Plc feedforward compensation control method and system considering power grid disturbance

Abstract

The application provides a PLC feedforward compensation control method and system considering power grid disturbance, which continuously and real-timely monitors communication quality of a PLC receiving signal, and once detects deterioration of the communication quality, immediately triggers injection of a detection signal into a power line channel, performs online channel transfer function identification, dynamically acquires and updates frequency response characteristics of the power line channel, and reconfigures feedforward compensation filter coefficients according to the frequency response characteristics. In this way, the system can accurately respond to rapid changes in the channel caused by power grid disturbance, effectively overcome channel notch points and dynamic fading, and avoid performance decline or even negative effects caused by parameter mismatch of a traditional static compensation model, so that the feedforward compensator can keep synchronization with channel conditions at all times, ensure real-time performance and effectiveness of compensation, and fundamentally improve compensation accuracy.

Description

Technical Field

[0001] This invention relates to the field of intelligent compensation technology, specifically to a PLC feedforward compensation control method and system that takes into account power grid disturbances. Background Technology

[0002] PLC technology, with its unique advantage of utilizing existing power line infrastructure for data transmission, has shown great application potential in fields such as smart grids and the Internet of Things. However, the inherent complexity, time-varying nature, and noise interference of power line channels severely restrict the communication quality and reliability of PLC systems. To effectively overcome channel distortion and improve data transmission performance, feedforward compensation control, as an important technique for pre-distorting and offsetting channel effects at the transmitting end, is widely used in PLC systems.

[0003] Most existing PLC feedforward compensation methods are based on static or quasi-static channel models, such as zero-crossing-point transmission or fixed impedance matching. These methods assume that channel characteristics are fixed or change slowly over a long period. However, real low-voltage distribution networks are typically dynamic, time-varying, and complex systems. Instantaneous load changes caused by user electricity consumption (such as a neighbor installing a new electric vehicle charging station or a factory starting up new frequency converters), as well as micro-topological changes such as plugging and unplugging appliances and switching on / off switches, all cause drastic and rapid changes in power line channel impedance over a wide frequency range, especially prone to forming deep channel notches within tens of milliseconds. This drastic time-varying characteristic quickly renders traditional fixed compensation models, which rely on preset or single-calibration methods, ineffective. These models not only fail to adapt to channel changes but may also have negative effects due to the mismatch between compensation parameters and actual channel conditions, leading to a significant decrease in communication reliability and transmission rate over time.

[0004] Therefore, an optimized PLC feedforward compensation control method that takes into account grid disturbances is needed. Summary of the Invention

[0005] The present invention aims to at least solve one of the technical problems existing in the prior art, and provides a PLC feedforward compensation control method and system that takes into account power grid disturbances.

[0006] In a first aspect, embodiments of the present invention provide a PLC feedforward compensation control method that takes into account power grid disturbances, comprising: Acquire the signal received by the PLC; Real-time monitoring of the communication quality of the PLC received signals is performed to obtain disturbance trigger flags; In response to the disturbance trigger flag being true, a probe transmission signal is injected from the transmitter into the power line channel, and a probe reception signal is received from the power line channel; Online channel transfer function identification is performed on the probe template signal and the probe received signal to obtain the updated channel frequency response; The feedforward compensation parameters are dynamically reconstructed based on the updated channel frequency response to obtain new feedforward filter coefficients; The original signal to be transmitted is input into a feedforward compensation filter to obtain a compensated transmitted signal, wherein the feedforward compensation filter has new feedforward filter coefficients.

[0007] According to another aspect of the present invention, a PLC feedforward compensation control system that takes into account power grid disturbances is provided, comprising: The signal acquisition module is used to acquire signals received by the PLC. The real-time communication quality monitoring module is used to monitor the communication quality of the signals received by the PLC in real time in order to obtain the disturbance trigger flag. The signal receiving module is used to inject a probe transmission signal from the transmitting end into the power line channel in response to a disturbance trigger flag being true, and to receive a probe reception signal from the power line channel. The online channel transfer function identification module is used to perform online channel transfer function identification on the probe template signal and the probe received signal to obtain the updated channel frequency response; The dynamic reconstruction module is used to dynamically reconstruct the feedforward compensation parameters based on the updated channel frequency response to obtain new feedforward filter coefficients. The feedforward compensation filter module is used to input the original signal to be transmitted into the feedforward compensation filter to obtain the compensated transmitted signal. The feedforward compensation filter has new feedforward filter coefficients.

[0008] Compared with existing technologies, the present invention provides a PLC feedforward compensation control method and system that takes into account power grid disturbances. By continuously monitoring the communication quality of the PLC received signals in real time, it immediately triggers a probe signal injection into the power line channel upon detecting communication quality deterioration. This enables online channel transfer function identification, dynamically acquiring and updating the frequency response characteristics of the power line channel, and reconstructing the feedforward compensation filter coefficients accordingly. In this way, the system can accurately respond to rapid channel changes caused by power grid disturbances, effectively overcome channel notch points and dynamic fading, and avoid the performance degradation or even negative impacts caused by parameter mismatch in traditional static compensation models. This allows the feedforward compensator to remain synchronized with the channel conditions at all times, ensuring the real-time performance and effectiveness of compensation, thereby fundamentally improving the accuracy of compensation. Attached Figure Description

[0009] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0010] Figure 1 A flowchart of a PLC feedforward compensation control method considering power grid disturbances according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the data flow of a PLC feedforward compensation control method considering power grid disturbances according to an embodiment of the present invention; Figure 3 This is a block diagram of a PLC feedforward compensation control system that takes into account power grid disturbances according to an embodiment of the present invention. Detailed Implementation

[0011] To enable those skilled in the art to better understand the technical solutions of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the described embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0012] Unless otherwise specifically stated, the technical or scientific terms used in the embodiments of this invention should be understood in their ordinary meaning as understood by one of ordinary skill in the art to which this invention pertains. The terms "comprising" or "including," as used in the embodiments of this invention, do not limit the shapes, numbers, steps, actions, operations, components, elements, and / or groups thereof mentioned, nor do they exclude the appearance or addition of one or more other different shapes, numbers, steps, actions, operations, components, elements, and / or groups thereof, or the inclusion of these.

[0013] Unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps described in these embodiments do not limit the scope of the invention. It should also be understood that, for ease of description, the dimensions of the various parts shown in the drawings are not drawn to actual scale, and techniques, methods, and apparatus known to those skilled in the art may not be discussed in detail; however, where appropriate, the illustrated techniques, methods, and apparatus should be considered part of the specification. In all the examples shown and discussed herein, any other specific example may have different values. It should be noted that similar symbols and letters in the following figures denote similar items; therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0014] In the description of the embodiments of the present invention, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In the embodiments of the present invention, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in a suitable manner in any one or more embodiments or examples. Furthermore, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in the embodiments of the present invention, as well as the features of different embodiments or examples.

[0015] Hereinafter, exemplary embodiments according to the present invention will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of the present invention, and not all embodiments of the present invention. It should be understood that the present invention is not limited to the exemplary embodiments described herein.

[0016] In the technical solution of this invention, a PLC feedforward compensation control method that takes into account power grid disturbances is proposed. Figure 1 This is a flowchart of a PLC feedforward compensation control method that takes into account power grid disturbances, according to an embodiment of the present invention. Figure 2 This is a system architecture diagram of a PLC feedforward compensation control method considering power grid disturbances according to an embodiment of the present invention. Figure 1 and Figure 2 As shown, the PLC feedforward compensation control method considering power grid disturbances according to an embodiment of the present invention includes the following steps: S1, acquiring the PLC received signal; S2, performing real-time communication quality monitoring on the PLC received signal to obtain a disturbance trigger flag; S3, in response to the disturbance trigger flag being true, injecting a probe transmission signal from the transmitting end into the power line channel, and receiving a probe reception signal from the power line channel; S4, performing online channel transfer function identification on the probe template signal and the probe reception signal to obtain an updated channel frequency response; S5, dynamically reconstructing the feedforward compensation parameters based on the updated channel frequency response to obtain new feedforward filter coefficients; S6, inputting the original signal to be transmitted into the feedforward compensation filter to obtain a compensated transmission signal, wherein the feedforward compensation filter has new feedforward filter coefficients.

[0017] Specifically, S1 involves acquiring the PLC received signal. The PLC received signal refers to the digital representation of the physical electrical signal received by the data transmitter after transmission through the power line channel. It should be understood that when a PLC (Power Line Communication) system is operating, it needs to continuously monitor and receive data streams from the power line channel. These signals carry information from the transmitter, but are also contaminated by the inherent complex noise, frequency-selective fading, and various power grid disturbances of the power line channel. In order to assess the channel condition in real time, effectively offset channel distortion, and ultimately recover the original data, it is essential to accurately capture these original received signals carrying the information.

[0018] In practice, a PLC physical layer transceiver (or modem) connected to the power line can be used to sense analog electrical signals propagating on the power line. These analog signals undergo necessary conditioning circuitry, such as filtering and amplification, before being converted into digital form by a high-speed analog-to-digital converter (ADC). The digitized received signal stream is captured by the system in a continuous or quasi-continuous manner and stored in memory or a buffer for access by subsequent real-time processing modules.

[0019] Specifically, S2 involves real-time monitoring of the communication quality of the PLC received signal to obtain a disturbance trigger flag. The inherent complexity, time-varying nature, and noise interference of power line channels cause their channel characteristics to constantly change. If the system cannot perceive these changes in channel state in real time and continues to use a fixed compensation model, it will be unable to effectively counteract channel distortion and may even produce negative effects, leading to communication interruptions or a sharp decline in performance. Therefore, by monitoring communication quality in real time, the system can utilize the communication system's own key performance indicators (KPIs) to determine whether a severe disturbance has occurred in the channel. This enables "problem-driven" on-demand channel identification, avoiding the ineffective consumption of system resources when the channel is stable and ensuring timely intervention when the channel deteriorates to restore long-term high-reliability communication.

[0020] In practice, the first step is to demodulate the PLC-received signal and estimate its noise power spectrum to obtain the noise power. During this process, the system continuously inputs the PLC-received signal into the demodulator, restoring it from its modulated form to the baseband signal. Simultaneously, the noise components in the signal are analyzed and estimated. Noise power spectrum estimation aims to accurately quantify the noise intensity at different frequencies, which is crucial for subsequent signal-to-noise ratio calculations.

[0021] Next, communication quality indicators (SNR) are quantified and calculated based on noise power, signal power, and decoder output data to obtain estimated signal-to-noise ratio (SNR) and estimated bit error rate (BER). After obtaining accurate noise power, combined with the signal power extracted from the demodulation process, the system can calculate the estimated SNR of the channel in real time. Simultaneously, by checking the difference between the decoder output data and the original transmitted data (usually obtained through some reference or verification mechanism), the BER can be calculated. These indicators directly reflect the performance status of the current communication link. The estimated SNR is an important indicator for measuring the ratio of signal strength to noise interference, while the estimated BER directly reflects the accuracy of data transmission.

[0022] Furthermore, the estimated signal-to-noise ratio (SNR) and estimated bit error rate (BER) are fused using multi-dimensional KPIs and a disturbance trigger decision is made to obtain a disturbance trigger flag. During this process, the system comprehensively analyzes and integrates multiple key performance indicators, such as the estimated SNR and BER, calculated in real time. For example, the system compares these KPIs with preset thresholds or monitors their trends over time. Once these KPIs are found to deteriorate and fall below preset performance thresholds—for example, a sharp drop in SNR or a significant increase in BER—it indicates that the channel may be affected by power grid disturbances, requiring immediate countermeasures. When these conditions are met, the system generates a disturbance trigger flag and sets it to the "true" state.

[0023] Taking the scheme of this invention as an example, the system continuously monitors the estimated signal-to-noise ratio (SNR) and estimated bit error rate (BER) every 50ms. During normal communication, if the estimated SNR is higher than 15dB and the estimated BER is lower than 10^-5, the disturbance trigger flag remains "false". However, once the estimated SNR is lower than 10dB for several consecutive monitoring periods, or the estimated BER is consistently higher than 10^-3, the system immediately sets the disturbance trigger flag to "true" to initiate the subsequent channel identification and compensation parameter reconstruction process. This mechanism ensures that the system can transmit data with maximum efficiency when the channel is stable, and only sacrifices instantaneous bandwidth to accurately obtain the channel model when the channel truly deteriorates, thereby achieving long-term high-reliability communication and providing precise instructions for subsequent detection and compensation parameter reconstruction, realizing fine-grained resource allocation.

[0024] Specifically, in step S3, in response to the disturbance trigger flag being true, a probe transmission signal is injected from the transmitting end into the power line channel, and a probe reception signal is received from the power line channel. It should be understood that when communication quality monitoring results indicate that the channel has been severely disturbed and the traditional fixed compensation model may fail, the system needs to immediately suspend or reduce normal service data transmission and actively acquire the accurate characteristics of the current channel. This detection strategy overcomes the limitations of traditional fixed detection methods. It ensures that the system can transmit data with maximum efficiency when the channel is stable. Only when the channel truly deteriorates and the key performance indicators (KPIs) fall below a preset threshold is an accurate channel model obtained by sacrificing instantaneous bandwidth, thereby restoring and ensuring long-term high-reliability communication, greatly improving the system's robustness and efficiency in complex power grid environments.

[0025] In practice, firstly, in response to the disturbance trigger flag being true, a probe signal template is generated based on the probe parameters. This means that the preceding real-time communication quality monitoring module has determined that key indicators such as the signal-to-noise ratio and bit error rate of the current PLC link have significantly deteriorated, and has set the disturbance trigger flag to true. This condition is a prerequisite for starting the probe procedure. At this point, the system will generate an ideal probe signal template in the digital domain according to the preset probe parameters (e.g., the bandwidth, duration, power level of the probe signal, and whether a pseudo-random sequence, a swept-frequency signal, or a specific OFDM training sequence is used). This template is a known digital sequence with good autocorrelation and cross-correlation characteristics, which is crucial for subsequent channel transfer function identification.

[0026] Next, the probe signal template is passed through a digital-to-analog converter (DAC) and a power amplifier to obtain the probe transmission signal, which is then injected into the power line channel from the transmitting end. In this process, the generated digital probe signal template is first fed into the DAC for conversion, transforming it from a discrete digital form into a continuous analog electrical signal. Subsequently, this analog signal is amplified by a power amplifier to ensure sufficient signal strength after injection into the power line channel, overcoming the inherent attenuation and noise interference of the channel, and effectively propagating to the receiving end. Finally, this power-amplified analog signal is injected into the power line channel from the transmitting end through a dedicated coupling device.

[0027] Then, a probe signal is received from the power line channel. During this process, while the probe signal is injected into the channel, the PLC device at the receiving end is in a listening state, capturing and continuously acquiring the signal transmitted from the power line channel. This captured signal is the probe signal, which is the actual version of the known probe signal injected at the transmitting end after transmission, attenuation, distortion, and superimposed channel noise and interference through the power line channel. This probe signal is then sent to the analog-to-digital converter on the receiving side for digital processing, for use by the subsequent online channel transfer function identification module.

[0028] Taking the scheme of this invention as an example, when the communication quality monitoring detects that the estimated signal-to-noise ratio is lower than a certain preset threshold (e.g., 5dB) for several consecutive frames, the disturbance trigger flag will be set to true. At this time, the transmitting end will immediately suspend service data transmission and generate a wideband training sequence containing multiple OFDM symbols as a probe signal template. This sequence is converted into an analog probe transmission signal by a DAC and a power amplifier and injected into the power line channel at a preset power (e.g., 20dBm). The receiving end will perform high-precision time synchronization acquisition at this moment, receive and digitize this probe reception signal from the channel, providing accurate input data for subsequent online channel transfer function identification, ensuring timely updates of the channel model, and thus restoring and optimizing communication performance.

[0029] Specifically, in step S4, the channel transfer function (CTF) of the probe template signal and the probe received signal is identified online to obtain the updated channel frequency response. It should be understood that online CTF identification is a core step in power line communication (PLC) feedforward compensation control that takes into account grid disturbances. Traditional identification methods employ a channel estimation strategy with imperceptible reliability, namely the classic zero-forcing complex division. The fundamental problem with this strategy is that it assigns equal confidence to the estimation results for all frequency points. However, a real PLC channel is a frequency-selective fading channel. Multipath effects inevitably lead to channel notch points with extremely low signal energy at certain specific locations in the spectrum. At these notch points, the energy of the received signal is completely dominated by noise, resulting in an extremely low signal-to-noise ratio. If zero-forcing estimation is still performed at this point, the noise is actually amplified significantly, resulting in a huge and meaningless erroneous spike at the corresponding frequency point of the estimated channel frequency response. Therefore, this mechanism ignores a deep physical correlation: the direct and strong positive correlation between the received signal energy at a specific frequency and the reliability of the channel estimate at that frequency. While a simple regularization factor can avoid a zero denominator in the calculation, it fails to proactively utilize this energy-reliability relationship to intelligently correct unreliable estimates already contaminated by noise due to low signal-to-noise ratios. The resulting channel frequency response model contains a large amount of distorted data, severely misleading subsequent compensation filter design and significantly reducing its compensation effect, or even producing negative consequences.

[0030] To address the aforementioned technical deficiencies, this invention proposes a channel frequency response reconstruction method based on subcarrier reliability assessment and weighted interpolation. This method actively identifies and quantifies the reliability of each frequency point estimate, and uses information from high-reliability frequency points to intelligently repair and reconstruct the channel response of low-reliability frequency points.

[0031] In practice, firstly, a Fast Fourier Transform (FFT) is performed on the probe template signal and the probe-received signal to obtain their frequency domain representations. Converting the time-domain probe signal to the frequency domain greatly simplifies the mathematical model for channel estimation, allowing the channel transfer function to be directly calculated using the frequency ratio of the received signal to the transmitted signal. This effectively identifies the attenuation and phase shift characteristics of the channel at different frequency components, laying the foundation for subsequent refined channel correction. During this process, the time-domain probe template signal and the probe-received signal are input into the Fast Fourier Transform (FFT) module. FFT, a fast algorithm for calculating the Discrete Fourier Transform (DFT), can convert N time-domain sampling points into N frequency-domain sampling points. For each signal, the FFT algorithm performs complex number operations on these time-domain samples in parallel or serially, decomposing them into a superposition of sine and cosine components at different frequencies (i.e., subcarriers). Each frequency-domain output value is a complex number containing the amplitude and phase information of that frequency component. This process allows the original time-domain signal to be fully and efficiently represented on the frequency axis.

[0032] Next, preliminary channel estimation and subcarrier credibility quantification are performed on the frequency domain representations of the probe template signal, the frequency domain representations of the probe received signal, and the noise power spectral density to obtain the original channel frequency response and subcarrier credibility weight vector. It should be understood that conventional zero-forcing channel estimation methods are unreliable at frequencies with poor signal-to-noise ratio (SNR). Therefore, before formally using any estimation results, a mechanism is established to distinguish the quality of the estimates. Specifically, a raw, unprocessed channel frequency response containing noise contamination is first obtained through zero-forcing division. Then, the SNR on each subcarrier is calculated, and this SNR is converted into a credibility weight value between 0 and 1 using a nonlinear Sigmoid mapping function. In this way, the abstract concept of credibility can be precisely mathematically quantified through the key physical quantity of SNR, successfully separating high-quality estimation data from noise-dominated poor-quality data in the spectral dimension. This provides precise guidance for subsequent targeted data repair, realizing a shift from passive protection to active diagnosis.

[0033] Furthermore, based on the subcarrier confidence weight vector, the original channel frequency response is subjected to channel notch point identification and interpolation repair to obtain a repaired channel frequency response. That is, a smart replacement method is used to ensure the integrity and accuracy of the channel model. Specifically, all frequency points are traversed. When the confidence weight of a frequency point is lower than a preset repair threshold, the point is determined to be a channel notch point, and its original estimated value is considered contaminated data and discarded. At this time, the system automatically finds the nearest high-confidence neighbor frequency points on both sides of the notch point, and uses the channel response values ​​of these two high-confidence neighbors to recalculate and fill in the channel response of the current notch point using a linear interpolation method. For frequency points with confidence values ​​higher than the threshold, their original estimated values ​​are directly inherited; this process is expressed by the formula:

[0034]

[0035] in, The channel frequency response after repair; and Notch points High-confidence neighbor frequency points on the left and right sides and The original channel frequency response at the location; A confidence threshold is set to determine whether repair is necessary. This step reconstructs corrupted data regions using data verified as healthy, a smart repair strategy that combines data-driven approaches with prior physical knowledge. This allows for the precise removal and repair of severely erroneous data caused by noise amplification, resulting in a repaired channel response free from the most severe estimation errors. This leads to a more accurate approximation of the actual channel conditions and significantly improves the fidelity of the channel model.

[0036] Subsequently, the repaired channel frequency response is subjected to confidence-weighted smoothing to obtain the updated channel frequency response. It should be understood that after interpolation repair, residual random noise may still exist in the channel frequency response, and unnatural transitions may exist at the junction of the original data and the interpolated data. Therefore, in the technical solution of this invention, the repaired channel frequency response... A moving average smoothing process is applied. Unlike traditional moving averages, this averaging process is weighted, meaning that within a smoothing window, the contribution of each frequency point to the final value of the center frequency depends on its own credibility weight. This implies that applying the credibility weight W(f) twice to the smoothing process gives greater influence to neighboring frequencies with more reliable original data when calculating the final value, while reducing the influence of neighbors with lower credibility (even after repair). This credibility-weighted smoothing mechanism effectively suppresses random noise while preserving the true details of the channel to the greatest extent possible. This results in a high-quality channel frequency response model that is accurate, smooth, and conforms to physical laws, providing a near-ideal input for subsequent feedforward compensation.

[0037] In summary, this method, by introducing and utilizing subcarrier reliability as a core quantitative indicator twice, can accurately identify and repair noise amplification pollution caused by deep fading of the power grid channel. This results in a channel transfer function model that is far more accurate, robust, and smoother than traditional methods in a dynamically changing and noisy PLC environment. Ultimately, it provides a high-quality, high-fidelity channel state description for the PLC feedforward compensation control system, enabling subsequent compensation filters to more accurately counteract channel distortion. This significantly improves the data transmission reliability, stability, and communication rate of power line communication in complex power grid environments.

[0038] Specifically, in step S5, the feedforward compensation parameters are dynamically reconstructed based on the updated channel frequency response to obtain new feedforward filter coefficients. It should be understood that although the previous step has obtained an updated channel frequency response reflecting the current power grid state through intelligent online identification, this frequency response is merely a mathematical model describing the channel distortion characteristics and cannot be directly used for signal processing. To counteract the attenuation and phase distortion of the power line channel, the transmitter must construct a filter with inverse channel characteristics. However, since the channel contains not only attenuation but also noise, simple mathematical inversion (i.e., directly calculating the reciprocal of the channel frequency response) often leads to extremely high gain at deep fading points (notch points), thereby infinitely amplifying background noise and degrading communication quality. Therefore, in the technical solution of this invention, through a dynamic reconstruction mechanism, the optimal balance point between counteracting channel distortion and suppressing noise amplification is found, generating a set of filter coefficients that can both balance the channel and maintain numerical stability to drive the feedforward compensation filter.

[0039] In practice, firstly, the updated channel frequency response is regularized based on the estimated signal-to-noise ratio (SNR) to obtain a regularized compensated frequency response. During this process, a regularization factor (usually related to the reciprocal of the SNR) is introduced. When the channel gain at a certain frequency is extremely low (deep fading) resulting in a poor SNR, the regularization mechanism limits the compensation gain at that frequency to prevent excessive noise amplification. Conversely, at frequencies with good channel conditions, near-ideal inverse channel characteristics are preserved. This process constructs an ideal compensation curve in the frequency domain that both equalizes the signal and suppresses noise.

[0040] Furthermore, based on the regularized compensation frequency response and filter length, the new feedforward filter coefficients are generated. That is, the frequency domain compensation characteristics obtained in the previous steps through online channel transfer function identification and regularization are transformed into a finite-length time-domain digital filter that can be deployed and applied in a real-time system. Dynamically changing power line channels require the feedforward compensation filter to be flexibly adjusted according to the latest channel state. Therefore, after each power grid disturbance is detected and channel identification and regularization are completed, the system needs to efficiently calculate a new set of filter coefficients based on the latest regularized compensation frequency response and the predetermined filter length parameters, thereby ensuring the reliability, stability, and communication rate of data transmission.

[0041] In this process, firstly, an inverse fast Fourier transform (IFT) is performed on the regularized compensated frequency response to obtain an infinitely long time-domain impulse response. This step aims to transform the frequency-domain characteristics of the already regularized compensated filter into a time-domain representation, thus obtaining a theoretically infinitely long impulse response. The IFT is an efficient algorithm used to convert a set of discrete frequency-domain samples into a set of discrete time-domain samples. For example, if the frequency response has N frequency points, an N-point IFT is performed to obtain N time-domain samples, which constitute the discrete form of the infinitely long time-domain impulse response.

[0042] Next, the infinite-length time-domain impulse response is truncated to obtain the windowed impulse response center. This step aims to extract the most relevant and energy-concentrated portion from the theoretically infinite-length time-domain impulse response and optimize its time-domain characteristics through windowing techniques, preparing for the final generation of finite-length filter coefficients. Specifically, after obtaining the infinite-length time-domain impulse response, the center portion of the time-domain impulse response to be extracted is determined. Considering that practical FIR filters are causal or quasi-causal, their most significant energy is usually concentrated around a certain time point. To avoid frequency response discontinuities and ripple effects that may result from truncation, a window function (e.g., rectangular window, Hamming window, Hanning window, etc.) is typically applied. This window function is multiplied by the infinite-length time-domain impulse response to smoothly attenuate the values ​​at both ends of the impulse response, reducing the side effects of truncation; finally, the system identifies and retains the impulse response center portion with the maximum energy or a specified interval after windowing, obtaining the windowed impulse response center. This process implies selecting an appropriate time delay and center point to capture the main impulse response energy.

[0043] Furthermore, points of length L are extracted from the center of the windowed impulse response as new feedforward filter coefficients. In this process, based on the system's preset filter length (e.g., L points), L consecutive samples are precisely selected from the center of the windowed impulse response as new feedforward filter coefficients, which are then loaded into the feedforward compensation filter. These coefficients define the convolution operation of the digital filter to compensate for the original signal to be transmitted. When selecting these points, it is typically ensured that the central energy region is completely covered, thereby maximizing the compensation effect.

[0044] Specifically, in step S6, the original signal to be transmitted is input into a feedforward compensation filter to obtain a compensated transmitted signal, wherein the feedforward compensation filter has new feedforward filter coefficients. That is, before the original signal is injected into the power line channel, it is actively preprocessed to compensate for the inherent frequency-selective fading, multipath effects, and channel characteristic changes caused by power grid disturbances. Through pre-compensation, the overall frequency response of the transmission link can be effectively leveled, minimizing signal distortion received at the receiver, thereby improving demodulation performance and reducing the bit error rate.

[0045] In this context, the original signal to be transmitted refers to the raw baseband data signal in a power line communication system that has not yet undergone any channel compensation processing. It represents the valid information to be transmitted through the power line channel and is the source of the communication task. This signal typically exists in the form of a digital sequence or its analog-to-digital conversion, representing the pure form of the final information carrier. The feedforward compensation filter is a digital signal processing device or algorithm module whose core function is to adjust the frequency response of the original signal to be transmitted in real time to pre-compensate for the distortion introduced by the power line channel. This filter is dynamically generated based on the real-time changing characteristics of the power line channel, and its characteristics are defined by new feedforward filter coefficients.

[0046] In practice, the first step is the coefficient loading sub-step, where the system updates the new feedforward filter coefficients calculated in the previous step into the register of the feedforward compensation filter. This operation ensures that the filter has the ability to compensate for specific power grid disturbances at the current moment, and the length of the filter coefficient vector is consistent with the number of taps set by the system. The second step is the real-time convolution sub-step, where when the original signal to be transmitted enters the filter in the form of a discrete-time sequence, the feedforward compensation filter performs a discrete-time convolution operation on the input signal and the filter coefficients. Specifically, in order to calculate the compensated transmitted signal sample output at the current moment, the filter multiplies the current and past series of original signal samples to be transmitted one by one with the new feedforward filter coefficients at the corresponding positions. That is, the latest signal sample is multiplied by the first coefficient, the signal sample from the previous moment is multiplied by the second coefficient, and so on, until the entire filter length is covered; finally, the results of all these multiplications are summed up, and the sum is the output value at the current moment. Through this point-by-point multiplication and addition operation, the filter applies the spectral shaping characteristics contained in the new feedforward filter coefficients to the original signal to be transmitted, completing the convolution from the time domain to the multiplication in the frequency domain, thereby generating a compensated transmission signal with predistortion characteristics.

[0047] In summary, the PLC feedforward compensation control method considering power grid disturbances according to embodiments of the present invention is explained. It continuously monitors the communication quality of the PLC received signals in real time. Once communication quality deterioration is detected, a probe signal is immediately injected into the power line channel to perform online channel transfer function identification, thereby dynamically acquiring and updating the frequency response characteristics of the power line channel, and reconstructing the feedforward compensation filter coefficients accordingly. In this way, the system can accurately respond to rapid channel changes caused by power grid disturbances, effectively overcome channel notch points and dynamic fading, and avoid the performance degradation or even negative impacts caused by parameter mismatch in traditional static compensation models. This allows the feedforward compensator to remain synchronized with the channel conditions at all times, ensuring the real-time performance and effectiveness of compensation, thereby fundamentally improving the accuracy of compensation.

[0048] Furthermore, a PLC feedforward compensation control system that takes into account power grid disturbances is also provided.

[0049] Figure 3 This is a block diagram of a PLC feedforward compensation control system that takes into account power grid disturbances, according to an embodiment of the present invention. Figure 3 As shown, a PLC feedforward compensation control system 300 considering power grid disturbances according to an embodiment of the present invention includes: a signal acquisition module 310 for acquiring PLC received signals; a real-time communication quality monitoring module 320 for real-time monitoring of the communication quality of the PLC received signals to obtain a disturbance trigger flag; a signal receiving module 330 for injecting a probe transmission signal from the transmitting end into the power line channel in response to the disturbance trigger flag being true, and receiving a probe reception signal from the power line channel; an online channel transfer function identification module 340 for performing online channel transfer function identification on the probe template signal and the probe reception signal to obtain an updated channel frequency response; a dynamic reconstruction module 350 for dynamically reconstructing the feedforward compensation parameters based on the updated channel frequency response to obtain new feedforward filter coefficients; and a feedforward compensation filtering module 360 ​​for inputting the original signal to be transmitted into the feedforward compensation filter to obtain a compensated transmission signal, wherein the feedforward compensation filter has new feedforward filter coefficients.

[0050] Furthermore, the real-time communication quality monitoring module 320 is specifically used for: demodulating the signal received by the PLC and estimating the noise power spectrum to obtain the noise power; performing quantitative calculations of communication quality indicators on the noise power, signal power, and decoder output data to obtain the estimated signal-to-noise ratio and the estimated bit error rate; and performing multi-dimensional KPI fusion and disturbance triggering decision on the estimated signal-to-noise ratio and the estimated bit error rate to obtain the disturbance triggering flag.

[0051] Furthermore, the signal receiving module 330 is specifically used to: generate a detection signal template based on the detection parameters in response to the disturbance trigger flag being true; pass the detection signal template through a digital-to-analog converter and a power amplifier to obtain a detection transmission signal, and inject it from the transmitting end into the power line channel.

[0052] As described above, the PLC feedforward compensation control system 300 considering grid disturbances according to embodiments of the present invention can be implemented in various wireless terminals, such as servers with PLC feedforward compensation control algorithms considering grid disturbances. In one possible implementation, the PLC feedforward compensation control system 300 considering grid disturbances according to embodiments of the present invention can be integrated into the wireless terminal as a software module and / or a hardware module. For example, the PLC feedforward compensation control system 300 considering grid disturbances can be a software module in the operating system of the wireless terminal, or it can be an application developed for the wireless terminal; of course, the PLC feedforward compensation control system 300 considering grid disturbances can also be one of many hardware modules of the wireless terminal.

[0053] Alternatively, in another example, the PLC feedforward compensation control system 300 that takes into account grid disturbances and the wireless terminal can also be separate devices, and the PLC feedforward compensation control system 300 that takes into account grid disturbances can be connected to the wireless terminal via wired and / or wireless networks, and transmit interactive information in accordance with an agreed data format.

[0054] It is understood that the above embodiments are merely exemplary implementations used to illustrate the principles of the present invention, and the present invention is not limited thereto. For those skilled in the art, various modifications and improvements can be made without departing from the spirit and essence of the present invention, and these modifications and improvements are also considered to be within the scope of protection of the present invention.

Claims

1. A PLC feedforward compensation control method considering power grid disturbances, characterized in that, include: Acquire the signal received by the PLC; Real-time monitoring of the communication quality of the PLC received signals is performed to obtain disturbance trigger flags; In response to the disturbance trigger flag being true, a probe transmission signal is injected from the transmitter into the power line channel, and a probe reception signal is received from the power line channel; Online channel transfer function identification is performed on the probe template signal and the probe received signal to obtain the updated channel frequency response; The feedforward compensation parameters are dynamically reconstructed based on the updated channel frequency response to obtain new feedforward filter coefficients; The original signal to be transmitted is input into a feedforward compensation filter to obtain a compensated transmitted signal, wherein the feedforward compensation filter has new feedforward filter coefficients.

2. The PLC feedforward compensation control method considering power grid disturbances according to claim 1, characterized in that, Real-time monitoring of communication quality of PLC received signals to obtain disturbance trigger flags, including: The noise power is obtained by demodulating the signal received by the PLC and estimating the noise power spectrum. The noise power, signal power, and decoder output data are used to perform quantitative calculations of communication quality indicators to obtain the estimated signal-to-noise ratio and the estimated bit error rate. The estimated signal-to-noise ratio and estimated bit error rate are fused with multi-dimensional KPIs and perturbation trigger decision to obtain the perturbation trigger flag.

3. The PLC feedforward compensation control method considering power grid disturbances according to claim 1, characterized in that, In response to a disturbance trigger flag being true, a probe transmission signal is injected from the transmitter into the power line channel, and a probe reception signal is received from the power line channel, including: In response to the disturbance trigger flag being true, a detection signal template is generated based on the detection parameters; The probe signal template is passed through a digital-to-analog converter and a power amplifier to obtain the probe transmission signal, which is then injected from the transmitting end into the power line channel.

4. The PLC feedforward compensation control method considering power grid disturbances according to claim 1, characterized in that, Online channel transfer function identification is performed on the probe template signal and the probe received signal to obtain the updated channel frequency response, including: Fast Fourier transform is performed on the probe template signal and the probe received signal to obtain the frequency domain representation of the probe template signal and the frequency domain representation of the probe received signal; Preliminary channel estimation and subcarrier confidence quantization are performed on the frequency domain representation of the probe template signal, the frequency domain representation of the probe received signal, and the noise power spectral density to obtain the original channel frequency response and subcarrier confidence weight vector. Based on the subcarrier confidence weight vector, channel notch point identification and interpolation repair are performed on the original channel frequency response to obtain the repaired channel frequency response; The repaired channel frequency response is subjected to confidence-weighted smoothing to obtain the updated channel frequency response.

5. The PLC feedforward compensation control method considering power grid disturbances according to claim 4, characterized in that, Based on the subcarrier reliability weight vector, channel notch point identification and interpolation repair are performed on the original channel frequency response to obtain a repaired channel frequency response. This includes: performing channel notch point identification and interpolation repair on the original channel frequency response using the following formula: in, The channel frequency response after repair; and Notch points High-confidence neighbor frequency points on the left and right sides and The original channel frequency response at the location; A confidence threshold for determining whether repair is needed.

6. The PLC feedforward compensation control method considering power grid disturbances according to claim 1, characterized in that, The feedforward compensation parameters are dynamically reconstructed based on the updated channel frequency response to obtain new feedforward filter coefficients, including: The updated channel frequency response is regularized based on the estimated signal-to-noise ratio to obtain the regularized compensated frequency response. The new feedforward filter coefficients are generated based on the regularized compensated frequency response and filter length.

7. The PLC feedforward compensation control method considering power grid disturbances according to claim 6, characterized in that, Based on the regularized compensated frequency response and filter length, the new feedforward filter coefficients are generated, including: The inverse fast Fourier transform is performed on the regularized compensated frequency response to obtain an infinitely long time-domain impulse response; The infinitely long time-domain impulse response is truncated to obtain the windowed impulse response center; Extract points equal to the length of the filter from the center of the windowed impulse response as new feedforward filter coefficients.

8. A PLC feedforward compensation control system that takes into account power grid disturbances, characterized in that, include: The signal acquisition module is used to acquire signals received by the PLC. The real-time communication quality monitoring module is used to monitor the communication quality of the signals received by the PLC in real time in order to obtain the disturbance trigger flag. The signal receiving module is used to inject a probe transmission signal from the transmitting end into the power line channel in response to a disturbance trigger flag being true, and to receive a probe reception signal from the power line channel. The online channel transfer function identification module is used to perform online channel transfer function identification on the probe template signal and the probe received signal to obtain the updated channel frequency response; The dynamic reconstruction module is used to dynamically reconstruct the feedforward compensation parameters based on the updated channel frequency response to obtain new feedforward filter coefficients. The feedforward compensation filter module is used to input the original signal to be transmitted into the feedforward compensation filter to obtain the compensated transmitted signal. The feedforward compensation filter has new feedforward filter coefficients.

9. The PLC feedforward compensation control system considering power grid disturbances according to claim 8, characterized in that, The real-time communication quality monitoring module is specifically used for: The noise power is obtained by demodulating the signal received by the PLC and estimating the noise power spectrum. The noise power, signal power, and decoder output data are used to perform quantitative calculations of communication quality indicators to obtain the estimated signal-to-noise ratio and the estimated bit error rate. The estimated signal-to-noise ratio and estimated bit error rate are fused with multi-dimensional KPIs and perturbation trigger decision to obtain the perturbation trigger flag.

10. The PLC feedforward compensation control system considering power grid disturbances according to claim 8, characterized in that, The signal receiving module is specifically used for: In response to the disturbance trigger flag being true, a detection signal template is generated based on the detection parameters; The probe signal template is passed through a digital-to-analog converter and a power amplifier to obtain the probe transmission signal, which is then injected from the transmitting end into the power line channel.

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