Power line communication repeater arrangement method, equipment and medium

Abstract

The invention discloses a power line communication repeater arrangement method and device and a medium, and relates to the technical field of communication, and the method comprises the steps: building an uplink model and a downlink model based on a power line communication system model and a signal propagation model through employing a frequency division multiplexing technology, and then carrying out the verification through employing a cyclic redundancy check algorithm; when the verification result is that the relay node needs to be started, calculating current channel state data and inputting the current channel state data into a preset channel state prediction model to obtain channel state data at the next moment; performing initial power random allocation based on the channel state data at the next moment to obtain initial signal source power and multiple initial user power; the method comprises the following steps: constructing a constraint function by taking communication quality guarantee as a target, constructing an optimization target function by taking the minimum total power as a target, and then sequentially carrying out initial power optimization solution and relay node position optimization solution by adopting a heuristic algorithm to obtain the optimization position of each relay node. According to the invention, the relay deployment position is optimized, so that the power consumption is reduced while the communication quality is ensured.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a method, device and medium for arranging a power line communication repeater. Background Art

[0002] Power Line Communication (PLC) technology refers to a communication method that uses power lines to transmit data and media signals. This technology loads high-frequency signals carrying information onto current, and then uses wires to transmit the adapter that receives the information to separate the high-frequency signal from the current and transmit it to a computer or telephone line to achieve information transmission.

[0003] The advantages of PLC are mainly reflected in the fact that it can use the existing distribution network for information transmission without rewiring, which greatly reduces the investment in network laying and reduces costs. At the same time, the power line network has the widest coverage and is large enough. As long as the power grid is unobstructed, the network can be guaranteed to be online and can provide high-speed transmission rates. In practical applications, the disadvantages of PLC include: (1) The topological structure of the power line is designed for power transmission rather than communication, and the quality of communication on the original topological structure cannot be guaranteed; (2) The power line, as the physical layer transmission medium of communication, has poor transmission characteristics and is susceptible to various interferences from inside and outside the network, resulting in a poor signal-to-noise ratio of the system; (3) Electromagnetic interference in the power line network will affect the transmission of weak current signals and other systems in the frequency band. Summary of the invention

[0004] The purpose of this application is to provide a power line communication repeater deployment method, device and medium to optimize the relay deployment position, thereby reducing power consumption while ensuring communication quality.

[0005] To achieve the above objectives, this application provides the following solutions:

[0006] In a first aspect, the present application provides a method for arranging a power line communication repeater, comprising:

[0007] Constructing a power line communication system model and a corresponding signal propagation model; the power line communication system model includes multiple nodes communicating through power lines, and the communication process between nodes adopts non-orthogonal multiple access technology; wherein one of the nodes is a signal source, and the other nodes are users;

[0008] Based on the power line communication system model and the signal propagation model, an uplink model and a downlink model are respectively constructed using frequency division multiplexing technology; the downlink model is used to execute the process of the signal source sending a signal to the user; the uplink model is used to execute the process of the user sending a signal to the signal source or the process of the user as a relay node sending a signal to other users;

[0009] Based on the uplink model and the downlink model, a cyclic redundancy check algorithm is used to check all the users to obtain a check result; the check result is whether the relay node needs to be turned on or not;

[0010] When the verification result indicates that the relay node needs to be turned on, the current channel state data of the power line communication system model is calculated, and then the current channel state data is input into a preset channel state prediction model to obtain the channel state data at the next moment; the preset channel state prediction model is obtained based on deep learning network training;

[0011] Based on the channel state data at the next moment, performing random initial power allocation to obtain an initial signal source power and multiple initial user powers in the power line communication system model;

[0012] A constraint function is constructed with the goal of ensuring communication quality, and an optimization objective function is constructed with the goal of minimizing total power. Then, based on the initial signal source power, multiple initial user powers, the channel state data at the next moment, and the preset minimum total channel capacity, a heuristic algorithm is used to sequentially perform initial power optimization solutions and relay node position optimization solutions to obtain the optimized position of each relay node.

[0013] In a second aspect, the present application provides a computer device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement a power line communication repeater deployment method.

[0014] In a third aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which implements a method for arranging a power line communication repeater when the computer program is executed by a processor.

[0015] According to the specific embodiments provided by the present application, the present application discloses the following technical effects: The present application provides a method, device and medium for arranging power line communication repeaters, constructs a power line communication system model and a corresponding signal propagation model, so that practical problems can be solved more accurately through mathematical methods; the non-orthogonal multiple access (NOMA) technology is introduced into the power line communication system model, allowing multiple users to share the same space-time resources, thereby increasing the number of accessible users, thereby improving the signal-to-noise ratio and spectrum efficiency. The present application also considers different topological structures under different application scenarios, and establishes a user model within the model, which makes the method more applicable to various scenarios. Compared with other methods that can only optimize a single topology, the applicability and extensiveness of the method are increased. In the present application, an uplink model and a downlink model are set up to realize the combination of NOMA and frequency division multiplexing (Frequency Division Duplexing, FDD), realize full-duplex communication of the system, and reduce the system latency. When it is necessary to open the relay node, the advantages of deep learning and heuristic optimization algorithms are combined to provide an efficient and reliable solution in the complex NOMA and FDD combined system, which can more accurately capture the time-varying characteristics of the channel, thereby improving the accuracy of power allocation and relay selection. In the processing of the heuristic optimization algorithm, the constraint function and optimization objective function are constructed by comprehensively considering the influence of power and interference, so as to not only consider the power minimization problem, but also comprehensively consider the interference problems caused by different relay selections, to ensure that the total power is minimized while meeting the communication quality, and it has strong adaptability and flexibility, suitable for complex and changing communication environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 It is a tree topology of power lines;

[0018] Figure 2 The topology of the power lines with direct links between users;

[0019] Figure 3 A schematic diagram of a flow chart of a method for arranging a power line communication repeater provided in one embodiment of the present application;

[0020] Figure 4 Schematic diagram of the corresponding power line communication system model when there are 5 users.

[0021] Reference numerals: 1 - signal source, 2 - user. DETAILED DESCRIPTION

[0022] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0023] Facing the shortcomings of existing PLC:

[0024] First, in order to verify the impact of topology on actual communication effects, considering the different characteristics of low-voltage distribution networks in actual applications, it is difficult to give a universal network topology. This application considers two possible physical topologies of power lines, such as Figure 1 , Figure 2 shown. Figure 1 The topological structure includes a signal source 1 and multiple user branches. A different number of users are connected to each branch, and the density, length and topological structure of the user 2 connections on each branch are different. The overall structure is similar to a tree structure. Figure 2 The overall topological structure of Figure 1 The topology is similar, but Figure 1 On the basis of, there may be a link connection between each individual user 2. By comparing the impact of the two topologies on communication and selecting the appropriate channel attenuation coefficient, the impact of the topology and channel physical characteristics on the signal can be effectively verified.

[0025] Secondly, for power line carrier communication, the attenuation strength of the channel is proportional to the frequency domain and distance of the transmitted signal. The greater the frequency of the transmitted signal, the greater the attenuation, and the longer the distance of the transmitted signal, the more serious the signal attenuation. For the impedance characteristics, it is related to the frequency of the input signal, the load access position, time and network load type. In addition, the multipath transmission characteristics and noise characteristics in the power line carrier need to be considered. In order to solve the problem of low signal-to-noise ratio in power line communication, NOMA technology is introduced. In NOMA technology, the signals of each user in the downlink are superimposed and sent together, and the power allocation of each signal is determined by the quality of the communication link of each user. Users with poor channel quality, that is, low channel gain, are allocated high transmission power, and vice versa. In the uplink, the transmission power of each user is only affected by the maximum transmission power of its device. In the downlink, each receiving end receives the superimposed signal from the base station, and each receiving end has its own serial interference cancellation (SIC) receiver. For the received signal, the required signal is obtained through continuous decoding. After receiving the superimposed signal, the receiving user uses the SIC technology to decode the received signal and eliminate interference. The basic idea is to first detect the user signal with the maximum power, then remove the user's information from the superimposed signal, and then continue to detect the user signal with the second largest power, and so on. NOMA technology allows multiple users to share the same space-time resources, thereby increasing the number of accessible users, thereby improving the signal-to-noise ratio and spectrum efficiency. At the same time, in order to solve the problem of short transmission distance, a relay collaborative communication method is introduced. Based on this, the present application proposes an optimization method to select the deployment location of the repeater in the power line network to achieve the purpose of cost saving.

[0026] In practical applications, the access of loads will inevitably bring about electromagnetic interference problems, especially in power lines. The generation of electromagnetic interference will sharply deteriorate the communication environment of weak current signals. Therefore, a certain safety margin is required for the electromagnetic to complete the entire communication process. Moreover, depending on the actual application situation, the circuit topology of the entire system is different, which brings different interference modes, including differential mode radiation and common mode radiation. By optimizing the repeater position, the electromagnetic interference factor is considered and optimized to effectively suppress the impact of electromagnetic interference on communication.

[0027] In summary, the interference, topology and channel characteristics that different user nodes may contain in power line carrier communication will vary greatly depending on the node location where the user resides, the distance from the signal transmitter and the load. When selecting relay user nodes, this application considers the influence of these factors and makes optimizations to achieve good relay effects while using as few relays as possible, so as to achieve the purpose of minimizing power consumption while ensuring communication quality and not bringing unnecessary redundant effects.

[0028] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0029] In an exemplary embodiment, Figure 3 As shown, a method for arranging a power line communication repeater is provided. The method is executed by a computer device, and specifically can be executed by a computer device such as a terminal or a server alone, or can be executed by a terminal and a server together, and includes the following steps 101 to 106.

[0030] Step 101, construct a power line communication system model and a corresponding signal propagation model; the power line communication system model includes multiple nodes communicating through power lines, and the communication process between nodes adopts non-orthogonal multiple access technology; wherein one of the nodes is a signal source S, and the other nodes are users. In actual applications, the number and location of users are randomly generated, and users can communicate with each other through power lines. After the random users are generated, in order to facilitate subsequent calculations, the users are generally sorted according to their distance from the signal source. When there are 5 users, the corresponding power line communication system model can be as follows Figure 4 As shown, Figure 4 U is used to represent a user, and correspondingly, the users are arranged from U1 to U5 according to their distance to the source.

[0031] There are channels between the signal source and the user, and between the users. Correspondingly, there is a channel gain, represented by the letter h. They are modeled as independent normal distribution random variables. The log-normal fading model is widely used in the power line communication system model, which can describe the network topology load mismatch and the multipath effect of the network. The probability density function of the channel gain f(h i )for:

[0032]

[0033] Among them, μ i and represents 10log10(h i ), h i is the channel gain of user i, specifically the channel gain from user i to signal source S.

[0034] In addition, considering the impairment caused by distance and frequency dependence in attenuation, A i (d i ,f) indicates, d i is the distance between nodes corresponding to user i, and f is the communication frequency. The noise of the channel includes background noise and impulse noise, which can be represented by the Bernoulli Gaussian noise model, and its probability density function f n (L) is:

[0035]

[0036] Wherein, δ(L) is the Dirac delta function, which represents the unit impulse function at L=0; L represents the number of users in the power communication system model. is zero and has a variance of σ 2 The probability density function of the Gaussian distribution. 0≤p<1 is the probability of the pulse component appearing.

[0037] The signal propagation model includes a signal function sent from the signal source and a signal function received at the user. The signal function sent from the signal source is: The signal receiving function at the user is: i =x s A i (d i ,f)h i +n i ; where x s is the transmitted signal of the signal source S, α i is the power allocation coefficient of user i. Generally speaking, as the distance decreases, the power allocation coefficient decreases, but the sum of the power allocation coefficients of all users is always 1; P s is the transmission power of the signal source S, x i is the signal to be received at user i, y i is the signal actually received by user i; A i (d i ,f) is the signal attenuation of user i; h i is the channel gain of user i, n i is the noise received by user i.

[0038] In the above step 101, the communication process uses non-orthogonal multiple access technology, and each user can act as a separate decoding and forwarding repeater. In order to ensure the communication quality of the entire power line communication system model, when the remote user cannot communicate normally due to excessive path loss caused by the distance from the signal source, it is necessary to select the user between the remote user and the signal source to start relaying, decode the signal and resend it once, so as to help the remote user receive the correct signal.

[0039] Step 102, based on the power line communication system model and the signal propagation model, an uplink model and a downlink model are respectively constructed using frequency division multiplexing technology; the downlink model is used to execute the process of the signal source sending a signal to the user; the uplink model is used to execute the process of the user sending a signal to the signal source or the process of the user sending a signal to other users as a relay node, and when the user works as a relay node, it can be regarded as a repeater.

[0040] Specifically, after obtaining the power line communication system model and signal propagation model, in order to achieve full-duplex communication in practice, a communication method combining non-orthogonal multiple access and frequency division duplex is proposed. Specifically, for the source and multiple users in the system, the uplink and downlink are transmitted on different frequency bands respectively, and NOMA technology is used in each frequency band. Mathematical modeling is also required to help the subsequent optimization process.

[0041] For the uplink model: The uplink spectrum f u Divided into M sub-bands, the bandwidth of each sub-band is B u / M.B u is the channel bandwidth in the uplink model. In the kth sub-band f uk On the assumption that there is K k Users perform NOMA transmission, user i is in f uk The transmitted signal on is expressed as The total signal received by user i in the uplink model is for:

[0042]

[0043] After user i transmits a signal, the corresponding receiving end uses serial interference cancellation technology to decode user signals one by one in order of power from large to small. Assuming that the signal power of user i is Then the user signal with the largest decoding power is for:

[0044]

[0045] The remaining signals can be decoded in sequence.

[0046] Among them, K k is the number of users communicating in the uplink model, is the sub-band f of user i in the uplink model uk The channel gain on is the sub-band f of user i in the uplink model at time t uk The transmitted signal on is the signal attenuation of user i during the communication process of the uplink model, is the sub-band f of the uplink model at time t uk Noise on is the channel gain from the signal source to other user j except user i, is the transmitted signal from the signal source to other users j except user i at time t, is the signal attenuation from the signal source to user j except user i.

[0047] For the downlink model: Downlink spectrum f d It is also divided into M sub-bands, and the bandwidth of each sub-band is B d / M.B d is the channel bandwidth in the downlink model. In the mth sub-band f dm On the assumption that there is L m The total signal transmitted by the signal source S in the downlink model is for:

[0048]

[0049] After the signal source S transmits a signal, the corresponding receiving end uses serial interference cancellation technology to decode user signals one by one in the order of power from large to small. Assume that user U j The signal power is Then the user signal with the largest decoding power is for:

[0050]

[0051] The remaining signals can be decoded in sequence.

[0052] Among them, L m is the number of users communicating in the downlink model, is the sub-band f of user j in the downlink model dm The channel gain on is the sub-band f of user j in the downlink model at time t dm The transmitted signal on is the sub-band f of user j in the downlink model dm The signal attenuation on is the sub-band f of the downlink model at time t dm Noise on is the channel gain from the signal source to other user k except user j, is the transmitted signal from the signal source to other user k except user j at time t, is the signal attenuation from the signal source to user k other than user j. Note that user i, user j, and user k in the uplink model and the downlink model are different users.

[0053] In the above step 102, the full-duplex communication model of the uplink and downlink is constructed. The downlink model is the process of the signal source sending a signal to the user, and the uplink model is the process of the user feeding back the verification code information and starting the relay decoding and forwarding.

[0054] Step 103, based on the uplink model and the downlink model, a cyclic redundancy check algorithm is used to check all the users to obtain a check result; the check result is whether the relay node needs to be turned on or not. In an application example, step 103 includes:

[0055] (31) The downlink model is used to execute the process of the signal source sending a signal to the user, and a check code is set when sending the signal; the check code is determined based on a cyclic redundancy check algorithm.

[0056] (32) The uplink model is used to execute a process in which the user sends a signal to the signal source, and verification code information is fed back when sending the signal.

[0057] (33) Determine whether the check code is correct or not based on the check code sent in the downlink model and the check code information fed back in the uplink model.

[0058] (34) When the verification code is correct, the verification result is marked as no need to enable the relay node; when the verification code is incorrect, the verification result is marked as need to enable the relay node.

[0059] Specifically, in order to help determine whether the user can communicate normally, when the transmitter sends information, it includes a set of check codes. The subsequent nodes recognize the check codes and determine whether the check codes are correct. The check code uses cyclic redundancy check. The basic idea is to first add a number, i.e., the check code used for verification, to the frame to be sent, and generate a new frame to send to the receiving end. This additional number must make the generated new frame divisible by a specific number selected by the transmitter and the receiver (modulo 2 division). After arriving at the receiving end, the received new frame is divided by (modulo 2 division) the selected divisor. Because the transmitter has added a number before sending the data frame, the "remainder removal" process has been performed (that is, it can be divided evenly), so the result should be no remainder. If there is a remainder, it means that an error occurred in the transmission process of the frame. If the check code is correct, it means that the current node can communicate normally without relaying. If the check code is incorrect, the relay needs to be enabled. In the downlink, frequency division multiplexing between 3kHz and 500kHz is generally used. In the uplink, feedback information is communicated at a frequency in the frequency gap of the downlink to ensure that the frequency does not conflict with the frequency used by the downlink.

[0060] Step 104, when the verification result is that the relay node needs to be turned on, the current channel state data of the power line communication system model is calculated, and then the current channel state data is input into a preset channel state prediction model to obtain the channel state data at the next moment; the preset channel state prediction model is obtained based on deep learning network training.

[0061] The current channel state data is any one of channel gain, signal-to-noise ratio, bit error rate, data rate, path loss model parameters, environmental noise, and time-varying characteristics; specifically, channel gain describes the degree of signal attenuation during transmission, which is used to calculate the received power of the signal, and then evaluate the quality of the communication link. The path loss model is estimated by measuring the signal strength between each node. The signal-to-noise ratio is the ratio of signal power to noise power, and is an important indicator for measuring signal quality. A high signal-to-noise ratio usually means better communication quality and lower bit error rate. The bit error rate is the ratio of the number of received error bits to the total number of received bits, which is used to evaluate the reliability of the communication link, and the bit error rate is calculated through actual data transmission tests. The data rate refers to the number of bits transmitted per unit time, which is used to evaluate the performance of the communication link, ensure that the minimum data rate requirements are met, and measure the actual transmission rate through transmission tests. The path loss model parameters include free space path loss, penetration loss, etc., which are used to predict the channel gain and signal attenuation between different locations, and the path loss model parameters are measured and fitted at multiple points. Environmental noise refers to the background noise around the power line, which is used to evaluate the signal-to-noise ratio and the quality of the communication link. The time-varying characteristics of the channel describe the law of channel changes over time, which is used to design communication strategies that adapt to time-varying channels. Finally, the current channel status data can also be used to plan the optimal location of repeaters, ensure signal coverage, and evaluate signal transmission paths and possible interference sources for the physical location of all user nodes and repeaters in the node location and power line topology.

[0062] After obtaining the above channel state data, the position of the relay node can be optimized using an algorithm based on this information. However, it should be noted that if one of the users is selected as a relay for decoding and forwarding, the channel state will also change. It is necessary to model the changed channel state so that the algorithm can be used to predict the channel state later. After the user turns on the relay, the signal received by the downlink will be decoded and forwarded through the uplink, so the uplink and downlink models obtained above need to be updated, as shown below.

[0063] (41) Downlink from the signal source to the user acting as a relay node: The signal source is in the downlink sub-band f d Send signal x BS (t) to relay node u r , the received signal for:

[0064]

[0065] in, is the corresponding signal x BS (t) In the downlink model, the signal source S is sent to the relay node u. r The channel gain, is the sub-band fd The signal received by the relay node is The decoded signal is

[0066] (42) Uplink from a user acting as a relay node to other users: Relay node u r In the uplink sub-band f u Send the decoded signal to To the receiving node u t , the received signal is:

[0067]

[0068] is the relay node u in the uplink model r To the receiving node u t The channel gain, is the sub-band f u The noise on the receiving node u t The received signal is The final decoded signal is

[0069] At this time, the signal-to-noise ratio in the downlink is:

[0070]

[0071] Among them, P S is the transmission power of the signal source S, N1 is the relay node u r The received noise power. r Channel capacity for:

[0072]

[0073] The signal-to-noise ratio of the uplink is:

[0074]

[0075] Among them, P r is the relay node u r The transmission power of the receiving node u t The received noise power. The channel capacity is:

[0076]

[0077] During the processing of the above link, the channel status and other information before and after the relay is enabled are obtained, providing data and model support for subsequent optimization.

[0078] In a specific application example, the deep learning network is a long short-term memory network, and the training process of the corresponding preset channel state prediction model includes: 1) collecting historical channel state information, user location and other related data from historical communication data, and then using MinMaxScaler to normalize and preprocess the collected data, and output normalized features for model training, so as to be used for deep learning model training. 2) Design and create a deep learning model LSTM suitable for time series prediction, design an appropriate loss function and optimizer to compile the model, and then use the normalized features of historical channel state information and user location to train the model so that it can predict future channel state information, thereby obtaining a preset channel state prediction model.

[0079] Step 105: Based on the next moment channel state data, random initial power allocation is performed to obtain initial signal source power and multiple initial user powers in the power line communication system model. The obtained initial signal source power and multiple initial user powers must ensure that they meet basic communication requirements.

[0080] Step 106, constructing a constraint function with the goal of ensuring communication quality, constructing an optimization objective function with the goal of minimizing total power, and then using a heuristic algorithm to sequentially perform initial power optimization solutions and relay node position optimization solutions based on the initial signal source power, multiple initial user powers, the channel state data at the next moment, and the preset minimum total channel capacity, to obtain the optimized position of each relay node.

[0081] The constraint functions include a link capacity limit function, a non-negative power constraint function, an error rate constraint function, a data rate constraint function, an electromagnetic interference constraint function and a location constraint function.

[0082] The link capacity limit function is:

[0083]

[0084] The non-negative power constraint function is: S ≥0; P r ≥0.

[0085] The error rate constraint function is: BER≤BER max .

[0086] The data rate constraint function is: R i ≥R min ,

[0087] The electromagnetic interference constraint function is: ij ≤E max , j.

[0088] The position constraint function is: r ,w r )∈Selectable user,

[0089] in, is the signal source S to relay node u in the downlink model r The channel capacity of is the relay node u in the uplink model r To the receiving node u t The channel capacity of is the signal source S to relay node u in the downlink model r The channel gain, C min is the preset minimum total channel capacity, BER is the bit error rate, BER max is the preset maximum bit error rate, R i is the data rate of user i, R min is the preset minimum data rate, E i,j is the electromagnetic interference between user i and user j, E max is the preset maximum electromagnetic interference, (v r ,w r ) is the relay node u r The user's location.

[0090] The optimization objective function is:

[0091] Among them, Z is the target value, P r is the relay node u r The transmission power, N is the number of relay nodes; P c For user u c The transmission power of user u c is the user who is not a relay node among all users, M is user u c The number of S is the transmission power of the signal source S.

[0092] By constructing the above optimization objective function and constraint function, the problem is simplified to requiring the minimum total power under the premise of ensuring the communication quality of the system. The preset minimum total channel capacity mentioned above is the minimum value of the sum of the uplink and downlink channel capacities. On the basis of the above optimization objective function and constraint function, based on the initial signal source power, multiple initial user powers, the channel state data at the next moment and the preset minimum total channel capacity, a heuristic algorithm is used to sequentially perform initial power optimization and relay node position optimization to obtain the optimized position of each relay node, including:

[0093] (61) Based on the initial signal source power, the multiple initial user powers, the channel state data at the next moment and the preset minimum total channel capacity, a heuristic algorithm simulated annealing is used for multiple iterations to perform initial power optimization on the optimization objective function based on the constraint function to obtain an optimized signal source power and multiple optimized user powers.

[0094] Specifically, the initial signal source power, multiple initial user powers, the channel state data at the next moment and the preset minimum total channel capacity are used as input, and then the solution process is determined as follows:

[0095] 611) Define functions to calculate total power and signal-to-noise ratio.

[0096] 612) Initialize the optimal power to obtain the optimal signal source power and multiple optimal user powers.

[0097] 613) Iterate a fixed number of times: calculate the total power, including the total power of the signal source and the total power of multiple users; check whether the capacity constraint is satisfied and whether the total power is minimized; if satisfied, update the optimal signal source power and the power of multiple optimal users; use random perturbations to adjust the optimal signal source power and the power of multiple optimal users.

[0098] 614) outputs optimized signal source power and multiple optimized user powers.

[0099] (62) Based on the optimized signal source power, the multiple optimized user powers, the channel state data at the next moment and the preset minimum total channel capacity, a heuristic algorithm simulated annealing is used for multiple iterations to optimize the relay node position of the optimization objective function based on the constraint function to obtain the optimized position of each relay node; the optimized position of the relay node is the position of the user serving as the relay node.

[0100] Specifically, the optimized signal source power, multiple optimized user powers, the channel state data at the next moment, and the preset minimum total channel capacity are used as inputs, and then the optimization solution process is as follows: set the minimum capacity requirement required for communication; use the heuristic optimization algorithm for iterative optimization, and select the power allocation that meets the requirements; select the relay node with the minimum total power and meets the communication quality requirements, and then output the optimized position of each relay node. So far, the application has obtained the repeater position that meets the minimum power sum and can complete the communication.

[0101] Through the above step 106, the present application designs and implements a new optimization algorithm, which combines the deep learning model to predict channel state information and the heuristic optimization algorithm for power allocation and relay selection, ensuring that the total power is minimized in the NOMA and frequency division multiplexing combined system while meeting the communication quality requirements and selecting the optimal relay location.

[0102] Compared with the prior art, this application has the following advantages:

[0103] (1) This application completely models the power line communication system and can more accurately solve practical problems through mathematical methods. At the same time, non-orthogonal multiple access technology is introduced to allow multiple users to share the same space-time resources, thereby increasing the number of accessible users and improving the signal-to-noise ratio and spectrum efficiency. At the same time, in order to solve the problem of short transmission distance, a relay collaborative communication method is introduced. In addition, considering the different topological structures in different application scenarios, this application establishes a randomly distributed random number of user models, which makes the algorithm more applicable to various scenarios. Compared with other methods that can only optimize a single topology, the applicability and breadth of the method are increased.

[0104] (2) This application introduces a check code mechanism and combines NOMA and FDD to achieve full-duplex communication of the system and reduce the system latency.

[0105] (3) This application combines the advantages of deep learning and heuristic optimization algorithms to provide an efficient and reliable solution in complex NOMA and FDD combined systems. The use of deep learning models to predict future channel state information can more accurately capture the time-varying characteristics of the channel compared to traditional methods, such as predictions based on statistical characteristics, thereby improving the accuracy of power allocation and relay selection. The heuristic optimization method (simulated annealing) can quickly find near-optimal solutions in a larger search space. Compared with traditional exhaustive methods or gradient descent methods, this method can obtain better power allocation and relay selection results within a limited time.

[0106] (4) This application not only considers the power minimization problem, but also comprehensively considers the interference problem caused by different relay selections to ensure that the total power is minimized while meeting the communication quality. Through the training and prediction of the deep learning model, it can adapt to different channel environments and user distribution conditions. The heuristic optimization algorithm can flexibly adjust the power allocation to meet the needs of different scenarios. Through iterative optimization, the power allocation and relay selection are continuously adjusted to gradually approach the optimal solution, avoiding the problem of local optimality.

[0107] In summary, this application combines deep learning and heuristic optimization to not only improve the accuracy of channel state prediction, but also quickly find near-optimal power allocation and relay selection solutions in complex optimization problems. This allows the method to significantly reduce total power consumption while ensuring communication quality, and has strong adaptability and flexibility, making it suitable for complex and changing communication environments.

[0108] In an exemplary embodiment, a computer device is provided, which may be a server or a terminal. The computer device includes a processor, a memory, an input / output interface (I / O for short) and a communication interface. The processor, the memory and the input / output interface are connected via a system bus, and the communication interface is connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a power line communication repeater arrangement method is implemented.

[0109] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0110] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0111] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0112] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0113] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0114] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0115] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0116] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for arranging a power line communication repeater, characterized in that: The power line communication repeater arrangement method comprises: Constructing a power line communication system model and a corresponding signal propagation model; the power line communication system model includes multiple nodes communicating through power lines, and the communication process between nodes adopts non-orthogonal multiple access technology; wherein one of the nodes is a signal source, and the other nodes are users; Based on the power line communication system model and the signal propagation model, an uplink model and a downlink model are respectively constructed using frequency division multiplexing technology; the downlink model is used to execute the process of the signal source sending a signal to the user; the uplink model is used to execute the process of the user sending a signal to the signal source or the process of the user as a relay node sending a signal to other users; Based on the uplink model and the downlink model, a cyclic redundancy check algorithm is used to check all the users to obtain a check result; the check result is whether the relay node needs to be turned on or not; When the verification result indicates that the relay node needs to be turned on, the current channel state data of the power line communication system model is calculated, and then the current channel state data is input into a preset channel state prediction model to obtain the channel state data at the next moment; the preset channel state prediction model is obtained based on deep learning network training; Based on the channel state data at the next moment, performing random initial power allocation to obtain an initial signal source power and multiple initial user powers in the power line communication system model; A constraint function is constructed with the goal of ensuring communication quality, and an optimization objective function is constructed with the goal of minimizing total power. Then, based on the initial signal source power, multiple initial user powers, the channel state data at the next moment, and the preset minimum total channel capacity, a heuristic algorithm is used to sequentially perform initial power optimization solutions and relay node position optimization solutions to obtain the optimized position of each relay node.

2. The method for arranging a power line communication repeater according to claim 1, characterized in that: The constraint functions include a link capacity limit function, a non-negative power constraint function, an error rate constraint function, a data rate constraint function, an electromagnetic interference constraint function and a position constraint function; The link capacity limit function is: The non-negative power constraint function is: S ≥0; P r ≥0; The error rate constraint function is: BER≤BER max ; The data rate constraint function is: The electromagnetic interference constraint function is: The position constraint function is: r , w r )∈Selectable user, in, is the signal source S to relay node u in the downlink model r The channel capacity of is the relay node u in the uplink model r To the receiving node u t The channel capacity, B d is the channel bandwidth in the downlink model, B u is the channel bandwidth in the uplink model, P S is the transmission power of the signal source S, P r is the relay node u r The transmission power, is the signal source S to relay node u in the downlink model r The channel gain, is the relay node u in the uplink model r To the receiving node u t The channel gain of N1 is the relay node u r The received noise power, N2 is the noise power received by the receiving node ut, C min is the preset minimum total channel capacity, BER is the bit error rate, BER max is the preset maximum bit error rate, R i is the data rate of user i, R min is the preset minimum data rate, E i，j is the electromagnetic interference between user i and user j, E max is the preset maximum electromagnetic interference, (v r , w r ) is the relay node u r The user's location.

3. The method for arranging power line communication repeaters according to claim 1, characterized in that: The optimization objective function is: Among them, Z is the target value, P r is the relay node u r The transmission power, N is the number of relay nodes; P c For user u c The transmission power of user u c is the user who is not a relay node among all users, M is user u c The number of S is the transmission power of the signal source S.

4. The method for arranging power line communication repeaters according to claim 1, characterized in that: Based on the initial signal source power, the multiple initial user powers, the channel state data at the next moment and the preset minimum total channel capacity, a heuristic algorithm is used to sequentially perform initial power optimization and relay node position optimization to obtain the optimized position of each relay node, including: According to the initial signal source power, the multiple initial user powers, the channel state data at the next moment and the preset minimum total channel capacity, a heuristic algorithm simulated annealing is used for multiple iterations to perform initial power optimization on the optimization objective function based on the constraint function to obtain an optimized signal source power and multiple optimized user powers; According to the optimized signal source power, multiple optimized user powers, the channel state data at the next moment and the preset minimum total channel capacity, a heuristic algorithm simulated annealing is used for multiple iterations to optimize the relay node position of the optimization objective function based on the constraint function to obtain the optimized position of each relay node; the optimized position of the relay node is the position of the user serving as the relay node.

5. The method for arranging power line communication repeaters according to claim 1, characterized in that: The signal propagation model includes a signal source sending signal function and a signal receiving signal function at the user; The signal function sent from the signal source is: The signal receiving function at the user is: i =x s A i (d i , f)h i +n i ; Among them, x s is the transmitted signal of the signal source S, L is the number of users in the power communication system model, α i is the power allocation coefficient of user i, P s is the transmission power of the signal source S, x i is the signal to be received at user i, y i is the signal actually received by user i; A i (d i , f) is the signal attenuation of user i, d i is the distance between nodes corresponding to user i, f is the communication frequency; h i is the channel gain of user i, n i is the noise received by user i.

6. The method for arranging power line communication repeaters according to claim 1, characterized in that: The total signal received by user i in the uplink model for: After user i transmits a signal, the corresponding receiving end uses serial interference cancellation technology to decode user signals one by one in order of power from large to small, and decodes the user signal with the largest power. for: Among them, K k is the number of users communicating in the uplink model, is the frequency sub-band f of user i in the uplink model uk The channel gain on is the sub-band f of user i in the uplink model at time t uk The transmitted signal on is the signal attenuation of user i during the communication process of the uplink model, is the sub-band f of the uplink model at time t uk Noise on is the channel gain from the signal source to other user j except user i, is the transmitted signal from the signal source to other users j except user i at time t, is the signal attenuation from the signal source to other user j except user i; The total transmitted signal of the signal source S in the downlink model for: After the signal source S transmits a signal, the corresponding receiving end uses serial interference cancellation technology to decode user signals one by one in order of power from large to small, and decodes the user signal with the largest power. for: Among them, L m is the number of users communicating in the downlink model, is the sub-band f of user j in the downlink model dm The channel gain on is the sub-band f of user j in the downlink model at time t dm The transmitted signal on is the sub-band f of user j in the downlink model dm The signal attenuation on is the sub-band f of the downlink model at time t dm Noise on is the channel gain from the signal source to other user k except user j, is the transmitted signal from the signal source to other user k except user j at time t, is the signal attenuation from the signal source to user k other than user j.

7. The method for arranging power line communication repeaters according to claim 1, characterized in that: Based on the uplink model and the downlink model, a cyclic redundancy check algorithm is used to check all the users to obtain a check result, including: The downlink model is used to execute the process of the signal source sending a signal to the user, and a check code is set when sending the signal; the check code is determined based on a cyclic redundancy check algorithm; The uplink model is used to execute a process in which the user sends a signal to the signal source, and verification code information is fed back when the signal is sent; Determine the correctness of the check code based on the check code sent in the downlink model and the check code information fed back in the uplink model; When the verification code is correct, the verification result is marked as no need to open the relay node; When the verification code is incorrect, the verification result is marked as requiring the relay node to be enabled.

8. The method for arranging power line communication repeaters according to claim 1, characterized in that: The current channel state data is any one of channel gain, signal-to-noise ratio, bit error rate, data rate, path loss model parameters, environmental noise, and time-varying characteristics; the deep learning network is a long short-term memory network.

9. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the power line communication repeater arrangement method according to any one of claims 1 to 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the power line communication repeater deployment method according to any one of claims 1 to 8 is implemented.

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