Power line communication frequency band detection method and device, and receiver

Abstract

The application discloses a power line communication frequency band detection method and device and a receiver, and the method comprises the following steps: buffering real-time received power line communication data; performing preamble signal detection according to current buffered data, and taking the current buffered data in the buffer as a preamble data sequence after detecting the preamble signal; and performing frequency band detection according to the preamble data sequence to determine a current communication frequency band. According to the application, the power line communication can be detected in real time, and the overall operation amount is reasonable and controllable.

Description

Technical Field

[0001] This invention relates to the field of power line communication technology, and specifically to a power line communication frequency band detection method and apparatus, and a receiver. Background Technology

[0002] Power line communication (PLC), also known as power line carrier communication, is a communication technology that transmits data over power lines. Unlike other wired communication methods, PLC operates in a more complex environment. Due to the diverse types of connected electrical devices, these devices generate significant noise interference on the power lines during operation, and the timing and frequency of this interference are highly variable. To address the high-noise channel environment, PLC protocols typically define multiple configurable communication frequency bands to avoid highly interfering frequencies. Furthermore, in many smart electronic product applications, proprietary communication frequency bands may be configured based on the specific channel environment.

[0003] In existing power line communication, both the transmitting and receiving ends must be configured to the same frequency band for data transmission to function correctly. In most current power line applications, the transmitting and receiving frequency bands are generally pre-configured. While this is relatively simple, it reduces the flexibility of frequency band switching, which requires complex upper-layer communication protocols or even software intervention. This approach reduces network access efficiency and limits applications that require automatic frequency band switching, such as adaptive frequency hopping and single-node simultaneous access to multiple networks.

[0004] Fast and accurate frequency band detection technology is the foundation of automatic frequency band switching. If the receiver can automatically determine the operating frequency band of the transmitted signal, it can greatly improve the efficiency of network access and also provide possibilities for a series of application extensions such as adaptive frequency hopping. However, the frequency band detection schemes currently used in power line communication are either inefficient or require large computing resources, which limits the use of frequency band detection technology in actual products. Summary of the Invention

[0005] This invention provides a method, apparatus, and receiver for detecting power line communication frequency bands, which can detect power line communication frequency bands in real time, and the overall computational load is reasonable and controllable.

[0006] Therefore, the embodiments of the present invention provide the following technical solutions:

[0007] On one hand, embodiments of the present invention provide a method for detecting power line communication frequency bands, the method comprising:

[0008] Buffer the real-time received power line communication data;

[0009] Preamble signal detection is performed based on the current cached data, and after the preamble signal is detected, the current cached data in the cache is used as the preamble data sequence.

[0010] Frequency band detection is performed based on the preamble data sequence to determine the current communication frequency band.

[0011] Optionally, the buffering of the real-time received power line communication data includes: storing the real-time received power line communication data into a FIFO buffer, wherein the maximum length of the FIFO buffer is the length of a complete preamble sequence.

[0012] Optionally, the preamble signal detection based on the current cached data includes:

[0013] Retrieve the current cached data from the FIFO buffer;

[0014] Perform autocorrelation detection on the current cached data to obtain the correlation value;

[0015] Whether a preamble signal was detected is determined based on the relevant values.

[0016] Optionally, performing autocorrelation detection on the current cached data to obtain the correlation value includes:

[0017] The current cached data is delayed by one or more preceding sequence repetition cycles to obtain delayed data;

[0018] Perform correlation operations on the delayed data and the current cached data to obtain the correlation value.

[0019] Optionally, determining whether a preamble signal is detected based on the correlation value includes:

[0020] If the correlation value is greater than a set threshold, then a preamble signal is detected;

[0021] Otherwise, it is determined that no preamble signal was detected.

[0022] Optionally, the step of determining the current communication frequency band based on the preamble data sequence includes:

[0023] The preceding data sequence is preprocessed to obtain the data to be detected;

[0024] The data to be detected is input into a pre-established classification model, and the current communication frequency band is determined based on the output of the classification model.

[0025] Optionally, the preprocessing of the preamble data sequence to obtain the data to be detected includes: accumulating the preamble data sequence according to a set repetition period to obtain the data to be detected.

[0026] On the other hand, embodiments of the present invention also provide a power line communication frequency band detection device, the device comprising: a buffer module, a preamble detection module, and a frequency band detection module;

[0027] The caching module is used to cache the power line communication data received in real time;

[0028] The preamble detection module is used to detect a preamble signal based on the current cached data in the cache module, and after detecting the preamble signal, lock the current cached data in the cache module and instruct the frequency band detection module to perform frequency band detection.

[0029] The frequency band detection module is used to obtain the current cached data from the cache module as a preamble data sequence after receiving the instruction from the preamble detection module, and perform frequency band detection based on the preamble data sequence to determine the current communication frequency band.

[0030] Optionally, the caching module is a FIFO buffer, and the maximum length of the FIFO buffer is the length of a complete preamble sequence.

[0031] Optionally, the leader detection module includes:

[0032] A data extraction unit is used to obtain the current cached data from the FIFO buffer;

[0033] The correlation calculation unit is used to perform autocorrelation detection on the current cached data to obtain a correlation value;

[0034] The correlation value detection unit is used to determine whether a preamble signal is detected based on the correlation value. After detecting the preamble signal, it locks the current cached data in the cache module and instructs the frequency band detection module to perform frequency band detection.

[0035] Optionally, the related computing unit includes:

[0036] The delay unit is used to delay the current cached data by one or more sequence repetition cycles to obtain delayed data;

[0037] The correlation value calculation unit is used to perform correlation operations on the delayed data and the current cached data to obtain the correlation value.

[0038] Optionally, the frequency band detection module includes:

[0039] The preceding data acquisition unit is used to acquire the current cached data as the preceding data sequence from the cache module after receiving the instruction from the preceding detection module;

[0040] The preprocessing unit is used to preprocess the preceding data sequence to obtain the data to be detected;

[0041] The classification unit is used to input the data to be detected into a pre-established classification model and determine the current communication frequency band based on the output of the classification model.

[0042] On the other hand, embodiments of the present invention also provide a power line communication receiver, including: a receiving module and the power line communication frequency band detection device described above;

[0043] The receiving module is used to receive power line communication data in real time;

[0044] The power line communication frequency band detection device is used to determine the current communication frequency band based on the power line communication data received in real time by the receiving module.

[0045] The power line communication frequency band detection method, apparatus, and receiver provided in this invention buffer the real-time received power line communication data, perform preamble signal detection based on the current buffered data, and, upon detection of the preamble signal, use the current buffered data as the preamble data; then, perform frequency band detection based on the preamble data to determine the current communication frequency band. This invention separates preamble detection and frequency band detection, enabling real-time communication frequency band detection even with high-speed data input.

[0046] Furthermore, the frequency band detection method using preprocessing and neural networks can achieve good frequency band resolution even under high noise conditions, making it suitable for power line communication environments.

[0047] This invention can be implemented using a combination of hardware and software, offering flexible solutions with controllable overall computing and storage resources. It is robust because no hardware modifications are required when the number of frequency bands changes. It can be applied to various narrow-band and wide-band power line communication standards, and is particularly suitable for high-speed communication applications with a large number of frequency bands. Attached Figure Description

[0048] Figure 1 This is a schematic diagram of the preamble structure of the IEEE P1901.1 protocol;

[0049] Figure 2 This is a flowchart of the power line communication frequency band detection method provided in the embodiments of the present invention;

[0050] Figure 3 This is a schematic diagram illustrating the accumulation of the leading data sequence in an embodiment of the present invention;

[0051] Figure 4 This is a schematic diagram of a power line communication frequency band detection device provided in an embodiment of the present invention;

[0052] Figure 5 This is a schematic diagram of a preamble detection module in one embodiment of the present invention;

[0053] Figure 6 This is a schematic diagram of a power line communication receiver in an embodiment of the present invention. Detailed Implementation

[0054] To make the above-mentioned objectives, features and beneficial effects of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0055] In major power line communication protocols, a continuously repeating preamble sequence is typically defined at the beginning of a data frame. This preamble sequence is used for receiver synchronization, for example... Figure 1 As shown, the preamble sequence of the Institute of Electrical and Electronics Engineers (IEEE) P1901.1 protocol (hereinafter referred to as P1901.1) consists of 10 repeated SYNCP symbols and 2 SYNCM symbols that are opposite to SYNCP (i.e., the SYNCM symbols have a 180° phase difference with the SYNCP symbols).

[0056] Different frequency bands have different preamble sequence values, but the preamble length and repetition period are the same. Based on this characteristic, this invention provides a power line communication frequency band detection method, device, and receiver. The method uses the preamble sequence to detect the communication frequency band. Specifically, the method first detects the preamble signal based on the real-time received power line communication data. After detecting the preamble signal, the method then detects the frequency band based on the current buffered data to determine the current communication frequency band. This enables real-time detection of the communication frequency band even with high-speed data input.

[0057] like Figure 2 The diagram shows a flowchart of a power line communication frequency band detection method provided in an embodiment of the present invention, which includes the following steps:

[0058] Step 201: Buffer the real-time received power line communication data.

[0059] In this embodiment of the invention, a First-In-First-Out (FIFO) buffer can be used to buffer the continuous data stream. That is, the power line communication data received in real time is stored in the FIFO buffer, and the subsequent detection process needs to extract the current buffered data from the FIFO buffer for detection.

[0060] The FIFO memory is divided into a write area and a read area. Read and write operations can be performed asynchronously. Data written in the write area is read out of the read area in the order it was written. In practical applications, the maximum length of the FIFO buffer can be set to the length of a complete preamble sequence. If the length of the FIFO buffer is less than the length of a complete preamble sequence, subsequent detection can still be completed, but this will have a certain impact on detection performance. In practical applications, adjustments can be made according to the requirements of detection performance.

[0061] In this embodiment of the invention, the FIFO buffer can be divided into two modes: working and locked. When working, it saves the received input data; when locked, the buffered data remains unchanged.

[0062] Step 202: Detect a preamble signal based on the current cached data, and after detecting the preamble signal, use the current cached data in the cache as the preamble data sequence.

[0063] Specifically, the current cached data is obtained from the FIFO buffer, autocorrelation detection is performed on the current cached data to obtain a correlation value, and the detection of a preamble signal is determined based on the correlation value.

[0064] Since the preamble signal is a sequence of repeated data, this characteristic is used to delay the received communication data by one or more preamble sequence repetition cycles to obtain delayed data. Then, the delayed data and the original data (i.e., the current buffered data) are correlated to obtain the correlation value.

[0065] When the received communication data is a preamble sequence with repeating sequence characteristics, the calculated correlation value will be large, while in other cases, the correlation value will be small. Therefore, the magnitude of the calculated correlation value can be used to determine whether a preamble signal has been detected; that is, the calculated correlation value can be used to determine whether the current buffered data is a preamble sequence.

[0066] For example, a threshold can be preset. If the relevant value is greater than the preset threshold, it is determined that a preamble signal has been detected; otherwise, it is determined that no preamble signal has been detected.

[0067] It should be noted that the threshold may vary depending on the specific method of the correlation calculation. For example, the correlation value of each bit in the delayed data and the original data can be calculated to obtain the total correlation value, which is then used for judgment. Alternatively, the total correlation value can be calculated, and then the average correlation value can be calculated based on the total number of data involved in the correlation calculation. The threshold will differ in these two cases, and in practical applications, it may need to be set according to the specific correlation calculation method used. This embodiment of the invention does not limit this.

[0068] In addition, it should be noted that under the same communication protocol, although the preamble values ​​of different frequency bands are different, the data repetition pattern is the same. Therefore, the autocorrelation delay detection method in this embodiment of the invention is applicable to preamble sequences of various frequency bands.

[0069] Step 203: Perform frequency band detection based on the preamble data sequence to determine the current communication frequency band.

[0070] In practical applications, the current communication frequency band can be determined using a classification model based on the preamble data. The classification model can be, but is not limited to, a neural network model; the input to the classification model is the preamble data, and the output is the frequency band category.

[0071] Neural networks possess strong classification capabilities, maintaining excellent performance even in noisy environments, making them suitable for high-noise channel environments in power line communication. Furthermore, neural networks offer flexibility, particularly in their ability to be easily adapted to the number of frequency bands used by the communication protocol employed in this solution. For instance, when increasing or decreasing the number of communication frequency bands as needed, only the number of output nodes in the neural network's output layer needs to be modified, with minimal impact on the overall computational scale of the neural network. This is highly advantageous for use in multi-band communication protocols or applications.

[0072] Furthermore, considering the long length of the preceding data sequence, inputting the entire preceding data sequence into the neural network model would result in a very large neural network, increasing the computational load and impacting computational efficiency.

[0073] Therefore, in another non-limiting embodiment of the present invention, the preamble data sequence can be preprocessed to obtain the data to be detected; then the data to be detected can be input into a pre-established classification model, and the current communication frequency band can be determined according to the output of the classification model.

[0074] For example, the preamble data sequence is accumulated according to a set repetition period to obtain the data to be detected. Taking the P1901.1 protocol as an example, the preamble data sequence has 12 repeating symbols, each symbol having 1024 sampling points. It should be noted that since the last two symbols are SYNCM, which is the opposite of the preceding SYNCP values, a subtraction operation is performed on the last two symbols.

[0075] The repeated addition process of the leading data sequence is as follows: Figure 3 As shown.

[0076] Reference Figure 3The first sampling point of each of the 1st to 12th symbols is accumulated to obtain the first accumulated value. Then the second sampling point of each of the 1st to 12th symbols is accumulated to obtain the second accumulated value. This process is repeated until 1024 accumulated values ​​are obtained. These 1024 accumulated values ​​are used as the data to be detected.

[0077] The preprocessing and accumulation operations described above reduce the length of the data sequence input to the neural network model, thus reducing the amount of input data and consequently decreasing the overall size of the neural network. Furthermore, since the preceding data is repeated, using repetitive cycles for data accumulation improves the signal-to-noise ratio, thereby increasing the classification success rate of the neural network.

[0078] Of course, in practical applications, other methods can also be used to reduce the amount of input data for the neural network model, such as selecting a portion of the sampled values ​​for each symbol in the preceding data sequence and accumulating them to obtain the data to be detected. This embodiment of the invention does not limit this.

[0079] It should be noted that various types of neural networks with classification functions can be applied to the present invention. Considering the scale of implementation, in specific applications, a Convolutional Neural Network (CNN) can be used for frequency band classification. The CNN may include an input layer, two convolutional layers, a fully connected layer, and an output layer.

[0080] The input and output nodes of the convolutional neural network can be adjusted according to the protocols that need to be supported. For example, for the P1901.1 protocol, the input layer has 1024 input nodes and the output layer contains two output nodes, corresponding to two classification outputs, which are the two communication frequency bands specified by the P1901.1 protocol.

[0081] Through simulation testing, with support for the P1901.1 protocol, the solution of this invention can achieve a 100% classification success rate when the signal-noise ratio (SNR) of the received communication data is equal to -10dB, that is, the frequency band detection accuracy can reach 100%, which can fully meet the needs of power line communication application scenarios.

[0082] The power line communication frequency band detection method provided in this invention buffers the real-time received power line communication data, detects a preamble signal based on the current buffered data, and uses the current buffered data as the preamble data after detecting the preamble signal. Then, frequency band detection is performed based on the preamble data to determine the current communication frequency band. This invention separates preamble detection and frequency band detection. In practical applications, the above detection process can be completed using a combination of hardware and software. Data buffering and preamble detection are implemented in hardware to meet the requirements of high data rate input, while frequency band detection is implemented in software, allowing for flexible adjustment of the number of detected frequency bands and control of the overall system hardware scale. Using the power line communication frequency band detection method provided in this invention, real-time frequency band detection can be achieved while also reasonably controlling overall computing resources.

[0083] Furthermore, by employing a classification model based on neural networks, the number of frequency bands can be flexibly increased or decreased by adding or reducing the input nodes and / or output nodes of the neural network according to different application scenarios. Specifically, the input nodes can be adjusted according to the number of sampling points of the preamble symbol, and the output nodes can be adjusted according to the number of working frequency bands.

[0084] For example, for the detection of the two operating frequency bands defined by the P1901.1 protocol: band0 (1.953MHz~11.96MHz) and band1 (2.441MHz~5.615MHz), the input nodes of the neural network can be set to 1024 and the output nodes to 2.

[0085] For example, for the detection of the three operating frequency bands specified in the International Telecommunication Union (ITU) standard G9903 protocol: CELENCE-A (39.938kHz~90.625kHz), CELENCE-B (98.4375kHz~121.875kHz), and FCC (159.375kHz~478.125kHz), the neural network can be set to have 256 input nodes and 3 output nodes.

[0086] For example, in addition to the three frequency bands mentioned above, the G3-PLC protocol also specifies a series of frequency bands such as CENELEC-C / BC / D / BCD / BD. For this, the input nodes of the neural network can be set to 256 and the output nodes to 8.

[0087] Accordingly, embodiments of the present invention also provide a power line communication frequency band detection device, such as... Figure 4 The diagram shown is a structural schematic of a power line communication frequency band detection device provided in an embodiment of the present invention.

[0088] The detection device 400 includes: a buffer module 401, a preamble detection module 402, and a frequency band detection module 403. Wherein:

[0089] The caching module 401 is used to cache the power line communication data received in real time;

[0090] The preamble detection module 402 is used to detect the preamble signal based on the current cached data in the cache module 401, and after detecting the preamble signal, lock the current cached data in the cache module 401 and prompt the frequency band detection module 403 to perform frequency band detection.

[0091] The frequency band detection module 403, upon receiving an instruction from the preamble detection module 402, retrieves the current cached data from the cache module 401 as a preamble data sequence, performs frequency band detection based on the preamble data sequence, and determines the current communication frequency band.

[0092] In practical applications, the caching module 401 can be a FIFO buffer, the maximum length of which is the length of a complete preamble sequence. The FIFO buffer can have two modes: working and locked. When working, it stores the received input data; when locked, the buffered data remains unchanged.

[0093] Since the preamble signal is a sequence of repeated data, the preamble detection module 402 can utilize this characteristic to determine whether a preamble signal has been detected by performing correlation operations on the current cached data and based on the obtained correlation value.

[0094] like Figure 5 As shown, in a non-limiting embodiment, the leader detection module 402 may include the following units:

[0095] Data extraction unit 421 is used to obtain the current cached data from the FIFO buffer;

[0096] The correlation operation unit 422 is used to perform autocorrelation detection on the current cached data to obtain a correlation value;

[0097] The correlation value detection unit 423 is used to determine whether a preamble signal is detected based on the correlation value. After detecting the preamble signal, it locks the current cached data in the cache module and instructs the frequency band detection module to perform frequency band detection.

[0098] Specifically, the correlation operation unit 422 may include a delay unit 4221 and a correlation value calculation unit 4222; the delay unit 4221 is used to delay the current cached data by one or more sequence repetition cycles to obtain delayed data; the correlation value calculation unit 4222 is used to perform correlation operations on the delayed data and the current cached data to obtain a correlation value.

[0099] Specifically, the correlation value detection unit 423 can determine whether a preamble signal is detected based on the magnitude of the correlation value and a preset threshold. If the correlation value is greater than the preset threshold, it is determined that a preamble signal is detected; otherwise, it is determined that a preamble signal is not detected.

[0100] Simultaneously refer to Figure 4 and Figure 5 After the correlation value detection unit 423 detects the preamble signal, it can send a lock indication signal to the cache module 401, causing the cache module 401 to save the currently cached data, which is the preamble data sequence. Simultaneously, the correlation value detection unit 423 also needs to instruct the frequency band detection module 403 to begin frequency band detection. In practical applications, the correlation value detection unit 423 can instruct the frequency band detection module 403 to begin frequency band detection via an interrupt or by sending an indication signal; this embodiment of the invention does not limit the specific method used.

[0101] Accordingly, after receiving the corresponding instruction, the frequency band detection module 403 obtains the current cached data from the cache module 401 as a preamble data sequence, and determines the current communication frequency band by detecting the preamble data sequence.

[0102] In a non-limiting embodiment, the frequency band detection module 403 may include: a preamble data acquisition unit and a classification unit; wherein:

[0103] The preceding data acquisition unit is used to acquire the current cached data from the cache module as a preceding data sequence after receiving the instruction from the preceding detection module;

[0104] The classification unit is used to input the preamble data sequence into a pre-established classification model and determine the current communication frequency band based on the output of the classification model.

[0105] The classification model can be constructed by a corresponding model building module (not shown). The model building module can be part of the device of the present invention or can be independent of the device of the present invention, and there is no limitation thereto.

[0106] In practical applications, the classification model can be a neural network model, such as CNN.

[0107] In another non-limiting embodiment, the frequency band detection module 403 may further include: a preprocessing unit for preprocessing the preamble data sequence, for example, accumulating the preamble data sequence according to a set repetition period to obtain the data to be detected.

[0108] Accordingly, in this embodiment, the classification unit is used to input the data to be detected into a pre-established classification model and determine the current communication frequency band based on the output of the classification model.

[0109] By performing accumulation operations on the preceding data sequence through the preprocessing unit, the length of the data sequence input to the neural network model can be reduced, which means reducing the amount of input data to the neural network model and thus reducing the overall size of the neural network. Simultaneously, since the preceding data is repeated, using repetitive cycles for data accumulation can improve the signal-to-noise ratio of the data, thereby increasing the classification success rate of the neural network.

[0110] It should be noted that, in practical applications, the modules of the power line communication frequency band detection device provided in this embodiment of the invention can be implemented in a combination of hardware and software. For example, the buffer module and the preamble detection module are implemented in hardware, while the frequency band detection module is implemented in software. This allows the preamble detection and frequency band detection to be performed separately, thereby enabling real-time detection of the communication frequency band under high-speed data input conditions.

[0111] Furthermore, the frequency band detection uses a preprocessing and neural network approach, which can achieve good frequency band resolution even in high-noise environments, making it suitable for power line communication environments.

[0112] Accordingly, embodiments of the present invention also provide a power line communication receiver, such as... Figure 6 As shown, the receiver 600 includes: a receiving module 601 and the aforementioned power line communication frequency band detection device 400. Wherein:

[0113] The receiving module 601 is used to receive power line communication data in real time;

[0114] The power line communication frequency band detection device 400 is used to determine the current communication frequency band based on the power line communication data received in real time by the receiving module 601.

[0115] Regarding the modules / units included in the various devices and products described in the above embodiments, they can be software modules / units, hardware modules / units, or a combination of both. For example, for devices and products applied to or integrated into a chip, all modules / units can be implemented using hardware methods such as circuits, or at least some modules / units can be implemented using software programs running on a processor integrated within the chip, while the remaining (if any) modules / units can be implemented using hardware methods such as circuits. For devices and products applied to or integrated into a chip module, all modules / units can be implemented using hardware methods such as circuits. Different modules / units can be located in the same component (e.g., chip, circuit module, etc.) or different components of the chip module, or at least some modules / units can be implemented using hardware methods such as circuits. The implementation is achieved through a software program that runs on a processor integrated within the chip module. The remaining modules / units (if any) can be implemented using hardware methods such as circuits. For various devices and products applied to or integrated into terminal equipment, each of their modules / units can be implemented using hardware methods such as circuits. Different modules / units can be located in the same component (e.g., chip, circuit module, etc.) or different components within the terminal equipment. Alternatively, at least some modules / units can be implemented using a software program that runs on a processor integrated within the terminal equipment, while the remaining modules / units (if any) can be implemented using hardware methods such as circuits.

[0116] It should be noted that "multiple" in the embodiments of this application refers to two or more.

[0117] The descriptions of "first," "second," etc., appearing in the embodiments of this application are for illustrative purposes and to distinguish the objects being described. They have no order and do not indicate any special limitation on the number of devices in the embodiments of this application, nor do they constitute any limitation on the embodiments of this application.

[0118] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless means.

[0119] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0120] In the several embodiments provided in this application, it should be understood that the disclosed methods, apparatuses, and systems can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for example, the division of units is merely a logical functional division, and other division methods may exist in actual implementation; for example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0121] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0122] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can be physically included separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0123] The integrated unit implemented as a software functional unit described above can be stored in a computer-readable storage medium. This software functional unit, stored in a storage medium, includes several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute some steps of the methods described in the various embodiments of this application.

[0124] While this application discloses the above information, it is not limited thereto. Any person skilled in the art can make various modifications and alterations without departing from the spirit and scope of this application; therefore, the scope of protection of this application shall be determined by the scope defined in the claims.

Claims

1. A method for detecting power line communication frequency bands, characterized in that, The method includes: Buffer the real-time received power line communication data; Preamble signal detection is performed based on the current cached data, and after the preamble signal is detected, the current cached data in the cache is used as the preamble data sequence. Frequency band detection is performed using a pre-built classification model based on the preamble data sequence to determine the current communication frequency band. The frequency band detection process includes: accumulating the preamble data sequence according to a set repetition period to obtain the data to be detected; inputting the data to be detected into a pre-built classification model, and determining the current communication frequency band based on the output of the classification model. The input nodes of the classification model are determined based on the number of sampling points of the preamble symbol, and the output nodes of the classification model are determined based on the number of operating frequency bands.

2. The method according to claim 1, characterized in that, The buffering of real-time received power line communication data includes: The real-time received power line communication data is stored in a FIFO buffer, the maximum length of which is the length of a complete preamble sequence.

3. The method according to claim 2, characterized in that, The preamble detection based on the current cached data includes: Retrieve the current cached data from the FIFO buffer; Perform autocorrelation detection on the current cached data to obtain the correlation value; Whether a preamble signal was detected is determined based on the relevant values.

4. The method according to claim 3, characterized in that, The autocorrelation test performed on the current cached data to obtain the correlation value includes: The current cached data is delayed by one or more preceding sequence repetition cycles to obtain delayed data; Perform correlation operations on the delayed data and the current cached data to obtain the correlation value.

5. The method according to claim 3, characterized in that, The step of determining whether a preamble signal is detected based on the correlation value includes: If the correlation value is greater than a set threshold, then a preamble signal is detected; Otherwise, it is determined that no preamble signal was detected.

6. A power line communication frequency band detection device, characterized in that, The device includes: a buffer module, a preamble detection module, and a frequency band detection module; The caching module is used to cache the power line communication data received in real time; The preamble detection module is used to detect a preamble signal based on the current cached data in the cache module, and after detecting the preamble signal, lock the current cached data in the cache module and instruct the frequency band detection module to perform frequency band detection. The frequency band detection module, upon receiving an instruction from the preamble detection module, retrieves the current cached data from the cache module as a preamble data sequence, and performs frequency band detection based on the preamble data sequence using a pre-built classification model to determine the current communication frequency band. The frequency band detection process includes: accumulating the preamble data sequence according to a set repetition period to obtain the data to be detected; inputting the data to be detected into the pre-built classification model, and determining the current communication frequency band based on the output of the classification model.

7. The apparatus according to claim 6, characterized in that, The caching module is a FIFO buffer, and the maximum length of the FIFO buffer is the length of a complete preamble sequence.

8. The apparatus according to claim 7, characterized in that, The leader detection module includes: A data extraction unit is used to obtain the current cached data from the FIFO buffer; The correlation calculation unit is used to perform autocorrelation detection on the current cached data to obtain a correlation value; The correlation value detection unit is used to determine whether a preamble signal is detected based on the correlation value. After detecting the preamble signal, it locks the current cached data in the cache module and instructs the frequency band detection module to perform frequency band detection.

9. The apparatus according to claim 8, characterized in that, The relevant computation unit includes: The delay unit is used to delay the current cached data by one or more sequence repetition cycles to obtain delayed data; The correlation value calculation unit is used to perform correlation operations on the delayed data and the current cached data to obtain the correlation value.

10. The apparatus according to any one of claims 6 to 9, characterized in that, The frequency band detection module includes: The preceding data acquisition unit is used to acquire the current cached data as the preceding data sequence from the cache module after receiving the instruction from the preceding detection module; The preprocessing unit is used to preprocess the preceding data sequence to obtain the data to be detected; The classification unit is used to input the data to be detected into a pre-established classification model and determine the current communication frequency band based on the output of the classification model.

11. A power line communication receiver, characterized in that, include: The receiving module, and the power line communication frequency band detection device as described in any one of claims 6 to 10; The receiving module is used to receive power line communication data in real time; The power line communication frequency band detection device is used to determine the current communication frequency band based on the power line communication data received in real time by the receiving module.

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