A signal integrity closed-loop optimization system based on HPLC and HRF fusion communication

Abstract

The application discloses a signal integrity closed-loop optimization system based on HPLC and HRF fusion communication, and relates to the technical field of power Internet of Things communication.The technical points of the system are as follows: the system realizes real-time monitoring of double-channel state and noise through a signal integrity sensing module, and realizes full-band self-adaptive impedance matching through a dynamic impedance matching module in turn;an intelligent noise cognition and avoidance module actively avoids interference through AI noise fingerprint identification;an isomerism resource collaborative scheduling module uniformly allocates power and modulation modes by adopting an isomerism water injection algorithm;an anti-crosstalk front-end circuit design module suppresses inter-module crosstalk on hardware;and a collaborative transmission module realizes data fragmentation and double-link collaborative transmission.The application realizes closed-loop optimization from noise identification, impedance matching, resource scheduling to hardware anti-interference, significantly improves the throughput, reliability and coverage range of the HPLC+HRF dual-mode communication system, and has good practical value in a complex power grid environment.

Description

Technical Field

[0001] This invention relates to the field of power Internet of Things (IoT) communication technology, specifically to a signal integrity closed-loop optimization system based on HPLC and HRF fusion communication. Background Technology

[0002] Power line communication (PLC) offers advantages such as no need for additional wiring and wide coverage, but it is susceptible to power grid noise interference and severe signal attenuation. High-frequency wireless communication, on the other hand, boasts high bandwidth and low latency, but suffers from weak wall penetration and limited coverage. While combining the two can achieve complementarity, in practical applications, due to significant differences in channel characteristics, signals are prone to impedance mismatch, delay jitter, and multipath interference during cross-media transmission, leading to a decline in overall communication quality.

[0003] Power communication technology has evolved from narrowband PLC to HPLC, and then to "HPLC+HRF dual-mode" technology. Dual-mode technology is a key communication method for low-voltage distribution networks, but it brings complex signal integrity issues. Electromagnetic noise generated by equipment such as frequency converters and charging piles within the power grid can damage communication units; coupling interference exists between HPLC power line signals and HRF wireless signals, affecting communication quality; three-phase four-wire power grids have a "cross-phase communication bottleneck," leading to dynamic channel imbalance, and static resource allocation strategies cause performance rigidity; deeper applications require support for minute-level data acquisition and proactive power outage reporting, posing higher challenges to communication real-time performance, reliability, and equipment energy consumption.

[0004] Therefore, the present invention aims to provide a signal integrity closed-loop optimization system based on HPLC and HRF fusion communication to solve the above problems. Summary of the Invention

[0005] The purpose of this invention is to solve the above-mentioned problems and provide a signal integrity closed-loop optimization system based on HPLC and HRF fusion communication. By deeply integrating and coordinating the control of HPLC and HRF communication methods, the system's reliability, throughput and coverage are significantly improved.

[0006] To achieve the above objectives, the technical solution of the present invention is as follows:

[0007] This invention provides a closed-loop optimization system for signal integrity based on HPLC and HRF fusion communication. The system includes a dynamic impedance matching module, an intelligent noise recognition and avoidance module, a heterogeneous resource collaborative scheduling module, an anti-crosstalk front-end circuit module, and a collaborative transmission module.

[0008] Signal integrity sensing module:

[0009] Upon power-up of the communication system, the signal integrity sensing module simultaneously initiates real-time probing of both the HPLC and HRF channels. For the HPLC channel, the module actively sends specific probe signals to evaluate the channel response; for the HRF channel, it continuously scans the intensity of the received signals to obtain dual-channel noise samples for both the HPLC and HRF signal channels. This module also continuously monitors the background noise level in the communication environment and possesses a high sensitivity to capturing sudden noise events, providing data support for subsequent dynamic adaptation.

[0010] Dynamic impedance matching module:

[0011] The system embeds low-power probe signals during communication idle periods or in data frames, and the SoC injects a wideband sweep signal into the power line. Using a directional coupler, incident and reflected wave signals are simultaneously acquired, and the complex impedance matrix of the current channel across the entire communication bandwidth is calculated in real time. .

[0012] SoC based By employing a conjugate matching algorithm or a lookup table method, the optimal matching network parameters (L / C value) are solved in real time, and the adjustable matching network is driven to dynamically adjust, thereby improving the output impedance of the module. Approaching The conjugate value of the [value]. Through this mechanism, full-band adaptive impedance matching is achieved, significantly improving power transmission efficiency while greatly suppressing signal reflection.

[0013] Intelligent noise recognition and avoidance module:

[0014] The system incorporates a lightweight noise fingerprinting engine, integrating a pre-trained deep learning model (such as a one-dimensional convolutional neural network) to perform real-time analysis of dual-channel noise samples acquired by the ADC. When the perception module captures a high-power noise segment, the engine extracts its multi-dimensional features, including time-domain envelope, spectral features, and autocorrelation characteristics, to construct the "fingerprint" vector of the noise.

[0015] The feature vector is input into an offline-trained CNN classification model. The AI ​​model identifies the type of noise, and typical output categories include: "background noise", "periodic impulse noise", "asynchronous impulse noise", "narrowband interference", etc.

[0016] Based on the identification results, corresponding decisions are made: if periodic impulse noise is identified, the SoC will accurately predict the time window of its next occurrence and instruct the HPLC modulator to suspend the transmission of key data symbols during that period, which can be compensated by blank coding or interleaving coding; if narrowband interference is identified, the resource scheduler will mark the interfered subcarrier as disabled in the OFDM subcarrier mapping table and will not allocate power or data; for HRF channels, the transmit power will be adaptively adjusted or the optimal antenna beam will be selected to avoid interference based on the interference characteristics.

[0017] Heterogeneous resource collaborative scheduling module: Heterogeneous resource scheduling (solving the attenuation problem):

[0018] A unified resource scheduler aggregates real-time signal-to-noise ratio (SNR) information from HPLC subcarriers and HRF subchannels to construct a unified heterogeneous channel state matrix. The scheduler treats all subchannels in both types of channels as a virtual resource pool. Under the constraints of total transmit power and bit error rate, it executes a "heterogeneous water-filling algorithm": treating the total system power as "water" and each subchannel as a "container," it prioritizes allocating more power to the subchannel with the highest SNR and employing higher-order modulation methods (such as 1024-QAM) until it reaches its power limit or SNR bottleneck, then switches to the next best subchannel. Through this mechanism, the total system capacity approaches the Shannon limit, achieving efficient resource utilization.

[0019] Anti-crosstalk front-end circuit design module:

[0020] At the hardware level, through co-design of the PCB and RF front-end, independent LDO power trees and segmented ground planes are configured for the digital / analog circuits of the HPLC and the HRF RF circuits, and single-point connections are achieved using ferrite beads or isolation transformers to suppress crosstalk on the power path. In terms of structural layout, physical isolation and shielding are implemented for high-radiation / sensitive components such as the HPLC coupling transformer and HRF antenna.

[0021] Notch filters targeting the other party's frequency band are inserted at the output of the HPLC transmitter amplifier and the input of the HRF receiver LNA to effectively absorb out-of-band harmonics and blocking interference. Fine-grained time-division transmission control logic is introduced into the protocol stack to avoid overlap between the high-power transmission of the HPLC and the high-sensitivity reception of the HRF in extreme cases, thus eliminating the possibility of crosstalk from a time perspective.

[0022] Cooperative transmission module for cooperative transmission (system-level protection):

[0023] For upper-layer data packets, the SoC divides them into K data slices and generates forward error correction (FEC) redundancy for each slice. Based on real-time link quality assessment (such as HPLC bit error rate mutation), the cooperative transmission protocol decision-maker can dynamically select transmission strategies: for example, sending odd-numbered data slices via HPLC (e.g., data slices 1, 3, 5... via HPLC) and even-numbered data slices via HRF (e.g., data slices 2, 4, 6... via HRF); or simultaneously sending all data slices via dual links to obtain diversity gain.

[0024] The receiving end reassembles and performs FEC decoding on data fragments transmitted from different links. Even if one link is completely interrupted, as long as the other link transmits a sufficient proportion of data fragments, the original data packets can still be successfully recovered, significantly improving system robustness.

[0025] The present invention also provides an apparatus for implementing the above system, wherein the apparatus is embedded with a SoC chip for implementing the above system, the SoC chip internally integrating an HPLC modulation and demodulation core, an HRF baseband processing core, a signal integrity sensing module and a central decision unit, and externally connected to the SoC chip are an HPLC front-end AFE, an HRF radio frequency front-end, a memory and a clock circuit.

[0026] Compared with existing technologies, the beneficial effects of this solution are:

[0027] This invention deeply integrates dynamic impedance matching, AI noise fingerprinting, unified scheduling of heterogeneous resources, and hardware anti-crosstalk design to construct a closed-loop optimization system. Utilizing a heterogeneous channel "water-filling" algorithm, it focuses energy on the optimal sub-channel, maximizing the signal-to-noise ratio and resisting path loss, even approaching channel capacity limits under adverse channel conditions. Relying on a dynamic impedance matching network, it maintains a low voltage standing wave ratio, eliminating impedance mismatch caused by power line load variations in real time and reducing signal reflection energy. Through AI noise identification, it shifts from passive suppression to active recognition and avoidance, avoiding contaminated spectrum or time slots, achieving a transformation from "anti-interference" to "interference avoidance." Through heterogeneous link collaboration, HPLC and HRF channels complement each other, creating a highly available virtual communication link with communication efficiency exceeding that of a single link. This reduces system bit error rate, increases throughput by over 30%, and enhances network robustness and coverage in complex environments. Attached Figure Description

[0028] Figure 1 This is a flowchart of the system in an embodiment of the present invention;

[0029] Figure 2 This is a flowchart of dynamic impedance matching;

[0030] Figure 3 Noise identification and avoidance decision graph;

[0031] Figure 4 Diagram of heterogeneous resource scheduling. Detailed Implementation

[0032] To enable those skilled in the art to better understand the present invention, the technical solution of the present invention will be described in further detail below with reference to the embodiments and accompanying drawings. Obviously, the described embodiments are merely some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort should fall within the scope of protection of the present invention.

[0033] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other. The present invention will now be described in detail with reference to the embodiments.

[0034] Example 1: The system includes a dynamic impedance matching module, an intelligent noise recognition and avoidance module, a heterogeneous resource collaborative scheduling module, an anti-crosstalk front-end circuit module, and a collaborative transmission module;

[0035] Signal integrity sensing module:

[0036] Upon power-up of the communication system, the signal integrity sensing module simultaneously initiates real-time probing of both the HPLC and HRF channels. For the HPLC channel, the module actively sends specific probe signals to evaluate the channel response; for the HRF channel, it continuously scans the intensity of the received signals to obtain dual-channel noise samples for both the HPLC and HRF signal channels. This module also continuously monitors the background noise level in the communication environment and possesses a high sensitivity to capturing sudden noise events, providing data support for subsequent dynamic adaptation.

[0037] Dynamic impedance matching module:

[0038] The system embeds low-power probe signals during communication idle periods or in data frames, and the SoC injects a wideband sweep signal into the power line. Using a directional coupler, incident and reflected wave signals are simultaneously acquired, and the complex impedance matrix of the current channel across the entire communication bandwidth is calculated in real time. .

[0039] SoC based By employing a conjugate matching algorithm or a lookup table method, the optimal matching network parameters (L / C value) are solved in real time, and the adjustable matching network is driven to dynamically adjust, thereby improving the output impedance of the module. Approaching The conjugate value of the [value]. Through this mechanism, full-band adaptive impedance matching is achieved, significantly improving power transmission efficiency while greatly suppressing signal reflection.

[0040] Intelligent noise recognition and avoidance module:

[0041] The system incorporates a lightweight noise fingerprinting engine, integrating a pre-trained deep learning model (such as a one-dimensional convolutional neural network) to perform real-time analysis of dual-channel noise samples acquired by the ADC. When the perception module captures a high-power noise segment, the engine extracts its multi-dimensional features, including time-domain envelope, spectral features, and autocorrelation characteristics, to construct the "fingerprint" vector of the noise.

[0042] The feature vector is input into an offline-trained CNN classification model. The AI ​​model identifies the type of noise, and typical output categories include: "background noise", "periodic impulse noise", "asynchronous impulse noise", "narrowband interference", etc.

[0043] Based on the identification results, corresponding decisions are made: if periodic impulse noise is identified, the SoC will accurately predict the time window of its next occurrence and instruct the HPLC modulator to suspend the transmission of key data symbols during that period, which can be compensated by blank coding or interleaving coding; if narrowband interference is identified, the resource scheduler will mark the interfered subcarrier as disabled in the OFDM subcarrier mapping table and will not allocate power or data; for HRF channels, the transmit power will be adaptively adjusted or the optimal antenna beam will be selected to avoid interference based on the interference characteristics.

[0044] Heterogeneous resource collaborative scheduling module: Heterogeneous resource scheduling (solving the attenuation problem):

[0045] A unified resource scheduler aggregates real-time signal-to-noise ratio (SNR) information from HPLC subcarriers and HRF subchannels to construct a unified heterogeneous channel state matrix. The scheduler treats all subchannels in both types of channels as a virtual resource pool. Under the constraints of total transmit power and bit error rate, it executes a "heterogeneous water-filling algorithm": treating the total system power as "water" and each subchannel as a "container," it prioritizes allocating more power to the subchannel with the highest SNR and employing higher-order modulation methods (such as 1024-QAM) until it reaches its power limit or SNR bottleneck, then switches to the next best subchannel. Through this mechanism, the total system capacity approaches the Shannon limit, achieving efficient resource utilization.

[0046] Anti-crosstalk front-end circuit design module:

[0047] At the hardware level, through co-design of the PCB and RF front-end, independent LDO power trees and segmented ground planes are configured for the digital / analog circuits of the HPLC and the HRF RF circuits, and single-point connections are achieved using ferrite beads or isolation transformers to suppress crosstalk on the power path. In terms of structural layout, physical isolation and shielding are implemented for high-radiation / sensitive components such as the HPLC coupling transformer and HRF antenna.

[0048] Notch filters targeting the other party's frequency band are inserted at the output of the HPLC transmitter amplifier and the input of the HRF receiver LNA to effectively absorb out-of-band harmonics and blocking interference. Fine-grained time-division transmission control logic is introduced into the protocol stack to avoid overlap between the high-power transmission of the HPLC and the high-sensitivity reception of the HRF in extreme cases, thus eliminating the possibility of crosstalk from a time perspective.

[0049] Cooperative transmission module for cooperative transmission (system-level protection):

[0050] For upper-layer data packets, the SoC divides them into K data slices and generates forward error correction (FEC) redundancy for each slice. Based on real-time link quality assessment (such as HPLC bit error rate mutation), the cooperative transmission protocol decision-maker can dynamically select transmission strategies: for example, sending odd-numbered data slices via HPLC (e.g., data slices 1, 3, 5... via HPLC) and even-numbered data slices via HRF (e.g., data slices 2, 4, 6... via HRF); or simultaneously sending all data slices via dual links to obtain diversity gain.

[0051] The receiving end reassembles and performs FEC decoding on data fragments transmitted from different links. Even if one link is completely interrupted, as long as the other link transmits a sufficient proportion of data fragments, the original data packets can still be successfully recovered, significantly improving system robustness.

[0052] Example 2: System Hardware Structure

[0053] The system implements its functions through a highly integrated heterogeneous communication system-on-a-chip (SoC). This SoC integrates several key functional modules, including:

[0054] 1) The HPLC modulation and demodulation core is responsible for realizing the signal modulation and demodulation functions in high-speed power line carrier communication;

[0055] 2) HRF baseband processing core, used to complete the processing and protocol control of high-frequency wireless communication baseband signals;

[0056] 3) The signal integrity sensing module can monitor the channel status in real time and provide feedback on signal quality parameters;

[0057] 4) The central decision-making unit runs AI models for intelligent decision-making and dynamic resource scheduling, and is also responsible for the coordination and management of multiple tasks.

[0058] Outside the SoC, the system connects to several important components:

[0059] The HPLC front-end analog front-end (AFE) module includes the adjustable impedance matching network unique to this invention. This network employs a switched capacitor array and an adjustable inductor structure based on GaN or SOI technology, enabling wide-range adaptive impedance adjustment, which is controlled in real time by the SoC via a high-precision DAC.

[0060] The HRF front-end integrates a low-noise amplifier, a power amplifier, and a high-performance filter, which are responsible for signal amplification, transmission, and filtering, respectively, to ensure the stability and efficiency of the wireless communication link.

[0061] In addition, the system is equipped with a shared high-speed memory and a highly stable clock circuit, providing data caching and a precise timing reference for the entire communication system.

[0062] Example 3: Detailed Implementation

[0063] The following description uses an example of a dual-mode communication module for smart meters.

[0064] Hardware platform: Employs a heterogeneous SoC integrating an HPLC baseband, an HRF baseband, and a powerful DSP core. External expansion includes a high-speed ADC / DAC, an adjustable matching network chip, and an RF front-end module containing a notch filter.

[0065] Software process:

[0066] Power-on initialization (the purpose of power-on initialization is to ensure that all functions are ready before the system enters normal working state, thereby improving system reliability and user experience): complete hardware self-test and load AI noise recognition model.

[0067] Continuous monitoring loop:

[0068] a. Initiate frequency sweep during the quiet period to perform dynamic impedance matching.

[0069] b. The dual-channel ADC continuously samples the background signal, and the AI ​​engine performs noise fingerprint recognition and classification.

[0070] c. The scheduler dynamically generates resource allocation strategies and transmission plans based on the updated CSI and interference map.

[0071] Data transmission ring:

[0072] a. Data packets to be sent enter the scheduler for fragmentation and encoding.

[0073] b. Based on the strategy, the fragmented data is allocated to the corresponding physical resources of HPLC or HRF for modulation and transmission.

[0074] c. The receiving end performs synchronization, equalization, soft information merging, and decoding on the data from the two channels.

[0075] Real-time adjustment: Based on the ACK / NACK and channel estimation feedback from the receiver, the matching network parameters, avoidance strategies, and scheduling algorithm parameters are adjusted in real time.

[0076] The present invention constructs a highly adaptive and robust communication system through the closed-loop control of the above-mentioned hardware and software collaboration. It can effectively cope with complex and ever-changing field environments, providing unprecedented signal integrity protection for HPLC+HRF fusion communication systems, and has extremely high industrial application value.

[0077] The above specific embodiments are merely explanations of the present invention and are not intended to limit the present invention. After reading this specification, those skilled in the art can make modifications to these embodiments without contributing any inventive step, but as long as they are within the scope of the claims of the present invention, they are protected by patent law.

Claims

1. A closed-loop optimization system for signal integrity based on HPLC and HRF fusion communication, characterized in that: The system includes a signal integrity sensing module, a dynamic impedance matching module, an intelligent noise recognition and avoidance module, a heterogeneous resource collaborative scheduling module, an anti-crosstalk front-end circuit design module, and a collaborative transmission module. After the communication system is powered on and initialized, the signal integrity sensing module starts to detect the HPLC signal channel and HRF signal channel, continuously monitors background noise, captures sudden noise, obtains dual-channel noise samples, extracts feature vectors based on the noise power in the dual-channel noise samples, and transmits the extracted feature vectors to the intelligent noise recognition and avoidance module. The dynamic impedance matching module embeds a low-power probe signal in the communication idle time slot or in the data frame, and inputs a wideband sweep signal to the power line; it synchronously acquires the incident and reflected wave signals through a directional coupler, and calculates the complex impedance matrix of the current channel within the communication band in real time. ;according to Using a conjugate matching algorithm or lookup table method, the optimal matching network parameters are calculated in real time, and the adjustable network is driven to adjust the module's output impedance. Dynamic approximation The conjugate of the two elements enables full-band adaptive impedance matching, maximizing power transmission. The intelligent noise recognition and avoidance module is equipped with a lightweight noise fingerprint recognition device. The deep learning model in the lightweight noise fingerprint recognition device analyzes dual-channel noise samples in real time, and inputs the feature vectors collected by the dynamic impedance matching module into the deep learning model to classify the dual-channel noise samples and output the classification results. The heterogeneous resource collaborative scheduling module obtains each subcarrier of HPLC and each subchannel of HRF through the resource scheduler, organizes them into a signal-to-noise ratio list, and constructs a unified heterogeneous channel state information matrix using the dual-channel detection results; and uses the "heterogeneous water injection algorithm" to bring the system capacity close to the Shannon limit. The anti-crosstalk front-end circuit design module adopts a collaborative design of hardware PCB and RF front-end, providing independent LDO power trees and segmented ground planes for the HPLC digital / analog circuit and HRF RF circuit respectively, and connecting them at a single point through ferrite beads or isolation transformers; physical isolation and shielding are achieved using strong radiation / sensitive components; notch filters targeting the operating frequency band of the other are inserted at the output of the HPLC digital / analog circuit transmitter amplifier and the input of the HRF RF circuit receiver LNA to absorb out-of-band harmonics and blocking interference; and fine time-division transmission control logic is introduced into the protocol stack. The cooperative transmission module divides the upper-layer data packet into K data slices and generates forward error correction redundancy for each data slice. Based on real-time link quality assessment, the cooperative transmission protocol decision-maker can dynamically select a transmission strategy, or simultaneously send all data slices through dual links to obtain diversity gain. Finally, the receiving end reassembles and FEC decodes the data slices transmitted through different links.

2. The signal integrity closed-loop optimization system based on HPLC and HRF fusion communication as described in claim 1, characterized in that: When the classification result output by the deep learning model in the intelligent noise recognition and avoidance module is periodic impulse noise, the intelligent noise recognition and avoidance module accurately predicts the time window of its next occurrence and instructs the HPLC modulator to suspend the transmission of key data symbols during that period, which can be compensated by blank coding or interleaving coding. If it is identified as narrowband interference, the resource scheduler will mark the interfered subcarrier as disabled in the OFDM subcarrier mapping table and not allocate power or data. For HRF channels, the transmit power is adaptively adjusted or the optimal antenna beam is selected based on the interference characteristics to avoid interference.

3. The signal integrity closed-loop optimization system based on HPLC and HRF fusion communication as described in claim 1, characterized in that: The specific method of the "heterogeneous water injection algorithm" is as follows: the total system power is regarded as "water" and each sub-channel is regarded as a "container". More power is preferentially allocated to the sub-channel with the highest signal-to-noise ratio and a higher-order modulation method is used until the power limit or signal-to-noise ratio bottleneck is reached, and then the algorithm switches to the sub-optimal sub-channel. Through this mechanism, the total system capacity approaches the Shannon limit, realizing efficient use of resources.

4. The signal integrity closed-loop optimization system based on HPLC and HRF fusion communication as described in claim 1, characterized in that: Based on real-time link quality assessment, the collaborative transmission protocol decision-maker can dynamically select the transmission strategy to send odd-numbered data slices via HPLC and even-numbered data slices via HRF.

5. An apparatus for implementing the above system, characterized in that: The device is embedded with a SoC chip that implements the above system. The SoC chip integrates an HPLC modulation and demodulation core, an HRF baseband processing core, a signal integrity sensing module, and a central decision unit. The SoC chip is externally connected to an HPLC front-end AFE, an HRF radio frequency front-end, a memory, and a clock circuit.

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