Maximum Ratio Combining (MRC) technology in uplink information reception. The detected signal is represented as:

[0076] The third item represents the self-interference SI signal.

[0077] According to Shannon's theorem, The uplink traversal rate can be expressed as:

[0078] in It is received by HAP from The signal-to-interference-plus-noise ratio (SINR) of a signal can be expressed as:

[0079] The uplink information coverage probability is defined as its instantaneous rate being greater than a threshold. The probability of can be expressed as:

[0080] To ensure fairness among users, this embodiment assigns power allocation weights. Optimize the system to find a fair power distribution among users, so that users can obtain enough energy to complete uplink information transmission regardless of channel conditions.

[0081] Based on the minimization criterion, the following optimization problem was formulated to maximize the minimum rate among all users.

[0082]

[0083]

[0084]

[0085] in, The traversal rate is expressed as .

[0086] First, the expected energy harvesting rate of users during the downlink WET phase and the traversal rate during the uplink WIT phase are derived and analyzed. Then, the impact of self-interference and the number of antennas on the overall rate will be analyzed.

[0087] The uplink WIT rate is related to the uplink transmit power, which in turn is determined by the downlink receive power. Therefore, we first derive... Expected transmit power As shown in the following lemma.

[0088] Lemma 1 The expected uplink transmit power is:

[0089] The traversal speed is:

[0090] According to Jensen's inequality and functions The convexity can be obtained A tight lower bound , is represented as:

[0091] in represent: .

[0092] Through calculation You can get A close approximation of , which can be used to analyze system performance and derive . An approximate optimal solution. This can be given by the following lemma: Lemma 2. The approximate expression is .

[0093] Using Lemma 2, we can obtain A tight lower bound and an approximate analytical expression can be used to analyze the coverage performance of FD-WPCN.

[0094] For ease of analysis, and It can be rewritten in the following form:

[0095]

[0096] in

[0097]

[0098] In FD-WPCN, uplink information interference mainly originates from self-interference. Based on Lemma 2 and its proof, the approximate value of the expected power of the self-interference signal detected by HAP is expressed as: It can be given by the following formula:

[0099] And HAP detected An approximation of the expected power of the uplink transmission signal can be obtained from... Given:

[0100] As can be seen from the above formula, assuming and Big enough and Proportional and Proportional to each other, therefore, the uplink signal-to-interference ratio (SIR) is... and The ratio between them, and It is directly proportional. Specifically, as the number of antennas increases, the SIR increases, and the impact of SI on data rate performance gradually decreases. Therefore, multi-antenna technology has a good effect on suppressing SI, and as the number of antennas increases, the suppression effect on SI will gradually strengthen, while the coverage probability of users will also increase.

[0101] Assumption and Large enough, and .when At that time, one can obtain An upper bound is given by the following equation:

[0102] This indicates that with the increase in energy transfer power The increase, It will converge. This upper bound intuitively reflects the relationship between the user's uplink rate and various parameters in WPCN. Therefore, the user coverage probability can be analyzed using this method. In this embodiment, the user coverage probability is defined as the probability that the user's uplink rate is greater than a threshold. Since the instantaneous rate contains multiple random variables of uplink, downlink, and self-interference channels, this embodiment does not solve for their distribution, but it can still be qualitatively analyzed through the expected rate. From the above formula, it can be concluded that the user coverage probability is directly proportional to the number of transmit and receive antennas of the system, directly proportional to the user's downlink energy allocation weight, inversely proportional to the system's self-interference power, and inversely proportional to the user's distance. Since the uplink operates in TDMA mode, there is no multi-user interference, and the uplink signal interference is mainly full-duplex self-interference. Therefore, as the system's self-interference cancellation capability improves, the system's information coverage probability will also increase. In this chapter, the coverage probability will be mainly verified through Monte Carlo simulation, and the problem of solving the coverage probability will be solved by introducing random geometric mathematical tools.

[0103] To ensure energy coverage for users at the cell edge, enabling them to collect sufficient energy and maintain uplink speeds, this step will solve the fair and optimal energy allocation problem for FD-WPCN.

[0104] According to Lemma 2, using the up-traversal rate of FD-WPCN Analytical approximation , An approximate problem is:

[0105] Approximation problem The closed-form solution to the optimal solution can be given in the following theorem.

[0106] Theorem 1. Optimal Fairness Energy Beamforming Design for FD-WPCN It can be given by the following formula:

[0107] The weights of Theorem 1 Substitution optimal It can be represented as

[0108] The results show that the approximate traversal rate is equal for all users. Based on Theorem 1, this section presents a fair energy allocation strategy that achieves fairness among users. For edge users, this fair energy allocation method allows them to receive more energy during the WET phase, thereby improving uplink speed and ensuring uplink coverage. The effectiveness of this algorithm will be verified and discussed in the simulation results of the next step.

[0109] Monte Carlo simulations and numerical results demonstrate the performance of the proposed FD-WPCN and verify the improvement in coverage of the FD-WPCN system by the proposed fair energy beamforming strategy.

[0110] The simulation scenario settings are shown in Table 1.

[0111] Table 1 Model Parameter Configuration Information

[0112] For each experimental scenario, 10,000 repeated experiments were conducted using MATLAB, with a carrier frequency of 2.6 GHz. Since the small-scale fading channel employs the Rayleigh channel model, in each experiment, a model following the [model name missing] is generated. Complex Gaussian distributed random numbers are used to simulate the channel between multiple antennas and multiple users in both uplink and downlink. Simultaneously, users are randomly scattered according to the distance settings in the experimental scenario to simulate path loss. After obtaining multiple experimental data points for the corresponding indicators through simulation, the average of the results from 10,000 repeated experiments is calculated to obtain the final simulation results. Figures 2 to 5 Monte Carlo simulations were used to demonstrate and verify the performance of the full-duplex WPCN system in this chapter, including uplink information coverage probability, downlink energy coverage probability, and data rate, as well as the proposed fairness algorithm.

[0113] Example 3 This embodiment provides a wireless power supply communication network coverage enhancement system. This system is used to implement the wireless power supply communication network coverage enhancement methods in Embodiments 1 and 2. The system includes: The channel construction module constructs a multi-user MIMO FD-WPCN model. The FD-WPCN model is configured with a full-duplex hybrid access point. The hybrid access point is equipped with several transmit antennas and receive antennas to transmit downlink energy to multiple single-antenna users and receive uplink information. The energy harvesting module uses beamforming technology to transmit downlink energy to users and receive uplink information, determining the expected total energy collected by each user on the downlink. The user rate derivation module derives the user's traversal rate based on the total collected energy. The energy optimization module optimizes energy allocation based on the traversal rate under the constraint of maximizing the minimum rate of all users, and obtains the optimal closed-form solution for energy allocation. Based on the optimal closed-form solution, energy is allocated to each user to optimize the energy coverage among users.

Claims

1. A method for enhancing coverage of a wireless power supply communication network, characterized in that, include: Construct a multi-user MIMO FD-WPCN model, in which a full-duplex hybrid access point is configured. The hybrid access point is equipped with several transmit antennas and receive antennas for transmitting downlink energy to multiple single-antenna users and receiving uplink information. Using beamforming technology to transmit downlink energy to users and receive uplink information, the expected total energy collected by each user on the downlink is determined; The user's traversal rate is derived based on the total collected energy. Under the constraint of maximizing the minimum rate of all users, the energy allocation is optimized based on the traversal rate to obtain the optimal closed-form solution for energy allocation. Based on the optimal closed-form solution, energy is allocated to each user to optimize the energy coverage among users.

2. The wireless power supply communication network coverage enhancement method according to claim 1, characterized in that, In the FD-WPCN model, the hybrid access point receives uplink information from the user through the uplink channel matrix, and the hybrid access point transmits downlink energy to the user through the downlink channel matrix. The uplink channel matrix is ​​as follows: The downlink channel matrix is ​​as follows: In the formula, For the uplink channel matrix, This represents the small-scale fading channel matrix of the uplink channel. Let K be the K-order diagonal matrix of the uplink channel. This is the downlink channel matrix. This represents the small-scale fading channel matrix of the downlink channel. Let be the K-order diagonal matrix of the downlink channel.

3. The method for enhancing coverage of a wireless power supply communication network according to claim 2, characterized in that, Before communication, the user sends a pilot sequence of a set length to the hybrid access point in the FD-WPCN model, and estimates the uplink channel matrix and downlink channel matrix based on the pilot sequence. Interference signals in the uplink and downlink channel matrices under full-duplex mode are suppressed by radio frequency domain self-interference cancellation technology.

4. The method for enhancing coverage of a wireless power supply communication network according to claim 1, characterized in that, The communication process of the FD-WPCN model includes: Using beamforming technology, all users receive downlink energy from the downlink channel of the hybrid access point, and the downlink energy is collected to obtain the expected total energy; the energy used for uplink transmission information in the predicted total energy is collected from the k+1th time period of the previous transmission time slot to the current transmission time slot.

5. The method for enhancing coverage of a wireless power supply communication network according to claim 4, characterized in that, Determine the expected total energy collected by each user on the downlink, whereby the expected total energy is expressed as: in, In the formula, For the energy expected to be collected on the user's downlink, For the expected total energy, For energy conversion efficiency, This refers to the downlink transmission power. This is the transpose of the uplink and downlink channel vectors of the k-th user. The duration of a single time period. For downlink beamforming vector, For expectation operators.

6. The method for enhancing coverage of a wireless power supply communication network according to claim 5, characterized in that, The user's traversal rate is: In the formula, The duration of a single time period. As expected, For signal-to-interference-plus-noise ratio.

7. The method for enhancing coverage of a wireless power supply communication network according to claim 1, characterized in that, The hybrid access point employs maximum ratio combining (MRB) technology when receiving uplink information. It detects the radio frequency (RF) signal in the user's uplink received information and maximizes the power of the detected RF signal. The RF signal is: In the formula, This refers to the radio frequency signal in the uplink information. This refers to the downlink transmission power. This is the transpose of the self-interference channel matrix. For downlink power transmission cells, For downlink beamforming vector, This is the uplink noise vector at the hybrid access point. Uplink transmission power for users, It is the square of the magnitude of the uplink channel vector. For uplink transmission cells, the expected total energy of the uplink transmission power and the duration of k time periods are obtained.

8. The method for enhancing coverage of a wireless power supply communication network according to claim 1, characterized in that, The constraint to maximize minimum fairness is: In the formula, For the energy allocation optimization function, Let k be the traversal rate. Let K be the power allocation coefficient for user k, where K is the total number of users.

9. The method for enhancing coverage of a wireless power supply communication network according to claim 6, characterized in that, The closed-form solution for the energy allocation optimization is: In the formula, The optimal power allocation factor is... The number of transmitting antennas, For the total number of users, For the composite channel quality of the k-th user, The duration of a single time period. This is the optimal approximate solution for the k-th user. For fixed parameters of the environment and equipment, For energy conversion efficiency, For the downlink transmission power of the hybrid access point, The background noise power at the user receiver. This is a variable used to eliminate self-interference.

10. A wireless power supply communication network coverage enhancement system, characterized in that, include: The channel construction module constructs a multi-user MIMO FD-WPCN model. The FD-WPCN model is configured with a full-duplex hybrid access point. The hybrid access point is equipped with several transmit antennas and receive antennas for transmitting downlink energy to multiple single-antenna users and receiving uplink information. The energy harvesting module uses beamforming technology to transmit downlink energy to users and receive uplink information, and determines the expected total energy collected by each user on the downlink. The user rate derivation module derives the user's traversal rate based on the total collected energy. The energy optimization module optimizes energy allocation based on the traversal rate under the constraint of maximizing the minimum rate of all users, and obtains the optimal closed-form solution for energy allocation. Based on the optimal closed-form solution, energy is allocated to each user to optimize the energy coverage among users.

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