A method and system for intelligent selection and switching of power line broadband carrier communication channels

Abstract

The present application relates to the field of communication technology, in particular to a kind of power line broadband carrier communication channel intelligent selection and switching method and system.The present application introduces multi-modal channel quality basic data, including signal quality modal data, transmission performance modal data and interference characteristic modal data, combined with signal stability, transmission efficiency and anti-interference ability scoring mechanism, effectively improve the comprehensive evaluation precision of power line communication channel quality, by feedback link dynamic acquisition upstream and downstream equipment real-time communication state information, optimization correction channel quality score, and comprehensive consideration communication demand matching degree, further improve the intelligentization and self-adaptive ability of channel selection and switching, so as to be able to monitor the comprehensive evaluation index of communication channel in real time, according to the evaluation result, automatically select or switch to optimal communication channel, ensure the stability of communication quality and transmission efficiency, effectively improve the reliability of power line broadband carrier communication system.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of communication technology, in particular to a power line broadband carrier communication channel intelligent selection and switching method and system. BACKGROUND

[0002] Power line broadband carrier communication is a communication technology that uses existing power lines as a communication medium to achieve data transmission. PLC can transmit information in the existing power network by modulating data carriers into high-frequency signals of the power line. It is commonly used in smart grids, home automation, energy management, and other fields, especially in cases where additional wiring is not available, it can provide network connectivity for devices through power lines.

[0003] Currently, the channel intelligent selection and switching of power line broadband carrier communication is mainly through adaptive modulation and coding technology. The principle is to adjust the modulation order and coding rate according to the current quality of the channel. When the channel condition is good, higher-order modulation and lower coding rate are used to improve the data transmission rate, and when the channel quality is poor, the modulation order is reduced and the coding rate is increased to ensure the reliability of transmission. However, the quality of the power line communication channel is affected by various factors such as power equipment and environmental noise, which may make the evaluation of channel quality inaccurate, thereby affecting the adjustment effect of adaptive modulation and coding technology. SUMMARY

[0004] The main purpose of the present application is to provide a power line broadband carrier communication channel intelligent selection and switching method, which aims to solve the technical problems in the prior art.

[0005] The present application provides a power line broadband carrier communication channel intelligent selection and switching method, comprising:

[0006] Obtain multi-modal channel quality basic data of upstream devices, downstream devices and multiple candidate communication channels in a power line broadband carrier communication network, and obtain channel quality scores of corresponding candidate communication channels according to each multi-modal channel quality basic data;

[0007] According to the upstream device, the downstream device and each candidate communication channel, a corresponding feedback link is established, the upstream device sends a feedback request to the downstream device according to each feedback link, and the downstream device responds to the feedback request and returns corresponding feedback information;

[0008] According to the feedback information, a feedback correction factor is obtained, and the channel quality score of the corresponding candidate communication channel is optimized and corrected according to each feedback correction factor to obtain a corresponding corrected channel quality score;

[0009] According to the upstream communication requirement parameter of the upstream device, the downstream communication requirement parameter of the downstream device, and the total requirement matching degree of each candidate communication channel, and according to each total requirement matching degree and the corresponding modified channel quality score, a comprehensive evaluation index of each candidate communication channel is obtained;

[0010] The candidate communication channel corresponding to the maximum comprehensive evaluation index is selected as the current optimal communication channel, and a real-time comprehensive evaluation index of the current optimal communication channel is monitored in real time;

[0011] It is judged whether the real-time comprehensive evaluation index is less than a preset evaluation index;

[0012] If the real-time comprehensive evaluation index is less than the preset evaluation index, the candidate communication channel meeting the preset condition is switched to the current optimal communication channel;

[0013] If the real-time comprehensive evaluation index is not less than the preset evaluation index, the current optimal communication channel is not switched.

[0014] As preferred, the step of obtaining the channel quality score of each candidate communication channel according to the multi-modal channel quality basic data comprises:

[0015] Signal quality modal data, transmission performance modal data, and interference characteristic modal data are obtained according to the multi-modal channel quality basic data;

[0016] The number of error symbols received in a unit time, the total number of transmission symbols, the number of successfully transmitted bytes, and the instantaneous phase of the received signal are obtained according to the signal quality modal data, and the real-time bit error rate is obtained according to the number of error symbols and the total number of transmission symbols;

[0017] The instantaneous transmission rate is obtained according to the number of successfully transmitted bytes in a unit time, and the transmission rate fluctuation value is obtained according to the instantaneous transmission rate and a preset nominal rate;

[0018] The phase jitter amplitude is obtained according to the instantaneous phase and a preset ideal phase, and the signal stability score is obtained according to the phase jitter amplitude, the transmission rate fluctuation value, and the real-time bit error rate;

[0019] The channel actual use bandwidth, the received signal power, the noise power, the transmission time delay, and the throughput are obtained according to the transmission performance modal data, and the average signal-to-noise ratio is obtained according to the received signal power and the noise power;

[0020] The channel capacity is obtained according to the average signal-to-noise ratio and the channel actual use bandwidth, and the transmission efficiency score is obtained according to the channel capacity, the transmission time delay, and the throughput;

[0021] The fading depth, signal-to-interference ratio (SIR), and noise power spectral density are obtained based on the interference characteristic mode data, and an anti-interference capability score is obtained based on the fading depth, SIR, and noise power spectral density.

[0022] Preferably, the step of obtaining the fading depth, signal-to-interference ratio, and noise power spectral density based on the interference characteristic mode data, and obtaining the anti-interference capability score based on the fading depth, signal-to-interference ratio, and noise power spectral density, includes:

[0023] The received signal spectrum is obtained based on the interference characteristic mode data, and the pure noise band, useful signal band, and interference signal band are obtained based on the spectrum.

[0024] Extract a first power spectral density of a predetermined number of frequency points from the pure noise frequency band, and obtain the noise power spectral density based on multiple first power spectral densities;

[0025] Integrating the second power spectral density over all frequency points within the useful signal frequency band yields the useful signal power;

[0026] Integrate the third power spectral density over all frequency points within the interference signal band to obtain the interference signal power, and obtain the signal-to-interference ratio based on the useful signal power and the interference signal power;

[0027] Extract the signal amplitude spectrum within the useful signal frequency band, and obtain the fading peak and fading valley values ​​based on the signal amplitude spectrum;

[0028] The fading depth is obtained based on the fading peak and fading valley values, and the anti-interference capability score is obtained based on the fading depth, signal-to-interference ratio, and noise power spectral density.

[0029] Preferably, the step of obtaining the feedback correction factor based on the feedback information includes:

[0030] Based on the feedback information, obtain data reception integrity, buffer queue length, and multiple real-time received signal strengths;

[0031] The noise interference index, real-time data processing rate, rated processing rate, preset maximum allowable delay, and average delay time of data packets in the queue of the downstream device are obtained, and the data processing capability index is obtained based on the real-time data processing rate and rated processing rate.

[0032] The buffer queue delay attenuation factor is obtained based on the preset maximum allowable delay and the average delay time of data packets in the queue, and the buffer queue correction coefficient is obtained based on the buffer queue delay attenuation factor, the data processing capability index, and the buffer queue length.

[0033] An average signal strength is obtained based on multiple real-time received signal strengths, and a signal fluctuation coefficient is obtained based on the average signal strength and multiple real-time received signal strengths.

[0034] The maximum and minimum real-time received signal strengths are extracted from the multiple real-time received signal strengths, and a signal strength correction coefficient is calculated based on the maximum and minimum real-time received signal strengths, the signal fluctuation coefficient, and the noise interference index. The calculation formula is as follows:

[0035]

[0036] Where X(XZ) represents the signal strength correction coefficient, X(BD) represents the signal fluctuation coefficient, D(SX) represents the maximum real-time received signal strength, X(SX) represents the minimum real-time received signal strength, and Z(GR) represents the noise interference index.

[0037] Based on the data reception integrity, obtain the data priority weight, retransmission count, and total transmission count, and obtain the retransmission impact factor based on the retransmission count and total transmission count;

[0038] The data reception correction coefficient is obtained based on the retransmission impact factor, data priority weight, and data reception integrity, and the feedback correction factor is obtained based on the data reception correction coefficient, signal strength correction coefficient, and buffer queue correction coefficient.

[0039] Preferably, the step of obtaining the corresponding total demand matching degree based on the upstream communication demand parameters of the upstream device, the downstream communication demand parameters of the downstream device, and each candidate communication channel includes:

[0040] Based on the upstream communication requirement parameters, obtain the latency tolerance, allowable packet loss rate, and throughput requirements;

[0041] The receiving capability threshold, error correction capability, and synchronization accuracy requirements are obtained based on the downstream communication requirement parameters.

[0042] Obtain the actual channel delay, actual packet loss rate, channel bandwidth, and channel stability coefficient for each candidate communication channel;

[0043] The real-time matching degree is obtained based on the aforementioned delay tolerance, reception capability threshold, and actual channel delay.

[0044] The reliability matching degree is obtained based on the allowable packet loss rate, error correction capability, and actual packet loss rate of the channel.

[0045] The throughput matching degree is obtained based on the throughput requirement, synchronization accuracy requirement, channel bandwidth, and channel stability coefficient.

[0046] The total demand matching degree is obtained based on the throughput matching degree, reliability matching degree, and real-time matching degree.

[0047] Preferably, the step of switching the candidate communication channel that meets the preset conditions to the current optimal communication channel includes:

[0048] All remaining candidate communication channels are sorted according to the magnitude of the comprehensive evaluation index to obtain a candidate channel ranking table;

[0049] Obtain the key parameters of the first candidate communication channel in the candidate channel ranking table, and determine whether the key parameters meet the preset requirements;

[0050] If the key parameters do not meet the preset requirements, then the candidate communication channel ranked second in the candidate channel sorting table is obtained until the key parameters of the selected candidate communication channel meet the preset requirements.

[0051] If the key parameters meet the preset requirements, the target channel identifier of the candidate communication channel is obtained, and the target channel identifier is sent to the upstream device to generate a switching instruction, wherein the switching instruction includes a termination instruction, a start instruction, and a switching time;

[0052] The upstream device sends a termination command and a switching time to the current optimal communication channel so that the current optimal communication channel stops transmitting.

[0053] The upstream device sends the start command and switching time to a candidate communication channel whose key parameters meet preset requirements, switches the current optimal communication channel to the candidate communication channel, and starts transmission.

[0054] This application also provides a power line broadband carrier communication channel intelligent selection and switching system, including:

[0055] The first acquisition module is used to acquire multimodal channel quality basic data of upstream devices, downstream devices and multiple candidate communication channels in the power line broadband carrier communication network, and to acquire the channel quality score of the corresponding candidate communication channel based on each of the multimodal channel quality basic data.

[0056] The feedback module is used to establish a corresponding feedback link with each candidate communication channel based on the upstream device, the downstream device, and the upstream device. The upstream device sends a feedback request to the downstream device according to each feedback link, and the downstream device responds to the feedback request and returns the corresponding feedback information.

[0057] The correction module is used to obtain feedback correction factors based on the feedback information, and to optimize and correct the channel quality score of the corresponding candidate communication channel based on each feedback correction factor to obtain the corresponding corrected channel quality score.

[0058] The second acquisition module is used to obtain the corresponding total demand matching degree based on the upstream communication demand parameters of the upstream device, the downstream communication demand parameters of the downstream device and each candidate communication channel, and to obtain the comprehensive evaluation index of the corresponding candidate communication channel based on each total demand matching degree and the corresponding corrected channel quality score.

[0059] The selection module is used to select the candidate communication channel corresponding to the largest comprehensive evaluation index as the current optimal communication channel, and to monitor the real-time comprehensive evaluation index of the current optimal communication channel in real time.

[0060] The switching module is used to determine whether the real-time comprehensive evaluation index is less than the preset evaluation index;

[0061] If the real-time comprehensive evaluation index is less than the preset evaluation index, then the candidate communication channel that meets the preset conditions will be switched to the current optimal communication channel.

[0062] If the real-time comprehensive evaluation index is not less than the preset evaluation index, the current optimal communication channel will not be switched.

[0063] Preferably, the second acquisition module includes:

[0064] The first acquisition unit is used to acquire the latency tolerance, allowable packet loss rate and throughput requirement based on the upstream communication requirement parameters.

[0065] The second acquisition unit is used to acquire the receiving capability threshold, error correction capability and synchronization accuracy requirements based on the downstream communication requirement parameters.

[0066] The third acquisition unit is used to acquire the actual channel delay, actual packet loss rate, channel bandwidth and channel stability coefficient of each candidate communication channel;

[0067] The fourth acquisition unit is used to acquire the real-time matching degree based on the delay tolerance, the receiving capability threshold and the actual channel delay;

[0068] The fifth acquisition unit is used to acquire the reliability matching degree based on the allowable packet loss rate, error correction capability and actual packet loss rate of the channel;

[0069] The sixth acquisition unit is used to acquire the throughput matching degree based on the throughput requirement, synchronization accuracy requirement, channel bandwidth and channel stability coefficient;

[0070] The seventh acquisition unit is used to acquire the total demand matching degree based on the throughput matching degree, reliability matching degree, and real-time matching degree.

[0071] The present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the above-described intelligent selection and switching method for power line broadband carrier communication channels.

[0072] The present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the above-described intelligent selection and switching method for power line broadband carrier communication channels.

[0073] The beneficial effects of this invention are as follows: By introducing multimodal channel quality fundamental data, including signal quality mode data, transmission performance mode data, and interference characteristic mode data, and combining it with a scoring mechanism for signal stability, transmission efficiency, and anti-interference capability, this invention effectively improves the comprehensive evaluation accuracy of power line communication channel quality, avoids the negative impact of external interference factors such as power equipment and environmental noise on communication channel quality, dynamically obtains real-time communication status information of upstream and downstream devices through feedback links, optimizes and corrects channel quality scores, and comprehensively considers communication demand matching degree, further enhancing the intelligence and adaptive capability of channel selection and switching. This enables real-time monitoring of the comprehensive evaluation index of the communication channel, automatically selecting or switching to the optimal communication channel based on the evaluation results, ensuring the stability of communication quality and transmission efficiency, and effectively improving the reliability and performance of power line broadband carrier communication systems in complex environments. Attached Figure Description

[0074] Figure 1 This is a schematic diagram of a method flow according to an embodiment of the present invention.

[0075] Figure 2 This is a schematic diagram of the system structure according to an embodiment of the present invention.

[0076] Figure 3 This is a schematic diagram of the internal structure of a computer device according to an embodiment of this application.

[0077] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0078] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0079] like Figure 1 As shown, this application provides a method for intelligent selection and switching of power line broadband carrier communication channels, including:

[0080] S1. Obtain multimodal channel quality basic data of upstream devices, downstream devices and multiple candidate communication channels in the power line broadband carrier communication network, and obtain the channel quality score of the corresponding candidate communication channel based on each of the multimodal channel quality basic data.

[0081] S2. Establish a corresponding feedback link with each candidate communication channel based on the upstream device, downstream device and the upstream device. The upstream device sends a feedback request to the downstream device according to each feedback link. The downstream device responds to the feedback request and returns the corresponding feedback information.

[0082] S3. Obtain feedback correction factors based on the feedback information, and optimize and correct the channel quality score of the corresponding candidate communication channel based on each feedback correction factor to obtain the corresponding corrected channel quality score.

[0083] S4. Obtain the corresponding total demand matching degree based on the upstream communication demand parameters of the upstream device, the downstream communication demand parameters of the downstream device, and each candidate communication channel, and obtain the comprehensive evaluation index of the corresponding candidate communication channel based on each total demand matching degree and the corresponding corrected channel quality score.

[0084] S5. Select the candidate communication channel corresponding to the largest comprehensive evaluation index as the current optimal communication channel, and monitor the real-time comprehensive evaluation index of the current optimal communication channel in real time.

[0085] S6. Determine whether the real-time comprehensive evaluation index is less than the preset evaluation index;

[0086] If the real-time comprehensive evaluation index is less than the preset evaluation index, then the candidate communication channel that meets the preset conditions will be switched to the current optimal communication channel.

[0087] If the real-time comprehensive evaluation index is not less than the preset evaluation index, the current optimal communication channel will not be switched.

[0088] As described in steps S1-S6 above, the upstream device is the master device (such as a concentrator, gateway, control terminal, etc.) responsible for initiating data transmission and issuing commands in the network, while the downstream device is the slave device (such as a smart meter, sensor, actuator, etc.) that receives data or responds to commands from the upstream device. The two constitute a fixed communication link, and their communication requirements (such as bandwidth and latency) and feedback information (such as reception quality) are the core criteria for evaluating channel suitability. Candidate channels are the communication carriers that can be selected between the upstream and downstream devices. This invention obtains signal quality mode data, transmission performance mode data, and interference data from the upstream devices, downstream devices, and multiple candidate communication channels in the power line broadband carrier communication network. Obtaining multi-mode channel quality data, including interference characteristic mode data, provides more comprehensive and accurate information for subsequent channel assessment. Existing technologies often rely on a single data source or mode, such as focusing only on signal strength or transmission rate. This approach cannot accurately capture the true quality of power line communication channels. This invention, by integrating multi-dimensional data such as signal quality, transmission performance, and interference characteristics, can comprehensively reflect the actual performance of the channel, reducing misjudgments caused by single-mode data. This provides a more reliable basis for subsequent channel quality scoring. Compared to traditional technologies, using multi-mode data significantly improves the accuracy and reliability of channel quality assessment by integrating each signal quality mode data, transmission performance mode data, and interference characteristic mode data. The data corresponds to signal stability scores, transmission efficiency scores, and anti-interference capability scores. By evaluating signal stability, transmission efficiency, and anti-interference capability separately, a multi-dimensional quantitative assessment of the channel can be achieved. This detailed scoring method not only accurately reveals the channel's strengths and weaknesses across different dimensions but also effectively avoids attributing channel problems to a single factor. For example, a channel with good signal quality may suffer from poor anti-interference capability due to excessive interference, thus affecting communication performance. Traditional technologies may ignore these factors and focus only on a single dimension. However, this invention calculates and compares these scores separately, helping the system optimize channel selection based on actual conditions, thereby significantly improving communication stability and reliability. Furthermore, based on each signal stability score... The channel quality score of the corresponding candidate communication channel is obtained through a combination of transmission efficiency score and anti-interference capability score. A corresponding feedback link is established between the upstream and downstream devices and each candidate communication channel. The upstream device sends a feedback request to the downstream device based on each feedback link. The downstream device responds to the feedback request and returns corresponding feedback information, including data reception integrity, buffer queue length, and multiple real-time received signal strengths. Establishing feedback links enables bidirectional channel quality assessment and dynamic adjustment during communication. Traditional channel selection methods are mostly based on unidirectional data transmission and lack real-time, bidirectional feedback mechanisms. This invention, through the feedback link between the upstream and downstream devices, allows the system to adjust in real time according to the actual reception situation.For example, communication strategies can be optimized based on feedback information such as received signal strength and data integrity, thereby avoiding performance degradation caused by the device's failure to detect changes in transmission status in a timely manner.

[0089] Feedback correction factors are obtained by considering data reception integrity, buffer queue length, and multiple real-time received signal strengths. Based on each feedback correction factor, the channel quality score of the corresponding candidate communication channel is optimized and corrected to obtain the corresponding corrected channel quality score. Feedback correction factors are a crucial means for improving communication quality in this invention. Indicators such as real-time received signal strength, data reception integrity, and buffer queue length reflect the immediate state of communication, helping the system to react quickly. In traditional technologies, these factors are often not fed back or considered in a timely manner, causing the system to be unable to adjust communication parameters in real time, thus affecting performance. This invention, by accurately acquiring these data and calculating feedback correction factors, can accurately correct the channel quality score, thereby improving channel selection. Accuracy and stability are crucial; channel quality scoring is a vital basis for system evaluation of each candidate communication channel. Optimizing channel quality scoring through feedback correction factors allows for dynamic adjustments based on the actual communication environment. Existing channel quality assessments are often static, neglecting real-time environmental factors (such as noise variations and interference fluctuations). This invention, by introducing a feedback correction mechanism, can adjust the score in real-time during signal transmission, ensuring the selected channel is always in optimal condition. This mechanism enhances the system's adaptability and intelligence, avoids inefficient selection due to fixed evaluation standards, and improves communication efficiency and stability. This is achieved by separately acquiring upstream and downstream communication demand parameters from upstream and downstream devices, and then adjusting the score accordingly. The system obtains a total demand matching degree for each candidate communication channel by considering upstream and downstream communication demand parameters and parameters. By comprehensively considering the communication demand parameters of both upstream and downstream, the system can better match the channel with the actual demand. Traditional methods often ignore the specific demand differences between devices and may choose a channel even if it is not optimal. However, by introducing the calculation of the total demand matching degree, the system can select the most suitable channel according to specific communication needs, ensuring that the communication needs of upstream and downstream devices are optimally met, thereby improving the utilization of network resources and communication quality. The system obtains a comprehensive evaluation index for each candidate communication channel by using the total demand matching degree and the corresponding modified channel quality score, and selects the candidate communication channel corresponding to the highest comprehensive evaluation index. The channel is currently the optimal communication channel. The introduction of a comprehensive evaluation index synthesizes evaluation results from multiple dimensions, providing a comprehensive channel quality evaluation standard. Existing technologies typically rely on a single quality indicator for selection, which may lead to incomplete or inaccurate channel selection. This invention, by comprehensively considering the overall demand matching degree and the corrected channel quality score, enables the system to make the optimal selection, ensuring that the communication channel is not only of excellent quality but also adaptable to current network requirements. This comprehensive evaluation method significantly improves the system's intelligence and adaptability. It monitors the real-time comprehensive evaluation index of the current optimal communication channel and determines whether the real-time comprehensive evaluation index is less than a preset evaluation index. If the real-time comprehensive evaluation index is less than the preset evaluation index...The system switches from the current optimal communication channel to one of the remaining candidate communication channels. If the real-time comprehensive evaluation index is not less than the preset evaluation index, the current optimal communication channel is not switched. This real-time monitoring and dynamic channel switching mechanism ensures that the system can continuously provide the best communication quality under changing environmental conditions. Traditional technologies generally rely on fixed channel selection strategies, which cannot cope with real-time environmental changes. However, this invention, through real-time evaluation and automatic channel switching, allows the system to adjust promptly when network conditions change, avoiding performance degradation. This dynamic adjustment mechanism greatly improves the stability and flexibility of communication, ensuring the efficiency and reliability of the power line communication network. This invention overcomes the problem of poor adaptive modulation and coding technology performance caused by inaccurate channel quality evaluation in existing technologies by comprehensively using multiple technical means such as multimodal data evaluation, feedback correction, and demand matching. Compared with traditional technologies, this invention is more intelligent, flexible, and adaptable to complex and changing power line communication environments, thereby significantly improving communication quality, stability, and efficiency.

[0090] In one embodiment, step S1, which involves obtaining the channel quality score of the corresponding candidate communication channel based on each of the multimodal channel quality baseline data, includes:

[0091] S11. Obtain signal quality mode data, transmission performance mode data and interference characteristic mode data based on the multi-mode channel quality basic data. Obtain the number of erroneous symbols received per unit time, the total number of transmitted symbols, the number of successfully transmitted bytes and the instantaneous phase of the received signal based on the signal quality mode data. Obtain the real-time bit error rate based on the number of erroneous symbols and the total number of transmitted symbols.

[0092] S12. Obtain the instantaneous transmission rate based on the number of bytes successfully transmitted per unit time, and obtain the transmission rate fluctuation value based on the instantaneous transmission rate and the preset nominal rate.

[0093] S13. Obtain the phase jitter amplitude based on the instantaneous phase and the preset ideal phase, and calculate the signal stability score by weighted summation based on the phase jitter amplitude, the transmission rate fluctuation value and the real-time bit error rate.

[0094] S14. Obtain the actual bandwidth used by the channel, received signal power, noise power, transmission delay and throughput based on the transmission performance mode data, and obtain the average signal-to-noise ratio based on the ratio of received signal power to noise power;

[0095] The channel capacity is calculated based on the average signal-to-noise ratio and the actual bandwidth used by the channel, wherein the calculation formula is: Where R(RL) represents the channel capacity, X(DK) represents the actual bandwidth used by the channel, and P(XZ) represents the average signal-to-noise ratio;

[0096] S15. A transmission efficiency score is obtained by weighted summation based on the channel capacity, transmission delay and throughput.

[0097] S16. Obtain the fading depth, signal-to-interference ratio, and noise power spectral density based on the interference characteristic mode data, and obtain the anti-interference capability score based on the fading depth, signal-to-interference ratio, and noise power spectral density.

[0098] As described in steps S11-S16 above, the channel capacity calculation formula is the Shannon formula, making the calculation more stable and efficient. The number of error symbols is obtained by parsing the demodulated symbol sequence from the signal quality mode data at the receiving end and by obtaining the original reference symbol sequence at the transmitting end, and then comparing the demodulated symbol sequence with the original reference symbol sequence. The average transmission rate of the sliding window can be obtained from the instantaneous transmission rate, and then the transmission rate fluctuation value can be obtained by calculating the deviation amplitude between the average transmission rate and the preset nominal rate. The phase jitter amplitude refers to the peak value of the instantaneous phase deviation of the received signal from the ideal phase, reflecting... The stability of carrier synchronization can be assessed by orthogonally demodulating the received carrier signal in the signal quality mode data to obtain in-phase and quadrature components. The instantaneous phase can be obtained by calculating the ratio of the in-phase and quadrature components. The ideal phase is a linearly changing carrier phase. The instantaneous phase deviation can be obtained by the difference between the instantaneous phase and the ideal phase. The phase jitter amplitude can be obtained by taking the peak value of the deviation within a preset time period (the maximum fluctuation range of the phase deviation). Throughput refers to the amount of effective data successfully transmitted per unit time, reflecting the actual data transmission efficiency of the channel (distinct from the theoretical value of the channel capacity). The effective data volume can be obtained from the transmission performance mode data. The effective payload length of each successfully transmitted data frame and the total number of successfully transmitted frames within the statistical time window are extracted from the data. The total number of effective bits can be obtained based on the total number of frames and the effective payload length of each data frame. The throughput can be calculated by the ratio of the total number of effective bits to the statistical time window. Transmission delay refers to the time interval from when a data frame is sent from the sender to when it is fully received by the receiver, reflecting the real-time performance of data transmission. It can be obtained by extracting the transmission time when the data frame enters the physical layer at the sender and the reception time when the data frame completes demodulation and verification at the receiver from the transmission performance mode data. The one-way transmission delay can be obtained based on the difference between the reception time and the transmission time. Since power line channels are subject to sudden interference, outliers can be eliminated using a sliding window statistical method. This involves continuously collecting the one-way delay of a preset number of data frames, removing outliers that exceed the preset range, and then calculating the average of the remaining one-way delays to obtain the transmission delay. Channel capacity refers to the maximum data rate that can theoretically achieve error-free transmission under given channel conditions, reflecting the channel's limit transmission capability. The actual bandwidth used by the channel can be obtained by determining the main frequency band width of the signal through spectrum analysis. Then, by converting the average signal-to-noise ratio in dB form into a linear ratio, the channel capacity can be calculated using the average signal-to-noise ratio and the actual bandwidth used by the channel.

[0099] This invention obtains the number of erroneous symbols received, the total number of transmitted symbols, the number of successfully transmitted bytes, and the instantaneous phase of the received signal per unit time using signal quality mode data. The number of erroneous symbols and the total number of transmitted symbols can accurately measure the real-time bit error rate (BER) of the channel. BER is a key indicator for judging signal quality. Real-time acquisition of BER helps to quickly identify fluctuations in communication quality, especially in power line communication, where the BER changes more frequently due to interference from power equipment and environmental noise. Dynamically measuring these data can reflect the channel state in real time, unlike static or periodic evaluation methods, allowing for more precise adjustment of modulation and coding strategies. Obtaining the number of successfully transmitted bytes effectively assesses transmission stability and efficiency, avoiding reliance solely on transmission... While the number of symbols is a single metric, the instantaneous phase of the received signal is fundamental for evaluating phase noise and phase jitter, especially in power line communication, where phase jitter significantly impacts signal quality. Compared to simple signal strength or bit error rate (BER), instantaneous phase provides a more in-depth analysis of the signal waveform, enabling better diagnosis of communication quality issues caused by phase changes. Real-time BER can be obtained based on the number of erroneous symbols and the total number of transmitted symbols. Compared to traditional static BER assessment methods, real-time BER calculation allows for immediate evaluation of signal quality during actual communication. When the signal environment changes (such as variations in power line noise or load fluctuations), real-time BER feedback can quickly reflect channel changes, providing a more sensitive adjustment basis and facilitating timely adjustments to transmission strategies. By monitoring the bit error rate in real time, this invention ensures flexible adjustment of adaptive modulation and coding techniques. Especially in complex power line communication environments, traditional techniques may fail to respond promptly to instantaneous changes in channel quality, leading to adjustment lag. This invention, through real-time data feedback, significantly improves adjustment accuracy and enhances communication quality. The instantaneous transmission rate is obtained by measuring the number of bytes successfully transmitted per unit time, and the transmission rate fluctuation value is obtained based on the instantaneous transmission rate and a preset nominal rate. Obtaining the instantaneous transmission rate is a crucial parameter for evaluating channel dynamic performance. Traditional methods often rely on preset transmission rates or average transmission rates, but these methods cannot reflect instantaneous changes in the actual environment. This invention calculates the instantaneous rate by monitoring the number of successfully transmitted bytes in real time, allowing for flexible adjustments. For fluctuations during transmission, especially in power line channels, changes in instantaneous data rate during interference often more accurately reflect communication quality, enabling the system to respond quickly based on the instantaneous rate, thereby improving overall transmission efficiency and communication quality. Data rate fluctuations in the channel are a crucial parameter for measuring signal stability, particularly in power line communication where transmission rates can fluctuate significantly due to noise, interference, and other factors. Traditional channel quality assessments often overlook this, potentially leading to a failure to take timely action when data rate fluctuations are large. This invention, by calculating transmission rate fluctuation values, quantifies the amplitude of rate fluctuations, providing a more accurate basis for communication quality assessment. Real-time monitoring and calculation of transmission rate fluctuations allows for more precise adjustments to modulation and coding.This method helps avoid communication stability issues caused by excessive rate fluctuations and improves robustness during communication. It obtains phase jitter amplitude by comparing the instantaneous phase with a preset ideal phase, and calculates a signal stability score by weighted summation based on the phase jitter amplitude, transmission rate fluctuation, and real-time bit error rate. Phase jitter is a significant factor affecting signal stability, especially in power line communication, where phase errors can lead to signal distortion or loss. By obtaining the difference between the instantaneous phase and the ideal phase and calculating the phase jitter amplitude, phase problems in the signal can be effectively captured, allowing for optimization and adjustment of the communication link. Compared to traditional evaluation methods based on signal strength or bit error rate, the calculation of phase jitter amplitude can more precisely identify minute changes in the signal, thus aiding in... By identifying potential phase interference problems in advance and then improving anti-interference capabilities through phase compensation adjustments, this comprehensive scoring method, which considers multiple factors such as phase jitter, rate fluctuation, and bit error rate, can more comprehensively assess signal stability. Compared to traditional single indicators (such as bit error rate or signal strength), this comprehensive scoring method can consider the influence of different aspects and provide more comprehensive and accurate evaluation results. Signal stability scoring can provide a more refined adjustment basis for adaptive modulation and coding techniques, especially in complex environments such as power line communication, where it can promptly reflect changes in multiple signal quality factors, thereby achieving more precise adjustments. Transmission performance mode data is used to obtain the actual bandwidth used by the channel, received signal power, noise power, and transmission time. Delay and throughput are measured, and the average signal-to-noise ratio (SNR) is obtained based on the ratio of received signal power to noise power. Traditional channel assessment often ignores the actual bandwidth and throughput variations of the channel, leading to inaccurate channel capacity assessments. By acquiring data such as actual bandwidth, received signal power, and noise power, a comprehensive understanding of the channel's operating status can be obtained, providing a foundation for accurate channel capacity and throughput assessment. Transmission delay is a common problem in power line communication, especially in long-distance or complex environments. By acquiring real-time transmission delay data, communication quality can be assessed more accurately, providing a basis for delay optimization. The signal-to-noise ratio (SNR) is a key indicator of channel quality, directly affecting the bit error rate and transmission stability. Compared to traditional assessment methods based on fixed signal strength, this method provides a more accurate assessment of channel capacity and throughput. The method of calculating the actual signal-to-noise ratio (SNR) can more accurately reflect the current signal quality, especially in power line environments with significant noise interference. It can provide real-time feedback for communication system optimization. Channel capacity is calculated using the average SNR and the actual bandwidth used. Transmission efficiency is obtained by weighted summation of channel capacity, transmission delay, and throughput. By comprehensively considering channel capacity, delay, and throughput, transmission efficiency can be accurately calculated. In power line communication, delay and throughput are often affected by noise and interference from power equipment; therefore, this weighted summation method can more comprehensively evaluate the true efficiency of communication, avoiding misjudgments caused by a single indicator. Fading depth, signal-to-interference ratio (SNR), and noise power spectral density are obtained through interference characteristic mode data.The anti-interference capability score is obtained based on fading depth, signal-to-interference ratio (SIR), and noise power spectral density. In power line communication, fading and interference are the main factors affecting signal quality. By accurately measuring interference characteristics, such as fading depth and SIR, the anti-interference capability of the communication system can be effectively evaluated. Compared with traditional methods, this more detailed interference analysis can better cope with the variable interference environment of power lines. By comprehensively analyzing fading depth, SIR, and noise power spectral density, the anti-interference capability of the communication system can be accurately assessed. Power line communication is often affected by multiple interference sources. The comprehensive scoring method can more accurately reflect the system's performance under different interference environments and provide an effective basis for system optimization.

[0100] In one embodiment, step S16, which involves obtaining the fading depth, signal-to-interference ratio (SIR), and noise power spectral density based on the interference characteristic mode data, and obtaining an anti-interference capability score based on the fading depth, SIR, and noise power spectral density, includes:

[0101] S161. Obtain the spectrum of the received signal based on the interference characteristic mode data, and obtain the pure noise band, useful signal band and interference signal band based on the spectrum;

[0102] S162. Extract a preset number of frequency points from the pure noise frequency band to obtain the first power spectral density, and calculate the noise power spectral density by summing multiple first power spectral densities.

[0103] S163. Integrate the second power spectral density over all frequency points within the useful signal frequency band to obtain the useful signal power;

[0104] S164. Integrate the third power spectral density of all frequency points within the interference signal frequency band to obtain the interference signal power, and obtain the signal-to-interference ratio based on the ratio of the useful signal power to the interference signal power.

[0105] S165. Extract the signal amplitude spectrum within the useful signal frequency band, and obtain the fading peak value and fading valley value based on the signal amplitude spectrum;

[0106] S166. Obtain the fading depth based on the difference between the fading peak value and the fading valley value, and calculate the anti-interference capability score by weighted summation based on the fading depth, signal-to-interference ratio and noise power spectral density.

[0107] As described in steps S161-S166 above, the fading peak and fading trough are the minimum and maximum attenuation points in the signal amplitude spectrum, respectively. Both the fading peak and trough are located within the useful signal frequency band, and the distance between them is not less than the minimum frequency resolution. The pure noise frequency band refers to a frequency band without useful signals or strong interference. The useful signal frequency band refers to the communication frequency band preset by the system. The interference signal frequency band is the concentrated interference frequency band other than the useful signal frequency band. This invention obtains the spectrum diagram of the received signal through interference characteristic mode data, and obtains the pure noise frequency band, useful signal frequency band, and interference signal frequency band based on the spectrum diagram. By analyzing the spectrum of the received signal, noise, useful signals, and interference in the signal can be effectively identified. This method, which targets interference signals, offers significant advantages over traditional methods relying solely on single signal strength or time-domain analysis. Spectrum analysis reveals the distribution and characteristics of signals at different frequencies, aiding in more accurate identification of interference and noise sources. The spectrum provides detailed frequency domain information, displaying signal energy distribution and interference patterns, facilitating subsequent identification and handling of interference sources. This leads to a better assessment of the channel conditions in power line broadband carrier communication. Compared to traditional time-domain analysis methods, this invention is more reliable in complex environments, enabling real-time monitoring of interference characteristics in power line channels. By clearly distinguishing between pure noise bands, useful signal bands, and interference signal bands through spectrum analysis, it helps to more accurately identify and classify signal characteristics within different frequency bands. This allows for targeted optimization of subsequent analyses. For example, by specifically analyzing the interference signal frequency band, specific interference suppression techniques can be employed to improve communication quality. Compared to existing technologies, this invention can more precisely pinpoint the different characteristics of the signal spectrum, avoiding the limitations of a general assessment of the entire channel and improving the accuracy of signal processing. By extracting a predetermined number of frequency points from the pure noise frequency band and calculating the first power spectral density based on the sum of multiple first power spectral densities, the noise power spectral density can be obtained. Extracting frequency points from the pure noise frequency band for power spectral density calculation allows for a more accurate assessment of noise power, resulting in more precise noise background information. This is crucial for accurately measuring the noise level of the channel and avoids the limitations of traditional techniques. This method addresses the problem of inaccurate noise estimation and effectively extracts stable reference data from noisy environments, providing a reliable basis for subsequent signal processing. By selecting an appropriate number of frequency points for extraction, noise power can be estimated more accurately, reducing errors that may be caused by a single frequency point. Summing the power spectral densities of multiple frequency points yields a more accurate noise power spectral density, avoiding noise estimation errors caused by local signal fluctuations. Compared to single-frequency point calculations in existing technologies, weighted summation of multiple frequency points reduces the volatility of estimated noise power, improving measurement stability and reliability. The useful signal power is obtained by integrating the second power spectral density of all frequency points within the useful signal band.By integrating the third power spectral density at all frequency points within the interference signal band, the interference signal power is obtained. By integrating the power spectral density at all frequency points within the useful signal band, the useful signal power can be calculated comprehensively and accurately. Compared to traditional methods, this invention avoids the possibility of ignoring certain important frequency points or bands, providing a more comprehensive and accurate signal power estimate. Through comprehensive integration analysis, it avoids the signal omission and incomplete evaluation problems that may occur in existing methods, improving the accuracy of signal quality assessment. Compared to single-band analysis, this comprehensive approach to considering signal power better reflects the true strength of the useful signal, enhancing signal reliability. By accurately integrating the interference band, the interference signal power can be quantified. The power of the interference signal helps identify its strength and impact on system performance, providing reliable data support for subsequent interference suppression or filtering techniques. This helps the system accurately assess and effectively suppress interference sources. Compared to traditional methods that may not comprehensively or accurately process interference signals, this invention can more meticulously evaluate interference power, providing a basis for optimizing the anti-interference capability of communication systems. The signal-to-interference ratio (SIR) is obtained based on the ratio of useful signal power to interference signal power. The SIR is a key parameter for evaluating communication quality. By accurately calculating the power ratio of the useful signal to the interference signal, the anti-interference performance of the communication system can be more realistically reflected. This addresses the potential inaccuracies or limitations in existing technologies regarding SIR calculation. Compared to methods addressing the nonlinear effects of interference signals, this approach offers a more stable and accurate assessment of interference, reducing the impact of environmental noise or other external factors on interference ratio measurements. It improves the system's sensitivity to interference and response speed. By extracting the signal amplitude spectrum within the useful signal frequency band and obtaining fading peaks and valleys based on this spectrum, the extraction of the signal amplitude spectrum provides a detailed description of signal attenuation at various frequency points, offering crucial spectral information, particularly in multipath propagation and fading scenarios. Compared to existing methods, directly extracting the amplitude spectrum and describing fading characteristics through peaks and valleys allows for a more precise assessment of signal quality, especially in accurately predicting signal fading in complex environments, thus effectively complementing existing technologies. This invention addresses the limitations of accurately predicting fading and provides a more refined signal quality assessment. It obtains the fading depth by measuring the difference between fading peaks and troughs, and calculates an anti-interference capability score by weighted summation of fading depth, signal-to-interference ratio (SIR), and noise power spectral density. Fading depth is a key indicator of the degree of signal quality degradation. Calculating the fading depth by the difference between peaks and troughs better reflects the attenuation effects on the signal during propagation. Compared to the simplified fading models used in existing technologies, this invention provides a more detailed analysis method, enabling accurate measurement of signal fading in more variable and complex environments. This effectively quantifies the multipath effects experienced by the signal during transmission, helping to assess the actual transmission quality of the channel.By comprehensively summing the weighted average of fading depth, signal-to-interference ratio (SIR), and noise power spectral density, the anti-interference capability of a communication system can be fully evaluated. Compared to traditional single-index evaluation, this comprehensive evaluation method provides a more accurate and comprehensive system performance assessment. It enables dynamic evaluation of the system's anti-interference capability under different environmental and interference conditions, thereby guiding the adaptive adjustment and optimization of the system. By integrating these parameters, this invention effectively overcomes the limitations of traditional methods that may rely too heavily on a single index, providing a more comprehensive anti-interference capability score and helping the system make more precise adjustments and optimizations.

[0108] In one embodiment, step S3, which involves obtaining the feedback correction factor based on the feedback information, includes:

[0109] S31. Based on the feedback information, obtain the data reception integrity, buffer queue length and multiple real-time received signal strengths, obtain the noise interference index, real-time data processing rate, rated processing rate, preset maximum allowable delay and average delay time of data packets in the queue of the downstream device, and obtain the data processing capability index based on the ratio of the real-time data processing rate and the rated processing rate.

[0110] S32. Obtain the buffer queue delay attenuation factor based on the preset maximum allowable delay and the average delay time of data packets in the queue, and obtain the buffer queue correction coefficient based on the product of the buffer queue delay attenuation factor, the data processing capability index and the buffer queue length.

[0111] S33. Obtain an average signal strength based on the multiple real-time received signal strengths, and obtain a signal fluctuation coefficient based on the average signal strength and the multiple real-time received signal strengths;

[0112] S34. Extract the maximum and minimum real-time received signal strengths from the plurality of real-time received signal strengths, and calculate the signal strength correction coefficient based on the maximum and minimum real-time received signal strengths, the signal fluctuation coefficient, and the noise interference index, wherein the calculation formula is:

[0113]

[0114] Where X(XZ) represents the signal strength correction coefficient, X(BD) represents the signal fluctuation coefficient, D(SX) represents the maximum real-time received signal strength, X(SX) represents the minimum real-time received signal strength, and Z(GR) represents the noise interference index.

[0115] S35. Obtain the data priority weight, retransmission count, and total transmission count based on the data reception integrity, and obtain the retransmission impact factor based on the retransmission count and total transmission count.

[0116] S36. Obtain the data reception correction coefficient based on the product of the retransmission impact factor, data priority weight, and data reception integrity, and calculate the feedback correction factor by weighted summation based on the data reception correction coefficient, signal strength correction coefficient, and buffer queue correction coefficient.

[0117] As described in steps S31-S36 above, in the calculation formula of the signal strength correction coefficient, the calculation parameters need to be normalized first to eliminate the difference in dimensions between different variables. The purpose is to ensure that all variables are on the same order of magnitude, so as to make the calculation more stable and effective. The core function of the buffer queue delay attenuation factor is to quantify the impact of the delay of data packets in the buffer queue on the buffer queue length correction coefficient. By introducing the delay factor, the weight of the buffer queue length in the feedback correction is dynamically adjusted. The receiving time of each data packet entering the buffer queue is marked by the timestamp of the downstream device, and the processing time of each data packet leaving the queue (being processed) is marked. The delay of a single data packet is calculated, and the average delay time of the data packets in the buffer queue can be obtained by calculating the average value through a sliding window. The weight value corresponding to different data priorities is also different. The higher the data priority, the greater the corresponding weight.

[0118] This invention addresses the issue of noise interference in downstream devices. It assesses the quality of power line communication channels by acquiring the noise interference index, real-time data processing rate, rated processing rate, preset maximum allowable delay, and average delay time of data packets in the queue. Noise interference is a key factor affecting the quality of power line communication channels, potentially originating from power equipment, environmental noise, or electromagnetic interference from other devices. By obtaining the noise interference index, the degree of channel interference can be effectively evaluated, providing a more accurate reflection of channel quality and facilitating the selection of appropriate communication modes. Unlike existing technologies that only consider signal strength, this invention introduces the noise interference index for more precise channel quality assessment, avoiding inaccurate judgments due to ignoring noise effects. It also optimizes modulation and coding strategies, directly improving data processing speed. The ratio of real-time data processing rate to rated processing rate, which affects the throughput and latency of a communication system, reflects the system's processing capacity. Compared to existing technologies that rely solely on channel assessment for adaptive adjustment, this invention incorporates the actual data processing rate, making channel selection more closely match the system's actual processing capacity. This effectively avoids network bottlenecks caused by insufficient processing capacity. The latency of the buffer queue affects the timely transmission of data packets. By obtaining the maximum allowable latency and the average latency of data packets in the queue, the congestion situation of the queue can be assessed. Furthermore, by calculating an attenuation factor, the queue latency can be dynamically adjusted to ensure timely transmission. Compared to traditional methods that rely solely on a fixed queue length, this invention introduces a dynamic latency attenuation factor for the queue. This invention avoids situations where the queue length is insufficient or excessive, optimizes queue management, reduces transmission latency, and obtains a data processing capacity index based on the ratio of real-time data processing rate to rated processing rate. It also obtains a buffer queue latency decay factor by preset maximum allowable latency and the average latency of data packets in the queue, and a buffer queue correction coefficient by multiplying the buffer queue latency decay factor, data processing capacity index, and buffer queue length. Queue management depends not only on queue length but also on multiple factors such as data processing capacity and latency decay factor. By combining these factors, the queue correction coefficient can be evaluated more comprehensively, ensuring that the system can dynamically adjust the queue management strategy according to network conditions. This invention achieves dynamic queue management. The comprehensive evaluation of the system's state enables it to adaptively adjust its queuing strategy under varying network loads and processing capabilities, rather than relying on static queue lengths. This significantly improves system stability and transmission efficiency. The system obtains the average signal strength by analyzing multiple real-time received signal strengths and then calculates the signal fluctuation coefficient based on this average and the multiple real-time received signal strengths. Received signal strength fluctuations are common, especially in power line communication where signal volatility is high. By calculating the average of multiple signal strengths and the fluctuation coefficient, the channel's signal quality can be assessed more accurately, avoiding the random errors of single signal measurements. Compared to traditional signal strength measurement methods, this invention, by introducing a signal fluctuation coefficient, can reflect the stability and quality of the signal in real time.To ensure that channel selection and adjustment can more accurately adapt to the actual communication environment and avoid misadjustment caused by signal fluctuations, this method extracts the maximum and minimum real-time received signal strength from multiple real-time received signal strengths. A signal strength correction coefficient is calculated based on these values, along with the signal fluctuation coefficient and noise interference index. By combining the difference between the maximum and minimum real-time received signal strengths, the signal fluctuation coefficient, and the noise interference index, the signal strength correction coefficient can compensate for the impact of signal strength fluctuations caused by changes in the external environment, providing more stable signal evaluation results. This avoids the limitation of a single signal strength indicator failing to accurately reflect the actual signal quality. By comprehensively considering signal fluctuations, maximum and minimum values, and noise effects, this invention optimizes signal quality estimation and provides more accurate signal assessment. It obtains data priority weights, retransmission counts, and total transmission counts through data reception integrity, and derives a retransmission impact factor based on the retransmission count and total transmission count. Data reliability is directly related to the number of transmissions, and the number of retransmissions affects the bandwidth and latency of the entire system. By calculating the retransmission impact factor, the impact of retransmissions on system performance can be assessed, and adjustments can be made to optimize transmission efficiency. Unlike existing technologies that only assess network conditions through signal quality, this invention comprehensively considers data priority and retransmission counts, enabling more accurate prediction of the actual data transmission effect, thereby improving the overall stability and efficiency of the system. The data reception correction coefficient is obtained by multiplying the retransmission impact factor, data priority weight, and data reception integrity. Data reception integrity directly affects system performance. By combining multiple factors such as retransmission impact factor, data priority, and reception integrity, the reception strategy can be dynamically adjusted to optimize the data reception process and ensure timely transmission of high-priority data. Compared to simple data transmission quality monitoring, this approach comprehensively considers factors such as data priority, retransmission, and reception integrity, improving data transmission reliability and priority control. It avoids low-priority data excessively affecting the transmission of high-priority data. The feedback correction factor is obtained by weighted summation of the data reception correction coefficient, signal strength correction coefficient, and buffer queue correction coefficient. The final feedback correction factor is then... By comprehensively evaluating the overall system status through a weighted summation of various correction coefficients, this comprehensive index accurately reflects the operating status of the entire communication system in a real-world environment. Based on this feedback, channel selection and modulation strategies are adjusted. Unlike existing technologies that use a single index to adjust the system, the weighted summation method comprehensively considers multiple influencing factors, further improving the accuracy and dynamic adaptability of the adjustment strategy. This invention, by introducing multiple real-time data points and multi-level correction coefficients, makes channel selection and switching in power line communication more intelligent and precise. Compared with existing technologies, by comprehensively evaluating multiple factors such as noise interference, signal strength fluctuations, processing capabilities, and latency, this invention can more accurately reflect channel quality.Improving the adjustment effect of adaptive modulation and coding techniques enhances the stability and efficiency of power line broadband communication.

[0119] In one embodiment, step S4, which involves obtaining the corresponding total demand matching degree based on the upstream communication demand parameters of the upstream device, the downstream communication demand parameters of the downstream device, and each candidate communication channel, includes:

[0120] S41. Obtain the upstream communication requirement parameters of the upstream device and the downstream communication requirement parameters of the downstream device respectively, and obtain the latency tolerance, allowable packet loss rate and throughput requirement based on the upstream communication requirement parameters.

[0121] S42. Obtain the receiving capability threshold, error correction capability, and synchronization accuracy requirements based on the downstream communication requirement parameters.

[0122] S43. Obtain the actual channel delay, actual packet loss rate, channel bandwidth, and channel stability coefficient for each candidate communication channel;

[0123] S44. Calculate the real-time matching degree based on the aforementioned delay tolerance, receiving capability threshold, and actual channel delay, wherein the calculation formula is: Where S(PD) represents the real-time matching degree, X(SY) represents the actual channel delay, S(RD) represents the delay tolerance, and J(NY) represents the receiving capability threshold.

[0124] S45. Calculate the reliability matching degree based on the allowable packet loss rate, error correction capability, and actual packet loss rate of the channel, wherein the calculation formula is: Where K(PD) represents the reliability matching degree, X(SD) represents the actual packet loss rate of the channel, Y(DB) represents the allowable packet loss rate, and J(CN) represents the error correction capability;

[0125] S46. Calculate the throughput matching degree based on the throughput requirement, synchronization accuracy requirement, channel bandwidth, and channel stability coefficient, wherein the calculation formula is: Where T(PD) represents throughput matching degree, X(DK) represents channel bandwidth, T(TX) represents throughput requirement, T(JX) represents synchronization accuracy requirement, and X(WD) represents channel stability coefficient;

[0126] S47. Calculate the total demand matching degree by weighted summation based on the throughput matching degree, reliability matching degree, and real-time matching degree.

[0127] As described in steps S41-S47 above, in the calculation formulas for real-time matching degree, reliability matching degree, and throughput matching degree, it is necessary to first normalize the corresponding calculation parameters to eliminate the dimensional differences between different variables. The purpose is to ensure that all variables are on the same order of magnitude, thereby making the calculation more stable and effective. This invention obtains latency tolerance, allowable packet loss rate, and throughput requirements through upstream communication demand parameters. The acquisition of upstream communication requirements, especially latency tolerance, allowable packet loss rate, and throughput requirements, is of great significance for power line broadband carrier communication. Latency tolerance ensures the system's adaptability to data transmission delays, especially in complex power line communication environments where latency may be affected by physical delays between devices. The latency fluctuates due to changes in distance and power system variations. By quantifying latency tolerance, communication interruptions or quality degradation caused by excessive latency can be effectively avoided. Allowable packet loss rate takes into account uncertainties and packet loss in the network environment. Especially in power line communication, packet loss is unavoidable due to environmental noise and the influence of power equipment. Therefore, specifying packet loss rate limits can optimize data transmission stability. Throughput requirements reflect the data transmission rate requirements, ensuring that the communication system can adjust bandwidth according to actual needs, thereby avoiding data congestion and latency caused by insufficient bandwidth. Existing technologies mostly rely on fixed channel evaluation mechanisms, neglecting detailed considerations of different needs during communication. Introducing detailed parameters of upstream communication needs addresses this issue. This allows for more precise channel selection and adjustment based on actual needs, enabling the system to flexibly respond to different network conditions and service quality requirements. Compared to adaptive modulation and coding techniques, this invention, by comprehensively considering multiple upstream requirements, can provide more personalized services in dynamic environments, optimizing overall communication performance. It obtains receiver capability thresholds, error correction capabilities, and synchronization accuracy requirements through downstream communication requirement parameters. The acquisition of downstream communication requirements, especially receiver capability thresholds, error correction capabilities, and synchronization accuracy requirements, further ensures the reliability and stability of the communication system. The receiver capability threshold indicates the minimum signal strength or quality that the receiver can receive, ensuring effective operation even under weak signal conditions. Error correction capability, on the other hand, is related to the number of parameters... The ability to recover from errors during transmission is closely related to improving communication reliability in noisy and unstable power line environments. Synchronization accuracy requirements ensure the precision of clock synchronization, especially under conditions of significant latency or noise interference, ensuring the correct order and accurate reception of data packets. Traditional power line communication systems often neglect the specific needs of the receiver, relying primarily on a single assessment of channel quality while ignoring the individual differences in various communication requirements. This invention, through a detailed evaluation of receiver capability thresholds, error correction capabilities, and synchronization accuracy, can accurately select the appropriate communication channel based on downstream needs, avoiding reception problems or data errors caused by channel quality mismatch, thereby improving the overall system robustness and stability.Obtaining the actual channel delay, actual packet loss rate, channel bandwidth, and channel stability coefficient for each candidate communication channel is a crucial step in ensuring accurate communication selection and optimizing performance. Actual channel delay is a core parameter affecting the real-time performance of data transmission, providing precise delay information to help the system select a suitable channel for real-time transmission. The channel packet loss rate is closely related to the stability of data transmission, effectively assessing channel reliability and preventing data loss and quality degradation due to excessively high packet loss rates. Channel bandwidth directly impacts throughput requirements; insufficient bandwidth leads to data congestion and reduces overall system throughput, while excessive bandwidth may result in resource waste. Channel stability coefficients measure the long-term stability of channel quality, helping the system maintain communication stability and continuity in changing power line environments. Existing technologies often employ static channel quality assessments, neglecting the impact of dynamic environments on channel quality. This invention, however, dynamically acquires real-time quality parameters from multiple channels, more accurately reflecting the actual channel conditions under the current environment. This avoids performance degradation caused by inaccurate channel assessments. The comprehensive assessment method of this invention enables multi-dimensional and multi-level channel selection, significantly improving the system's adaptability and optimization capabilities in complex environments. Real-time matching degree is calculated using delay tolerance, receiver capability threshold, and actual channel delay. The comprehensive calculation can quantify the degree of matching between the channel and real-time requirements. The calculation of the real-time matching degree helps the system determine whether the current channel can meet the real-time requirements. Especially in power line communication, where channel delay and fluctuation are large, comparing the delay tolerance and the actual channel delay can effectively screen out the optimal channel that meets the real-time requirements. This avoids data delays or interruptions caused by excessive delay during real-time data transmission, ensuring timely information transmission. Existing technologies typically rely solely on channel delay and quality to select channels, neglecting upstream delay tolerance and downstream reception requirements. This invention, by comprehensively considering these factors, improves the accuracy of channel selection, enabling the system to flexibly adjust according to actual needs, avoiding the problems encountered in traditional methods. The limitations of traditional methods, such as the inability to automatically adjust according to actual needs, are addressed by calculating the reliability matching degree using the allowable packet loss rate, error correction capability, and actual channel packet loss rate. This calculation helps the system assess the reliability the channel can guarantee during data transmission. Especially in power line communication, packet loss is common due to noise and environmental factors. By comparing the allowable packet loss rate with the actual channel packet loss rate, and combining this with error correction capability, channel selection can be effectively optimized, ensuring high reliability of data transmission under different packet loss conditions. This invention plays a crucial role in improving the system's error recovery capability, especially in power line communication environments where error correction capability is paramount. Currently, most systems rely solely on the channel packet loss rate for selection.While traditional methods often neglect the combined impact of packet loss rate and error correction capability, this invention introduces error correction capability, enabling it to maintain high data transmission reliability even with high packet loss rates. This overcomes the over-reliance on packet loss rate in traditional methods and provides a more robust solution. Throughput matching is calculated using parameters such as throughput requirement, synchronization accuracy requirement, channel bandwidth, and channel stability coefficient. This calculation accurately assesses whether the channel can provide the required throughput, especially crucial in power line communication where channel bandwidth and stability directly impact system throughput. This matching calculation avoids insufficient throughput due to insufficient bandwidth or channel instability, thus optimizing data transmission efficiency and improving overall system performance. Existing technologies often ignore the impact of channel bandwidth and stability on throughput, relying solely on simple bandwidth evaluation. This invention, by comprehensively considering multiple factors, more accurately assesses channel throughput, avoiding the over-reliance on packet loss rate in traditional methods. To address the issue of wasted or insufficient throughput in traditional methods, this invention calculates the total demand matching degree by weighted summation of throughput matching degree, reliability matching degree, and real-time matching degree. This weighted summation method comprehensively evaluates multiple dimensions of demand, including real-time performance, reliability, and throughput, resulting in an overall matching degree. This weighted synthesis method comprehensively reflects the overall system performance, ensuring coordination and balance among different parameters, and improving the accuracy and reliability of channel selection. Existing technologies often employ single-dimensional evaluation, while this invention, through weighted synthesis, balances different communication demands, avoiding the shortcomings of traditional methods that sacrifice other aspects for one-sided optimization of a single performance characteristic. This enhances the system's adaptability and optimization capabilities under multiple demands. By comprehensively evaluating upstream demand, downstream demand, and channel quality, and employing multi-dimensional parameter calculation and weighted summation, this invention significantly improves the accuracy of channel selection and communication quality. Especially in complex power line communication environments, it overcomes the limitations of traditional methods, providing more stable and reliable communication services.

[0128] In one embodiment, step S6, which switches a candidate communication channel that meets preset conditions to the current optimal communication channel, includes:

[0129] S61. Sort all remaining candidate communication channels according to the size of the comprehensive evaluation index to obtain the candidate channel ranking table.

[0130] S62. Obtain the key parameters of the first candidate communication channel in the candidate channel sorting table, and determine whether the key parameters meet the preset requirements.

[0131] If the key parameters do not meet the preset requirements, then the candidate communication channel ranked second in the candidate channel sorting table is obtained until the key parameters of the selected candidate communication channel meet the preset requirements.

[0132] If the key parameters meet the preset requirements, the target channel identifier of the candidate communication channel is obtained, and the target channel identifier is sent to the upstream device to generate a switching instruction, wherein the switching instruction includes a termination instruction, a start instruction, and a switching time;

[0133] S63. The upstream device sends a termination command and a switching time to the current optimal communication channel so that the current optimal communication channel stops transmitting.

[0134] S64. The upstream device sends the start command and switching time to a candidate communication channel whose key parameters meet the preset requirements, switches the current optimal communication channel to the candidate communication channel and starts transmission.

[0135] As described in steps S61-S64 above, this invention obtains a candidate channel ranking table by sorting all remaining candidate communication channels according to the magnitude of the comprehensive evaluation index. Ranking the candidate communication channels using the comprehensive evaluation index ensures that channel selection does not rely solely on a single channel quality parameter, but rather comprehensively evaluates the effects of multiple factors to achieve a holistic assessment of communication channel quality. Compared to single quality evaluation indicators in existing technologies, the comprehensive evaluation index can more comprehensively and accurately reflect the overall quality of power line communication channels, reducing the risk of misleading selection due to a single factor. Existing technologies often rely on adaptive modulation and coding techniques, but adaptive techniques are significantly affected by channel quality fluctuations, leading to inaccurate evaluation results. Indeed, this invention weighs multiple factors through a comprehensive evaluation index, making the channel selection process more robust and avoiding over-reliance on individual factors, thus preventing inaccurate quality assessments. It obtains the key parameters of the first-ranked candidate communication channel in the candidate channel ranking list and determines whether these parameters meet preset requirements. If the key parameters do not meet the preset requirements, it obtains the second-ranked candidate communication channel in the ranking list, continuing until the key parameters of the selected candidate communication channel meet the preset requirements. By prioritizing the key parameters of the first-ranked candidate communication channel in the ranking list, it ensures that optimal selection begins. This strategy effectively reduces the computational and time overhead required in the selection process, because if the first-ranked channel meets the requirements, there is no need to... Further evaluation of other channels improves the efficiency of the entire handover process. Traditional technologies may randomly select or evaluate all channels out of order, potentially leading to resource waste or delays. This invention prioritizes the optimal selection through a sorting mechanism, ensuring that the most suitable channel is chosen first, thereby improving communication efficiency and response speed. By judging whether the key parameters of candidate channels meet preset requirements, it ensures that the selected communication channel not only meets the most basic quality requirements but also adapts to specific communication needs. These preset requirements can be flexibly adjusted according to the actual application environment, such as the operating status of power equipment and environmental noise, allowing for more precise selection of suitable channels and thus improving communication quality. Existing technologies typically rely only on simplified channel quality assessments, failing to... Considering the diverse needs of real-world applications, this invention determines channel suitability based on specific preset requirements, thus avoiding the selection of channels that do not meet actual needs. This improves the targeting and accuracy of channel selection. By sequentially selecting candidate communication channels from a sorting table one by one until a suitable channel is found, it ensures that the optimal solution is found during channel switching. If the first channel is unsuitable, the second and third channels are automatically selected, avoiding communication interruptions or quality degradation caused by incorrect selection. Traditional methods may rely on only one selection, and improper selection often leads to performance degradation. This invention, through a sorting and multi-round selection mechanism, adds redundancy guarantees, ensuring that the final selected channel is optimal under comprehensive evaluation.This invention significantly reduces quality fluctuations caused by improper channel selection. If key parameters meet preset requirements, the target channel identifier of the candidate communication channel is obtained and sent to the upstream device to generate a switching command. The switching command includes a termination command, a start command, and a switching time. By obtaining the target channel identifier, the switching target is determined, further ensuring the controllability and accuracy of the switching process. Clearly defining the identifier reduces signal interference or selection errors caused by unclear channel identifiers, ensuring a final switch to a suitable target channel. Many existing technologies have vague or unsystematic channel identifier management, potentially leading to identifier conflicts or unclear selection. This invention clearly defines the target channel identifier, ensuring accurate target channel positioning during channel switching, thereby improving the stability and reliability of the switching. By transmitting the target channel identifier to the upstream device to generate the switching command, automated and remote control of channel switching can be achieved, greatly improving the system's intelligence. This technology improves the efficiency and automation of communication channels, enabling rapid switching and scheduling, reducing manual intervention and reaction time, and enhancing the adaptability and emergency response capabilities of communication systems. Traditional channel switching often requires extensive manual intervention or localized control. However, this invention achieves a more efficient and automated operation by automatically generating switching commands from upstream devices, thereby reducing operational complexity and the risk of human error. The upstream device sends a termination command and switching time to the current optimal communication channel to stop transmission. The upstream device also sends a start command and switching time to a candidate communication channel whose key parameters meet preset requirements, switching the current optimal communication channel to the candidate channel and initiating transmission. This ensures that the current optimal communication channel can orderly stop transmission before switching, avoiding signal conflicts and interference. Precise time control ensures a smooth transition during channel switching, reducing the risk of signal loss or communication interruption. This method effectively ensures the continuity and stability of communication during handover. Existing technologies may experience signal interruptions or disordered handovers during the transition period. This invention, through explicit termination commands and handover times, ensures a smooth handover process, avoiding signal loss or interruption and improving user experience. By sending start commands and handover times from upstream devices, the timing of channel handover can be precisely controlled, ensuring the target communication channel begins transmission at the optimal time. Precise control of the handover time avoids signal instability or quality degradation due to untimely handover, ensuring high efficiency and stability of communication. Existing technologies often suffer from inaccurate timing or abrupt handovers, potentially leading to poor user experience or system performance degradation. This invention, through refined handover control, ensures optimal timing and method of signal handover, thereby minimizing the impact of handover on communication quality and enhancing system intelligence and flexibility.

[0136] like Figure 2As shown, this application also provides a power line broadband carrier communication channel intelligent selection and switching system, including:

[0137] The first acquisition module is used to acquire multimodal channel quality basic data of upstream devices, downstream devices and multiple candidate communication channels in the power line broadband carrier communication network, and to acquire the channel quality score of the corresponding candidate communication channel based on each of the multimodal channel quality basic data.

[0138] The feedback module is used to establish a corresponding feedback link with each candidate communication channel based on the upstream device, the downstream device, and the upstream device. The upstream device sends a feedback request to the downstream device according to each feedback link, and the downstream device responds to the feedback request and returns the corresponding feedback information.

[0139] The correction module is used to obtain feedback correction factors based on the feedback information, and to optimize and correct the channel quality score of the corresponding candidate communication channel based on each feedback correction factor to obtain the corresponding corrected channel quality score.

[0140] The second acquisition module is used to obtain the corresponding total demand matching degree based on the upstream communication demand parameters of the upstream device, the downstream communication demand parameters of the downstream device and each candidate communication channel, and to obtain the comprehensive evaluation index of the corresponding candidate communication channel based on each total demand matching degree and the corresponding corrected channel quality score.

[0141] The selection module is used to select the candidate communication channel corresponding to the largest comprehensive evaluation index as the current optimal communication channel, and to monitor the real-time comprehensive evaluation index of the current optimal communication channel in real time.

[0142] The switching module is used to determine whether the real-time comprehensive evaluation index is less than the preset evaluation index;

[0143] If the real-time comprehensive evaluation index is less than the preset evaluation index, then the candidate communication channel that meets the preset conditions will be switched to the current optimal communication channel.

[0144] If the real-time comprehensive evaluation index is not less than the preset evaluation index, the current optimal communication channel will not be switched.

[0145] In one embodiment, the second acquisition module includes:

[0146] The first acquisition unit is used to acquire the latency tolerance, allowable packet loss rate and throughput requirement based on the upstream communication requirement parameters.

[0147] The second acquisition unit is used to acquire the receiving capability threshold, error correction capability and synchronization accuracy requirements based on the downstream communication requirement parameters.

[0148] The third acquisition unit is used to acquire the actual channel delay, actual packet loss rate, channel bandwidth and channel stability coefficient of each candidate communication channel;

[0149] The fourth acquisition unit is used to acquire the real-time matching degree based on the delay tolerance, the receiving capability threshold and the actual channel delay;

[0150] The fifth acquisition unit is used to acquire the reliability matching degree based on the allowable packet loss rate, error correction capability and actual packet loss rate of the channel;

[0151] The sixth acquisition unit is used to acquire the throughput matching degree based on the throughput requirement, synchronization accuracy requirement, channel bandwidth and channel stability coefficient;

[0152] The seventh acquisition unit is used to acquire the total demand matching degree based on the throughput matching degree, reliability matching degree, and real-time matching degree.

[0153] It should be noted that each module and unit in the intelligent selection and switching system for power line broadband carrier communication channels corresponds one-to-one with the steps in the intelligent selection and switching method for power line broadband carrier communication channels.

[0154] like Figure 3 As shown, this application also provides a computer device, which can be a server, and its internal structure can be as follows: Figure 3 As shown, the computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores all data required for the intelligent selection and switching method of power line broadband carrier communication channels. The network interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements the intelligent selection and switching method of power line broadband carrier communication channels.

[0155] Those skilled in the art will understand that Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer equipment on which the present application is applied.

[0156] An embodiment of this application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements any of the above-described intelligent selection and switching methods for power line broadband carrier communication channels.

[0157] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media provided in this application and in the embodiments may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual-speed SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0158] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, apparatus, article, or method. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, apparatus, article, or method that includes that element.

[0159] The above description is merely a preferred embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A method for intelligent selection and switching of power line broadband carrier communication channels, characterized by, The method comprises the following steps: acquiring multi-modal channel quality basic data of an upstream device, a downstream device and a plurality of candidate communication channels in a power line broadband carrier communication network, and acquiring signal quality modal data, transmission performance modal data and interference feature modal data according to the multi-modal channel quality basic data, acquiring the number of error symbols received in a unit time, the total number of transmission symbols, the number of successfully transmitted bytes and the instantaneous phase of the received signal according to the signal quality modal data, and acquiring the real-time bit error rate according to the number of error symbols and the total number of transmission symbols; acquiring the instantaneous transmission rate according to the number of successfully transmitted bytes in a unit time, and acquiring the transmission rate fluctuation value according to the instantaneous transmission rate and a preset nominal rate; acquiring the phase jitter amplitude according to the instantaneous phase and a preset ideal phase, and acquiring the signal stability score according to the phase jitter amplitude, the transmission rate fluctuation value and the real-time bit error rate; acquiring the actual channel bandwidth, the received signal power, the noise power, the transmission delay and the throughput according to the transmission performance modal data, and acquiring the average signal-to-noise ratio according to the received signal power and the noise power; acquiring the channel capacity according to the average signal-to-noise ratio and the actual channel bandwidth, and acquiring the transmission efficiency score according to the channel capacity, the transmission delay and the throughput; acquiring the frequency spectrum of the received signal according to the interference feature modal data, and acquiring the pure noise frequency band, the useful signal frequency band and the interference signal frequency band according to the frequency spectrum; extracting the first power spectral density of a preset number of frequency points from the pure noise frequency band, and acquiring the noise power spectral density according to a plurality of the first power spectral densities; integrating the second power spectral density of all frequency points in the useful signal frequency band to obtain the useful signal power; integrating the third power spectral density of all frequency points in the interference signal frequency band to obtain the interference signal power, and acquiring the signal-to-interference ratio according to the useful signal power and the interference signal power; extracting the signal amplitude spectrum in the useful signal frequency band, and acquiring the fading peak value and the fading valley value according to the signal amplitude spectrum; acquiring the fading depth according to the fading peak value and the fading valley value, and acquiring the anti-interference ability score according to the fading depth, the signal-to-interference ratio and the noise power spectral density; establishing a corresponding feedback link between the upstream device, the downstream device and each candidate communication channel, the upstream device sending a feedback request to the downstream device according to each feedback link, and the downstream device responding to the feedback request and returning corresponding feedback information; acquiring the feedback correction factor according to the feedback information, and optimizing and correcting the channel quality score of the corresponding candidate communication channel according to each feedback correction factor to obtain the corresponding corrected channel quality score; acquiring the corresponding total demand matching degree according to the upstream communication demand parameter of the upstream device, the downstream communication demand parameter of the downstream device and each candidate communication channel, and acquiring the comprehensive evaluation index of the corresponding candidate communication channel according to each total demand matching degree and the corresponding corrected channel quality score; selecting the candidate communication channel corresponding to the maximum comprehensive evaluation index as the current optimal communication channel, and monitoring the real-time comprehensive evaluation index of the current optimal communication channel in real time; determining whether the real-time comprehensive evaluation index is less than a preset evaluation index; if the real-time comprehensive evaluation index is less than the preset evaluation index, switching the candidate communication channel meeting the preset condition to the current optimal communication channel; if the real-time comprehensive evaluation index is not less than the preset evaluation index, not switching the current optimal communication channel.

2. The method of claim 1, wherein, The step of obtaining the feedback correction factor according to the feedback information comprises: obtaining data reception integrity, buffer queue length and multiple real-time received signal strengths according to the feedback information, obtaining noise interference index, real-time data processing rate, rated processing rate, preset maximum allowed delay and average delay time of data packets in the queue of the downstream device, and obtaining data processing capacity index according to the real-time data processing rate and the rated processing rate; obtaining buffer queue delay attenuation factor according to the preset maximum allowed delay and the average delay time of data packets in the queue, and obtaining buffer queue correction coefficient according to the buffer queue delay attenuation factor, the data processing capacity index and the buffer queue length; obtaining average signal strength according to multiple real-time received signal strengths, and obtaining signal fluctuation coefficient according to the average signal strength and multiple real-time received signal strengths; extracting maximum real-time received signal strength and minimum real-time received signal strength from multiple real-time received signal strengths, and calculating signal strength correction coefficient according to the maximum real-time received signal strength, the minimum real-time received signal strength, the signal fluctuation coefficient and the noise interference index, wherein the calculation formula is: ； wherein X(XZ) represents the signal strength correction coefficient, X(BD) represents the signal fluctuation coefficient, D(SX) represents the maximum real-time received signal strength, X(SX) represents the minimum real-time received signal strength, and Z(GR) represents the noise interference index; obtaining data priority weight, retransmission number and total transmission number according to the data reception integrity, and obtaining retransmission influence factor according to the retransmission number and the total transmission number; obtaining data reception correction coefficient according to the retransmission influence factor, the data priority weight and the data reception integrity, and obtaining the feedback correction factor according to the data reception correction coefficient, the signal strength correction coefficient and the buffer queue correction coefficient.

3. The method of claim 1, wherein, The step of obtaining the corresponding total demand matching degree according to the upstream communication demand parameter of the upstream device, the downstream communication demand parameter of the downstream device and each candidate communication channel comprises: obtaining delay tolerance, allowable packet loss rate and throughput demand according to the upstream communication demand parameter; obtaining receiving capacity threshold, error correction capability and synchronization accuracy demand according to the downstream communication demand parameter; obtaining channel actual delay, channel actual packet loss rate, channel bandwidth and channel stability coefficient of each candidate communication channel; obtaining real-time matching degree according to the delay tolerance, the receiving capacity threshold and the channel actual delay; obtaining reliability matching degree according to the allowable packet loss rate, the error correction capability and the channel actual packet loss rate; obtaining throughput matching degree according to the throughput demand, the synchronization accuracy demand, the channel bandwidth and the channel stability coefficient; obtaining total demand matching degree according to the throughput matching degree, the reliability matching degree and the real-time matching degree.

4. The method of claim 1, wherein, The step of switching the candidate communication channel satisfying the preset condition to the current optimal communication channel comprises: sorting all the remaining candidate communication channels according to the size of the comprehensive evaluation index to obtain a candidate channel sorting table; obtaining a key parameter of the candidate communication channel at the first position in the candidate channel sorting table, and judging whether the key parameter satisfies a preset requirement; if the key parameter does not satisfy the preset requirement, obtaining a candidate communication channel at the second position in the candidate channel sorting table until the key parameter of the selected candidate communication channel satisfies the preset requirement; if the key parameter satisfies the preset requirement, obtaining a target channel identifier of the candidate communication channel, and sending the target channel identifier to an upstream device to generate a switching instruction, wherein the switching instruction comprises a termination instruction, a start instruction and a switching time; the upstream device sends the termination instruction and the switching time to the current optimal communication channel to stop transmission of the current optimal communication channel; the upstream device sends the start instruction and the switching time to the candidate communication channel whose key parameter satisfies the preset requirement, switches the current optimal communication channel to the candidate communication channel and starts transmission.

5. A power line broadband carrier communication channel intelligent selection and switching system, characterized by, comprises: The first acquisition module is used for acquiring the multi-modal channel quality basic data of the upstream device, the downstream device and the plurality of candidate communication channels in the power line broadband carrier communication network, and acquiring the signal quality modal data, the transmission performance modal data and the interference characteristic modal data according to the multi-modal channel quality basic data, acquiring the number of error symbols received in a unit time, the total number of transmission symbols, the number of successfully transmitted bytes and the instantaneous phase of the received signal according to the signal quality modal data, and acquiring the real-time bit error rate according to the number of error symbols and the total number of transmission symbols; the instantaneous transmission rate is acquired according to the number of successfully transmitted bytes in a unit time, and the transmission rate fluctuation value is acquired according to the instantaneous transmission rate and a preset nominal rate; the phase jitter amplitude is acquired according to the instantaneous phase and a preset ideal phase, and the signal stability score is acquired according to the phase jitter amplitude, the transmission rate fluctuation value and the real-time bit error rate; the channel actual use bandwidth, the received signal power, the noise power, the transmission delay and the throughput are acquired according to the transmission performance modal data, and the average signal-to-noise ratio is acquired according to the received signal power and the noise power; the channel capacity is acquired according to the average signal-to-noise ratio and the channel actual use bandwidth, and the transmission efficiency score is acquired according to the channel capacity, the transmission delay and the throughput; the frequency spectrum diagram of the received signal is acquired according to the interference characteristic modal data, and the pure noise frequency band, the useful signal frequency band and the interference signal frequency band are acquired according to the frequency spectrum diagram; the first power spectral density of a preset number of frequency points in the pure noise frequency band is extracted, and the noise power spectral density is acquired according to a plurality of the first power spectral densities; the second power spectral density of all frequency points in the useful signal frequency band is integrated to obtain the useful signal power; the third power spectral density of all frequency points in the interference signal frequency band is integrated to obtain the interference signal power, and the signal-to-interference ratio is acquired according to the useful signal power and the interference signal power; extracting a signal amplitude spectrum in the useful signal frequency band, and obtaining a fading peak value and a fading valley value according to the signal amplitude spectrum; obtaining a fading depth according to the fading peak value and the fading valley value, and obtaining an anti-interference capability score according to the fading depth, a signal-to-interference ratio and a noise power spectrum density; a feedback module configured to establish a corresponding feedback link between the upstream device, the downstream device and each candidate communication channel, and configured to send a feedback request from the upstream device to the downstream device according to each feedback link, and configured to respond to the feedback request and return corresponding feedback information from the downstream device; a correction module configured to obtain a feedback correction factor according to the feedback information, and configured to optimize and correct the channel quality score of the corresponding candidate communication channel according to each feedback correction factor to obtain a corresponding corrected channel quality score; a second obtaining module configured to obtain a corresponding total demand matching degree according to the upstream communication demand parameter of the upstream device, the downstream communication demand parameter of the downstream device and each candidate communication channel, and configured to obtain a comprehensive evaluation index of the corresponding candidate communication channel according to each total demand matching degree and the corresponding corrected channel quality score; a selection module configured to select the candidate communication channel corresponding to the maximum comprehensive evaluation index as the current optimal communication channel, and configured to monitor the real-time comprehensive evaluation index of the current optimal communication channel in real time; a judgment switching module configured to judge whether the real-time comprehensive evaluation index is less than a preset evaluation index; if the real-time comprehensive evaluation index is less than the preset evaluation index, switching the candidate communication channel satisfying the preset condition as the current optimal communication channel; if the real-time comprehensive evaluation index is not less than the preset evaluation index, not switching the current optimal communication channel.

6. The power line broadband carrier communication channel intelligent selection and switching system of claim 5, wherein, The second obtaining module comprises: a first obtaining unit configured to obtain a time delay tolerance, an allowable packet loss rate and a throughput demand according to the upstream communication demand parameter; a second obtaining unit configured to obtain a receiving capability threshold, an error correction capability and a synchronization accuracy demand according to the downstream communication demand parameter; a third obtaining unit configured to obtain a channel actual time delay, a channel actual packet loss rate, a channel bandwidth and a channel stability coefficient of each candidate communication channel; a fourth obtaining unit configured to obtain a real-time matching degree according to the time delay tolerance, the receiving capability threshold and the channel actual time delay; a fifth obtaining unit configured to obtain a reliability matching degree according to the allowable packet loss rate, the error correction capability and the channel actual packet loss rate; a sixth obtaining unit configured to obtain a throughput matching degree according to the throughput demand, the synchronization accuracy demand, the channel bandwidth and the channel stability coefficient; a seventh obtaining unit configured to obtain a total demand matching degree according to the throughput matching degree, the reliability matching degree and the real-time matching degree. 7.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is configured to perform the method according to any one of claims 1-6 when the computer program is executed by the processor. The processor executes the computer program to realize the steps of the method in any one of claims 1 to 4.

8. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to realize the steps of the method in any one of claims 1 to 4.

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