Multi-user subcarrier power distribution optimization method, system and device for power line carrier communication network and medium

Abstract

The invention relates to the technical field of power line carrier power distribution, and discloses a multi-user subcarrier power distribution optimization method, system and device for a power line carrier communication network and a medium, and the method comprises the steps that a central coordinator carries out channel estimation through pilot signals, obtains channel responses of different physical injection ports, and carries out parameter initialization; selecting an injection port based on the channel response; initial subcarrier distribution is carried out, an equivalent baseband channel matrix is constructed, and an initial baseband precoding matrix is calculated to obtain an equivalent signal-to-noise ratio of each subcarrier; by taking maximization of the total throughput as a target, carrying out optimization solution by adopting a genetic algorithm to obtain an optimal power distribution scheme; according to the invention, the subcarriers can be adaptively allocated according to the frequency response characteristic of the power line channel; optimizing a power injection matrix under the constraint of total power to improve the throughput of the system; the minimum rate requirement of the weak channel ammeter is ensured, and multi-port injection and multi-user parallel communication are supported.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power line carrier power distribution, and in particular to a multi-user subcarrier power distribution optimization method, system, device and medium for a power line carrier communication network. BACKGROUND

[0002] Power line carrier communication (PLC) has developed to a broadband high-speed stage, and OFDM modulation technology is generally used in the system to divide the broadband power line channel into hundreds to thousands of orthogonal subcarriers to combat severe frequency selective fading; adaptive modulation and subcarrier allocation algorithms based on channel estimation are introduced, and channel cognitive perception technology is introduced to monitor and dynamically allocate resources in real time, to master the signal-to-noise ratio of each subcarrier in real time through periodic pilot measurement, and to dynamically adjust the modulation order to improve the spectral utilization and adaptability.

[0003] However, since the power line itself is not designed for communication, the channel characteristics are poor; the line impedance varies greatly at different frequencies and time periods, which can cause severe reflection and standing wave; the multi-branch structure of the low-voltage distribution network and the random access and disconnection of a large number of household appliances introduce strong impulse noise, narrowband interference and multipath time-varying interference, which together cause significant differences in transmission loss between different subcarriers. The traditional OFDM subcarrier allocation method uses fixed allocation, polling allocation or a simple greedy algorithm based on average signal-to-noise ratio, which cannot utilize such a large channel difference for targeted optimization, and also leads to unsatisfactory throughput and robustness of the system in extreme noise environments or remote meter scenarios. SUMMARY

[0004] In view of the above existing problems, the present application is proposed.

[0005] Therefore, the present application provides a multi-user subcarrier power distribution optimization method and system for a power line carrier communication network to solve the problem that the channel loss difference of the power line carrier cannot be utilized and optimized, resulting in waste of transmission power, limited total throughput of the system and poor robustness.

[0006] To solve the above technical problems, the present application provides the following technical solutions: In a first aspect, the present application provides a multi-user subcarrier power distribution optimization method for a power line carrier communication network, comprising: The central coordinator performs channel estimation through a pilot signal, obtains the channel response of each meter node on each subcarrier corresponding to different physical injection ports, and performs parameter initialization; Based on the channel response, an injection port is selected; An initial subcarrier allocation is performed, an equivalent baseband channel matrix is constructed, and an initial baseband precoding matrix is calculated to obtain an equivalent signal-to-noise ratio of each subcarrier; Based on the allocated subcarriers and the equivalent signal-to-noise ratio, an optimal power allocation scheme is obtained by using a genetic algorithm for optimization solving with the target of maximizing total throughput; Based on the optimal power allocation scheme, communication configuration is performed on each meter node, and iteration updating is performed.

[0007] As a preferred scheme of the multi-user subcarrier power allocation optimization method for the power line carrier communication network, the central coordinator performs channel estimation through a pilot signal, obtains channel responses of each meter node on each subcarrier corresponding to different physical injection ports, and the channel responses include: The central coordinator sends a pilot signal to a line, activates each physical injection port, and sends a known pilot symbol, and each meter measures and reports a respective receiving response; The overall channel response and the port-specific response data are obtained by using a channel estimation algorithm once.

[0008] As a preferred scheme of the multi-user subcarrier power allocation optimization method for the power line carrier communication network, parameter initialization is performed, and the parameter initialization includes: Channel gains and average attenuation spectra of each frequency point are calculated according to pilot measurement; An equivalent channel is initialized according to a respective receiving response of each meter; And system parameters and genetic algorithm parameters are set.

[0009] As a preferred scheme of the multi-user subcarrier power allocation optimization method for the power line carrier communication network, an injection port is selected based on a channel response, and the selection includes: Based on the channel response, average coupling gains of each physical injection port to all meter nodes are calculated, and the first ports are selected.

[0010] The preferred technical scheme has the beneficial effect that the difference between the ports is utilized. By selecting the ports with the best channel conditions, the equivalent signal-to-noise ratio of the receiving end can be directly improved, and a foundation is laid for subsequent high-rate transmission.

[0011] As a preferred scheme of the multi-user subcarrier power allocation optimization method for the power line carrier communication network, an initial subcarrier allocation is performed, an equivalent baseband channel matrix is constructed, and an initial baseband precoding matrix is calculated to obtain an equivalent signal-to-noise ratio of each subcarrier, and the calculation includes: According to the channel gains, initial subcarrier allocation is performed, and a set of subcarriers served by each meter and calculate an equivalent baseband channel matrix; based on the equivalent baseband channel matrix, calculate a baseband precoding matrix; based on the baseband precoding matrix, calculate the signal-to-noise ratio and communication rate of the current subcarrier allocation.

[0012] The beneficial effects of the preferred technical solution are: through the calculation of the precoding matrix, the signal is coherently superimposed at the target meter, and is mutually canceled at the non-target meter, thereby suppressing the co-channel interference.

[0013] As a preferred scheme of the multi-user subcarrier power allocation optimization method for a power line carrier communication network, wherein: based on the allocated subcarriers and the equivalent signal-to-noise ratio, the total throughput is maximized, including: The total throughput is maximized, and the constraint conditions of simultaneously satisfying the total transmit power constraint and the minimum rate of each meter are set, which is expressed as: wherein, is the signal-to-interference-plus-noise ratio of the subcarrier allocated to the meter ; is the Shannon capacity of the meter on the subcarrier , which represents the theoretically maximum data rate that can be achieved on the corresponding subcarrier; is the power of the subcarrier allocated to the meter ; is the upper limit of the total transmit power of the CCO.

[0014] As a preferred scheme of the multi-user subcarrier power allocation optimization method for a power line carrier communication network, wherein: a genetic algorithm is used for optimization and solution to obtain an optimal power allocation scheme, including: Initialize the genetic algorithm to generate chromosomes, each of which encodes the allocation state of each subcarrier; Calculate the fitness of the current chromosome, and the fitness represents the total throughput; Use the roulette method to select individuals with fitness meeting the preset standard to form a mating pool; Uniformly cross the subcarrier allocation sub-blocks to generate new solutions; if the power constraint or QoS constraint is violated, discard and regenerate; Randomly flip some subcarrier allocation bits to form new individuals; and iteratively update until the maximum number of times, and output the optimal power allocation scheme.

[0015] In a second aspect, the present invention provides a multi-user subcarrier power allocation optimization system for power line carrier communication networks, comprising: The initialization module is used by the central coordinator to perform channel estimation through pilot signals, obtain the channel response of each meter node on each subcarrier corresponding to different physical injection ports, and perform parameter initialization. The selection module is used to select the injection port based on the channel response; The calculation module is used to perform initial subcarrier allocation, construct an equivalent baseband channel matrix, and calculate the initial baseband precoding matrix to obtain the equivalent signal-to-noise ratio of each subcarrier; The solution module is used to optimize the solution using a genetic algorithm based on the allocated subcarriers and equivalent signal-to-noise ratio, with the goal of maximizing the total throughput, to obtain the optimal power allocation scheme; The allocation update module is used to configure the communication of each meter node based on the optimal power allocation scheme and update it iteratively.

[0016] Thirdly, the present invention provides a computer device, comprising: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions, which, when executed by the processor, implement the steps of a multi-user subcarrier power allocation optimization method for power line carrier communication networks.

[0017] Fourthly, the present invention provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the multi-user subcarrier power allocation optimization method for a power line carrier communication network.

[0018] Compared with existing technologies, the advantages of this invention are as follows: Based on a multi-user communication structure consisting of a central coordinator (CCO) and multiple meter nodes, this invention combines the frequency selectivity and multi-port coupling characteristics of power line channels, and utilizes a genetic algorithm (GA) to intelligently optimize subcarrier allocation and power configuration. This maximizes the total system throughput under total transmit power constraints and improves the communication quality of meters with weak links. Overall, it can adaptively allocate subcarriers according to the frequency response characteristics of power line channels; optimize the power injection matrix under total power constraints to improve system throughput; guarantee the minimum rate requirement for meters with weak channels; and support multi-port injection and multi-user parallel communication. Attached Figure Description

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiments description. Obviously, the drawings in the following description only some of the embodiments of the present application, and for those skilled in the art, without creative labor, can also obtain other drawings according to these drawings.

[0020] Figure 1 The overall flowchart of a multi-user subcarrier power allocation optimization method for a power line carrier communication network according to an embodiment of the present application. DETAILED DESCRIPTION

[0021] In order to make the above-mentioned purposes, features and advantages of the present application more apparent and easy to understand, the specific embodiments of the present application will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only some of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should be within the scope of protection of the present application.

[0022] Embodiment 1, refer to Figure 1 According to an embodiment of the present application, a multi-user subcarrier power allocation optimization method for a power line carrier communication network is provided, comprising: S100: The central coordinator performs channel estimation through the pilot signal, obtains the channel response of each power meter node on each subcarrier corresponding to different physical injection ports, and performs parameter initialization; S200: Select the injection port based on the channel response; S300: Perform initial subcarrier allocation, construct an equivalent baseband channel matrix, and calculate an initial baseband precoding matrix to obtain the equivalent signal-to-noise ratio of each subcarrier; S400: Based on the allocated subcarriers and the equivalent signal-to-noise ratio, the genetic algorithm is used to optimize the solution to maximize the total throughput, and the optimal power allocation scheme is obtained; S500: Based on the optimal power allocation scheme, the communication configuration of each power meter node is performed, and the iteration is updated.

[0023] It should be noted that the power line carrier communication (PLC) channel has serious problems such as frequency selective fading, impedance discontinuity and multi-branch interference, which leads to significant differences in transmission loss of different frequency subcarriers. The traditional OFDM subcarrier allocation method fails to utilize channel differences for optimal allocation, thereby limiting the system throughput and robustness.

[0024] Therefore, by the steps S100-S500, the adaptive resource allocation for the complex power distribution line channel is realized by jointly optimizing the injection port coupling matrix estimation, the baseband precoding matrix and the subcarrier-meter mapping, which is suitable for the smart grid data acquisition and centralized meter reading scene.

[0025] Embodiment 2, with reference to Figure 1 For an embodiment of the present application, based on the above embodiment, a multi-user subcarrier power allocation optimization method for a power line carrier communication network is provided.

[0026] S100: The central coordinator performs channel estimation through a pilot signal, obtains channel responses of each meter node on each subcarrier corresponding to different physical injection ports, and performs parameter initialization; In the embodiment of the present application, the step S100 of the central coordinator performing channel estimation through a pilot signal to obtain channel responses of each meter node on each subcarrier corresponding to different physical injection ports includes steps A1-A2: A1: The central coordinator sends a pilot signal to the line, activates each physical injection port, and sends a known pilot symbol, each meter measures and reports its own received response; In an optional embodiment, the CCO can activate each transmission channel one by one ; The number of CCO physical injection ports; In another optional embodiment, the CCO can also activate the ports simultaneously in a code division multiplexing manner.

[0027] Specifically, after the CCO sends a pilot signal to the line, all meter nodes measure and return initial received responses of different frequency points ; Among them, the meter On the subcarrier The received response of each port The transmission channel pilot is represented as : ; Among them, The known pilot symbol; The injection coupling matrix describes the coupling relationship between each digital channel and the physical port; The noise of each port Under the transmission channel.

[0028] A2: Obtain the overall channel response and port-specific response data at one time through a channel estimation algorithm.

[0029] In an optional embodiment, the least square estimation algorithm can be used to obtain the overall channel response and port-specific response data at one time through a least square estimation algorithm from multiple Solving , the overall channel response is obtained at one time and the port-specific response data.

[0030] In another alternative embodiment, when the central coordinator activates all physical injection ports to send orthogonal or quasi-orthogonal spread spectrum pilot sequences simultaneously in a code division multiplexing manner, each meter node can separate and obtain the specific channel response of the meter to all injection ports and the overall superimposed channel response at one time by performing matched filtering or correlation despreading operation with the locally stored spread spectrum code sequence corresponding to each port.

[0031] In the embodiments of the present application, the parameter initialization in step S100 includes the following steps A3-A5: A3: calculating the channel gain of each frequency point according to pilot measurement and average attenuation spectrum; A4: initializing the equivalent channel according to the respective receiving response of each meter ; Specifically, the equivalent channel is initialized and is represented as: A5: setting the system parameters and genetic algorithm parameters.

[0032] Specifically, the system parameters can include: the total number of subcarriers of the system , the number of meter nodes , the number of CCO physical injection ports , the number of effective transmission channels ≤ , the upper limit of the total transmission power of the CCO , the noise power , the minimum rate requirement of the meter , etc.

[0033] Specifically, the genetic algorithm parameters can include: the number of chromosomes , the maximum number of generations of the genetic algorithm , the crossover probability , the mutation probability .

[0034] In the embodiments of the present application, the selection of injection ports based on the channel response in step S200 includes: Based on the channel response, the average coupling gain of each physical injection port to all meter nodes is calculated, and the first ports are selected.

[0035] Specifically, the average coupling gain can be represented as:​ Wherein, CCO can have multiple physical injection ports, such as three-phase line access points or multi-coupling transformer ports. Different ports have different coupling characteristics to each meter, forming a matrix .

[0036] In an alternative embodiment, since the line topology and the injection port position are known, the average coupling gain of each port obtained in the initialization is periodically updated, that is, based on the obtained channel estimation results, the average coupling gain of each physical injection port to all meter nodes is calculated, and the calculation is periodically repeated to update the average coupling gain.

[0037] It should be noted that S200 ranks the average coupling gain of each port from high to low, and directly takes the top ports, and the other ports are directly abandoned in this round of optimization and do not participate in subsequent precoding and power allocation. Only the top ports that are most beneficial to the whole network communication are selected, and these selected ports are used to transmit signals, so that the complexity of subsequent optimization can be greatly reduced, because the dimension of the precoding matrix is directly determined by . And in the case of multiple ports transmitting at the same time, reasonable port selection is the premise of effectively suppressing inter-port interference by subsequent precoding technology.

[0038] In the embodiments of the present application, initial subcarrier allocation is performed in step S300, and an equivalent baseband channel matrix is constructed, and an initial baseband precoding matrix is calculated to obtain the equivalent signal-to-noise ratio of each subcarrier, including the following steps B1-B3: B1: According to the channel gain , initial subcarrier allocation is performed to obtain the subcarrier served meter set , and the equivalent baseband channel matrix is calculated; In another alternative embodiment, initial subcarrier allocation can also be performed by meter priority.

[0039] Specifically, the calculation of the equivalent baseband channel matrix is represented as: B2: Based on the equivalent baseband channel matrix, the baseband precoding matrix is calculated; Specifically, the zero forcing (ZF) or regularized minimum mean square error (RZF / MMSE) method can be used to obtain the baseband precoding matrix, represented as: Wherein, .

[0040] B3: Based on the baseband precoding matrix, the signal-to-noise ratio and communication rate calculation is performed on the allocation of the current subcarrier.

[0041] Specifically, the electric meter In the subcarrier The received signal is: Specifically, the electric meter In the subcarrier The ratio of the strength of the received useful signal to the strength of the received interference signal (noise plus interference) (signal-to-noise ratio) can be represented as follows: Wherein, The power allocated to the electric meter In the subcarrier .

[0042] Specifically, the communication rate of the device can be represented as: It should be noted that the main purpose of S300 is to allocate resources and manage interference in the frequency domain and signal domain; different subcarriers are allocated to different electric meters, realizing multi-user diversity. The system can allocate good subcarriers to the users who need them, maximizing the overall spectrum efficiency. By calculating the precoding matrix, the form of the transmitted signal can be actively changed, so that the signals are coherently superimposed at the target electric meter, and are mutually canceled at the non-target electric meter, which can greatly suppress co-channel interference and improve the capacity of the multi-user system; After precoding processing, the equivalent signal-to-noise ratio on each subcarrier becomes more accurate, providing an input basis for subsequent steps.

[0043] At the same time, the purpose of calculating the initial baseband precoding matrix is to provide a basis for the subsequent genetic algorithm. Without the precoding matrix, the genetic algorithm needs to solve a complex multi-user interference problem again for each subcarrier allocation scheme evaluated, while with the precoding matrix, the interference is approximately eliminated, and the rate calculation becomes a simple diagonal channel, and the genetic algorithm can evaluate thousands of individuals per generation.

[0044] S400: Based on the allocated subcarriers and the equivalent signal-to-noise ratio, a genetic algorithm is used to optimize and solve to maximize the total throughput, and an optimal power allocation scheme is obtained; It should be noted that at this time, the power Allocated to the electric meter In the subcarrier Is unknown, so the objective function of the entire system can be represented by the following scheme.

[0045] In this embodiment of the application, step S400, based on the allocated subcarriers and equivalent signal-to-noise ratio, aims to maximize the total throughput, and includes: With the goal of maximizing total throughput, and setting constraints that simultaneously satisfy the total transmission power constraint and the minimum rate of each meter, it is expressed as: in, It is a subcarrier Assigned to electricity meters The signal-to-interference-plus-noise ratio; It is a subcarrier Power meter The Shannon capacity represents the theoretical maximum data rate achievable on the corresponding subcarrier; subcarrier Allocated to electricity meters The power; This represents the upper limit of the total transmit power of the CCO.

[0046] It should be noted that maximizing the sum of the Shannon capacities of all subcarriers and all meter nodes, i.e., maximizing the total throughput of the system, is equivalent to maximizing the data transmission efficiency of the entire network, ensuring that available spectrum resources are fully utilized to support high-speed communication.

[0047] Furthermore, in order to quickly solve this power allocation optimization problem, a genetic algorithm (GA-PA) is introduced to use the power vector as a chromosome variable to optimize the fitness function and ensure power constraints.

[0048] In this embodiment of the application, step S400 uses a genetic algorithm to optimize and solve the problem to obtain the optimal power allocation scheme, including the following steps C1-C6: C1: Initialize the genetic algorithm and generate... Each chromosome encodes 1 chromosome, and each chromosome encodes 1 chromosome. Indicates the allocation status of each subcarrier; C2: Calculate the current chromosome fitness, where fitness represents the total throughput; Specifically, the total throughput for each chromosome can be expressed as: It should be noted that the fitness function Directly corresponds to the total throughput of the objective function; Indicates subcarrier The set of meters allocated is determined by chromosome coding.

[0049] C3: Individuals whose fitness meets the preset criteria are selected using a roulette wheel method to form a mating pool; C4: Uniformly cross the sub-block of sub-carrier allocation, generate a new solution; if the power constraint or QoS constraint is violated, discard the regenerated one; Specifically, the power constraint is as follows: It should be noted that this constraint ensures that the total transmit power on all subcarriers does not exceed , preventing device overload and meeting energy efficiency requirements.

[0050] The QoS constraint is as follows: It should be noted that this constraint ensures that each meter node can obtain the minimum necessary data rate, ensuring fairness and service reliability.

[0051] C5: Randomly flip some sub-carrier allocation bits to form a new individual; C6: Perform iterative updates until the maximum number of times, and output the optimal power allocation scheme.

[0052] Specifically, repeat C2-C5 until the maximum number of times, and output the optimal allocation scheme .

[0053] It should be noted that the objective function embodies the core goal of system design, i.e., under limited power resources, by intelligently allocating power and sub-carriers, the overall network throughput is maximized, while ensuring the minimum service quality of each user, which enables the system to achieve efficient and reliable communication in complex power line channel environment.

[0054] S500: Based on the optimal power allocation scheme, configure the communication of each meter node, and perform iterative updates.

[0055] Specifically, CCO will issue the optimization results to each meter, configure the corresponding sub-carrier and power; if the channel changes significantly or the topology is updated, re-execute S100-S400, and the typical update period is 10-100 seconds.

[0056] It should be noted that through iterative updates, the system can continuously track changes in channel state and re-optimize, thereby always maintaining high performance operation; the iterative mechanism makes the system robust to temporary measurement errors or sudden disturbances, and can self-correct in the next cycle, providing stability and reliability for long-term communication.

[0057] Overall, this scheme can adaptively maximize the overall data transmission capacity of the entire network in a complex, time-varying power line channel environment, while ensuring that each user can obtain stable and reliable service.

[0058] Embodiment 3, the above is a schematic scheme of a multi-user subcarrier power allocation optimization method for a power line carrier communication network. It should be noted that the technical scheme of the system for multi-user subcarrier power allocation optimization for a power line carrier communication network and the technical scheme of the method for multi-user subcarrier power allocation optimization for a power line carrier communication network described above belong to the same concept. The technical details of the system for multi-user subcarrier power allocation optimization for a power line carrier communication network in this embodiment are not described in detail, and can be seen from the description of the technical scheme of the method for multi-user subcarrier power allocation optimization for a power line carrier communication network.

[0059] The embodiment also provides another system for multi-user subcarrier power allocation optimization for a power line carrier communication network, comprising: The initialization module is configured to perform channel estimation by the central coordinator through a pilot signal, obtain channel responses of each electricity meter node on each subcarrier corresponding to different physical injection ports, and perform parameter initialization. The selection module is configured to select an injection port based on the channel responses. The calculation module is configured to perform initial subcarrier allocation, construct an equivalent baseband channel matrix, and calculate an initial baseband precoding matrix to obtain an equivalent signal-to-noise ratio of each subcarrier. The solving module is configured to perform optimization and solving by using a genetic algorithm based on the allocated subcarriers and the equivalent signal-to-noise ratio, so as to maximize the total throughput, and obtain an optimal power allocation scheme. The allocation updating module is configured to perform communication configuration on each electricity meter node based on the optimal power allocation scheme, and iteratively update.

[0060] The embodiment also provides a computer device suitable for the case of implementing a multi-user subcarrier power allocation optimization method for a power line carrier communication network, comprising a memory and a processor. The memory is configured to store computer executable instructions, and the processor is configured to execute the computer executable instructions to implement the method for multi-user subcarrier power allocation optimization for a power line carrier communication network proposed in the above embodiment.

[0061] The embodiment also provides a storage medium having a computer program stored thereon. The program is executed by a processor to implement the method for multi-user subcarrier power allocation optimization for a power line carrier communication network proposed in the above embodiment.

[0062] The storage medium proposed in the embodiment and the method for multi-user subcarrier power allocation optimization for a power line carrier communication network proposed in the above embodiment belong to the same inventive concept. The technical details not described in detail in the embodiment can be seen from the above embodiment, and the embodiment has the same beneficial effects as the above embodiment.

[0063] Those skilled in the art can clearly understand the present application by the above description of the embodiments. Based on such understanding, the technical solutions of the present application can be embodied in the form of a software product, which can be stored in a computer readable storage medium, such as a floppy disk, a ROM, a RAM, a FLASH, a hard disk, or an optical disc, and includes a number of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute the methods of various embodiments of the present application.

[0064] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present application but not limit the present application. Although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or equivalently replaced without departing from the spirit and scope of the present application, and all modifications and equivalent replacements should be covered in the scope of the claims of the present application.

Claims

1. A method for optimizing multi-user subcarrier power allocation in power line carrier communication networks, characterized in that, include: The central coordinator performs channel estimation using pilot signals, obtains the channel response of each meter node on each subcarrier corresponding to different physical injection ports, and initializes the parameters. Select the injection port based on the channel response; Perform initial subcarrier allocation, construct an equivalent baseband channel matrix, and calculate the initial baseband precoding matrix to obtain the equivalent signal-to-noise ratio of each subcarrier; Based on the allocated subcarriers and equivalent signal-to-noise ratio, and with the goal of maximizing the total throughput, a genetic algorithm is used to optimize and solve the problem to obtain the optimal power allocation scheme. Based on the optimal power allocation scheme, communication configuration is performed for each meter node, and the configuration is updated iteratively.

2. The method for optimizing multi-user subcarrier power allocation in a power line carrier communication network as described in claim 1, characterized in that, The central coordinator performs channel estimation using pilot signals to obtain the channel response of each meter node at different physical injection ports on each subcarrier, including: The central coordinator sends pilot signals to the line, activates each physical injection port, and sends known pilot symbols. Each meter measures and reports its own reception response. The overall channel response and port-specific response data are obtained in one go through the channel estimation algorithm.

3. The method for optimizing multi-user subcarrier power allocation in a power line carrier communication network as described in claim 2, characterized in that, Perform parameter initialization, including: Calculate the channel gain and average attenuation spectrum at each frequency point based on pilot measurements; Initialize the equivalent channel based on the individual received responses from each meter; Then set the system parameters and genetic algorithm parameters.

4. The method for optimizing multi-user subcarrier power allocation in a power line carrier communication network as described in claim 3, characterized in that, Based on the channel response, the injection port is selected, including: Based on the channel response, the average coupling gain from each physical injection port to all meter nodes is calculated, and the first... One port.

5. The method for optimizing multi-user subcarrier power allocation in a power line carrier communication network as described in claim 4, characterized in that, Initial subcarrier allocation is performed, and an equivalent baseband channel matrix is ​​constructed. The initial baseband precoding matrix is ​​calculated to obtain the equivalent signal-to-noise ratio of each subcarrier, including: Based on the channel gain, perform initial subcarrier allocation and obtain subcarriers. Service meter collection And calculate the equivalent baseband channel matrix; The baseband precoding matrix is ​​calculated based on the equivalent baseband channel matrix; Based on the baseband precoding matrix, the signal-to-noise ratio and communication rate are calculated for the current subcarrier allocation.

6. The method for optimizing multi-user subcarrier power allocation in a power line carrier communication network as described in claim 5, characterized in that, Based on the allocated subcarriers and equivalent signal-to-noise ratio, the goal is to maximize total throughput, including: With the goal of maximizing total throughput, and setting constraints that simultaneously satisfy the total transmission power constraint and the minimum rate of each meter, it is expressed as: in, It is a subcarrier Assigned to electricity meters The signal-to-interference-plus-noise ratio; It is a subcarrier Power meter The Shannon capacity represents the theoretical maximum data rate achievable on the corresponding subcarrier; subcarrier Allocated to electricity meters The power; This represents the upper limit of the total transmit power of the CCO.

7. The method for optimizing multi-user subcarrier power allocation in a power line carrier communication network as described in claim 6, characterized in that, The optimal power allocation scheme is obtained by using a genetic algorithm for optimization, including: Initialize the genetic algorithm and generate Each chromosome is encoded to represent the subcarrier allocation status; Calculate the current chromosome fitness, where fitness represents the total throughput; The roulette wheel method was used to select individuals whose fitness met the preset criteria to form a mating pool; The subcarriers are uniformly cross-allocated to generate new solutions; if power constraints or QoS constraints are violated, the solution is discarded and regenerated. Randomly flip some of the subcarrier allocation bits to form a new individual; It then iterates and updates the algorithm until the maximum number of iterations is reached, at which point the optimal power allocation scheme is output.

8. A multi-user subcarrier power allocation optimization system for power line carrier communication networks, employing the method described in any one of claims 1-7, characterized in that, include: The initialization module is used by the central coordinator to perform channel estimation through pilot signals, obtain the channel response of each meter node on each subcarrier corresponding to different physical injection ports, and perform parameter initialization. The selection module is used to select the injection port based on the channel response; The calculation module is used to perform initial subcarrier allocation, construct an equivalent baseband channel matrix, and calculate the initial baseband precoding matrix to obtain the equivalent signal-to-noise ratio of each subcarrier; The solution module is used to optimize the solution using a genetic algorithm based on the allocated subcarriers and equivalent signal-to-noise ratio, with the goal of maximizing the total throughput, to obtain the optimal power allocation scheme; The allocation update module is used to configure the communication of each meter node based on the optimal power allocation scheme and update it iteratively.

9. A computer device, characterized in that, include: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, they implement the steps of the multi-user subcarrier power allocation optimization method for a power line carrier communication network as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, It stores computer-executable instructions that, when executed by a processor, implement the steps of the multi-user subcarrier power allocation optimization method for a power line carrier communication network as described in any one of claims 1 to 7.

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