Physical layer simulation verification method and system for power line carrier and wireless dual-mode communication network

Abstract

The invention belongs to the technical field of power line carrier communication, and particularly relates to a physical layer simulation verification method and system for a power line carrier and a wireless dual-mode communication network. The physical layer simulation verification method and system of the power line carrier and wireless dual-mode communication network comprises the following steps: S1, establishing a comprehensive dual-mode physical layer mathematical model including physical layer characteristics of power line carrier and wireless communication; according to the physical layer simulation verification method and system, the dynamic parameter adjustment and parallel computing technology is adopted, computing resources are effectively utilized, redundant simulation is reduced, the precision and reliability of a simulation result are ensured through self-adaptive step length adjustment and an anomaly detection algorithm, and the system performance is comprehensively tested and optimized through a cross validation method and an optimization iteration module. Meanwhile, manual intervention is reduced, the automation degree of data processing and analysis is improved, the simulation time is greatly shortened, the efficiency is improved, and the accuracy and reliability of a simulation result are remarkably improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of power line carrier communication, and particularly relates to a physical layer simulation verification method and system for a power line carrier and wireless dual-mode communication network. Background Art

[0002] Broadband power line carrier communication technology uses the power line as the information medium. After a series of signal processing and transformation of the data, the encoded data is sent to the power line by using the OFDM modulation method to achieve high-speed data transmission. Broadband power line carrier communication technology can enable the power line to have the function of data communication without affecting power transmission.

[0003] With the development of technology, in addition to power line carrier communication, micro-power wireless communication technology has also been introduced, forming a so-called "dual-mode" communication network. This network can transmit data either through the power line or wirelessly, improving the flexibility and reliability of communication.

[0004] Broadband dual-mode communication technology is based on broadband power line carrier communication technology and adds micro-power wireless technology. After a series of signal processing and transformation of the data, the encoded data is sent into the air by using the OFDM modulation method. Through the coordinated work of two paths, namely the power line and space radiation, this dual-mode communication network is realized.

[0005] However, the existing physical layer simulation verification methods and systems for power line carrier and wireless dual-mode communication networks are of low efficiency and accuracy, and cannot provide stable and reliable support for applications. Therefore, it is urgent to design a physical layer simulation verification method and system for power line carrier and wireless dual-mode communication networks to solve the above problems. Summary of the Invention

[0006] The purpose of the present invention is to provide a physical layer simulation verification method and system for a power line carrier and wireless dual-mode communication network, so as to solve the problems in the above background art that the existing physical layer simulation verification methods and systems for power line carrier and wireless dual-mode communication networks are of low efficiency and accuracy and cannot provide stable and reliable support for applications.

[0007] The physical layer simulation verification method for a power line carrier and wireless dual-mode communication network includes the following steps:

[0008] S1: Establish a comprehensive dual-mode physical layer mathematical model, including the physical layer characteristics of power line carrier and wireless communication;

[0009] S2: Identify and determine various input configuration parameters to be simulated and verified in the dual-mode physical layer, including modulation mode, coding rate, and channel bandwidth;

[0010] S3: Set the effective range for each parameter and generate a simulation configuration vector file that traverses these ranges;

[0011] S4: Read the simulation configuration vector file, automatically extract and configure the corresponding parameters, and perform continuous simulation;

[0012] S5: Capture the input and output data during the simulation, and through the simulation input and output closed-loop, automatically compare the simulation output results with the expected results;

[0013] S6: Conduct simulation verification for the dual-channel cross-transceiving function in the dual-mode physical layer, and test and verify the collaborative working ability of the power line carrier and wireless communication modes under different working conditions;

[0014] S7: Optimize and iterate the model and parameters according to the simulation results until the design requirements are met.

[0015] Preferably, step S2 includes introducing a dynamic parameter adjustment mechanism to automatically adjust the effective range of the parameters according to the real-time results of the simulation, reducing unnecessary simulation times, and using machine learning algorithms to analyze historical simulation data and intelligently select the parameters that have the greatest impact on the simulation results for key verification. The formula for the dynamic parameter adjustment formula is:

[0016]

[0017] where,

[0018] θ is the parameter,

[0019] α is the learning rate,

[0020] (θ) is the objective function.

[0021] Preferably, step S4 includes: adopting parallel computing technology to simultaneously execute multiple simulation experiments, significantly shortening the simulation time, and automatically adjusting the simulation step size according to the complexity of the simulation to improve efficiency while ensuring simulation accuracy. The adaptive step size formula is:

[0022]

[0023] where,

[0024] h is the step size,

[0025] β is the adjustment coefficient.

[0026] Preferably, step S5 includes: introducing an anomaly detection algorithm to automatically identify the outliers in the simulation results, reducing the workload of manual inspection, generating a visual report, and intuitively showing the comparison between the simulation results and the expected results for quick analysis and decision-making.

[0027] Preferably, step S6 includes: in the simulation verification of the dual-channel cross transceiver function, introducing a cross-verification method to ensure the collaborative working ability of the two communication modes under different working conditions, and simulating the collaborative working of the dual-channel under different load conditions to verify the load balancing ability of the system.

[0028] The physical layer simulation verification system of the power line carrier and wireless dual-mode communication network includes an integrated simulation platform, an intelligent parameter management module, an efficient simulation execution engine, a result analysis and verification module, a collaborative working verification module, and an optimization iteration module.

[0029] Preferably, the integrated simulation platform adopts a high-performance computing platform, supports parallel computing and distributed processing, and forms the physical layer models of power line carrier and wireless communication to realize the collaborative simulation of dual-mode communication.

[0030] Preferably, the intelligent parameter management module uses machine learning algorithms to automatically identify and select the parameters that have the greatest impact on the simulation results, and realizes dynamic parameter adjustment, automatically optimizing the parameter settings according to the real-time results of the simulation. The efficient simulation execution engine adopts an adaptive step size adjustment algorithm to dynamically adjust the simulation step size according to the complexity of the simulation, realizes parallel simulation technology, and executes multiple simulation experiments simultaneously.

[0031] Preferably, the result analysis and verification module introduces an anomaly detection algorithm to automatically identify the outliers in the simulation results and generate a visual report to intuitively display the comparison between the simulation results and the expected results.

[0032] Preferably, the optimization iteration module optimizes and iterates the model and parameters according to the simulation results, and uses a feedback mechanism to feedback the optimization results to the simulation platform to realize closed-loop optimization.

[0033] Compared with the prior art, the beneficial effects of the present invention are: the physical layer simulation verification method and system of the power line carrier and wireless dual-mode communication network adopt dynamic parameter adjustment and parallel computing technology to effectively utilize computing resources, reduce redundant simulations, ensure the accuracy and reliability of the simulation results through the adaptive step size adjustment and anomaly detection algorithms, comprehensively test and optimize the system performance by using the cross-verification method and the optimization iteration module, while reducing manual intervention and improving the automation degree of data processing and analysis. This system not only greatly shortens the simulation time and improves the efficiency, but also significantly improves the accuracy and reliability of the simulation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 It is the platform block diagram of the steps of the dual-mode physical layer verification method of the present invention;

[0035] Figure 2 It is the platform block diagram of the optimization process of the dual-mode physical layer verification of the present invention;

[0036] Figure 3 Physical layer simulation and verification system for power line carrier and wireless dual-mode communication network of the present invention

[0037] Platform block diagram;

[0038] Figure 4 Platform block diagram of the dual-channel cross-verification method of the present invention. Specific implementation manners

[0039] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0040] Please refer to the attached Figures 1-4 , several embodiments provided by the present invention:

[0041] Physical layer simulation and verification method for power line carrier and wireless dual-mode communication network, including the following steps:

[0042] S1: Establish a comprehensive dual-mode physical layer mathematical model, including the physical layer characteristics of power line carrier and wireless communication;

[0043] S2: Identify and determine various input configuration parameters to be simulated and verified in the dual-mode physical layer, including modulation mode, coding rate, and channel bandwidth;

[0044] S3: Set effective ranges for each parameter and generate a simulation configuration vector file that traverses these ranges;

[0045] S4: Read the simulation configuration vector file, automatically extract and configure the corresponding parameters, and perform continuous simulation;

[0046] S5: Capture the input and output data during the simulation process, and automatically compare the simulation output results with the expected results through the simulation input and output closed loop;

[0047] S6: Perform simulation verification on the dual-channel cross-transceiving function in the dual-mode physical layer, and test and verify the collaborative working ability of the power line carrier and wireless communication modes under different working conditions;

[0048] S7: Optimize and iterate the model and parameters according to the simulation results until the design requirements are met.

[0049] Furthermore, step S2 includes introducing a dynamic parameter adjustment mechanism to automatically adjust the effective range of parameters according to the real-time results of the simulation, reducing unnecessary simulation times. Also, using machine learning algorithms to analyze historical simulation data and intelligently select the parameters that have the greatest impact on the simulation results for key verification. During the simulation process, the system should monitor the changes in key parameters and simulation results in real time, and dynamically adjust the effective range of parameters through preset rules or algorithms. At the same time, the parameter adjustment should be optimized based on the current simulation results and historical data to reduce simulation times and computational resource consumption. The computer will clean and preprocess the historical simulation data to ensure data quality for effective machine learning analysis. Evaluate the trained model and improve the accuracy and generalization ability of the model through techniques such as cross-validation and hyperparameter tuning. The formula for the dynamic parameter adjustment formula is:

[0050]

[0051] Where,

[0052] θ is the parameter,

[0053] α is the learning rate,

[0054] (θ) is the objective function.

[0055] Furthermore, step S4 includes: adopting parallel computing technology to execute multiple simulation experiments simultaneously, significantly shortening the simulation time. Using a distributed computing framework (such as MPI, OpenMP, GPU acceleration, etc.) to achieve parallel computing, so as to run multiple simulation experiments on different computing nodes simultaneously. Using a resource management system (such as Slurm, Torque, etc.) to allocate and schedule computing resources to ensure the efficiency and fairness of parallel computing. At the same time, automatically adjust the simulation step size according to the complexity of the simulation to improve efficiency while ensuring simulation accuracy. Monitor the error and stability during the simulation process in real time as the basis for adjusting the step size. Design an adaptive step size adjustment algorithm, such as a step size control algorithm based on error estimation, to automatically adjust the step size according to the complexity of the simulation and the current error. At the same time, find the optimal step size through an optimization algorithm under the premise of ensuring simulation accuracy to improve simulation efficiency. The adaptive step size formula is:

[0056]

[0057] Where,

[0058] h is the step size,

[0059] β is the adjustment coefficient.

[0060] Furthermore, step S5 includes: introducing an anomaly detection algorithm to automatically identify outliers in the simulation results, reducing the workload of manual inspection, generating a visual report to intuitively display the comparison between the simulation results and the expected results, facilitating quick analysis and decision-making. The simulation system will be able to automatically identify outliers, reduce the workload of manual inspection, and help users quickly analyze and make decisions through an intuitive visual report. This system not only improves work efficiency but also enhances the quality and speed of decision-making.

[0061] Furthermore, step S6 includes: in the simulation verification of the dual-channel cross transceiver function, introducing a cross-validation method to ensure the collaborative working ability of the two communication modes under different working conditions, and simulating the collaborative working of the dual-channel under different load conditions to verify the load balancing ability of the system. Introducing a cross-validation method in the simulation verification of the dual-channel cross transceiver function is an effective means to ensure the collaborative working ability of the two communication modes under different working conditions and verify the load balancing ability of the system, including the following steps:

[0062] a. Design simulation test cases:

[0063] Create a series of test cases covering different working conditions and load conditions.

[0064] Each test case should have clear inputs, expected outputs, and verification conditions.

[0065] b. Implement cross-validation:

[0066] Run the test cases in mode A and record the results.

[0067] Switch to mode B and use the same test cases for verification to ensure the results are consistent.

[0068] Analyze the performance differences between the two modes to ensure normal collaborative working.

[0069] c. Verify the load balancing ability:

[0070] Monitor the performance of the dual-channel when the load changes.

[0071] Analyze indicators such as data transmission efficiency, latency, and packet loss rate to ensure that the system can achieve load balancing when the load changes.

[0072] d. Performance analysis and optimization:

[0073] Based on the simulation results, identify performance bottlenecks and potential problems.

[0074] Optimize the system to improve communication efficiency, reduce latency, and packet loss rate.

[0075] e. Documentation and reporting:

[0076] Record all test cases, test results, and optimization measures.

[0077] Prepare a detailed test report, including the test process, result analysis, optimization suggestions, etc.

[0078] Through the above steps, the collaborative working ability of the dual-channel cross transceiver function under different working conditions can be comprehensively verified, and it is ensured that the system can achieve load balancing under different load conditions.

[0079] A physical layer simulation verification system for a power line carrier and wireless dual-mode communication network, including an integrated simulation platform, an intelligent parameter management module, an efficient simulation execution engine, a result analysis and verification module, a collaborative working verification module, and an optimization iteration module.

[0080] Furthermore, the integrated simulation platform adopts a high-performance computing platform, supports parallel computing and distributed processing, and integrates the physical layer models of power line carrier and wireless communication to achieve co-simulation of dual-mode communication.

[0081] Furthermore, the intelligent parameter management module uses machine learning algorithms to automatically identify and select the parameters that have the greatest impact on the simulation results, and realizes dynamic parameter adjustment, automatically optimizing the parameter settings according to the real-time results of the simulation. The efficient simulation execution engine adopts an adaptive step size adjustment algorithm, dynamically adjusts the simulation step size according to the complexity of the simulation, and implements parallel simulation technology to execute multiple simulation experiments simultaneously. The integrated simulation platform, while supporting high-performance computing, parallel computing, and distributed processing, integrates the physical layer models of power line carrier and wireless communication, and can achieve co-simulation of dual-mode communication.

[0082] Furthermore, the result analysis and verification module introduces an anomaly detection algorithm to automatically identify the outliers in the simulation results, and generates a visualization report to intuitively display the comparison between the simulation results and the expected results. In order to enhance the capabilities of the result analysis and verification module, an anomaly detection algorithm is introduced to automatically identify the outliers in the simulation results, and combined with the visualization report to intuitively display the comparison between the simulation results and the expected results. The result analysis and verification module will be able to more effectively process the simulation data, automatically identify the outliers, and visually display the comparison between the simulation results and the expected results through the visualization report, thereby helping researchers quickly understand the simulation output and make necessary adjustments and optimizations.

[0083] Furthermore, the optimization iteration module optimizes and iterates the model and parameters according to the simulation results, and uses a feedback mechanism to feedback the optimization results to the simulation platform to achieve closed-loop optimization. This module optimizes and iterates the model and parameters according to the simulation results, and uses a feedback mechanism to feedback the optimization results to the simulation platform to achieve closed-loop optimization. This system will greatly improve the accuracy and efficiency of the simulation model, while reducing the need for manual intervention.

[0084] Working principle: First, establish a comprehensive mathematical model that covers the physical layer characteristics of power line carrier and wireless communication. This model includes channel characteristics, modulation and demodulation techniques, coding methods, etc., to ensure that it can accurately simulate the physical layer behavior of dual-mode communication, identify and determine various input configuration parameters that need to be verified by simulation, such as modulation mode, coding rate, channel bandwidth, etc. Introduce a dynamic parameter adjustment mechanism to automatically adjust the effective range of parameters according to the real-time results of the simulation, reducing unnecessary simulation times. Use machine learning algorithms to analyze historical simulation data, intelligently select the parameters that have the greatest impact on the simulation results for key verification, set the effective range for the parameters, and generate a simulation configuration vector file that traverses these ranges. These files will be used for subsequent simulation experiments to ensure comprehensive coverage of the parameters, read the simulation configuration vector file, automatically extract and configure the corresponding parameters, and perform continuous simulations. Adopt parallel computing technology to execute multiple simulation experiments simultaneously, significantly shortening the simulation time, capture the input and output data during the simulation process, and automatically compare the simulation output results with the expected results through the closed-loop of simulation input and output. Introduce an anomaly detection algorithm to automatically identify outliers in the simulation results, generate a visual report, intuitively display the comparison between the simulation results and the expected results, conduct simulation verification for the dual-channel cross-transceiving function in the dual-mode physical layer, and test and verify the collaborative working ability of the power line carrier and wireless communication modes under different working conditions. Introduce a cross-validation method to ensure the collaborative working ability of the two communication modes under different working conditions and verify the load balancing ability of the system. According to the simulation results, optimize and iterate the model and parameters until the design requirements are met. Use a feedback mechanism to feedback the optimization results to the simulation platform to achieve closed-loop optimization.

[0085] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and can be implemented in other specific forms without departing from the spirit or basic characteristics of the present invention. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be included in the present invention. Any reference signs in the claims should not be regarded as limiting the claimed rights.

Claims

1. A physical layer simulation verification method for a power line carrier and wireless dual-mode communication network, characterized in that: The following steps are involved: S1: Build a comprehensive dual-mode physical layer mathematical model, including the physical layer characteristics of power line carrier and wireless communication; S2: Identify and determine the various input configuration parameters that need to be simulated and verified in the dual-mode physical layer, including modulation mode, coding rate, and channel bandwidth; S3: Set a valid range for each parameter and generate a simulation configuration vector file that traverses these ranges; S4: read the simulation configuration vector file, automatically extract and configure the corresponding parameters, and perform continuous simulation; S5: Capture input and output data during the simulation process, and automatically compare the simulation output results with the expected results through the closed loop of simulation input and output; S6: Simulate and verify the dual-channel cross-transmission and reception function in the dual-mode physical layer, and test and verify the collaborative working capabilities of the power line carrier and wireless communication modes under different working conditions; S7: Based on the simulation results, the model and parameters are optimized and iterated until the design requirements are met.

2. The physical layer simulation verification method of the power line carrier and wireless dual-mode communication network according to claim 1 is characterized in that: Step S2 includes introducing a dynamic parameter adjustment mechanism to automatically adjust the effective range of the parameters according to the real-time simulation results, reduce the number of unnecessary simulations, and use a machine learning algorithm to analyze historical simulation data and intelligently select the parameters that have the greatest impact on the simulation results for key verification. The formula for the dynamic parameter adjustment formula is: in, θ is a parameter, α is the learning rate, (θ) is the objective function.

3. The physical layer simulation verification method of the power line carrier and wireless dual-mode communication network according to claim 1 is characterized in that: Step S4 includes: using parallel computing technology to execute multiple simulation experiments simultaneously, greatly shortening the simulation time, and automatically adjusting the simulation step size according to the complexity of the simulation to ensure the simulation accuracy while improving the efficiency. The adaptive step size formula is: in, h is the step size, β is the adjustment coefficient.

4. The physical layer simulation verification method of the power line carrier and wireless dual-mode communication network according to claim 1 is characterized in that: Step S5 includes: introducing an anomaly detection algorithm to automatically identify outliers in the simulation results, reducing the workload of manual inspection, generating a visual report, intuitively displaying the comparison between the simulation results and the expected results, and facilitating rapid analysis and decision-making.

5. The physical layer simulation verification method of the power line carrier and wireless dual-mode communication network according to claim 4 is characterized in that: Step S6 includes: in the simulation verification of the dual-channel cross-transmission and reception function, a cross-verification method is introduced to ensure the collaborative working ability of the two communication modes under different working conditions, and the collaborative working of the dual channels under different load conditions is simulated to verify the load balancing ability of the system.

6. The physical layer simulation verification system of power line carrier and wireless dual-mode communication network is characterized by: It includes an integrated simulation platform, an intelligent parameter management module, an efficient simulation execution engine, a result analysis and verification module, a collaborative work verification module and an optimization iteration module.

7. The physical layer simulation verification system of the power line carrier and wireless dual-mode communication network according to claim 6 is characterized in that: The integrated simulation platform adopts a high-performance computing platform, supports parallel computing and distributed processing, and forms physical layer models of power line carrier and wireless communication to achieve collaborative simulation of dual-mode communication.

8. The physical layer simulation verification system of the power line carrier and wireless dual-mode communication network according to claim 6 is characterized in that: The intelligent parameter management module uses a machine learning algorithm to automatically identify and select the parameters that have the greatest impact on the simulation results, and implements dynamic parameter adjustment, automatically optimizing parameter settings based on the real-time results of the simulation. The efficient simulation execution engine uses an adaptive step adjustment algorithm to dynamically adjust the simulation step size according to the complexity of the simulation, implements parallel simulation technology, and executes multiple simulation experiments simultaneously.

9. The physical layer simulation verification system of the power line carrier and wireless dual-mode communication network according to claim 6, characterized in that: The result analysis and verification module introduces an anomaly detection algorithm to automatically identify outliers in the simulation results and generate a visual report to intuitively show the comparison between the simulation results and the expected results.

10. The physical layer simulation verification system of the power line carrier and wireless dual-mode communication network according to claim 6, characterized in that: The optimization iteration module optimizes and iterates the model and parameters according to the simulation results, and uses a feedback mechanism to feed back the optimization results to the simulation platform to achieve closed-loop optimization.

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