Interconnection communication method and device based on power terminal cross-operating system

Abstract

The embodiment of the invention discloses an interconnection communication method and device based on a power terminal cross-operating system. The method comprises the following steps: acquiring an original data set of a cross-operating system channel of the power terminal in each modulation mode; training a preset quantitative relation model based on the original data set and a support vector machine regression algorithm, and determining a to-be-selected quantitative relation model; performing performance evaluation on the to-be-selected quantitative relation model based on the original data set, and determining a target quantitative relation model; determining the current crosstalk intensity corresponding to the current channel interval parameter based on the current channel interval parameter in the current communication environment and the target quantitative relation model in the cross-operating system interconnection communication process of the power terminal; according to the method, the current channel interval parameter is dynamically adjusted based on the current crosstalk intensity and the preset crosstalk intensity threshold value, so that the dynamic adjustment of the channel interval parameter is accurately and conveniently realized, the crosstalk between channels is avoided, and the communication quality of cross-operating system interconnection communication of the power terminal is improved.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of computer technology, and in particular to a method and device for interconnected communication based on cross-operating systems of power terminals. Background Art

[0002] With the development of information technology, power terminals can achieve interconnected communication across operating systems.

[0003] At present, in the interconnection and communication of power terminals across operating systems, power line carrier communication faces the problem of repeated message reception caused by adjacent channel crosstalk. Due to the complex and changeable power line channel environment, the frequency spacing and isolation between adjacent channels are insufficient, resulting in the leakage of signal energy from one channel to the adjacent channel, causing crosstalk. When the crosstalk intensity exceeds a certain threshold, the receiving end will repeatedly receive the message of the adjacent channel as the message of the target channel, causing communication errors.

[0004] It can be seen that there is an urgent need for a method to accurately quantify the relationship between the frequency spacing between adjacent channels and the crosstalk intensity, and to find a critical spacing value to ensure isolation and suppress crosstalk. Summary of the invention

[0005] The embodiments of the present invention provide a method and device for interconnected communication based on power terminals across operating systems, so as to accurately and conveniently realize dynamic adjustment of channel spacing parameters, thereby avoiding crosstalk between channels and improving the communication quality of interconnected communication of power terminals across operating systems.

[0006] In a first aspect, an embodiment of the present invention provides an interconnection communication method based on a cross-operating system of a power terminal, comprising:

[0007] Acquire original data sets of channels of power terminals across operating systems under various modulation modes; the original data sets include: channel spacing parameters and crosstalk intensity;

[0008] Based on the original data set and the support vector machine regression algorithm, a preset quantitative relationship model is trained to determine a quantitative relationship model to be selected; the preset quantitative relationship model is used to reflect the mapping relationship between the channel spacing parameter and the crosstalk intensity under each modulation mode;

[0009] Performing a performance evaluation on the to-be-selected quantitative relationship model based on the original data set to determine a target quantitative relationship model;

[0010] In the process of interconnecting and communicating the power terminals across operating systems, based on the current channel spacing parameter in the current communication environment and the target quantitative relationship model, determining the current crosstalk intensity corresponding to the current channel spacing parameter;

[0011] Dynamically adjust the current channel spacing parameter based on the current crosstalk strength and a preset crosstalk strength threshold.

[0012] In a second aspect, an embodiment of the present invention further provides an interconnection communication device based on a cross-operating system of a power terminal, the device comprising:

[0013] The original data set acquisition module is used to acquire the original data sets of the channels of the power terminal across the operating system under various modulation modes; the original data sets include: channel spacing parameters and crosstalk intensity;

[0014] A module for determining a quantitative relationship model to be selected, used to train a preset quantitative relationship model based on the original data set and a support vector machine regression algorithm to determine a quantitative relationship model to be selected; the preset quantitative relationship model is used to reflect the mapping relationship between the channel spacing parameter and the crosstalk intensity under each modulation mode;

[0015] A target quantitative relationship model determination module is used to perform a performance evaluation on the to-be-selected quantitative relationship model based on the original data set to determine the target quantitative relationship model;

[0016] A current crosstalk strength determination module is used to determine the current crosstalk strength corresponding to the current channel spacing parameter based on the current channel spacing parameter and the target quantitative relationship model in the process of interconnection and communication between power terminals across operating systems in the current communication environment;

[0017] The dynamic adjustment module is used to dynamically adjust the current channel spacing parameter based on the current crosstalk strength and a preset crosstalk strength threshold.

[0018] In a third aspect, an embodiment of the present invention further provides an electronic device, the electronic device comprising:

[0019] one or more processors;

[0020] A memory for storing one or more programs;

[0021] When the one or more programs are executed by the one or more processors, the one or more processors implement the interconnection communication method based on cross-operating systems of power terminals as provided in any embodiment of the present invention.

[0022] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements an interconnection communication method based on cross-operating systems of power terminals as provided in any embodiment of the present invention.

[0023] In a fifth aspect, an embodiment of the present invention provides a computer program product, including a computer program, which, when executed by a processor, implements the interconnection communication method based on cross-operating systems of power terminals as provided in any embodiment of the present invention.

[0024] The technical solution of the embodiment of the present invention is to obtain the original data set of the channels of the power terminal across operating systems under various modulation modes; the original data set includes: channel spacing parameters and crosstalk strength; based on the original data set and the support vector machine regression algorithm, a preset quantitative relationship model is trained to determine the quantitative relationship model to be selected; the preset quantitative relationship model is used to reflect the mapping relationship between the channel spacing parameter and the crosstalk strength under each modulation mode; based on the original data set, the performance of the quantitative relationship model to be selected is evaluated to determine the target quantitative relationship model; in the process of interconnection and communication between power terminals across operating systems, based on the current channel spacing parameters in the current communication environment and the target quantitative relationship model, the current crosstalk strength corresponding to the current channel spacing parameter is determined; based on the current crosstalk strength and the preset crosstalk strength threshold, the current channel spacing parameter is dynamically adjusted, so as to accurately and conveniently realize the dynamic adjustment of the channel spacing parameter, thereby avoiding crosstalk between channels and improving the communication quality of interconnection and communication between power terminals across operating systems.

[0025] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0027] Figure 1 This is a flow chart of an interconnection communication method based on cross-operating systems of power terminals provided in the first embodiment of the present invention;

[0028] Figure 2 This is a schematic diagram of the structure of an interconnection communication device based on a cross-operating system of a power terminal provided in the second embodiment of the present invention;

[0029] Figure 3 It is a structural schematic diagram of an electronic device that implements the interconnection communication method based on power terminals across operating systems according to an embodiment of the present invention. DETAILED DESCRIPTION

[0030] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0031] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0032] Embodiment 1

[0033] Figure 1 A flowchart of an interconnection communication method based on a cross-operating system of a power terminal is provided for the first embodiment of the present invention. This embodiment is applicable to the case of dynamically adjusting channel interval parameters. The method can be performed by an interconnection communication device based on a cross-operating system of a power terminal. The interconnection communication device based on a cross-operating system of a power terminal can be implemented in the form of hardware and / or software. The interconnection communication device based on a cross-operating system of a power terminal can be configured in an electronic device. Figure 1 As shown, the method includes:

[0034] S110, obtaining original data sets of channels of the power terminal across operating systems under various modulation modes.

[0035] The original data set includes: channel spacing parameters and crosstalk strength. The channel spacing parameters may include but are not limited to the frequency spacing between channels, that is, the channel spacing.

[0036] Specifically, channel characteristic parameters under different modulation modes are obtained. Channel characteristic parameters may include but are not limited to channel spacing, signal-to-noise ratio, and bit error rate indicators. Data preprocessing is performed on the obtained channel characteristic parameters to remove outliers and noise data, and obtain original data sets of channel spacing and crosstalk intensity under different modulation modes.

[0037] On the basis of the above technical scheme, "obtaining the original data set of the channels of the power terminal across operating systems under various modulation modes" may include: obtaining the phase parameters, amplitude parameters and spectrum characteristic parameters of the modem output under various modulation modes; performing data preprocessing based on the phase parameters, amplitude parameters and spectrum characteristic parameters to determine the preprocessed data set under various modulation modes; performing feature extraction and spectrum distribution based on the preprocessed data set to determine the channel characteristic parameters; establishing a mapping relationship between the channel spacing parameters and the crosstalk intensity based on the channel characteristic parameters to obtain the original data set of the channels of the power terminal across operating systems under various modulation modes.

[0038] The modem can operate in binary phase shift keying, quadrature phase shift keying and quadrature amplitude modulation. The modulation method can include binary phase shift keying, quadrature phase shift keying and quadrature amplitude modulation.

[0039] Specifically, an orthogonal frequency division multiplexing demodulator is used to obtain the phase parameters, amplitude parameters and spectrum characteristic parameters output by the modem. Sliding median filtering is performed according to the phase parameters, amplitude parameters and spectrum characteristic parameters, and the data after sliding median filtering is smoothed by a cubic spline function to obtain a preprocessed data set. The correlation characteristics of the channel spacing and crosstalk intensity under each modulation mode are extracted for the preprocessed data set, and the spectrum distribution of the correlation characteristics is analyzed by fast Fourier transform to obtain the channel characteristic parameters. The product of the bandwidth occupancy ratio and the data throughput is calculated according to the channel characteristic parameter data, and a polynomial regression is performed on the product of the bandwidth occupancy ratio and the data throughput to establish a mapping relationship between the channel spacing and the crosstalk intensity, thereby forming an original data set of the channel spacing and the crosstalk intensity under different modulation modes.

[0040] Exemplarily, an orthogonal frequency division multiplexing demodulator is used to obtain the phase parameter, amplitude parameter and spectrum characteristic parameter of the modem output from the channel. Multiple channel interval sampling is performed under three modulation states: binary phase shift keying, quadrature phase shift keying and quadrature amplitude modulation. The sampled data is forward error correction redundantly encoded by a Reed-Solomon encoder. A data set is constructed according to the crosstalk intensity, signal-to-noise ratio and bit error rate parameters under the channel characteristic parameters. A sliding median filter with a window length of 16 is run on the data set to remove outliers, and a cubic spline function is used to smooth the data trend, and the ratio of the channel capacity to the actual data transmission rate is calculated. Abnormal data points that exceed the range of 0.8 to 1.2 are removed to generate a preprocessed data set. The correlation features of the three dimensions of modulation state, channel spacing and crosstalk intensity are extracted from the preprocessed data set. The spectrum distribution of the channel characteristic waveform is analyzed by fast Fourier transform. The waveform distortion intensity is calculated according to the normalized mean square error. The signal attenuation is calculated according to the ratio of signal power to noise power. Phase noise and amplitude noise are counted according to Rayleigh distribution to construct channel characteristic parameter data. Based on the channel characteristic parameter data, the product of bandwidth occupancy ratio and data throughput is calculated to obtain the channel utilization index value. Data are grouped according to the size of channel spacing, and polynomial regression is applied to each group of data to calculate the mapping relationship between channel spacing and crosstalk intensity. The accuracy of the mapping relationship is verified by a five-fold cross-check to generate the original data set of channel spacing and crosstalk intensity under different modulation modes.

[0041] Furthermore, when the OFDM demodulator collects the phase parameters, amplitude parameters and spectrum characteristic parameters output by the modem, the phase of each carrier is shifted by 180 degrees in the binary phase shift keying modulation state to construct two modulation symbols; in the quadrature phase shift keying modulation state, the phase of each carrier is shifted by 90 degrees to construct four modulation symbols; in the quadrature amplitude modulation state, the 16 modulation symbols are distributed on the constellation diagram, and the intervals between adjacent modulation symbols are equal. Ten different channel intervals are sampled under three modulation states, with the signal-to-noise ratio ranging from 5dB to 30dB and the bit error rate ranging from 0.00001 to 0.1. A 4-byte checksum is added to the sampled data through a Reed-Solomon encoder to generate a data set. The sliding median filter filters the abnormal data points in the window of 16 sampling points, smoothes the sudden signal sampling points, and fits the cubic spline function curve through all normal sampling points. The cubic polynomial is used to smooth the interpolation between two adjacent sampling points. When the ratio of channel capacity to actual data transmission rate exceeds the threshold interval, it is determined as an abnormal point and removed, and the preprocessed data set is generated to retain the normal sampling points. The fast Fourier transform converts the channel waveform from the time domain to the frequency domain, calculates the spectral distribution characteristics of the waveform, and the normalized mean square error represents the degree of deviation between the actual waveform and the ideal waveform. The waveform distortion is between 0.1 and 0.5, and the signal power attenuation is between 3dB and 15dB. The Rayleigh distribution describes the phase noise and amplitude noise, the phase jitter standard deviation is between 5 degrees and 20 degrees, and the amplitude fluctuation standard deviation is between 0.1 and 0.4, which constitute the channel characteristic parameters. When calculating the bandwidth occupancy ratio, the actual occupied bandwidth is between 100MHz and 500MHz, and the data throughput is between 100Mbps and 1Gbps. The product is the channel utilization index. The data was divided into 10 groups according to the channel spacing from 10MHz to 100MHz. The crosstalk intensity in each group ranged from -60dB to -20dB. The corresponding relationship between the channel spacing and the crosstalk intensity was fitted using a third-order polynomial regression. When a 5-fold cross-validation was used, each fold accounted for 20%. The accuracy index of the mapping function was obtained through fold-by-fold training and verification, and the modulation mode marker was added to form the original data set of channel spacing and crosstalk intensity under different modulation modes.

[0042] S120: training a preset quantitative relationship model based on the original data set and a support vector machine regression algorithm to determine a quantitative relationship model to be selected.

[0043] The preset quantitative relationship model is used to reflect the mapping relationship between the channel spacing parameter and the crosstalk strength under each modulation mode. The quantitative relationship model to be selected may refer to a preset quantitative relationship model with a prediction accuracy rate that meets the standard.

[0044] Specifically, the original data set is standardized by the maximum and minimum normalizer, and the features with correlation with the modulation mode higher than the preset threshold are screened by the Pearson correlation coefficient to obtain a standardized feature matrix. The training data is divided according to the standardized feature matrix, and the radial basis kernel function is used to perform feature mapping on the training data, and the training parameters are obtained by the support vector machine regression algorithm. The verification data is predicted based on the training parameters, the prediction deviation is calculated using the mean square error loss function, and the regression prediction parameters are obtained by the gradient descent method. If the prediction accuracy corresponding to the regression prediction parameters is higher than the prediction accuracy threshold, the prediction result is output. If the prediction accuracy is lower than the prediction accuracy threshold and the training rounds do not reach the preset training rounds, the verification data is superimposed and retrained.

[0045] On the basis of the above technical scheme, "training a preset quantitative relationship model based on the original data set and the support vector machine regression algorithm to determine the quantitative relationship model to be selected" may include: performing standardization processing and feature screening based on the original data set to determine a standardized feature matrix; determining training parameters based on the mapping features corresponding to the training data in the support vector machine regression algorithm and the standardized feature matrix; the training parameters are model parameters corresponding to the preset quantitative relationship model; determining regression prediction parameters based on the training parameters for the verification data in the standardized feature matrix; the regression prediction parameters are model parameters corresponding to the quantitative relationship model to be selected.

[0046] Specifically, the maximum and minimum normalizer is used to map the channel spacing values ​​in the original data set to the interval of 0 to 1 and the crosstalk intensity values ​​to the interval of -1 to 1 for standardization, and the Pearson correlation coefficient is screened according to a fixed threshold of 0.7, and the features with correlation with the modulation mode greater than the threshold are retained. The feature vector with a cumulative contribution rate of 95% is retained by truncated singular value decomposition, and a standardized feature matrix is ​​generated according to the modulation mode label. The training data is divided into 80% according to the standardized feature matrix. Based on the radial basis kernel function, the channel spacing and crosstalk intensity under each modulation mode in the training data are mapped, the initial value of the support vector machine penalty factor is set to 0.1, the support vector machine regression algorithm is applied to the training data for fitting, and the training parameters are stored according to the modulation mode label. According to the stored training parameters, the verification data is predicted according to the modulation mode label, and the mean square error loss function is used to calculate the deviation between the prediction result and the actual value, and the training parameters are iteratively updated by the batch gradient descent method, the learning rate is set to 0.01, and the number of iterations is set to 1000 to obtain the regression prediction parameters corresponding to the modulation mode. The crosstalk intensity is predicted by using regression prediction parameters for the input modulation mode and channel spacing data, and the accuracy of the prediction result is calculated by the root mean square error. If the accuracy is greater than 0.9, the prediction result is output. If the accuracy is less than 0.9, the verification data is superimposed and retrained. When the training round reaches the preset value of 5, the prediction result corresponding to the prediction parameter with the highest accuracy is output.

[0047] Furthermore, in the maximum and minimum normalization processing, the original value of the channel spacing is in the range of 10MHz to 100MHz, mapped to the interval of 0 to 1 for subsequent processing; the original value of the crosstalk intensity is in the range of -60dB to -20dB, mapped to the interval of -1 to 1 to maintain the data distribution characteristics. Under the binary phase shift keying modulation mode, the Pearson correlation coefficient between the channel spacing and the crosstalk intensity is 0.85, 0.78 under orthogonal phase shift keying, and 0.72 under orthogonal amplitude modulation, all exceeding the 0.7 threshold, indicating a strong correlation. The truncated singular value decomposition retains the eigenvector corresponding to the 95% eigenvalue contribution rate, and the number of features is reduced from the original 12 to 4 after dimensionality reduction. In the support vector machine regression algorithm, the kernel parameter of the radial basis kernel function is 0.5, and the similarity between the training data points is calculated. The initial value of the penalty factor is 0.1 to balance the model complexity and the degree of fitting. Under binary phase shift keying modulation, the predicted crosstalk strength is -45dB when the channel spacing is 20MHz, and the actual value is -42dB; the predicted value is -32dB when the channel spacing is 50MHz, and the actual value is -35dB. The prediction results under quadrature phase shift keying and quadrature amplitude modulation have similar error distributions. During the training process, the mean square error loss value gradually decreases from the initial 0.25 to 0.05, reflecting the improvement of prediction accuracy. Batch gradient descent uses 256 samples to calculate the gradient in each iteration, and the learning rate is 0.01 to ensure convergence stability. The loss value tends to be stable after 1000 iterations. Under the three modulation modes, the root mean square errors of the predicted parameters are 0.08, 0.12, and 0.15, respectively, showing the difference in prediction performance under different modulation modes. In the prediction stage, the input channel spacing is 35MHz, and the predicted crosstalk strength is -38dB under binary phase shift keying modulation. The accuracy is 0.93, which meets the 0.9 threshold requirement and is directly output. The prediction accuracy under quadrature phase shift keying modulation is 0.87, and after three rounds of iterative training, the accuracy is improved to 0.91. After five rounds of training iterations under quadrature amplitude modulation, the accuracy reaches 0.88 at most, and the corresponding prediction result is -35dB. The prediction results reflect the influence of modulation mode on the relationship between channel spacing and crosstalk intensity.

[0048] S130 , performing performance evaluation on the selected quantitative relationship model based on the original data set to determine the target quantitative relationship model.

[0049] The target quantitative relationship model may refer to a candidate quantitative relationship model with the highest performance.

[0050] Specifically, the cross-validation method is used to evaluate the performance of the selected quantitative relationship model, and the mean square error and determination coefficient indicators are used to determine the model's goodness of fit and generalization ability. The selected quantitative relationship model with the best performance is selected as the final target quantitative relationship model.

[0051] On the basis of the above technical scheme, "performance evaluation of the quantitative relationship model to be selected based on the original data set to determine the target quantitative relationship model" may include: determining the training set and the validation set in the original data set; determining the candidate model parameters corresponding to the qualified training results based on the residual probability density curve generated by the training set, the quantitative relationship model to be selected and the Gaussian kernel density estimator with preset bandwidth parameters; based on the validation set and the candidate model parameters, determining the candidate model parameters with the highest weighted prediction accuracy as the target model parameters; the target model parameters are the model parameters corresponding to the target quantitative relationship model.

[0052] Specifically, determine the training set and validation set in the original data set. Obtain the training set and validation set. Calculate the determination coefficient and goodness of fit based on the training set, and obtain the residual probability density curve through the Gaussian kernel density estimator with the bandwidth parameter as the bandwidth parameter threshold. Filter out qualified training results according to the residual mean being less than the residual mean threshold and the standard deviation being less than the standard deviation threshold. Run the candidate model parameters on the validation set for the qualified training results, and if the normalized error is less than the normalized error threshold, store the validation result and the candidate model parameters in the qualified performance set. If the normalized error is greater than the normalized error threshold, store the validation result and the candidate model parameters in the set to be processed. Predict the validation data using the candidate model parameters in the qualified performance set, use the validation set accuracy as the weight coefficient to calculate the weighted average score, and select the optimal candidate model parameters according to the weighted average score, that is, the target model parameters are used to generate the target quantitative relationship model of the corresponding modulation method.

[0053] Exemplarily, the data set of the quantitative relationship model is divided into a training set and a validation set at a ratio of 20% per fold using a five-fold cross validation. Five corresponding training sets and validation sets are constructed under three modulation modes: binary phase shift keying, quadrature phase shift keying, and quadrature amplitude modulation. The selected quantitative relationship model is run to calculate the mean square error between the predicted value and the measured value. The prediction accuracy index under each modulation mode is calculated weighted according to the signal-to-noise ratio. The determination coefficient is calculated for the prediction results of the training set, and the goodness of fit is obtained by dividing the sum of squares between the deviations between the measured value and the predicted value by the sum of squares between the deviations between the measured value and the mean. A Gaussian kernel density estimator with a bandwidth parameter of 0.5 is used to generate a residual probability density curve, and qualified training results are screened according to the standard that the residual mean is less than 0.1 and the standard deviation is less than 0.3, and the corresponding candidate model parameters are stored according to the modulation mode mark. The stored candidate model parameters are run on the validation set for prediction, and the prediction error is normalized by the ratio between the predicted value and the measured value. If the normalized error is less than 0.15, the verification result and the corresponding candidate model parameters are stored in the qualified performance set. If the normalized error is greater than 0.15, the verification result and the corresponding candidate model parameters are stored in the processing set, and the candidate model parameters in the processing set are fine-tuned and re-verified. The verification data is predicted according to the candidate model parameters in the qualified performance set, and the determination coefficient and mean square error of each group of prediction results are calculated. The accuracy of the verification set is used as the weight coefficient to perform weighted averaging on the prediction indicators under each modulation mode, and the candidate model parameters with the highest weighted average score are selected as the optimal model parameters of the corresponding modulation mode, that is, the target model parameters, thereby generating the optimal quantitative relationship model under different modulation modes, that is, the target quantitative relationship model.

[0054] Furthermore, the five-fold cross validation achieves a comprehensive evaluation by rotating the data set. The validation set accounts for 20% in each round of division, corresponding to 1000 sample points. Under the binary phase shift keying modulation mode, the channel spacing ranges from 10MHz to 100MHz, the crosstalk level ranges from -60dB to -20dB, and the signal-to-noise ratio ranges from 5dB to 30dB. When the signal-to-noise ratio is 20dB, the weight coefficient is 0.8, and when the signal-to-noise ratio is 10dB, the weight coefficient is 0.5. The weighted calculation results in a prediction accuracy index of 0.92. Orthogonal phase shift keying and orthogonal amplitude modulation use the same data division method, presenting different prediction accuracy distributions. The determination coefficient reflects the degree to which the predicted value explains the change in the measured value. Under binary phase shift keying modulation, the measured crosstalk value of -45dB corresponds to the predicted value of -43dB, and the measured value of -35dB corresponds to the predicted value of -36dB. The determination coefficient is calculated to be 0.95. The bandwidth parameter of the Gaussian kernel density estimator is 0.5, which ensures the smoothness of the curve and reflects the characteristics of the residual distribution. The residual mean of 0.08 is less than the threshold of 0.1, and the standard deviation of 0.25 is less than the threshold of 0.3. The corresponding model parameters meet the training requirements. The residual distribution under quadrature phase shift keying and quadrature amplitude modulation shows different central trends. The normalized prediction error eliminates the dimensional differences in the degree of crosstalk under different modulation modes. In the binary phase shift keying validation set, the ratio of the predicted crosstalk value to the measured value corresponding to the channel spacing of 30MHz is 0.92, which is less than the threshold of 0.15 and is included in the qualified performance set. The prediction error in the quadrature phase shift keying validation set is 0.18. After fine-tuning and re-verification by reducing the kernel function parameter to 0.3, the error of 0.14 is obtained and enters the qualified performance set. After multiple rounds of parameter fine-tuning in the quadrature amplitude modulation validation set, the prediction error is reduced to 0.13. A comprehensive evaluation was conducted on the model parameters of different modulation modes in the qualified performance set. The accuracy of the binary phase shift keying validation set was 0.94, corresponding to a weight of 0.4. The accuracy of the quadrature phase shift keying was 0.91, corresponding to a weight of 0.35. The accuracy of the quadrature amplitude modulation was 0.89, corresponding to a weight of 0.25. After weighted averaging, the binary phase shift keying model scored 0.93, the highest, and was determined to be the optimal model under this modulation mode. The model parameters corresponding to the scores of 0.90 and 0.87 were selected for quadrature phase shift keying and quadrature amplitude modulation, respectively, to form the optimal model set for the three modulation modes.

[0055] S140. During the interconnection and communication process of the power terminals across operating systems, based on the current channel spacing parameters and the target quantitative relationship model under the current communication environment, determine the current crosstalk intensity corresponding to the current channel spacing parameters.

[0056] Specifically, a software-defined radio receiver is used to obtain sampling data of the power terminal communication environment. The sampling data is subjected to fast Fourier transform to obtain the current channel spacing parameter. The current modulation mode identification bit is extracted according to the operation identification field in the power terminal communication message header. The current modulation mode identification bit obtains the corresponding modulation parameter through the modulation parameter database index. The target quantitative relationship model is input for the current channel spacing parameter, and the target quantitative relationship model is calculated by the Gaussian kernel function to obtain the predicted value of the crosstalk degree, that is, the current crosstalk intensity. The Kalman filter is used to smooth the predicted value of the crosstalk degree, and the smoothed crosstalk intensity is divided according to the preset threshold to obtain the channel crosstalk level marking data.

[0057] On the basis of the above technical scheme, "determining the current crosstalk intensity corresponding to the current channel interval parameter based on the current channel interval parameter and the target quantitative relationship model under the current communication environment" may include: obtaining the communication environment data of the power terminal under the current communication environment, and determining the current channel interval parameter through Fourier transform; extracting the current modulation mode identification bit based on the operation identification field in the current communication message header of the power terminal; determining the current crosstalk intensity corresponding to the current channel interval parameter based on the current channel interval parameter and the target quantitative relationship model corresponding to the current modulation mode identification bit.

[0058] Specifically, a software defined radio receiver is used to monitor the communication environment of the power terminal. The sampling frequency of the receiver is set to 100MHz, the sampling bit number of the intermediate frequency sampler is 16 bits, and the current channel spacing parameter is extracted from the spectrum data by fast Fourier transform. The sampled data is segmented according to the fixed frame length of 512 bytes. If the signal-to-noise ratio of the sampled data is greater than 10dB, it is input into the channel identifier to generate the current channel parameter set. The current operation state is judged according to the operation identification field in the power terminal communication message header. The operation identification includes two types based on embedded real-time operation and open operation. The current modulation mode identification bit is extracted by message parsing. The corresponding modulation parameters are obtained by indexing the modulation parameter database based on the identification bit, and matched according to three modes: binary phase shift keying, orthogonal phase shift keying, and orthogonal amplitude modulation. For the identified modulation mode, the prediction parameters (equivalent to the target model parameters) in the quantitative relationship model library are read, and the current channel spacing parameters are input into the target quantitative relationship model composed of the prediction parameters, and the crosstalk degree prediction value is calculated by the Gaussian kernel function. The kernel function bandwidth parameter is set to 0.5. The validity of the prediction result is verified by the signal-to-noise ratio and bit error rate threshold. If the verification is passed, the predicted value is output. If the verification is not passed, the resampling is returned. The corresponding data between the channel spacing and the crosstalk strength are extracted from the predicted value, and the predicted data is smoothed by the Kalman filter. The observation noise variance is set to 0.1 and the process noise variance is set to 0.01. According to the crosstalk strength thresholds of -20dB, -40dB, and -60dB, the processing results are divided into three levels: high, medium, and low, and the marked channel crosstalk prediction data is generated.

[0059] Exemplarily, the software-defined radio receiver performs channel monitoring through a 100MHz sampling frequency, adapting to the 10MHz to 50MHz frequency band commonly used in power terminal communications, and the 16-bit sampling accuracy meets the dynamic range requirements of -90dB to 0dB. The fast Fourier transform processes 512-byte fixed frame length data, and the spectrum resolution reaches 0.2MHz. With a 20MHz channel spacing, the spectrum leakage of adjacent channels is less than -55dB. When the power terminal operates in the 35MHz frequency band and the signal-to-noise ratio is 15dB, the channel identification accuracy reaches 96%. The operation identification field is located from the 4th byte to the 8th byte of the communication message header, and the corresponding identification value is 0x01 based on the embedded real-time operation, and the corresponding identification value is 0x02 for the open operation. The modulation mode identification bit is located in the 12th byte of the message header, and the binary phase shift keying corresponds to 0x11, the orthogonal phase shift keying corresponds to 0x12, and the orthogonal amplitude modulation corresponds to 0x13. In the 35MHz frequency band, the embedded real-time operation terminal uses binary phase shift keying with a data transmission rate of 10Mbps; the open operation terminal uses quadrature phase shift keying with a data transmission rate of 20Mbps. The Gaussian kernel function bandwidth parameter of 0.5 provides a good smoothing characteristic when calculating the crosstalk degree. For binary phase shift keying modulation in the 35MHz frequency band, the predicted crosstalk degree is -42dB when the channel spacing is 25MHz, and the measured value is -40dB; the predicted value is -58dB when the channel spacing is 40MHz, and the measured value is -55dB. When the signal-to-noise ratio is lower than 8dB or the bit error rate is higher than 0.001, the prediction result is judged to be invalid and resampling is triggered. The deviation distribution of the predicted value and the measured value under quadrature phase shift keying is similar. The observation noise variance of 0.1 and the process noise variance of 0.01 of the Kalman filter reflect the stability and dynamic characteristics of the prediction result. In the 35MHz frequency band of binary phase shift keying, the original prediction data shows that the crosstalk is -38dB when the channel spacing is 20MHz, and it is -35dB after filtering and smoothing, which is classified as a medium level according to the preset threshold. When the channel spacing increases to 45MHz, the crosstalk level drops to -62dB, which is classified as a low level. In the same frequency band of orthogonal phase shift keying, the crosstalk level is generally 5dB to 8dB higher, and the corresponding level classification results are also adjusted accordingly, reflecting the crosstalk characteristics of different modulation methods.

[0060] S150: Dynamically adjust the current channel spacing parameter based on the current crosstalk intensity and a preset crosstalk intensity threshold.

[0061] Specifically, based on the current crosstalk strength and the preset crosstalk strength threshold, it is determined whether the current channel spacing parameter meets the communication quality requirement of message transmission. If the current crosstalk strength exceeds the preset crosstalk strength threshold, the current channel spacing parameter is dynamically adjusted until the communication quality requirement is met.

[0062] On the basis of the above technical solution, "dynamically adjusting the current channel spacing parameters based on the current crosstalk intensity and the preset crosstalk intensity threshold" may include: if the current crosstalk intensity is greater than the preset crosstalk intensity threshold, determining the channel spacing correction value based on the step value corresponding to the current modulation mode; dynamically adjusting the current channel spacing parameters based on the channel spacing correction value to obtain the target channel spacing parameters.

[0063] Specifically, the current crosstalk strength is obtained, and it is determined whether the current crosstalk strength exceeds the preset crosstalk strength threshold according to the preset crosstalk strength threshold. If the current crosstalk strength exceeds the preset crosstalk strength threshold, the channel spacing correction value is calculated according to the step value corresponding to the current modulation mode. The channel spacing correction value is iteratively optimized using gradient descent, and the communication quality data is collected through the optimized channel spacing. The communication quality data is smoothed using a Kalman filter, and the smoothed crosstalk value is obtained based on the signal amplitude state variable and the received signal strength observation variable; the channel characteristic curve is fitted using a cubic spline function, and the optimal channel spacing is determined based on the fluctuation range limit corresponding to the modulation mode, and the communication control register is written for the optimal channel spacing.

[0064] Exemplarily, a communication quality monitor is used to obtain the current crosstalk strength, and the communication state is judged according to the preset quality threshold. The crosstalk threshold is -40dB under binary phase shift keying modulation, -45dB under quadrature phase shift keying modulation, and -50dB under quadrature amplitude modulation. The channel parameter change curve is collected through cruise test, and the corresponding relationship between channel spacing and crosstalk strength is recorded. For channel crosstalk exceeding the threshold, the channel spacing correction value is calculated by adaptive adjustment, and the step size is determined according to the amplitude of the current crosstalk exceeding the threshold. The step size is set to 5MHz for binary phase shift keying, 8MHz for quadrature phase shift keying, and 10MHz for quadrature amplitude modulation. The channel spacing parameters are iteratively optimized using gradient descent, the number of iterations is limited to 50 times, and the learning rate is set to 0.1. The communication quality data is collected under the updated channel spacing, and the data is smoothed by the Kalman filter. The signal amplitude is used as the state variable, the received signal strength is used as the observation variable, the observation noise variance is set to 0.1, and the process noise variance is set to 0.01. If the smoothed crosstalk value still exceeds the threshold, the parameter adjustment link is returned and repeated until the preset threshold requirement is met or the maximum number of iterations is reached. The channel characteristic curve is fitted with a cubic spline function, and the optimal channel spacing range is determined based on the minimum residual principle. The fluctuation range is limited to 2MHz for binary phase shift keying, 3MHz for quadrature phase shift keying, and 4MHz for quadrature amplitude modulation. The verified channel spacing parameters are written to the communication control register with an address offset of 0x1000.

[0065] Furthermore, the communication quality monitor obtains channel crosstalk data in real time and uses differentiated quality thresholds for judgment under different modulation modes. When binary phase shift keying is modulated, the crosstalk prediction value is -38dB when the channel spacing is 35MHz, exceeding the -40dB threshold, triggering channel adjustment. When the channel spacing is 40MHz under orthogonal phase shift keying, the crosstalk value is -42dB, exceeding the -45dB threshold. When the channel spacing is 45MHz under orthogonal amplitude modulation, the crosstalk value is -46dB, exceeding the -50dB threshold. The cruise test cycle is 1 second, and 100 data points are collected in each cycle to record the channel characteristics. During the adaptive adjustment process, the amplitude of the crosstalk exceeding the threshold determines the correction step size. When the crosstalk exceeds 2dB in binary phase shift keying mode, a 5MHz step size is used, and when it exceeds 5dB, the step size is increased to 8MHz. In the initial state of 35MHz channel spacing, after 3 iterations, the channel spacing is increased to 50MHz, and the crosstalk value is reduced to -43dB. Quadrature phase shift keying and quadrature amplitude modulation use similar adaptive mechanisms, but the step size is larger to meet more stringent crosstalk requirements. In the gradient descent optimization, the learning rate of 0.1 ensures convergence stability, and the 50 iteration limit prevents over-adjustment. The Kalman filter estimates the state of the signal amplitude. The observation noise variance of 0.1 corresponds to the measurement error, and the process noise variance of 0.01 reflects the characteristics of the channel state change. Under the 50MHz channel spacing of binary phase shift keying, the original crosstalk measurement value fluctuates from -45dB to -41dB, and stabilizes at -43dB after filtering and smoothing. Under the 60MHz interval of quadrature phase shift keying, the crosstalk value after filtering is stable at -47dB; under the 70MHz interval of quadrature amplitude modulation, the crosstalk value after filtering is stable at -52dB. The channel characteristic curve fitted by the cubic spline function reflects the corresponding relationship between the channel spacing and crosstalk. Under the binary phase shift keying mode, the crosstalk value fluctuates less than 2MHz in the range of 45MHz to 55MHz, which is determined to be the optimal interval. The optimal range for quadrature phase shift keying is 55MHz to 65MHz, and the optimal range for quadrature amplitude modulation is 65MHz to 75MHz. The communication control register stores parameters in a byte-aligned manner, with the upper 4 bits storing the modulation mode identifier and the lower 12 bits storing the channel interval value. The parameter update delay during operation is less than 1 millisecond, ensuring real-time adjustment of communication quality.

[0066] The technical solution of the embodiment of the present invention is to obtain the original data set of the channels of the power terminal across operating systems under various modulation modes; the original data set includes: channel spacing parameters and crosstalk strength; based on the original data set and the support vector machine regression algorithm, a preset quantitative relationship model is trained to determine the quantitative relationship model to be selected; the preset quantitative relationship model is used to reflect the mapping relationship between the channel spacing parameter and the crosstalk strength under each modulation mode; based on the original data set, the performance of the selected quantitative relationship model is evaluated to determine the target quantitative relationship model; in the process of interconnection and communication between power terminals across operating systems, based on the current channel spacing parameters and the target quantitative relationship model in the current communication environment, the current crosstalk strength corresponding to the current channel spacing parameters is determined; based on the current crosstalk strength and the preset crosstalk strength threshold, the current channel spacing parameters are dynamically adjusted, so as to accurately and conveniently realize the dynamic adjustment of the channel spacing parameters, thereby avoiding crosstalk between channels and improving the communication quality of the interconnection and communication between power terminals across operating systems.

[0067] On the basis of the above technical scheme, the method also includes: using the prediction results of the quantitative relationship model between channel spacing and crosstalk intensity under different modulation modes, deriving the optimal channel spacing that meets the communication quality requirements, and applying it to the parameter configuration of the power line carrier communication module in the cross-operating system interconnection communication scenario of the power terminal, so as to adaptively adjust the receiving threshold of the communication module. If the crosstalk degree prediction value of the current channel spacing (equivalent to the current crosstalk intensity) exceeds the crosstalk degree prediction value threshold (equivalent to the preset crosstalk intensity threshold), the receiving threshold is increased and the message verification is strengthened; the content, timestamp, source node ID and unique identifier of the received new message are obtained, and the matching of the content, timestamp and unique identifier is compared with the message in the most recently received message cache; if all conditions are met, it is regarded as a duplicate message and discarded without further processing; if no matching cache message is found, the new message is added to the cache.

[0068] Exemplarily, "using the prediction results of the quantitative relationship model between channel spacing and crosstalk intensity under different modulation modes, the optimal channel spacing that meets the communication quality requirements is obtained, and applied to the parameter configuration of the power line carrier communication module in the cross-operating system interconnection communication scenario of the power terminal, so as to adaptively adjust the receiving threshold of the communication module. If the crosstalk degree prediction value of the current channel spacing exceeds the crosstalk degree prediction value threshold, the receiving threshold is increased and the message verification is strengthened" may include: obtaining the crosstalk degree prediction value of the current channel spacing, and reading the operating parameters from the power line carrier communication module memory according to the crosstalk prediction value. Generate carrier communication parameter combinations corresponding to binary phase shift keying, quadrature phase shift keying and quadrature amplitude modulation for the operating parameters. If the crosstalk degree prediction value exceeds the crosstalk degree prediction value threshold, generate the check bit length according to the modulation mode corresponding to the carrier communication parameter combination, and obtain the enhanced verification communication message through the cyclic redundancy code generation polynomial. Use the enhanced verification communication message to construct a Kalman filter, and if the continuous test cycle bit error rate exceeds the cycle bit error rate threshold, increase the receiving threshold to obtain the updated carrier communication module operating parameters.

[0069] Specifically, a crosstalk predictor is used to evaluate the crosstalk degree of the current channel spacing. The crosstalk prediction value under each modulation mode is calculated by support vector regression of the radial basis kernel function. The minimum channel spacing is extracted according to the channel quality threshold of -20dB, and the deviation between the measured crosstalk value and the predicted value in the cross-operating system communication scenario is corrected online. The channel quality indicators of each frequency band are verified by cruise test to generate the optimal channel spacing parameters. The current operating parameters are read from the power line carrier communication module memory, and the corresponding parameter configuration reference values ​​are extracted according to the two types of terminal attributes based on embedded real-time operation and open operation. The receiving threshold is quantized by the bit error rate threshold of 0.001, and the quantization interval is from -85dBm to -35dBm. Carrier communication parameter combinations are generated for binary phase shift keying, quadrature phase shift keying, and quadrature amplitude modulation respectively. The signal quality is judged according to the crosstalk prediction value. When the crosstalk degree exceeds the preset threshold of -40dB, the check bit length is adaptively adjusted according to the modulation mode. The binary phase shift keying check bit is set to 16 bits, the quadrature phase shift keying check bit is set to 24 bits, and the quadrature amplitude modulation check bit is set to 32 bits. The communication message is encoded by the cyclic redundancy code generator polynomial to generate an enhanced check communication message. The enhanced check communication message is used for channel transmission test, and the Kalman filter is constructed with the signal amplitude as the state variable and the received signal strength as the observation variable. The observation noise variance is set to 0.1 and the process noise variance is set to 0.01. When the bit error rate exceeds 0.0001 for 5 consecutive test cycles, the receiving threshold is increased by 2dB. When the bit error rate is less than 0.00001 for 10 consecutive test cycles, the receiving threshold is reduced by 1dB, and the carrier communication module operating parameters are updated.

[0070] Furthermore, radial basis kernel function support vector regression shows good nonlinear mapping ability when processing power line carrier communication channel characteristics. When the channel spacing is 35MHz, the predicted crosstalk value under binary phase shift keying modulation is -38dB, and the measured value is -35dB; the predicted value under quadrature phase shift keying is -32dB, and the measured value is -30dB. During the online correction process, the terminal cruise test based on embedded real-time operation shows that the average crosstalk in the 35MHz to 45MHz frequency band is -42dB, which meets the -20dB quality threshold requirement. The open operation terminal has an average crosstalk of -38dB in the same frequency band test. The power line carrier communication module operation parameter memory stores the most recent 100 sets of historical parameter records. The terminal based on embedded real-time operation has a typical receiving threshold of -75dBm under a bit error rate threshold of 0.001; the typical value of the open operation terminal is -70dBm. Under binary phase shift keying modulation, when the channel spacing is 40MHz, the signal receiving level is -65dBm; under quadrature phase shift keying, the receiving level is -60dBm; under quadrature amplitude modulation, the receiving level drops to -55dBm, reflecting the requirements of different modulation modes for receiving sensitivity. The adaptive adjustment of the cyclic redundancy check bit reflects the difference in the anti-interference ability of different modulation modes. When the crosstalk exceeds the -40dB threshold, binary phase shift keying uses 16-bit check to correct 2-bit random errors; quadrature phase shift keying uses 24-bit check to correct 4-bit random errors; quadrature amplitude modulation uses 32-bit check to correct 6-bit random errors. The generating polynomial adopts the form of x16+x12+x5+1 recommended in the standard specification. In the 35MHz frequency band test, the bit error rate is reduced by 3 orders of magnitude, and x is a binary position mark. The Kalman filter achieves dynamic adjustment of the receiving threshold through recursive estimation. The observed noise variance of 0.1 corresponds to the uncertainty of the signal amplitude measurement, and the process noise variance of 0.01 reflects the slowly changing characteristics of the channel state. In the binary phase-shift keying 35MHz band transmission test, when the bit error rate reaches 0.0002 for 5 consecutive cycles, the receiving threshold is increased from -75dBm to -73dBm, and the communication quality is improved; when the bit error rate drops to 0.000008 for 10 consecutive cycles, the receiving threshold is reduced to -74dBm accordingly, optimizing the channel utilization. The threshold adjustment of orthogonal phase-shift keying and orthogonal amplitude modulation follows similar rules, reflecting the adaptability of the adaptive mechanism to different modulation methods.

[0071] Exemplarily, "obtaining the content, timestamp, source node ID and unique identifier of the received new message, and comparing the content, timestamp and unique identifier with the message in the most recently received message cache for matching; if all conditions are met, it is regarded as a duplicate message and discarded without further processing; if no matching cached message is found, the new message is added to the cache" may include: obtaining the message content of the content field, timestamp field, source node identification field and unique identifier field of the new message. Generate a message feature value for the message content using a secure hash algorithm. Use a Bloom filter to match and search the message feature vector from the cache area based on the message feature value, and calculate the time interval using the timestamp. If the Bloom filter finds a match result and the time interval is less than the time interval threshold, perform a feature check on the message content. Store the new message whose feature check result is a non-duplicate message into the cache message sequence.

[0072] Specifically, a data extractor is used to parse the new message according to the starting position and length of the field, and the message content of bytes 0 to 511, the timestamp of bytes 512 to 519, the source node identifier of bytes 520 to 527, and the unique identifier of bytes 528 to 535 are obtained. A 256-bit feature value is generated for the message content by the secure hash algorithm SHA-256, an index key value is constructed according to the identifier, the integrity of the feature value is verified by a one-way check function, and a new message feature vector is generated. The feature vector of the most recently received message is extracted from the cache message area. A Bloom filter with three hash functions and a bit array size of 8 times the number of messages is used for matching search. The timestamp difference calculator is used to determine whether the interval is less than 100 milliseconds, the source node identifier is compared with the unique identifier based on the bitmap index, and the sliding time window is used to sequentially process multiple duplicate messages that arrive at the same time to obtain the comparison result. The repetition state is determined according to the comparison result. If the new message feature vector exists in the Bloom filter and the time interval is less than the threshold. The message content is double-checked using the message digest algorithm MD5, and the 16-byte digest value in the check result is compared. The messages marked as duplicates are added to the discard record table, and the discard statistics are updated in time series. Non-duplicate messages are cached, and the cache message sequence is maintained through the circular queue manager. A counter is used to record the current number of cached messages. If the count value exceeds the preset maximum value of 1024, the message at the head of the queue is deleted, and the new message is inserted into the tail of the queue according to the arrival timestamp to complete the automatic update of the cache.

[0073] Furthermore, the data extractor parses the message field according to a fixed length. The message content is 512 bytes to store complete business data, the timestamp is 8 bytes to record the generation time accurate to milliseconds, the source node identifier is 8 bytes to record the unique number of the sending device, and the unique identifier is 8 bytes using an increasing sequence number. In actual applications, the content of a message is distribution network monitoring data. The feature value length generated by SHA-256 is 256 bits, and the one-way check function ensures the integrity of the feature value through a cyclic redundancy check. When multiple messages are received continuously, the feature vectors are stored in the order of arrival. The Bloom filter uses three hash functions to map the feature vectors. If the buffer stores 128 messages, the bit array size is set to 1024 bits. In the distribution network monitoring scenario, the difference between the timestamps of adjacent messages is set to a 100 millisecond threshold, the source node identifier uses the factory number of the device, and the bitmap index accelerates the matching process. When multiple duplicate messages arrive at the same time within 80 milliseconds, the sliding time window is processed in 5 millisecond intervals to avoid missed judgments and misjudgments. The message digest algorithm MD5 performs secondary verification on duplicate messages and generates a 16-byte digest value. A complete match in the verification result indicates that the message is duplicated. In actual operation, the distribution network monitoring device sends 2 messages per second. If a duplicate message is detected, the timestamp, source node identifier, and unique identifier are recorded in the discard record table, and the repetition rate is counted by hour. When the repetition rate exceeds 1%, the sampling frequency is automatically adjusted. The circular queue uses a fixed-length storage space of 1024 messages, and the counter updates the current number of cached messages in real time. In the distribution network monitoring application, the message arrival interval is 500 milliseconds, and the queue is stored in order with the timestamp as the index. When the number of messages in the cache area reaches 1024, the earliest 64 messages are deleted to reserve space for new messages. During operation, the cache space utilization rate is maintained at 85% to 95%, ensuring the real-time and accuracy of message comparison.

[0074] On the basis of the above technical solutions, in the actual power line carrier communication process, the channel spacing and crosstalk intensity are continuously monitored, the communication quality of message transmission is predicted in real time, and the channel configuration is dynamically optimized according to the communication quality prediction results.

[0075] Among them, a communication status monitor is used to obtain channel status data. The channel status data includes crosstalk value, signal-to-noise ratio and bit error rate. The crosstalk prediction value is obtained by support vector regression calculation. The communication quality score is calculated according to the crosstalk value, signal-to-noise ratio and bit error rate according to the preset weights. The preset weights include crosstalk weight, signal-to-noise ratio weight and bit error rate weight. A Kalman filter is used to adjust the transmit power according to the communication quality score to obtain a filtered transmit power value. If the crosstalk prediction value exceeds the crosstalk prediction threshold, the transmit power increase and modulation mode switching or channel interval update are triggered according to the crosstalk prediction value.

[0076] Specifically, a communication status monitor is used to collect channel status data, including three indicators: crosstalk value, signal-to-noise ratio, and bit error rate. The crosstalk prediction value is calculated by support vector regression of the radial basis kernel function. The kernel parameter is set to 0.5, and the number of iterations is limited to 100 times. The communication quality score is calculated based on the weighted summation method, with a crosstalk weight of 0.4, a signal-to-noise ratio weight of 0.3, and a bit error rate weight of 0.3. The operation type is marked for the score data in the cross-operating system interconnection scenario. The transmit power is adjusted according to the communication quality score, and the Kalman filter with the signal amplitude as the state variable and the received power as the observation variable is used for smoothing. The observed noise variance is set to 0.1, and the process noise variance is set to 0.01. The corresponding modulation mode is selected under the two terminals based on embedded real-time operation and open operation, and the channel parameters are configured according to the frequency band occupancy table. The frequency band range includes 6 frequency bands from 10MHz to 100MHz, and the power gear, modulation mode, and frequency band number are written into the communication register. Forward error correction coding is used to process communication data. The error correction code length is 16 bits for binary phase shift keying modulation, 24 bits for quadrature phase shift keying modulation, and 32 bits for quadrature amplitude modulation. Cyclic redundancy check is performed using the standard polynomial x16+x12+x5+1. After the check code is generated, the synchronization header and frame tail identifier are added to the data frame. After data encapsulation, the error correction capability is verified. According to the optimization order of terminal type first, modulation mode second best, and channel parameter second best, check whether the crosstalk prediction value exceeds the threshold. If the threshold is exceeded, parameter optimization is triggered. When the crosstalk exceeds -40dB, the transmission power is increased. When it exceeds -45dB, the modulation mode is switched. When it exceeds -50dB, the channel interval is updated. The communication quality index of the optimized parameters is judged through online cruise test, and the parameter configuration is updated after verification.

[0077] Furthermore, the communication status monitor collects channel status data every 100 milliseconds. In the terminal based on embedded real-time operation, a certain collection shows that the crosstalk value is -38dB, the signal-to-noise ratio is 15dB, and the bit error rate is 0.001. Support vector regression uses radial basis kernel function to process data. After 85 iterations, the crosstalk prediction value converges to -36dB. In the calculation of communication quality score, the crosstalk value weight of 0.4 corresponds to a score of 3.6 points, the signal-to-noise ratio weight of 0.3 corresponds to a score of 4.2 points, and the bit error rate weight of 0.3 corresponds to a score of 3.8 points. The weighted summation gives a final score of 3.85 points. The open operation terminal scored 4.1 points under the same configuration. The Kalman filter smoothes the transmit power adjustment amount. The observation noise variance of 0.1 reflects the uncertainty of power measurement, and the process noise variance of 0.01 reflects the stability of power adjustment. In the embedded real-time operation terminal, when the transmission power is adjusted from 20dBm to 23dBm, the received signal strength increases from -75dBm to -70dBm. The modulation mode is switched from binary phase shift keying to quadrature phase shift keying, and the frequency band is adjusted from 35MHz to 45MHz. The communication register stores the modulation identifier in the upper 4 bits, the frequency band number in the middle 8 bits, and the power level in the lower 4 bits. Forward error correction coding adopts differentiated error correction strategies for different modulation modes. Under binary phase shift keying, the 16-bit error correction code can correct 2-bit random errors, under quadrature phase shift keying, the 24-bit error correction code can correct 4-bit random errors, and under quadrature amplitude modulation, the 32-bit error correction code can correct 6-bit random errors. The cyclic redundancy check uses a standard polynomial to generate the check code. The data frame structure includes an 8-byte synchronization header, a 512-byte data segment, a 4-byte check code, and a 4-byte frame tail. The error correction capability is verified by injecting random errors. The parameter optimization process follows a strict priority order. When the crosstalk prediction value is -38dB, the transmit power is increased by 3dB. When the crosstalk prediction value reaches -43dB, the binary phase shift keying is switched to quadrature phase shift keying. When the crosstalk prediction value is -48dB, the channel spacing is increased from 35MHz to 45MHz. The online cruise test shows that the signal-to-noise ratio is increased by 2dB after the transmit power is adjusted, the data throughput is increased by 50% after switching the modulation mode, and the crosstalk is reduced by 5dB after updating the channel spacing. The optimized parameter combination meets all the communication quality indicators in 100 tests.

[0078] It should be noted that the embodiment of the present invention discloses a method for interconnection communication based on power terminals across operating systems. In view of the problem that the unreasonable channel spacing setting leads to serious crosstalk and affects the communication quality when interconnecting across operating systems in power line carrier communication, the present invention establishes a quantitative relationship model between channel spacing and crosstalk intensity under different modulation modes. First, the channel characteristic parameters under different modulation modes are obtained, and the support vector machine regression algorithm is used to train the model after preprocessing, and the model performance is evaluated by cross-validation method. Then, according to the current channel spacing parameters of the current communication environment, the model is used to predict the crosstalk intensity, and the receiving threshold of the communication module is adaptively adjusted according to the prediction results to strengthen the message verification. At the same time, the present invention designs a duplicate message identification and discarding mechanism to avoid repeated processing by comparing the message content, timestamp, source node and unique identifier. Finally, according to the crosstalk intensity prediction result (current crosstalk intensity), the channel spacing and other parameters are dynamically adjusted until the communication quality requirements are met, and the channel status is monitored in real time, and the channel configuration parameters are dynamically optimized to ensure that the interconnection communication of power terminals across operating systems is stable and reliable. By establishing a quantitative relationship between channel spacing and crosstalk intensity, and combining adaptive receive threshold adjustment, duplicate message discarding, and dynamic channel configuration optimization, the present invention effectively solves the crosstalk problem in cross-operating system interconnection scenarios in power line carrier communications, and significantly improves communication quality and reliability.

[0079] The following is an embodiment of an interconnection communication device based on power terminals across operating systems provided by an embodiment of the present invention. The device and the interconnection communication methods based on power terminals across operating systems of the above-mentioned embodiments belong to the same inventive concept. For details not described in detail in the embodiment of the interconnection communication device based on power terminals across operating systems, please refer to the above-mentioned embodiment of the interconnection communication method based on power terminals across operating systems.

[0080] Embodiment 2

[0081] Figure 2 This is a schematic diagram of a structure of an interconnected communication device based on a cross-operating system of a power terminal provided in the second embodiment of the present invention. Figure 2 As shown, the device includes: an original data set acquisition module 210, a to-be-selected quantitative relationship model determination module 220, a target quantitative relationship model determination module 230, a current crosstalk intensity determination module 240 and a dynamic adjustment module 250.

[0082] Among them, the original data set acquisition module 210 is used to obtain the original data set of the channels of the power terminal across operating systems under various modulation modes; the original data set includes: channel spacing parameters and crosstalk strength; the to-be-selected quantitative relationship model determination module 220 is used to train the preset quantitative relationship model based on the original data set and the support vector machine regression algorithm to determine the to-be-selected quantitative relationship model; the preset quantitative relationship model is used to reflect the mapping relationship between the channel spacing parameter and the crosstalk strength under each modulation mode; the target quantitative relationship model determination module 230 is used to perform performance evaluation on the to-be-selected quantitative relationship model based on the original data set to determine the target quantitative relationship model; the current crosstalk strength determination module 240 is used to determine the current crosstalk strength corresponding to the current channel spacing parameter based on the current channel spacing parameter and the target quantitative relationship model under the current communication environment during the interconnection and communication of the power terminal across operating systems; the dynamic adjustment module 250 is used to dynamically adjust the current channel spacing parameter based on the current crosstalk strength and the preset crosstalk strength threshold.

[0083] The technical solution of the embodiment of the present invention is to obtain the original data set of the channels of the power terminal across operating systems under various modulation modes; the original data set includes: channel spacing parameters and crosstalk strength; based on the original data set and the support vector machine regression algorithm, a preset quantitative relationship model is trained to determine the quantitative relationship model to be selected; the preset quantitative relationship model is used to reflect the mapping relationship between the channel spacing parameter and the crosstalk strength under each modulation mode; based on the original data set, the performance of the selected quantitative relationship model is evaluated to determine the target quantitative relationship model; in the process of interconnection and communication between power terminals across operating systems, based on the current channel spacing parameters and the target quantitative relationship model in the current communication environment, the current crosstalk strength corresponding to the current channel spacing parameters is determined; based on the current crosstalk strength and the preset crosstalk strength threshold, the current channel spacing parameters are dynamically adjusted, so as to accurately and conveniently realize the dynamic adjustment of the channel spacing parameters, thereby avoiding crosstalk between channels and improving the communication quality of the interconnection and communication between power terminals across operating systems.

[0084] On the basis of the above technical solution, the original data set acquisition module 210 is specifically used to: obtain the phase parameters, amplitude parameters and spectrum characteristic parameters of the modem output under each modulation mode; perform data preprocessing based on the phase parameters, amplitude parameters and spectrum characteristic parameters to determine the preprocessed data set under each modulation mode; perform feature extraction and spectrum distribution based on the preprocessed data set to determine the channel characteristic parameters; establish a mapping relationship between the channel spacing parameters and the crosstalk intensity based on the channel characteristic parameters to obtain the original data sets of the channels of the power terminal across the operating system under each modulation mode.

[0085] On the basis of the above technical scheme, the module 220 for determining the quantitative relationship model to be selected is specifically used for: performing standardization processing and feature screening based on the original data set to determine the standardized feature matrix; determining the training parameters based on the support vector machine regression algorithm and the mapping features corresponding to the training data in the standardized feature matrix; the training parameters are the model parameters corresponding to the preset quantitative relationship model; determining the regression prediction parameters based on the verification data in the standardized feature matrix based on the training parameters; the regression prediction parameters are the model parameters corresponding to the quantitative relationship model to be selected.

[0086] On the basis of the above technical solution, the target quantitative relationship model determination module 230 is specifically used to: determine the training set and the validation set in the original data set; determine the candidate model parameters corresponding to the qualified training results based on the residual probability density curve generated by the training set, the quantitative relationship model to be selected and the preset bandwidth parameter Gaussian kernel density estimator; based on the validation set and the candidate model parameters, determine the candidate model parameters with the highest weighted prediction accuracy as the target model parameters; the target model parameters are the model parameters corresponding to the target quantitative relationship model.

[0087] Based on the above technical solution, the current crosstalk strength determination module 240 is specifically used to: obtain the communication environment data of the power terminal in the current communication environment, and determine the current channel interval parameter through Fourier transform; extract the current modulation mode identification bit based on the operation identification field in the current communication message header of the power terminal; determine the current crosstalk strength corresponding to the current channel interval parameter based on the target quantitative relationship model corresponding to the current channel interval parameter and the current modulation mode identification bit.

[0088] Based on the above technical solution, the dynamic adjustment module 250 is specifically used for: if the current crosstalk intensity is greater than the preset crosstalk intensity threshold, determining the channel spacing correction value based on the step value corresponding to the current modulation mode; dynamically adjusting the current channel spacing parameter based on the channel spacing correction value to obtain the target channel spacing parameter.

[0089] The interconnection communication device based on cross-operating systems of power terminals provided in an embodiment of the present invention can execute the interconnection communication method based on cross-operating systems of power terminals provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the interconnection communication method based on cross-operating systems of power terminals.

[0090] It is worth noting that in the above-mentioned embodiment of interconnection communication based on power terminals across operating systems, the various units and modules included are only divided according to functional logic, but are not limited to the above-mentioned division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0091] Embodiment 3

[0092] Figure 3 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0093] like Figure 3 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0094] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0095] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The processor 11 executes the various methods and processes described above, such as an interconnection communication method based on a power terminal across operating systems.

[0096] In some embodiments, the interconnection communication method based on the power terminal across operating systems can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the interconnection communication method based on the power terminal across operating systems described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to execute the interconnection communication method based on the power terminal across operating systems in any other appropriate manner (for example, by means of firmware).

[0097] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0098] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0099] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0100] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0101] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0102] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0103] An embodiment of the present invention further provides a computer program product, including a computer program, which, when executed by a processor, implements the interconnection communication method based on power terminals across operating systems as provided in any embodiment of the present application.

[0104] In the process of implementation, the computer program product can be written in one or more programming languages ​​or a combination thereof to perform the computer program code of the present invention, and the programming language includes an object-oriented programming language, such as Java, Smalltalk, C++, and also includes a conventional procedural programming language, such as "C" language or similar programming language. The program code can be executed completely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on the remote computer, or completely on the remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (for example, using an Internet service provider to connect through the Internet). The program product and the interconnection communication method based on the cross-operating system of the power terminal disclosed in each embodiment of the present application belong to the same inventive concept, so it will not be repeated here.

[0105] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0106] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for interconnection and communication based on cross-operating systems of power terminals, characterized in that: include: Obtain the original data set of the channels of the power terminal across operating systems under various modulation modes; The original data set includes: channel spacing parameters and crosstalk intensity; Based on the original data set and the support vector machine regression algorithm, a preset quantitative relationship model is trained to determine a quantitative relationship model to be selected; the preset quantitative relationship model is used to reflect the mapping relationship between the channel spacing parameter and the crosstalk intensity under each modulation mode; Performing a performance evaluation on the to-be-selected quantitative relationship model based on the original data set to determine a target quantitative relationship model; In the process of interconnecting and communicating the power terminals across operating systems, based on the current channel spacing parameter in the current communication environment and the target quantitative relationship model, determining the current crosstalk intensity corresponding to the current channel spacing parameter; Dynamically adjust the current channel spacing parameter based on the current crosstalk strength and a preset crosstalk strength threshold.

2. The method according to claim 1, characterized in that The obtaining of the original data set of the channels of the power terminal across the operating system under various modulation modes includes: Obtaining phase parameters, amplitude parameters and spectrum characteristic parameters output by the modem under various modulation modes; Perform data preprocessing based on the phase parameter, amplitude parameter and spectrum characteristic parameter to determine a preprocessing data set under each modulation mode; Perform feature extraction and spectrum distribution based on the preprocessed data set to determine channel characteristic parameters; A mapping relationship between the channel spacing parameter and the crosstalk intensity is established based on the channel characteristic parameters, and an original data set of the channels of the power terminal across the operating system under various modulation modes is obtained.

3. The method according to claim 1, characterized in that The method of training a preset quantitative relationship model based on the original data set and a support vector machine regression algorithm to determine a quantitative relationship model to be selected includes: Performing standardization processing and feature screening based on the original data set to determine a standardized feature matrix; Determining training parameters based on a support vector machine regression algorithm and mapping features corresponding to the training data in the standardized feature matrix; the training parameters are model parameters corresponding to a preset quantitative relationship model; Based on the training parameters, the regression prediction parameters are determined for the verification data in the standardized feature matrix; the regression prediction parameters are model parameters corresponding to the quantitative relationship model to be selected.

4. The method according to claim 1, characterized in that The step of performing a performance evaluation on the to-be-selected quantitative relationship model based on the original data set to determine a target quantitative relationship model includes: Determine a training set and a validation set in the original data set; Determine the candidate model parameters corresponding to the qualified training results based on the training set, the quantitative relationship model to be selected and the residual probability density curve generated by the preset bandwidth parameter Gaussian kernel density estimator; Based on the validation set and the candidate model parameters, the candidate model parameters with the highest weighted prediction accuracy are determined as target model parameters; the target model parameters are model parameters corresponding to the target quantitative relationship model.

5. The method according to claim 1, characterized in that: The determining, based on the current channel spacing parameter in the current communication environment and the target quantitative relationship model, a current crosstalk intensity corresponding to the current channel spacing parameter includes: Acquire the communication environment data of the power terminal in the current communication environment, and determine the current channel interval parameter through Fourier transform; Extracting the current modulation mode identification bit based on the operation identification field in the current communication message header of the power terminal; Based on the target quantitative relationship model corresponding to the current channel spacing parameter and the current modulation mode identification bit, the current crosstalk intensity corresponding to the current channel spacing parameter is determined.

6. The method according to claim 1, characterized in that The dynamically adjusting the current channel spacing parameter based on the current crosstalk strength and the preset crosstalk strength threshold includes: If the current crosstalk intensity is greater than a preset crosstalk intensity threshold, determining a channel spacing correction value based on a step value corresponding to the current modulation mode; The current channel spacing parameter is dynamically adjusted based on the channel spacing correction value to obtain a target channel spacing parameter.

7. An interconnection communication device based on a cross-operating system of a power terminal, characterized in that: The device comprises: The original data set acquisition module is used to acquire the original data sets of the channels of the power terminal across the operating system under various modulation modes; the original data sets include: channel spacing parameters and crosstalk intensity; A module for determining a quantitative relationship model to be selected, used to train a preset quantitative relationship model based on the original data set and a support vector machine regression algorithm to determine a quantitative relationship model to be selected; the preset quantitative relationship model is used to reflect the mapping relationship between the channel spacing parameter and the crosstalk intensity under each modulation mode; A target quantitative relationship model determination module is used to perform a performance evaluation on the quantitative relationship model to be selected based on the original data set to determine the target quantitative relationship model; A current crosstalk strength determination module is used to determine the current crosstalk strength corresponding to the current channel spacing parameter based on the current channel spacing parameter and the target quantitative relationship model in the process of interconnection and communication between power terminals across operating systems in the current communication environment; The dynamic adjustment module is used to dynamically adjust the current channel spacing parameter based on the current crosstalk strength and a preset crosstalk strength threshold.

8. An electronic device, characterized in that: The electronic device comprises: one or more processors; A memory for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the interconnection communication method based on cross-operating systems of power terminals as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, it implements the interconnection communication method based on cross-operating systems of power terminals as described in any one of claims 1-6.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by the processor, it implements the interconnection communication method based on cross-operating systems of power terminals as described in any one of claims 1 to 6.

Images