HPLC signal synchronization method, device and equipment based on dual-mode communication system

Abstract

The application discloses a kind of HPLC signal synchronization method, device and equipment based on dual-mode communication system, belong to communication technical field.The HPLC signal synchronization method based on dual-mode communication system includes: determining effective positive correlation peak based on the autocorrelation value of known signal sequence;When the continuous quantity of effective positive correlation peak exceeds quantity threshold value, the initial value of second dynamic threshold value used for detecting negative correlation peak is determined based on continuous quantity;The initial value of second dynamic threshold value is compared with negative autocorrelation value, when negative autocorrelation value is less than the initial value of second dynamic threshold value, second dynamic threshold value is updated based on negative autocorrelation value, and update value is obtained;Multiple negative autocorrelation values corresponding to signal sequence are traversed until any negative autocorrelation value is not less than the update value obtained last time, and negative correlation peak is determined;The synchronization position of signal sequence is determined according to the signal position of negative correlation peak.The application realizes high-precision power line carrier signal synchronization.

Description

Technical Field

[0001] This invention belongs to the field of communication technology, and in particular relates to an HPLC signal synchronization method, apparatus and equipment based on a dual-mode communication system. Background Technology

[0002] With the rapid development of smart grids, smart homes, and industrial automation systems, communication systems are gradually evolving towards multi-standard collaboration. In practical deployments, an increasing number of systems adopt dual-mode communication architectures, simultaneously supporting High-speed Power Line Communication (HPLC) and other communication modes (such as Low-speed Power Line Communication or wireless communication) in the same terminal or network node to improve communication coverage, system reliability, and service continuity. In such dual-mode communication systems, HPLC typically serves as the primary communication link carrying high-speed data services, and its communication performance has a decisive impact on the overall system operation.

[0003] HPLC systems commonly employ Orthogonal Frequency Division Multiplexing (OFDM) modulation at the physical layer. This technique divides the high-speed data stream into multiple parallel, low-speed subcarriers for transmission, improving spectral efficiency while providing good resistance to multipath interference. However, OFDM systems are highly sensitive to the accuracy of time and frequency synchronization, especially at the receiver. Synchronization deviations can disrupt the orthogonality between subcarriers, leading to inter-symbol interference (ISI) and inter-carrier interference (ICI), resulting in a significant degrade in demodulation performance.

[0004] In related technologies, HPLC signal synchronization typically relies on the peak characteristics of correlation calculation results for determination, such as identifying frame boundaries or synchronization positions by detecting significant peaks in the correlation function. However, under power line channel conditions, the signal is often superimposed with colored background noise, narrowband interference, and random bursts of impulse noise, significantly perturbing the shape of the correlation function. Especially in complex noise environments, the local fluctuations in the correlation function, excluding the main peak, exhibit strong uncertainty, making synchronization determination susceptible to interference. Summary of the Invention

[0005] This invention aims to solve at least one of the technical problems existing in the prior art. To this end, this invention proposes an HPLC signal synchronization method, apparatus, and device based on a dual-mode communication system to achieve high-precision power line carrier signal synchronization.

[0006] In a first aspect, the present invention provides an HPLC signal synchronization method based on a dual-mode communication system, the method comprising: Given a received signal sequence, the autocorrelation value is determined based on the known signal sequence, and if the autocorrelation value is greater than the initial value of the first dynamic threshold, an effective positive correlation peak is determined. When the number of consecutive valid positive correlation peaks exceeds the quantity threshold, the initial value of the second dynamic threshold for detecting negative correlation peaks is determined based on the number of consecutive peaks. The negative autocorrelation value is compared with the initial value of the second dynamic threshold. When the negative autocorrelation value is less than the initial value of the second dynamic threshold, the second dynamic threshold is updated based on the negative autocorrelation value to obtain an updated value. The updated value is used to compare with the next negative autocorrelation value. Traverse multiple negative autocorrelation values ​​corresponding to the signal sequence until any negative autocorrelation value is not less than the updated value obtained in the previous update, and determine the negative autocorrelation peak; The synchronization position of the signal sequence is determined based on the signal position of the negative correlation peak.

[0007] According to one embodiment of the present invention, determining the initial value of a second dynamic threshold for detecting negatively correlated peaks based on the number of consecutive peaks specifically includes: determining a threshold coefficient corresponding to the second dynamic threshold based on the number of consecutive effective positively correlated peaks; and determining the initial value of the second dynamic threshold based on the threshold coefficient and the initial value of the first dynamic threshold.

[0008] According to one embodiment of the present invention, the threshold coefficient is the sum of the reciprocal of the consecutive number of peaks and the preset bias term; the absolute value of the initial value of the second dynamic threshold is not greater than the absolute value of the initial value of the first dynamic threshold; the larger the consecutive number of effective positive correlation peaks, the smaller the initial value of the second dynamic threshold.

[0009] According to one embodiment of the present invention, determining the initial value of a second dynamic threshold for detecting negative correlation peaks based on a continuous number of peaks specifically includes: acquiring the peak values ​​of a continuous number of valid positive correlation peaks, determining the mean value of the peak values ​​of the valid positive correlation peaks, and determining a reference negative value for the mean value of the peak values; determining a threshold coefficient corresponding to the second dynamic threshold based on the continuous number of peaks; and multiplying the reference negative value by the threshold coefficient to determine the initial value of the second dynamic threshold.

[0010] According to one embodiment of the present invention, the threshold coefficient is the sum of the reciprocal of the consecutive number and the preset bias term; the absolute value of the initial value of the second dynamic threshold is not greater than the absolute value of the reference negative value; the larger the consecutive number of effective positive correlation peaks, the smaller the initial value of the second dynamic threshold.

[0011] According to one embodiment of the present invention, determining the synchronization position of a signal sequence based on the signal position of a negative correlation peak specifically includes: determining the synchronization position based on the signal position of the negative correlation peak when the distance between the negative correlation peak and the previous positive correlation peak is within a preset distance range; and setting the consecutive number of valid positive correlation peaks to zero and re-determining valid positive correlation peaks when the distance between the negative correlation peak and the previous positive correlation peak is greater than the preset distance range.

[0012] According to one embodiment of the present invention, when a signal sequence is received, determining the autocorrelation value based on a known signal sequence specifically includes: performing a cross-correlation operation on the signal sequence and the known signal sequence to obtain a cross-correlation result; obtaining the target historical cross-correlation result, and performing an autocorrelation operation on the cross-correlation result and the target historical cross-correlation result to obtain an autocorrelation value.

[0013] According to one embodiment of the present invention, cross-correlation operation is performed on a signal sequence and a known signal sequence to obtain a cross-correlation result, specifically including: determining the sign coefficient corresponding to each sampling point based on the signal amplitude corresponding to each sampling point in the signal sequence; wherein the sign of the signal amplitude is consistent with the sign of the sign coefficient; determining the sign sequence corresponding to the signal sequence based on the sign coefficient corresponding to each sampling point; and performing cross-correlation operation on the sign sequence and the known signal sequence to obtain a cross-correlation result.

[0014] In a second aspect, the present invention provides an HPLC signal synchronization device based on a dual-mode communication system, the device comprising: The receiving module is used to determine the autocorrelation value based on the known signal sequence when a signal sequence is received, and to determine the effective positive correlation peak when the autocorrelation value is greater than the initial value of the first dynamic threshold. The determination module is used to determine the initial value of the second dynamic threshold for detecting negative correlation peaks based on the number of consecutive valid positive correlation peaks when the number of consecutive peaks exceeds the number threshold. The comparison module is used to compare the negative autocorrelation value with the initial value of the second dynamic threshold. When the negative autocorrelation value is less than the initial value of the second dynamic threshold, the second dynamic threshold is updated based on the negative autocorrelation value to obtain an updated value. The updated value is used to compare with the next negative autocorrelation value. The traversal module is used to traverse multiple negative autocorrelation values ​​corresponding to the signal sequence until any negative autocorrelation value is not less than the updated value obtained in the previous update, and to determine the negative autocorrelation peak. The synchronization module is used to determine the synchronization position of the signal sequence based on the signal position of the negative correlation peak.

[0015] Thirdly, the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the HPLC signal synchronization method based on a dual-mode communication system as described in the first aspect above.

[0016] Fourthly, the present invention provides a non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the HPLC signal synchronization method based on a dual-mode communication system as described in the first aspect above.

[0017] Fifthly, the present invention provides a chip including a processor and a communication interface, the communication interface and the processor being coupled, the processor being used to run programs or instructions to implement the HPLC signal synchronization method based on a dual-mode communication system as described in the first aspect.

[0018] In a sixth aspect, the present invention provides a computer program product, including a computer program that, when executed by a processor, implements the HPLC signal synchronization method based on a dual-mode communication system as described in the first aspect above.

[0019] The above-described one or more technical solutions in the embodiments of the present invention have at least one of the following technical effects: By detecting signal sequences, upon receiving a signal sequence, the autocorrelation value is determined based on the known signal sequence. When the autocorrelation value exceeds a first dynamic threshold, a valid positive correlation peak is identified. This process filters and confirms periodic sequences in the wireless signal. The first dynamic threshold effectively distinguishes between positive correlation peaks generated by genuine synchronization sequences and false positive correlation peaks caused by interference, thus reliably identifying the start position of the synchronization sequence in a power line channel environment and providing a data foundation for subsequent wireless signal synchronization. When the number of consecutive valid positive correlation peaks exceeds a certain threshold, an initial value for a second dynamic threshold used to detect negative correlation peaks is determined based on this number. Using the number of consecutive valid positive correlation peaks as a measure of channel conditions, a dynamic threshold adjustment mechanism for detecting negative correlation peaks is constructed, improving the robustness and accuracy of negative correlation peak detection under different channel environments. The negative autocorrelation value is compared with the initial value of the second dynamic threshold; when the negative autocorrelation value is less than the initial value of the second dynamic threshold, the detection is performed based on the negative autocorrelation value. The autocorrelation value is used to update the second dynamic threshold, resulting in an updated value. This updated value is then compared with the next autocorrelation value of the negative autocorrelation value. An iterative update strategy guides the search for the negative correlation peak along the decreasing direction of the autocorrelation value, effectively eliminating local fluctuation interference on the search path and significantly improving the accuracy of the negative correlation peak's location. Multiple autocorrelation values ​​corresponding to the signal sequence are traversed until any negative autocorrelation value is not less than the previously updated value. This continuous comparison continues until the autocorrelation value stops decreasing, improving the accuracy and reliability of the negative correlation peak's location determination. The synchronization position of the signal sequence is determined based on the signal position of the negative correlation peak. Utilizing the positional relationship between the positive and negative correlation peaks in the synchronization sequence structure, the negative correlation peak position is converted into a frame synchronization position. The synchronization location is then associated with the detection of the negative correlation peak, improving the accuracy and anti-interference capability of the obtained synchronization position. This results in higher precision and stability, achieving high-precision power line carrier signal synchronization.

[0020] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0021] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which: Figure 1 This is a schematic diagram of the structure of the frame preamble signal provided in some embodiments of the present invention; Figure 2 This is a flowchart illustrating the HPLC signal synchronization method based on a dual-mode communication system provided in some embodiments of the present invention; Figure 3This is a simulation diagram of autocorrelation results under low signal-to-noise ratio conditions provided in some embodiments of the present invention; Figure 4 This is a simulation diagram of autocorrelation results under high signal-to-noise ratio conditions provided in some embodiments of the present invention; Figure 5 This is a schematic diagram of the HPLC signal synchronization device based on a dual-mode communication system provided in some embodiments of the present invention; Figure 6 This is a schematic diagram of the structure of an electronic device provided in some embodiments of the present invention. Detailed Implementation

[0022] The technical solutions of the embodiments of the present invention will be clearly described below with reference to the accompanying drawings. 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 embodiments of the present invention are within the scope of protection of the present invention.

[0023] The terms "first," "second," etc., used in the specification and claims of this invention are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0024] With the widespread deployment of power line communication and other carrier communication systems in smart grids, smart homes, and industrial automation, the requirements for real-time and reliable data transmission in communication systems are increasing. Orthogonal Frequency Division Multiplexing (OFDM) is a modulation technique widely used in modern communication systems. Its core idea is to decompose a high-speed data stream into multiple parallel low-speed subcarrier signals for transmission. Because the subcarriers maintain strict orthogonality in the frequency domain, OFDM technology effectively improves spectrum utilization while also possessing good resistance to multipath interference.

[0025] However, in order to maintain the orthogonality between subcarriers, OFDM systems have extremely high requirements for the accuracy of time synchronization and frequency synchronization, especially at the receiver. If the synchronization deviation is large, it will cause the orthogonality between subcarriers to be destroyed, thereby causing serious inter-symbol interference (ISI) and inter-carrier interference (ICI), which will seriously affect the demodulation performance.

[0026] During long-term experiments and analysis of HPLC signal synchronization based on a dual-mode communication system, the inventors discovered that synchronization decision methods relying solely on fixed thresholds or single statistical characteristics are difficult to adapt to both low signal-to-noise ratio (SNR) and strong interference scenarios. On the one hand, under low SNR conditions, the amplitude of the correlation function is generally suppressed by noise, making it difficult to distinguish some features with decision significance. On the other hand, in scenarios with high SNR but accompanied by pulse interference, transient interference introduces abnormal correlation fluctuations, reducing the stability of synchronization feature determination.

[0027] Further research shows that during the synchronization process of power line carrier signals, the number of consecutive effective positive correlation peaks in the correlation function is not randomly distributed, but closely related to the current channel conditions: when the channel quality is poor, the number of detectable positive correlation peaks is limited; while when the channel quality is good, the positive correlation peaks exhibit stronger continuity and consistency. This phenomenon has not yet been systematically utilized in existing synchronization methods.

[0028] Based on the above findings, this invention proposes a novel technical approach: instead of basing synchronization decisions solely on fixed thresholds or isolated correlation features, it introduces an analysis of the overall structural characteristics of the correlation results. The detection results of continuous positive correlation peaks are used as important reference information reflecting the instantaneous channel state, and an adaptive synchronization decision mechanism is constructed accordingly. By statistically analyzing the number of continuous positive correlation peaks, changes in channel quality can be dynamically reflected during synchronization, providing a more reliable basis for the subsequent determination of key features.

[0029] In view of this, embodiments of the present invention provide an HPLC signal synchronization method, apparatus, and device based on a dual-mode communication system, aiming to solve the problem of insufficient signal frame synchronization accuracy caused by inaccurate detection of negative correlation peaks under complex power line channels. By introducing a dynamic threshold initialization mechanism based on the number of consecutive positive correlation peaks and an iterative negative correlation peak search strategy, the accuracy of negative correlation peak detection is improved, thereby achieving high-precision power line carrier signal synchronization.

[0030] The HPLC signal synchronization method, apparatus, and equipment based on a dual-mode communication system provided in this invention will be described in detail below with reference to the accompanying drawings and through specific embodiments and application scenarios.

[0031] In a typical HPLC frame structure, industry technical specifications detail the physical layer, data link layer, and application layer protocols of the broadband carrier communication standard, as well as related verification specifications. In these specifications, OFDM symbols are typically transmitted sequentially as individual PPDU (Physical Protocol Data Unit) frames. Each PPDU frame typically contains a preamble, a frame control (FC) signal, and a payload (PL). The preamble is used for frame synchronization and channel estimation. The FC signal describes basic frame information, such as modulation scheme and subcarrier distribution. The payload describes the actual data to be transmitted.

[0032] Figure 1 This is a schematic diagram of the structure of the frame preamble signal provided in some embodiments of the present invention. For example... Figure 1 As shown, the frame preamble consists of a series of periodically repeating synchronization symbols. The SYNCP (Synchronization Pattern) provides a synchronization signal to the receiver, enabling it to identify the start of a frame; this can be called the synchronization sequence. The SYNCM (Synchronization Marker) marks the end of a frame; this can be called the marker sequence. Its design aims to utilize the correlation between the received signal and a locally known sequence (e.g., SYNCP) to achieve time synchronization by detecting the position of the correlation peak. Crucially, a significant negative correlation peak is generated at the boundary between the SYNCP and SYNCM sequences in the frame preamble. In this embodiment, the position of the negative correlation peak is used to locate the start boundary of the frame. In this approach, the detection accuracy of the negative correlation peak directly determines the accuracy of subsequent signal synchronization.

[0033] Typically, a frame preamble consists of 10.5 SYCNP sequences and 2.5 SYNCM sequences. Each SYCNP sequence includes 1024 sample points, and each SYNCM sequence includes 1024 sample points. During data transmission, data is first organized into logical frames by the upper-layer protocol. These logical frames are then encapsulated into PPDU frames and transmitted to the physical layer. The physical layer performs OFDM modulation on the PPDU frames and transmits them as a continuous signal over the power line.

[0034] The HPLC signal synchronization method based on a dual-mode communication system provided by this invention can be applied to an HPLC signal synchronization system based on a dual-mode communication system, which includes a signal transmitting device and a signal receiving device. The signal transmitting device is used to transmit a carrier signal. The carrier signal includes a frame preamble signal, a frame control signal, and a data payload.

[0035] For example, the signal transmitting device receives data from the data link layer, performs a series of power line carrier signal processing and transformation, and processes the encoded data using OFDM modulation to modulate the frame preamble, frame control signal and data payload into an OFDM signal, also known as a carrier signal, and then transmits the carrier signal to the power line.

[0036] After detecting a signal from the power line, the signal receiving device enters frame synchronization mode to precisely locate the frame synchronization position for subsequent data frame extraction. After signal synchronization is complete, the signal receiving device extracts the data payload carried in the carrier signal based on the frame control signal, and restores it to decoded data information through decoding and demodulation processing, ultimately sending it to the data link layer for subsequent protocol parsing.

[0037] The signal transmitting and receiving devices can be, for example, electronic devices, such as power line communication terminals, concentrators, smart meters, communication module embedded devices, or communication test terminals. Alternatively, the electronic devices can also be devices with computing capabilities or intelligent robots, used to perform the signal acquisition, processing, and synchronization steps in this invention.

[0038] The HPLC signal synchronization method based on a dual-mode communication system provided by this invention can adaptively handle complex channel characteristics such as burst noise and periodic interference in power lines. It is applicable to smart grid communication, industrial automation, home broadband power line networks, and other wireless or wired communication systems based on OFDM modulation, and has broad practicality and promotional value.

[0039] The present invention provides an HPLC signal synchronization method based on a dual-mode communication system. The subject executing the method can be a signal receiving device, or a functional module or functional entity in the signal receiving device that can implement the method.

[0040] The following description uses a signal receiving device as an example to illustrate the HPLC signal synchronization method based on a dual-mode communication system provided by this invention.

[0041] Figure 2 This is a schematic flowchart of an HPLC signal synchronization method based on a dual-mode communication system provided in some embodiments of the present invention. For example... Figure 2 As shown, the HPLC signal synchronization method based on a dual-mode communication system includes steps 210 to 250.

[0042] Step 210: Upon receiving a signal sequence, determine the autocorrelation value based on the known signal sequence, and if the autocorrelation value is greater than the initial value of the first dynamic threshold, determine the effective positive correlation peak.

[0043] The signal sequence is composed of sampled signal points of a certain length arranged in chronological order. A sample point refers to the signal value acquired at a certain sampling period when sampling a continuous signal. The sampling period can be determined according to the actual situation.

[0044] The initial value of the first dynamic threshold is a pre-set initial threshold value used in the positive correlation peak detection process, and is a positive number. The threshold coefficient is a scaling factor related to the number of consecutive valid positive correlation peaks, used to adjust the strictness of the second initial threshold relative to the first initial threshold.

[0045] Signal receiving devices typically obtain discrete sampling points by sampling a continuous signal at uniform time intervals. A set of a predetermined number of discrete sampling points forms a signal sequence. For example, the length of the signal sequence is 1024 sampling points.

[0046] Alternatively, the signal receiving device can set a sliding window of a certain length, and the signal within the sliding window is the current signal sequence. The length of the sliding window can be 1024, corresponding to 1024 sampled signal points.

[0047] For a received signal sequence, the signal receiving device performs a correlation assessment based on the known signal sequence to obtain an autocorrelation value. The autocorrelation value has a positive or negative sign, and the absolute value of the autocorrelation value is called the autocorrelation result.

[0048] Furthermore, a known signal sequence refers to a pre-determined signal sequence. In embodiments of the present invention, the known signal sequence can be a locally stored synchronization sequence, i.e., a local SYNCP sequence.

[0049] For example, a signal receiving device performs sliding matching on a received signal sequence, calculating the cross-correlation result between the signal at each sampling point in the signal sequence and a known signal sequence to characterize the correlation between them. Each sampling point corresponds to a cross-correlation result, and the entire cross-correlation process outputs a set of continuous cross-correlation sequences.

[0050] To improve the accuracy and computational efficiency of cross-correlation matching, it is typically required that the input signal sequence used for matching be of the same length as the local synchronization sequence. Therefore, the length of the input signal sequence is the same as the length of the known signal sequence, and the known signal sequence corresponds to the synchronization sequence. This maximizes the preservation of the signal correlation characteristics, avoids recognition errors caused by data truncation or alignment deviations, and reduces unnecessary consumption of computational resources. For example, the length of both the input signal sequence and the local SYNCP sequence is 1024.

[0051] In some implementations, since autocorrelation is the cross-correlation between a signal and itself, the autocorrelation value can be obtained by calculating the cross-correlation between the signal and itself. Cross-correlation measures the degree of correlation between a received signal sequence and a known signal sequence, and is typically determined by calculating the sum of the products of the received and known signal sequences. Therefore, the signal receiving device can first perform a cross-correlation operation on the signal sequence and the known signal sequence to obtain the cross-correlation result; each time a cross-correlation result is calculated, the signal receiving device stores it, so that subsequent autocorrelation operations can be performed on the cross-correlation result and the historically calculated cross-correlation results to obtain the autocorrelation value.

[0052] In other implementations, the signal receiving device can establish a neural network or machine learning model related to the signal sequence by mapping the historical signal sequence to the known signal sequence, and after training, use the current signal sequence as input to obtain the autocorrelation value output by the neural network or machine learning model.

[0053] In some other embodiments, the signal receiving device may also extract a portion containing a known signal sequence from the received signal sequence and perform autocorrelation operation on that portion, for example, by calculating the sum of the products between the signal at each sampling point and the signal at the sampling point after a certain time delay, to obtain the autocorrelation value.

[0054] When the received signal sequence is aligned with a locally known synchronization sequence (such as SYNCP) under a specific time delay, the cross-correlation result, after autocorrelation processing, will produce a significant positive peak at the corresponding position, i.e., a positive correlation peak. This peak characterizes the appearance of a periodic synchronization pattern in the received signal and is a key basis for identifying the start position of the data frame.

[0055] To reliably identify genuine positive correlation peaks, this embodiment of the invention introduces a first dynamic threshold as a criterion. This first dynamic threshold is not fixed but is dynamically updated during the detection process based on the changing trend of the autocorrelation value, starting from its initial value. The core logic is that positive correlation peaks generated by genuine synchronous sequences are typically accompanied by a continuous increase in autocorrelation value, while fluctuations caused by noise lack this continuity.

[0056] Specifically, during the continuous calculation of autocorrelation values, the signal receiving device starts from the initial value of the first dynamic threshold and compares each newly obtained autocorrelation value with the current first dynamic threshold. If the autocorrelation value exceeds the current threshold, it indicates that it may be approaching or at the rising edge of a correlation peak. At this time, the signal receiving device updates the first dynamic threshold with the larger autocorrelation value, raising it to a new level, and continues to check subsequent sampling points.

[0057] Through iterative processing, the first dynamic threshold increases continuously. When the autocorrelation value no longer exceeds the current first dynamic threshold—that is, when the autocorrelation values ​​of several consecutive sampling points are lower than or equal to the first dynamic threshold—it indicates that the rising process has ended and the peak has appeared. At this point, the autocorrelation value and its position corresponding to the last successful update of the first dynamic threshold can be preliminarily identified as a "maximum positive correlation peak."

[0058] In some embodiments, since sudden interference such as impulse noise may also produce similar isolated peaks, it is necessary to verify the validity of the initially determined maximum positive correlation peak to confirm whether it is generated by a real synchronization sequence.

[0059] For example, the verification methods include, but are not limited to, one or more of the following: continuity checks or local signal-to-noise ratio assessments.

[0060] Among them, the continuity check refers to determining whether the time interval between the maximum positive correlation peak and the previously (or subsequently) detected peak is consistent with the period length of the known synchronization sequence (such as within a reasonable deviation range of about 1024 sampling points).

[0061] Local signal-to-noise ratio (SNR) assessment refers to selecting a segment of signal near the peak position of the maximum positive correlation peak, calculating its SNR or the ratio to the noise level, in order to verify the significance of its peak.

[0062] Only after the largest positive correlation peak passes the validity verification will it be determined as a valid positive correlation peak. The position of this valid positive correlation peak will be used in subsequent processes such as accumulating the number of consecutive valid positive correlation peaks or determining the starting point for negative correlation peak search. After finding the current valid peak, the first dynamic threshold will be reset to the first initial threshold, and the signal receiving device will then begin a new round of positive correlation peak search and determination process to find the next valid positive correlation peak.

[0063] In other words, by using a dynamically updated rather than fixed first dynamic threshold, the trend of the true positive correlation peak can be adaptively determined, effectively filtering out most noise fluctuations below the threshold and some isolated interference peaks. Validating the maximum positive correlation peak ensures the reliability of the identified positive correlation peak, providing a foundation for subsequent accurate determination of synchronization status and location of negative correlation peaks, thereby improving the robustness of the entire synchronization process in complex noise environments.

[0064] Step 220: When the number of consecutive valid positive correlation peaks exceeds the number threshold, determine the initial value of the second dynamic threshold for detecting negative correlation peaks based on the number of consecutive peaks.

[0065] Among them, the effective positive correlation peak refers to the positive correlation peak that is confirmed to be generated by a real synchronization sequence (such as SYNCP) after being screened and verified by the first dynamic threshold in step 210. The continuous number refers to the number of effective positive correlation peaks detected consecutively. The number threshold is a preset positive integer used to determine whether a sufficient number of effective positive correlation peaks have been accumulated to enter the negative correlation peak detection stage.

[0066] For example, the quantity threshold could be 2, meaning that when the number of consecutively detected valid positive correlation peaks is 2, it is determined that a sufficient number of valid positive correlation peaks have been accumulated.

[0067] The second dynamic threshold is a dynamic threshold value used to detect negatively correlated peaks. Its initial value is negative and it is updated in subsequent steps.

[0068] In some embodiments, the signal receiving device records the number of consecutively detected valid positive correlation peaks using an adjacent count value. Whenever a new valid positive correlation peak is detected, the signal receiving device determines whether the time interval between it and the previous valid positive correlation peak is within a expected range. If it is within the range, the adjacent count value is incremented; if it is not within the range, the adjacent count value is reset. When the adjacent count value exceeds a preset threshold, the signal receiving device determines that a sufficient number of valid positive correlation peaks have accumulated. At this point, the signal receiving device records the first subsequent autocorrelation value as a negative autocorrelation value.

[0069] For example, the signal receiving device uses an adjacent count value, Begincount. Whenever a maximum positive correlation peak is detected, after finding the position of the maximum positive correlation peak, it skips 20 sampling points and then calculates the average of the absolute values ​​of the autocorrelation of 1000 points. This segment of data is considered noise. The ratio of the autocorrelation value of the maximum positive correlation peak to the average absolute value of the autocorrelation of this segment is calculated. If the ratio is greater than a set threshold, the maximum positive correlation peak is considered valid, and Begincount = 1. After finding the next maximum positive correlation peak, the signal receiving device determines whether the distance between the position of the current maximum positive correlation peak and the previous maximum positive correlation peak is within the range of 1024 ± 20. If it is within the range, it means that a continuous correlation peak has been found, and Begincount continues to accumulate. If it is not within the range, it means that a SYNCP sequence was missed between the position of the current maximum positive correlation peak and the previous maximum positive correlation peak, and Begincount is reset to 1.

[0070] Subsequently, the signal receiving device calculates the initial value of the second dynamic threshold used to detect negative correlation peaks based on the number of currently accumulated consecutive valid positive correlation peaks.

[0071] In some implementations, the signal receiving device can calculate the initial value of the second dynamic threshold based on the preset initial value of the first dynamic threshold used to detect positive correlation peaks.

[0072] In other implementations, the signal receiving device may calculate the initial value of the second dynamic threshold based on the average peak value of a consecutive number of valid positive correlation peaks that have been detected.

[0073] Step 230: Compare the negative autocorrelation value with the initial value. When the negative autocorrelation value is less than the initial value, update the second dynamic threshold based on the negative autocorrelation value to obtain the updated value. The updated value is used to compare with the next negative autocorrelation value.

[0074] Specifically, after determining the initial value of the second dynamic threshold, the signal receiving device compares the determined negative autocorrelation value with the initial value of the second dynamic threshold. If the negative autocorrelation value is not less than (i.e., greater than or equal to) the initial value of the second dynamic threshold, it indicates that the position of the negative autocorrelation value is not the starting position of the negative correlation peak. The signal receiving device will continue to read the next autocorrelation value and continue to compare it with the initial value of the second dynamic threshold until a negative autocorrelation value less than the initial value of the second dynamic threshold is found.

[0075] When the signal receiving device finds a negative autocorrelation value that is less than the initial value of the current second dynamic threshold, it indicates that the device has entered the declining region of the negative autocorrelation peak. At this point, the signal receiving device updates the initial value of the second dynamic threshold based on the current negative autocorrelation value, setting the new second dynamic threshold to the current negative autocorrelation value. The updated threshold will be used as the benchmark for the next comparison, used to compare the current negative autocorrelation value with the next negative autocorrelation value.

[0076] It should be noted that when the signal receiving device finds a negative autocorrelation value smaller than the current second dynamic threshold, it immediately updates the second dynamic threshold to that smaller negative autocorrelation value, thereby guiding the search process to continuously move towards a smaller negative autocorrelation value, thus effectively determining the downward trend of the negative correlation peak.

[0077] Step 240: Traverse the multiple negative autocorrelation values ​​corresponding to the signal sequence until any negative autocorrelation value is not less than the updated value obtained in the previous update, and determine the negative correlation peak.

[0078] Here, traversal refers to processing each negative autocorrelation value corresponding to the signal sequence in sequence according to the time order or the sampling point order. The updated value obtained in the last update refers to the second dynamic threshold that was most recently updated in step 230.

[0079] Specifically, after updating the second dynamic threshold in step 230, the signal receiving device continues to traverse subsequent negative autocorrelation values. For each new negative autocorrelation value encountered, the signal receiving device compares it with the second dynamic threshold obtained in the previous update.

[0080] If the new negative autocorrelation value is less than the second dynamic threshold obtained in the previous update, it indicates that the signal receiving device may be approaching the lowest point of the negative autocorrelation peak. The signal receiving device will then perform an update operation again, setting the new negative autocorrelation value equal to the second dynamic threshold obtained in the previous update, and then continue to read the next negative autocorrelation value, repeating this process.

[0081] If the new negative autocorrelation value is not less than the second dynamic threshold obtained in the last update, it indicates that the negative autocorrelation value has stopped decreasing and has begun to show an upward or flat trend, and has now passed the trough of the negative autocorrelation peak. At this time, the signal receiving device records the negative autocorrelation value corresponding to the last successful update of the second dynamic threshold (i.e., the current value of the second dynamic threshold) and its corresponding signal position, determines that the signal position as the negative autocorrelation peak, and does not repeat the above comparison process.

[0082] Through this continuous comparison and updating, the signal receiving device can effectively search for the decreasing trajectory of the negative autocorrelation value until it finds the minimum point or a local minimum. This process effectively smooths out random fluctuations or small dips in the signal, ensuring that the finally located point is a continuously verified and significant negative extreme point, thereby greatly improving the accuracy and anti-interference capability of negative correlation peak location detection.

[0083] Step 250: Determine the synchronization position of the signal sequence based on the signal position of the negative correlation peak.

[0084] Here, the signal position refers to the specific sampling point index or timestamp corresponding to the negative correlation peak, while the synchronization position refers to the starting position of the entire data frame, that is, the final positioning position of frame synchronization.

[0085] Specifically, the signal receiving device identifies the autocorrelation value and its position corresponding to the last update recorded at the end of step 240 as a negative correlation peak. This position is the approximate location of the beginning of the synchronization sequence (such as SYNCM) in the received signal.

[0086] In some implementations, if the distance between the negative correlation peak and the previous positive correlation peak is within a preset distance range, the synchronization position is determined based on the signal position of the negative correlation peak. If the distance between the negative correlation peak and the previous positive correlation peak is greater than the preset distance range, the consecutive number of effective positive correlation peaks is set to zero, and the effective positive correlation peaks are re-determined.

[0087] The previous positive correlation peak refers to the last positive correlation peak that is verified and recorded as valid by the signal receiving device before the negative correlation peak in the time sequence of signal processing.

[0088] Specifically, after identifying a negative correlation peak, the signal receiving device reads the signal position of the previous positive correlation peak and calculates the distance between the negative correlation peak and the previous positive correlation peak. If the distance between the negative correlation peak and the previous positive correlation peak is greater than a preset distance range, it indicates that the interval between the negative correlation peak and the previous valid positive correlation peak deviates from the frame preamble structure specified by the communication protocol (e.g., the fixed length relationship between the SYNCP sequence and the SYNCM sequence). This means that the currently detected negative correlation peak is a pseudo-synchronization marker caused by noise, interference, or channel distortion, rather than a true SYNCM start point. Therefore, to ensure synchronization reliability, the signal receiving device resets the cumulative number of consecutive valid positive correlation peaks to zero and restarts the search and verification of valid positive correlation peaks to attempt to establish the correct synchronization process.

[0089] When the interval between the negative correlation peak and the previous positive correlation peak is not greater than a preset interval range, it indicates that the interval between the negative correlation peak and the previous valid positive correlation peak conforms to the expected frame structure, thus verifying that the negative correlation peak is a true and valid synchronization boundary marker (i.e., the start position of the SYNCM sequence). In this case, the signal receiving device uses the signal position of the negative correlation peak as the reference for calculating frame synchronization and uses the signal position of the negative correlation peak as the synchronization position. In other implementations, the synchronization position of the signal sequence is determined based on the signal position of the effective negative correlation peak, specifically including: firstly obtaining the length of the known signal sequence; and then determining the synchronization position of the signal sequence based on the signal position of the effective negative correlation peak and the length of the known signal sequence.

[0090] Due to the known frame structure, there is a fixed phase or positional relationship between SYNCP and SYNCM. For example, in an HPLC system, SYNCM follows the last complete SYNCP. Therefore, the frame start position can be deduced from the position of the effective negative correlation peak.

[0091] For example, the signal receiving device acquires the known length of the SYNCP (e.g., 1024 sampling points). Then, based on the signal position of the effective negative correlation peak and this known length, the synchronization position of the signal sequence is determined. A common calculation method is to shift (i.e., subtract) 1024 sampling points forward from the signal position of the effective negative correlation peak; the resulting position is the frame synchronization position. This position corresponds to the boundary between the SYNCP and SYNCM sequences, which is the starting reference point for subsequent extraction of frame control signals and data payloads.

[0092] Therefore, by combining the detected negative correlation peak position with the known frame structure, high-precision frame synchronization positioning can be achieved. Since the detection process of the negative correlation peak introduces an adaptive threshold initialization and iterative mechanism based on the number of positive correlation peaks, its position accuracy is significantly improved, which in turn makes the final determined synchronization position more reliable and stable, providing a foundation for subsequent data demodulation.

[0093] The HPLC signal synchronization method based on a dual-mode communication system provided by the present invention detects a signal sequence. Upon receiving the signal sequence, it determines the autocorrelation value based on the known signal sequence and identifies valid positive correlation peaks when the autocorrelation value exceeds a first dynamic threshold. This method filters and confirms periodic sequences in the wireless signal. The first dynamic threshold effectively distinguishes between positive correlation peaks generated by genuine synchronization sequences and false positive correlation peaks caused by interference, thus reliably identifying the starting position of the synchronization sequence in a power line channel environment and providing a data foundation for subsequent wireless signal synchronization. When the number of consecutive valid positive correlation peaks exceeds a quantity threshold, an initial value for a second dynamic threshold used to detect negative correlation peaks is determined based on the number of consecutive peaks. The number of consecutive valid positive correlation peaks is used as a measure of channel conditions, constructing a dynamic threshold adjustment mechanism for detecting negative correlation peaks. This improves the robustness and accuracy of negative correlation peak detection under different channel environments. The negative autocorrelation value is compared with the initial value of the second dynamic threshold. When the negative autocorrelation value is small... When the second dynamic threshold is initialized, it is updated based on the negative autocorrelation value to obtain an updated value. This updated value is then compared with the next autocorrelation value of the negative autocorrelation value. An iterative update strategy is adopted to guide the search for the negative correlation peak along the direction of decreasing autocorrelation value, which can effectively eliminate local fluctuation interference on the search path and improve the accuracy of the negative correlation peak position. Multiple autocorrelation values ​​corresponding to the signal sequence are traversed until any negative autocorrelation value is not less than the updated value obtained in the previous update. By continuously comparing until the autocorrelation value stops decreasing, the accuracy and reliability of the negative correlation peak position determination are improved. The synchronization position of the signal sequence is determined based on the signal position of the negative correlation peak. Using the positional relationship between the positive and negative correlation peaks in the synchronization sequence structure, the position of the negative correlation peak is converted into the frame synchronization position. The synchronization positioning is associated with the detection of the negative correlation peak, which improves the accuracy and anti-interference capability of the obtained synchronization position, and has higher precision and stability, realizing high-precision power line carrier signal synchronization.

[0094] In power line carrier communication, the setting of the second dynamic threshold used to detect negative correlation peaks is crucial. However, power line channel conditions are complex and variable, and a fixed negative threshold cannot adapt to the instantaneous signal-to-noise ratio. Under poor channel conditions, an overly strict threshold may fail to detect true negative peaks that are submerged in noise; under good channel conditions, an overly lenient threshold may misjudge noise fluctuations as targets, leading to synchronization point shifts.

[0095] Based on this, in some embodiments, the initial value of the second dynamic threshold for detecting negative correlation peaks is determined based on the number of consecutive peaks, specifically including: determining the threshold coefficient corresponding to the second dynamic threshold based on the number of consecutive effective positive correlation peaks; and determining the initial value of the second dynamic threshold based on the threshold coefficient and the preset initial value of the first dynamic threshold.

[0096] It should be noted that the reference negative value refers to the negative number obtained by taking the opposite of the positive value used to characterize the intensity of the positive correlation peak (such as the preset initial value of the first dynamic threshold) during the calculation of the initial value of the second dynamic threshold. It is an intermediate quantity connecting the intensity of the positive correlation peak and the detection threshold of the negative correlation peak. The reason for this is that the positive correlation peak is the positive peak value of the autocorrelation value, while the negative correlation peak to be detected is the negative valley value of the autocorrelation result. Therefore, it is necessary to convert a reference value characterizing the intensity of the positive peak into a negative value as a benchmark for setting the detection threshold of the negative peak.

[0097] In some implementations, the signal receiving device first determines a threshold coefficient based on the number of consecutive valid positive correlation peaks using a preset mapping relationship or calculation formula. Then, the signal receiving device takes the negative of the preset initial value of the first dynamic threshold to obtain a reference negative value, and multiplies the reference negative value by the threshold coefficient to obtain the initial value of the second dynamic threshold.

[0098] The threshold coefficient is the sum of the reciprocal of the consecutive numbers and the preset bias term.

[0099] For example, let the number of consecutive valid positive correlation peaks be... The default bias is ,by For example, let the threshold coefficient be... The mapping relationship between the threshold coefficient and the number of consecutive effective positive correlation peaks is as follows: (1) After this, let the initial value of the preset first dynamic threshold be... Take its opposite to obtain the reference negative value. Then combine it with the threshold coefficient Multiplying these values ​​yields the initial value of the second dynamic threshold, as shown in the following formula: (2) For example, if When two consecutive positive correlation peaks are detected, , When eight consecutive positive correlation peaks are detected, .

[0100] The above calculation uses the number of continuously detected valid positive correlation peaks as a reliable basis for evaluating the instantaneous quality of the current channel, and dynamically adjusts the initial strictness of negative correlation peak detection accordingly.

[0101] It should be noted that the absolute value of the initial value of the second dynamic threshold is not greater than the absolute value of the initial value of the first dynamic threshold; the greater the number of consecutive effective positive correlation peaks, the smaller the initial value of the second dynamic threshold. When the number of consecutive effective positive correlation peaks is small (e.g., When the signal is low, it usually indicates that the current channel conditions are poor and the signal-to-noise ratio is low. Figure 3 These are simulation diagrams of autocorrelation results under low signal-to-noise ratio conditions provided in some embodiments of the present invention. For example... Figure 3 As shown in the figure, the horizontal axis represents the sampling point index, indicating the discrete sampling point positions of the signal sequence in time order, with an interval of 1000 sampling points; the vertical axis represents the autocorrelation value, with an interval of 0.5, to present the contrast between signal and noise in a strong noise background. Figure 3 The vertical axis ranges from -1 to 2. Under low signal-to-noise ratio (SNR) conditions, the true positive and negative correlation peaks are not obvious and are difficult to distinguish from noise-induced fluctuations, resulting in a high risk of misjudgment. Therefore, even if two consecutive positive correlation peaks are detected, the reliability is low. To address this, the initial value of the second dynamic threshold is set to a negative number with a large absolute value, making the initial value of the second dynamic threshold close to the initial value of the first dynamic threshold. In other words, the detection threshold for negative correlation peaks is set more stringently. This is because, under low SNR conditions, actively increasing the detection threshold for negative correlation peaks can reduce the probability of misjudging noise fluctuations as target negative correlation peaks, effectively preventing missynchronization.

[0102] Furthermore, when the number of consecutive effective positive correlation peaks is large (e.g. When the signal-to-noise ratio (SNR) is high, it indicates that the channel conditions are good and the SNR is high. Under high SNR conditions, the true negative correlation peak can be clearly displayed. Figure 4 These are simulation diagrams of autocorrelation results under high signal-to-noise ratio conditions provided in some embodiments of the present invention. For example... Figure 4 As shown in the figure, the horizontal axis represents the sampling point index, indicating the discrete sampling point positions of the signal sequence in time order, with intervals of 1000 sampling points; the vertical axis represents the autocorrelation value. Figure 4The solid black line represents the initial value of the first dynamic threshold, 400, and the dashed black line represents the initial value of the second dynamic threshold, -250, obtained in this embodiment of the invention. This result preprocesses the impulse noise by zeroing it out. Although zeroing the impulse noise may cause fluctuations in the peak values ​​of some positive correlation peaks, most are still significantly higher than the initial value of the dynamic threshold. For the negative correlation peaks to be detected, their amplitudes are also reduced due to the same zeroing process (i.e., the absolute value of the negative autocorrelation decreases). At this point, if the strict threshold under low signal-to-noise ratio is still used, it may not be possible to effectively detect the true negative peaks. Therefore, a smaller initial value for the second dynamic threshold can be selected, which is equivalent to lowering the initial threshold for detecting negative correlation peaks. The reason for this is that under high signal-to-noise ratio conditions, due to the inherently better signal quality, the final determination of negative correlation peaks will rely more on subsequent iterative updates. The main function of the initial value of the second dynamic threshold is to provide a relatively relaxed triggering condition. By lowering the initial value of the second dynamic threshold, the true negative correlation peaks can be more easily triggered to trigger subsequent searches, avoiding missed detections.

[0103] In the above embodiments, parameterized adaptation is achieved by associating the initial value of the second dynamic threshold with the initial value of the first dynamic threshold and dynamically scaling it using the number of consecutive positively correlated peaks. When the number of consecutive peaks is small, the threshold coefficient is close to 1, which helps to prevent noise misjudgment. When the number of consecutive peaks is large, the threshold coefficient decreases, the absolute value of the initial value of the second dynamic threshold becomes smaller, the setting is relatively loose, and it is conducive to searching for the true negatively correlated peaks.

[0104] In the process of dynamically determining the initial value of the second dynamic threshold based on the number of consecutive effective positive correlation peaks, the above embodiment uses a preset initial value of the first dynamic threshold to calculate the initial value of the second dynamic threshold. However, in actual power line channels, signal attenuation and gain are time-varying, and a preset fixed reference value may not accurately match the instantaneous state of the current channel.

[0105] Based on this, in some embodiments, determining the initial value of the second dynamic threshold for detecting negative correlation peaks based on the number of consecutive peaks specifically includes: acquiring the peak values ​​of a consecutive number of valid positive correlation peaks, determining the mean value of the peak values ​​of the valid positive correlation peaks, and determining a reference negative value for the mean value of the peak values; determining the threshold coefficient corresponding to the second dynamic threshold based on the number of consecutive peaks; and multiplying the reference negative value by the threshold coefficient to determine the initial value of the second dynamic threshold.

[0106] The peak value of an effective positive correlation peak refers to the autocorrelation value of each of the confirmed consecutive effective positive correlation peaks, which characterizes the significance of the synchronization sequence at the corresponding position.

[0107] Specifically, the signal receiving device first determines the threshold coefficient based on the number of consecutive valid positive correlation peaks using a preset mapping relationship or calculation formula. Unlike directly using the initial value of the first dynamic threshold, this embodiment of the invention determines the initial value of the second dynamic threshold based on the peak values ​​of a consecutive number of valid positive correlation peaks.

[0108] In some implementations, the signal receiving device acquires the peak values ​​of a consecutive number of valid positive correlation peaks, determines the average peak value of the consecutive valid positive correlation peaks, and determines a reference negative value for the average peak value; the reference negative value is multiplied by a threshold coefficient to determine the initial value of the second dynamic threshold.

[0109] Specifically, the signal receiving device calculates the arithmetic mean of the peak values ​​of a consecutive number of valid positive correlation peaks to obtain the peak mean. Then, the negative value of the obtained peak mean is calculated to obtain a reference negative value. This reference negative value is then multiplied by the threshold coefficient to obtain the initial value of the second dynamic threshold.

[0110] In some implementations, the threshold coefficient is the sum of the reciprocals of consecutive numbers and a preset bias term.

[0111] For example, let the number of consecutive valid positive correlation peaks be... The default bias is ,by For example, the threshold coefficient is The mapping relationship between the threshold coefficient and the number of consecutive effective positive correlation peaks is shown in formula (1) above. The signal receiving device extracts... The peak values ​​of the effective positive correlation peaks are used to calculate the initial value of the second dynamic threshold. .

[0112] Let the mean peak value of the effective positive correlation peak be... ,Will Negating the value yields a reference negative value. Then combine it with the threshold coefficient Multiplication, as shown in the following formula: (3) For example, if continuous detection There are 10 effective positive correlation peaks, with peak values ​​of 380, 410, 395, 400, and 405, respectively. If the threshold coefficient ,but It can be approximated as an integer. .

[0113] It should be noted that the absolute value of the initial value of the second dynamic threshold is not greater than the absolute value of the reference negative value; the greater the number of consecutive effective positive correlation peaks, the smaller the initial value of the second dynamic threshold.

[0114] In the above embodiments, by introducing the peak value of the effective positive correlation peak as the calculation benchmark for the initial value of the second dynamic threshold, and utilizing the peak value of the synchronization signal strength directly derived from the current channel, the calculated initial value of the second dynamic threshold can sense channel changes. The detection threshold of the negative correlation peak is set within a reasonable range relative to the current actual signal strength. By calculating the average of multiple consecutive peak values, the abnormal impact that may be caused by impulse noise or other instantaneous interference on the amplitude of a single positive correlation peak can be effectively smoothed, making the reference strength used to calculate the negative threshold more stable and reliable, and further improving the stability of signal synchronization under transient interference.

[0115] It should be noted that determining the initial value of the second dynamic threshold by using the average peak value of the effective positive correlation peaks is a more sensitive and accurate method for determining the initial value of the second dynamic threshold in some application scenarios. Specifically, this method determines the second dynamic threshold of the negative correlation peak based on the peak value change of the synchronization signal under the current channel conditions, enabling it to more closely track the instantaneous state of the channel.

[0116] Compared to the initial value based on the first dynamic threshold, the initial value of the second threshold determined in this embodiment of the invention has a higher degree of matching with the current signal strength. In the subsequent iterative search for negative correlation peaks, since the initial value of the second threshold is closer to the expected range of the true negative correlation peak, the signal receiving device can converge to the accurate signal position of the negative correlation peak with fewer comparisons and updates. This reduces the computational complexity of the iteration process and the processing delay to a certain extent, thereby significantly improving the efficiency of searching for and determining negative correlation peaks while ensuring detection accuracy.

[0117] In HPLC, signal synchronization is a key technology for accurate data transmission and reception. Current synchronization techniques using cross-correlation are ineffective in power line communication environments with strong noise interference such as narrowband interference, background noise, and low signal-to-noise ratios, failing to meet the requirements of high-reliability communication. Therefore, this invention proposes a method for calculating autocorrelation values ​​that combines cross-correlation and autocorrelation operations to improve the accuracy and robustness of signal synchronization.

[0118] Based on this, in some embodiments, when a signal sequence is received, the autocorrelation value is determined based on the known signal sequence, specifically including: performing a cross-correlation operation on the signal sequence and the known signal sequence to obtain a cross-correlation result; obtaining the target historical cross-correlation result, and performing an autocorrelation operation on the cross-correlation result and the target historical cross-correlation result to obtain an autocorrelation value.

[0119] In this embodiment of the invention, the signal receiving device performs a cross-correlation operation on the received signal sequence and a locally known signal sequence to calculate the cross-correlation result for each sampling point in the signal sequence. The known signal sequence is, for example, a known synchronization sequence SYNCP. The cross-correlation result can be, for example, the sum of the products of the signal value at each sampling point in the signal sequence and the signal value at each sampling point in the known signal sequence.

[0120] For example, a signal receiving device performs sliding matching on a received signal sequence, calculating the cross-correlation result between the signal at each sampling point in the signal sequence and a known signal sequence to characterize the correlation between them. Each sampling point corresponds to a cross-correlation result, and the entire cross-correlation process outputs a set of continuous cross-correlation sequences.

[0121] The signal receiving device saves the cross-correlation result for each sampling point as it is calculated. For example, the signal receiving device can maintain a buffer in memory to store the cross-correlation results of multiple sampling points over a period of time for subsequent analysis.

[0122] For the cross-correlation result of the current sampling point, the signal receiving device extracts the target historical cross-correlation result from the historical cross-correlation results, and performs autocorrelation calculation on the current cross-correlation result and the target historical cross-correlation result to calculate the autocorrelation value.

[0123] In the above embodiments, by combining cross-correlation and autocorrelation operations, and performing autocorrelation operations between the current cross-correlation results and historical data, the correlation peak can be highlighted more significantly, thereby more accurately identifying repeated synchronization patterns and improving the accuracy and reliability of synchronization detection.

[0124] In communication systems based on orthogonal frequency division multiplexing (OFDM) technology, such as high-speed power line communication, accurate frame synchronization is required at the receiving end to achieve effective decoding of the received signal. Cross-correlation is a commonly used synchronization detection method. By calculating the similarity between the received signal sequence and a locally stored known signal sequence, the starting position of the synchronization sequence in the received signal can be located. However, in power line communication scenarios, the signal is easily affected by interference factors such as burst impulse noise, narrowband interference, and background noise. Traditional amplitude-dependent cross-correlation methods may be unsuitable for practical application environments with limited hardware resources or harsh channel conditions due to the complexity of multiplication calculations and sensitivity to amplitude fluctuations.

[0125] Furthermore, signal synchronization efficiency is also a key factor in high-speed power line carrier communication. Typical cross-correlation operations involve multiplying the received signal sequence with a locally known signal sequence, which not only consumes significant computational resources but is also relatively inefficient.

[0126] Based on this, in some embodiments, a cross-correlation operation is performed on the signal sequence and a known signal sequence to obtain a cross-correlation result. Specifically, this includes: determining the sign coefficient corresponding to each sampling point based on the signal amplitude corresponding to each sampling point in the signal sequence; wherein the sign of the signal amplitude is consistent with the sign of the sign coefficient; determining the sign sequence corresponding to the signal sequence based on the sign coefficient corresponding to each sampling point; and performing a cross-correlation operation on the sign sequence and the known signal sequence to obtain a cross-correlation result.

[0127] Specifically, for the received signal sequence, the signal receiving device determines the symbol coefficient corresponding to each sampling point based on the signal amplitude corresponding to each sampling point in the signal sequence.

[0128] The sign of the sign coefficient corresponds to the sign of the signal amplitude. In other words, each sign coefficient represents the polarity of the signal amplitude at that sampling point, with +1 indicating a positive value. 1 represents a negative value, and 0 represents 0 or approximately 0.

[0129] For example, if a signal receiving device receives a signal sequence of length 1024, including 1024 sampling points, the signal receiving device can quickly obtain the symbol coefficient corresponding to each sampling point by incrementing the sign coefficient by 1 if the amplitude is positive and decrementing it by -1 if the amplitude is negative. The symbol coefficients corresponding to each sampling point constitute a symbol sequence corresponding to the signal sequence, such as {+1,+1,-1,...,+1,-1}.

[0130] Furthermore, the signal receiving device can perform cross-correlation operations based on the symbol sequence and the known signal sequence. Since only the symbol coefficients corresponding to each sampling point are taken, the product operation between the symbol sequence corresponding to the signal sequence and the known signal sequence is converted into a simple addition and subtraction operation during the cross-correlation operation, which greatly reduces the amount of computation.

[0131] In the above embodiments, by simplifying the received signal amplitude to its corresponding sign coefficient and retaining only the positive and negative polarities, compared with the traditional cross-correlation operation which performs product operations on specific amplitudes, the computational complexity and dependence on amplitude accuracy are effectively reduced, the processing efficiency is improved, and the stability and real-time performance of synchronous identification are enhanced.

[0132] In some embodiments, cross-correlation is performed on the symbol sequence and the known signal sequence to obtain the cross-correlation result. Specifically, this includes: for any sampling point, multiplying the symbol coefficient corresponding to the sampling point with the known signal at the same position in the known signal sequence to obtain the cross-correlation value corresponding to the sampling point; and obtaining the cross-correlation result based on the sum of the cross-correlation values ​​corresponding to each sampling point in the signal sequence.

[0133] Specifically, for any sampling point in the received symbol sequence, the signal receiving device extracts its corresponding symbol coefficient, such as +1, -1, or 0. The signal receiving device then multiplies this symbol coefficient with the symbol at the same position in the known signal sequence to obtain the cross-correlation value corresponding to the current sampling point.

[0134] Then, the signal receiving device sums the cross-correlation values ​​of each sampling point in the entire signal sequence, and the sum is the cross-correlation result between the current signal sequence and the known sequence.

[0135] Taking a sliding window of length 1024 points as an example: First, extract the 1024 sampling points covered by the current sliding window from the received signal sequence; calculate the symbol coefficients of the amplitudes of these 1024 sampling points one by one to form a symbol sequence of length 1024; then, multiply the symbol sequence with the locally stored SYNCP sequence point by point to calculate the product at each pair of positions; sum these 1024 product values ​​to obtain a cross-correlation result value, which serves as the cross-correlation index corresponding to the current sliding window position; repeat the above process, updating the cross-correlation result sequence as the sliding window moves.

[0136] In the above embodiments, by converting the signal amplitude into sign coefficients, floating-point multiplication calculations are avoided, greatly reducing the amount of computation and improving processing efficiency. Even in low signal-to-noise ratio environments, correlation peaks can be effectively identified, improving synchronization robustness. In addition, since only the positive and negative sign coefficients of the signal are taken, the hardware implementation difficulty and processing latency are also greatly reduced, making it suitable for deployment in resource-constrained communication terminals or embedded platforms.

[0137] The HPLC signal synchronization method based on a dual-mode communication system provided in this embodiment of the invention can be executed by an HPLC signal synchronization device based on a dual-mode communication system. This embodiment of the invention uses an HPLC signal synchronization device based on a dual-mode communication system executing the HPLC signal synchronization method as an example to illustrate the HPLC signal synchronization device based on a dual-mode communication system provided in this embodiment of the invention.

[0138] Figure 5 This is a schematic diagram of the HPLC signal synchronization device based on a dual-mode communication system provided in some embodiments of the present invention. For example... Figure 5 As shown, the HPLC signal synchronization device based on a dual-mode communication system includes: a receiving module 501, a determining module 502, a comparison module 503, a traversal module 504, and a synchronization module 505.

[0139] The receiving module 501 is used to determine the autocorrelation value based on the known signal sequence when a signal sequence is received, and to determine the effective positive correlation peak when the autocorrelation value is greater than the initial value of the first dynamic threshold. The determination module 502 is used to determine the initial value of the second dynamic threshold for detecting negative correlation peaks based on the number of consecutive valid positive correlation peaks when the number of consecutive valid positive correlation peaks exceeds the number threshold. The comparison module 503 is used to compare the negative autocorrelation value with the initial value of the second dynamic threshold. When the negative autocorrelation value is less than the initial value of the second dynamic threshold, the second dynamic threshold is updated based on the negative autocorrelation value to obtain an updated value. The updated value is used to compare with the next negative autocorrelation value. Traversal module 504 is used to traverse multiple negative autocorrelation values ​​corresponding to the signal sequence until any negative autocorrelation value is not less than the updated value obtained in the previous update, and to determine the negative autocorrelation peak; Synchronization module 505 is used to determine the synchronization position of the signal sequence based on the signal position of the negative correlation peak.

[0140] The HPLC signal synchronization device based on a dual-mode communication system provided in this embodiment of the invention detects a signal sequence. Upon receiving the signal sequence, it determines the autocorrelation value based on the known signal sequence and identifies valid positive correlation peaks when the autocorrelation value exceeds a first dynamic threshold. This screens and confirms periodic sequences in the wireless signal. The first dynamic threshold effectively distinguishes between positive correlation peaks generated by genuine synchronization sequences and false positive correlation peaks caused by interference, thus reliably identifying the starting position of the synchronization sequence in a power line channel environment and providing a data basis for subsequent wireless signal synchronization. When the number of consecutive valid positive correlation peaks exceeds a quantity threshold, an initial value for a second dynamic threshold used to detect negative correlation peaks is determined based on the number of consecutive peaks. The number of consecutive valid positive correlation peaks is used as a measure of channel conditions, constructing a dynamic threshold adjustment mechanism for detecting negative correlation peaks. This improves the robustness and accuracy of negative correlation peak detection under different channel environments. The negative autocorrelation value is compared with the initial value of the second dynamic threshold. When the negative autocorrelation value is small... When the second dynamic threshold is initialized, it is updated based on the negative autocorrelation value to obtain an updated value. This updated value is then compared with the next autocorrelation value of the negative autocorrelation value. An iterative update strategy is adopted to guide the search for the negative correlation peak along the direction of decreasing autocorrelation value, which can effectively eliminate local fluctuation interference on the search path and improve the accuracy of the negative correlation peak position. Multiple autocorrelation values ​​corresponding to the signal sequence are traversed until any negative autocorrelation value is not less than the updated value obtained in the previous update. By continuously comparing until the autocorrelation value stops decreasing, the accuracy and reliability of the negative correlation peak position determination are improved. The synchronization position of the signal sequence is determined based on the signal position of the negative correlation peak. Using the positional relationship between the positive and negative correlation peaks in the synchronization sequence structure, the position of the negative correlation peak is converted into the frame synchronization position. The synchronization positioning is associated with the detection of the negative correlation peak, which improves the accuracy and anti-interference capability of the obtained synchronization position, and has higher precision and stability, realizing high-precision power line carrier signal synchronization.

[0141] In some embodiments, the determining module is configured to determine the threshold coefficient corresponding to the second dynamic threshold based on the number of consecutive valid positive correlation peaks; and to determine the initial value of the second dynamic threshold based on the threshold coefficient and the initial value of the first dynamic threshold.

[0142] In some embodiments, the threshold coefficient is the sum of the reciprocal of the consecutive numbers and the preset bias term; the absolute value of the initial value of the second dynamic threshold is not greater than the absolute value of the initial value of the first dynamic threshold; the larger the consecutive number of effective positive correlation peaks, the smaller the initial value of the second dynamic threshold.

[0143] In some embodiments, the determining module is configured to acquire the peak values ​​of a consecutive number of valid positive correlation peaks, determine the mean of the peak values ​​of the valid positive correlation peaks, and determine a reference negative value for the mean of the peak values; determine the threshold coefficient corresponding to the second dynamic threshold based on the consecutive number; and multiply the reference negative value by the threshold coefficient to determine the initial value of the second dynamic threshold.

[0144] In some embodiments, the threshold coefficient is the sum of the reciprocal of the consecutive numbers and the preset bias term; the absolute value of the initial value of the second dynamic threshold is not greater than the absolute value of the reference negative value; the larger the consecutive number of effective positive correlation peaks, the smaller the initial value of the second dynamic threshold.

[0145] In some embodiments, the synchronization module is configured to determine the synchronization position based on the signal position of the negative correlation peak when the distance between the negative correlation peak and the previous positive correlation peak is within a preset distance range; and to set the consecutive number of valid positive correlation peaks to zero and redetermine the valid positive correlation peaks when the distance between the negative correlation peak and the previous positive correlation peak is greater than the preset distance range.

[0146] In some embodiments, the receiving module is configured to perform cross-correlation operation on the signal sequence and a known signal sequence to obtain the cross-correlation result; obtain the target historical cross-correlation result; and perform autocorrelation operation on the cross-correlation result and the target historical cross-correlation result to obtain the autocorrelation value.

[0147] In some embodiments, the receiving module is configured to determine the symbol coefficient corresponding to each sampling point based on the signal amplitude corresponding to each sampling point in the signal sequence; wherein the sign of the signal amplitude is consistent with the sign of the symbol coefficient; determine the symbol sequence corresponding to the signal sequence based on the symbol coefficient corresponding to each sampling point; and perform cross-correlation operation on the symbol sequence and the known signal sequence to obtain the cross-correlation result.

[0148] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0149] The HPLC signal synchronization device based on a dual-mode communication system in this embodiment of the invention can be an electronic device or a component within an electronic device, such as an integrated circuit or a chip. This electronic device can be a terminal or other devices besides a terminal, such as a server.

[0150] The HPLC signal synchronization device based on a dual-mode communication system provided in this embodiment of the invention can realize all the processes implemented in the above-described HPLC signal synchronization method embodiment based on a dual-mode communication system. To avoid repetition, these processes will not be described again here.

[0151] In some embodiments, Figure 6 These are schematic diagrams of the structure of an electronic device provided in some embodiments of the present invention. For example... Figure 6 As shown, this embodiment of the invention also provides an electronic device 600, including a processor 601, a memory 602, and a computer program stored in the memory 602 and executable on the processor 601. When the program is executed by the processor 601, it implements the various processes of the above-described embodiment of the HPLC signal synchronization method based on a dual-mode communication system and achieves the same technical effect. To avoid repetition, it will not be described again here.

[0152] This invention provides a non-transitory computer-readable storage medium storing a computer program. When executed by a processor, the computer program implements the various processes of the above-described embodiment of the HPLC signal synchronization method based on a dual-mode communication system and achieves the same technical effect. To avoid repetition, it will not be described again here.

[0153] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable media, such as computer read-only memory (ROM), random-access memory (RAM), magnetic disks, or optical disks.

[0154] The computer-readable storage medium may include: read-only memory (ROM), random-access memory (RAM), magnetic disk or optical disk, etc.

[0155] This invention provides a computer program product, including a computer program that, when executed by a processor, implements the above-described HPLC signal synchronization method based on a dual-mode communication system.

[0156] This invention provides a chip that includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is used to run programs or instructions to implement the various processes of the above-described embodiment of the HPLC signal synchronization method based on a dual-mode communication system, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0157] It should be understood that the chip mentioned in the embodiments of the present invention may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.

[0158] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of the present invention is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0159] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the related technology, can be embodied in the form of a computer software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0160] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of the present invention.

[0161] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0162] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

Claims

1. A method for HPLC signal synchronization based on a dual-mode communication system, characterized in that, include: Upon receiving a signal sequence, an autocorrelation value is determined based on the known signal sequence, and if the autocorrelation value is greater than the initial value of a first dynamic threshold, an effective positive correlation peak is determined. When the number of consecutive valid positive correlation peaks exceeds a threshold, a threshold coefficient corresponding to a second dynamic threshold is determined based on the number of consecutive valid positive correlation peaks; an initial value of the second dynamic threshold is determined based on the threshold coefficient and the initial value of the first dynamic threshold; the threshold coefficient is the sum of the reciprocal of the number of consecutive peaks and a preset bias term; the absolute value of the initial value of the second dynamic threshold is not greater than the absolute value of the initial value of the first dynamic threshold; the larger the number of consecutive valid positive correlation peaks, the smaller the initial value of the second dynamic threshold; The negative autocorrelation value is compared with the initial value of the second dynamic threshold. When the negative autocorrelation value is less than the initial value of the second dynamic threshold, the second dynamic threshold is updated based on the negative autocorrelation value to obtain an updated value. The updated value is used to compare with the next negative autocorrelation value. Traverse multiple negative autocorrelation values ​​corresponding to the signal sequence until any negative autocorrelation value is not less than the updated value obtained in the previous update, and determine the negative autocorrelation peak; The synchronization position of the signal sequence is determined based on the signal position of the negative correlation peak.

2. The HPLC signal synchronization method based on a dual-mode communication system according to claim 1, characterized in that, The initial value of the second dynamic threshold for detecting negatively correlated peaks based on the number of consecutive peaks includes: The peak values ​​of a consecutive number of valid positive correlation peaks are obtained, the mean value of the peak values ​​of the valid positive correlation peaks is determined, and a reference negative value of the mean value of the peak values ​​is determined. The threshold coefficient corresponding to the second dynamic threshold is determined based on the continuous quantity; The initial value of the second dynamic threshold is determined by multiplying the reference negative value by the threshold coefficient.

3. The HPLC signal synchronization method based on a dual-mode communication system according to claim 2, characterized in that, The threshold coefficient is the sum of the reciprocal of the consecutive number and the preset bias term; the absolute value of the initial value of the second dynamic threshold is not greater than the absolute value of the reference negative value; the larger the consecutive number of the effective positive correlation peaks, the smaller the initial value of the second dynamic threshold.

4. The HPLC signal synchronization method based on a dual-mode communication system according to claim 1, characterized in that, Determining the synchronization position of the signal sequence based on the signal position of the negative correlation peak includes: If the distance between the negative correlation peak and the previous positive correlation peak is within a preset distance range, the synchronization position is determined based on the signal position of the negative correlation peak. If the distance between the negative correlation peak and the previous positive correlation peak is greater than a preset distance range, the number of consecutive effective positive correlation peaks is set to zero, and the effective positive correlation peaks are redefined.

5. The HPLC signal synchronization method based on a dual-mode communication system according to claim 1, characterized in that, The step of determining the autocorrelation value based on the known signal sequence upon receiving the signal sequence includes: Perform a cross-correlation operation between the signal sequence and the known signal sequence to obtain the cross-correlation result; Obtain the target's historical cross-correlation results, and perform autocorrelation calculations on the cross-correlation results and the target's historical cross-correlation results to obtain the autocorrelation value.

6. The HPLC signal synchronization method based on a dual-mode communication system according to claim 5, characterized in that, The step of performing a cross-correlation operation between the signal sequence and the known signal sequence to obtain the cross-correlation result includes: Based on the signal amplitude corresponding to each sampling point in the signal sequence, the sign coefficient corresponding to each sampling point is determined; wherein, the sign of the signal amplitude is consistent with the sign of the sign coefficient; Based on the symbol coefficients corresponding to each sampling point, determine the symbol sequence corresponding to the signal sequence; Perform cross-correlation operation on the symbol sequence and the known signal sequence to obtain the cross-correlation result.

7. An HPLC signal synchronization device based on a dual-mode communication system, characterized in that, The device includes: The receiving module is configured to determine an autocorrelation value based on a known signal sequence upon receiving a signal sequence, and to determine an effective positive correlation peak if the autocorrelation value is greater than an initial value of a first dynamic threshold. The determining module is configured to, when the number of consecutive effective positive correlation peaks exceeds a quantity threshold, determine a threshold coefficient corresponding to a second dynamic threshold based on the number of consecutive effective positive correlation peaks; determine an initial value of the second dynamic threshold based on the threshold coefficient and an initial value of a first dynamic threshold; the threshold coefficient is the sum of the reciprocal of the number of consecutive peaks and a preset bias term; the absolute value of the initial value of the second dynamic threshold is not greater than the absolute value of the initial value of the first dynamic threshold; the larger the number of consecutive effective positive correlation peaks, the smaller the initial value of the second dynamic threshold; The comparison module is used to compare the negative autocorrelation value with the initial value of the second dynamic threshold. When the negative autocorrelation value is less than the initial value of the second dynamic threshold, the second dynamic threshold is updated based on the negative autocorrelation value to obtain an updated value. The updated value is used to compare with the next negative autocorrelation value. The traversal module is used to traverse multiple negative autocorrelation values ​​corresponding to the signal sequence until any negative autocorrelation value is not less than the updated value obtained in the previous update, and to determine the negative correlation peak. A synchronization module is used to determine the synchronization position of the signal sequence based on the signal position of the negative correlation peak.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the HPLC signal synchronization method based on a dual-mode communication system as described in any one of claims 1-6.

Images