Signal bandwidth identification method, electronic device, and storage medium

Abstract

The application discloses a signal bandwidth identification method, an electronic device and a storage medium, and belongs to the technical field of communication. The method comprises the following steps: receiving a to-be-processed signal; sampling the to-be-processed signal by using a preset sampling rate to obtain a sampling signal; determining a target sequence from the sampling signal; detecting the peak point number of the target sequence; determining a target signal bandwidth based on the peak point number of the target sequence and a bandwidth reference template, wherein the bandwidth reference template is used for indicating the corresponding relationship between a plurality of different signal bandwidths and peak point numbers. According to the application, the peak point number of the target sequence is detected, and then the target signal bandwidth is determined based on the peak point number of the target sequence and the bandwidth reference template, so that the process is simple, the bandwidth of the to-be-processed signal can be quickly determined, subsequent related steps can be performed, and time consumption is reduced.

Description

Technical Field

[0001] This application relates to the field of communication technology, specifically to a method for identifying signal bandwidth, an electronic device, and a storage medium. Background Technology

[0002] With the evolution of Wi-Fi versions, five bandwidth types now exist: 20M, 40M, 80M, 160M, and 320M. To demodulate a Wi-Fi signal, the default approach is to select a primary 20M bandwidth based on channel allocation for demodulation and analysis, recovering the SIGNAL field carrying bandwidth information. Subsequent processing is then configured according to the demodulated bandwidth. However, because the structure of the SIGNAL field differs between different Wi-Fi versions, and even among different PPDU (Physical Layer Protocol Data Unit) formats within the same Wi-Fi version, demodulation and analysis of Wi-Fi signals requires first determining the Wi-Fi version and PPDU format before selecting the appropriate analysis method. Determining the Wi-Fi version and PPDU format necessitates first identifying the received signal, such as its bandwidth. Summary of the Invention

[0003] This application provides a method, electronic device, and storage medium for identifying signal bandwidth, which can quickly determine the signal bandwidth for subsequent steps, reducing time consumption. The technical solution is as follows:

[0004] On the one hand, a method for identifying signal bandwidth is provided, the method comprising:

[0005] Receive signals to be processed;

[0006] The signal to be processed is sampled using a preset sampling rate to obtain a sampled signal;

[0007] Determine the target sequence from the sampled signal;

[0008] Detect the number of peak points in the target sequence;

[0009] The target signal bandwidth is determined based on the number of peak points and the bandwidth reference template of the target sequence. The bandwidth reference template is used to indicate the correspondence between multiple different signal bandwidths and the number of peak points.

[0010] Optionally, determining the target sequence from the sampled signal includes:

[0011] Identify the starting point of the specified field sequence in the sampled signal;

[0012] The sequence signal within a preset time period, starting from the starting point of the specified field sequence, is determined as the target sequence;

[0013] The specified field sequence is an L-STF sequence.

[0014] Optionally, the detection of the number of peak points in the target sequence includes:

[0015] The target sequence is divided into multiple subsequences according to the periodic repetition of a specified field, and the period length of each subsequence is equal.

[0016] Detect the number of valid peak points corresponding to each of the plurality of subsequences;

[0017] The sum of the effective peak points corresponding to the multiple subsequences is determined as the peak point number of the target sequence.

[0018] Optionally, detecting the number of valid peak points corresponding to each of the plurality of subsequences includes:

[0019] Preliminary peak detection is performed on the sampling points of each of the multiple subsequences to determine the candidate peak points in the multiple subsequences;

[0020] The plurality of subsequences are sequentially used as the target subsequence;

[0021] Determine whether the sampling point at the same position as the candidate peak point in the target subsequence in the remaining subsequence is also a candidate peak point in the remaining subsequence, wherein the remaining subsequence is the sequence other than the target subsequence among the plurality of subsequences;

[0022] When the number of times that the sampling point at the same position as the candidate peak point in the target subsequence is also a candidate peak point in the remaining subsequence is greater than the number of times the candidate peak point in the remaining subsequence is determined to be a valid peak point, the candidate peak point in the target subsequence is determined to be a valid peak point. The number of times the threshold is positively correlated with the signal-to-noise ratio and the number of the multiple subsequences.

[0023] Optionally, the preliminary peak detection of sampling points in each of the plurality of sub-sequences to determine candidate peak points in the plurality of sub-sequences includes:

[0024] The value of the sampling point is compared with the value of the previous sampling point and the value of the next sampling point, wherein the previous sampling point is the sampling point before the sampling point and the next sampling point is the sampling point after the sampling point;

[0025] If the value of the sampling point is greater than the value of the previous sampling point and greater than the value of the next sampling point, then the sampling point is determined as the candidate peak point.

[0026] Optionally, determining the target signal bandwidth based on the peak count and bandwidth reference template of the target sequence includes:

[0027] Based on the number of peak points, the initial signal bandwidth is determined from the bandwidth reference template;

[0028] The target signal bandwidth is obtained by filtering the target sequence based on the initial signal bandwidth.

[0029] Optionally, filtering the target sequence based on the initial signal bandwidth to obtain the target signal bandwidth includes:

[0030] Use the initial signal bandwidth as the current cutoff frequency;

[0031] The target sequence is filtered using the current cutoff frequency to obtain a filtered target sequence.

[0032] Update the target sequence with the filtered target sequence;

[0033] Detect the number of peak points in the target sequence;

[0034] Based on the peak point count, alternative bandwidths are matched from the bandwidth reference template;

[0035] Compare whether the candidate bandwidth is equal to the current cutoff frequency;

[0036] If the candidate bandwidth is not equal to the current cutoff frequency, the current cutoff frequency is updated to the candidate bandwidth, and the target sequence is filtered using the current cutoff frequency until the candidate bandwidth is equal to the current cutoff frequency.

[0037] If the alternative bandwidth is equal to the current cutoff frequency, then the alternative bandwidth is used as the target signal bandwidth.

[0038] Optionally, after filtering the target sequence based on the initial signal bandwidth, the method further includes:

[0039] The target sequence is segmented and periodically averaged, the segmentation and periodic averaging including:

[0040] The target sequence is divided into multiple subsequences according to the periodic repetition of a specified field, and the period length of each subsequence is equal.

[0041] For each sampling point in the plurality of subsequences: calculate the average value of the sampling points in the plurality of subsequences, and update the sampling point based on the average value;

[0042] The multiple subsequences after updating the sampling points are integrated to obtain the target sequence after segmentation and periodic averaging.

[0043] Optionally, before detecting the number of peak points in the target sequence, the method further includes:

[0044] The target sequence is segmented and periodically averaged, the segmentation and periodic averaging including:

[0045] The target sequence is divided into multiple subsequences according to the periodic repetition of a specified field, and the period length of each subsequence is equal.

[0046] For each sampling point in the plurality of subsequences: calculate the average value of the sampling points in the plurality of subsequences, and update the sampling point based on the average value;

[0047] The multiple subsequences after updating the sampling points are integrated to obtain the target sequence after segmentation and periodic averaging;

[0048] The number of peak points detected in the target sequence includes:

[0049] The number of peak points in the target sequence after segmentation and periodic averaging is detected.

[0050] Optionally, determining the target signal bandwidth based on the peak count and bandwidth reference template of the target sequence includes:

[0051] Compare the number of peak points in the target sequence with the difference between the number of peak points corresponding to multiple different signal bandwidths in the bandwidth reference template;

[0052] The signal bandwidth corresponding to the peak number that differs the least from the peak number of the target sequence in the bandwidth reference template is determined as the target signal bandwidth.

[0053] Optionally, the signal to be processed is a WIFI signal, and the preset sampling rate is greater than 320MHz.

[0054] On the other hand, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the signal bandwidth identification method described above.

[0055] On the other hand, a computer-readable storage medium is provided, wherein a computer program is stored therein, and the computer program can be executed by a processor to implement the steps of the signal bandwidth identification method described above.

[0056] On the other hand, a computer program product containing instructions is provided, which, when run on a computer, cause the computer to perform the steps of the signal bandwidth identification method described above.

[0057] The technical solution provided in this application can bring at least the following beneficial effects:

[0058] The embodiments of this application detect the number of peak points in the target sequence, and then determine the target signal bandwidth based on the number of peak points in the target sequence and the bandwidth reference template. The process is simple and can quickly determine the bandwidth of the signal to be processed in order to perform subsequent related steps, reducing the time consumption. Attached Figure Description

[0059] Figure 1 A flowchart illustrating a method for identifying signal bandwidth provided in an embodiment of this application;

[0060] Figure 2 A flowchart of an iterative filtering method provided in an embodiment of this application;

[0061] Figure 3 A flowchart illustrating another method for identifying signal bandwidth provided in an embodiment of this application;

[0062] Figure 4 A flowchart illustrating another method for identifying signal bandwidth provided in an embodiment of this application;

[0063] Figure 5 A flowchart illustrating another method for identifying signal bandwidth provided in an embodiment of this application. Detailed Implementation

[0064] The present invention will now be described in further detail with reference to specific embodiments and accompanying drawings. Similar elements in different embodiments are referred to by associated similar element reference numerals. In the following embodiments, many details are described to facilitate a better understanding of this application. However, those skilled in the art will readily recognize that some features may be omitted in different situations, or may be replaced by other elements, materials, or methods. In some cases, certain operations related to this application are not shown or described in the specification. This is to avoid obscuring the core parts of this application with excessive description. For those skilled in the art, detailed description of these related operations is not necessary; they can fully understand the related operations based on the description in the specification and general technical knowledge in the art.

[0065] Furthermore, the features, operations, or characteristics described in the specification can be combined in any suitable manner to form various embodiments. At the same time, the steps or actions in the method description can be rearranged or adjusted in a manner obvious to those skilled in the art. Therefore, the various orders in the specification and drawings are only for the clear description of a particular embodiment and do not imply a necessary order, unless otherwise stated that a particular order must be followed.

[0066] The serial numbers assigned to components in this document, such as "first" and "second," are used only to distinguish the described objects and have no sequential or technical meaning. The terms "connection" and "linkage" used in this application, unless otherwise specified, include both direct and indirect connections (linkages).

[0067] Before providing a detailed description of the signal bandwidth identification method provided in the embodiments of this application, the application scenarios involved in the embodiments of this application will be introduced first.

[0068] As Wi-Fi versions have evolved, bandwidth has expanded from 20Mbps to a maximum of 320Mbps to support higher transmission rates. Specifically, 802.11a / g only supports 20Mbps bandwidth, 802.11n supports 20Mbps and 40Mbps bandwidth, 802.11ac / ax supports 20Mbps, 40Mbps, 80Mbps, and 160Mbps bandwidth, and 802.11be supports 20Mbps, 40Mbps, 80Mbps, 160Mbps, and 320Mbps bandwidth.

[0069] Traditional bandwidth identification is accomplished by analyzing the bandwidth indicator bit in the SIGNAL field. First, based on the channel allocation rules and the current center frequency, the primary 20MHz channel is selected and downsampled to 20MHz. Then, signal acquisition and timing synchronization are completed by detecting the L-STF (Legacy Short Training Field) and L-LTF (Legacy Long Training Field) in the preamble. After that, L-STF is used for coarse frequency offset estimation, L-LTF is used for fine frequency offset estimation, and L-SIG (Legacy SIGNAL Field) is used for channel estimation and equalization. Finally, the SIGNAL field located after L-SIG, which is specific to the frame type, is parsed. Different methods are used to extract the bandwidth indicator bit for different frame formats. However, this method requires designing specialized approaches for different Wi-Fi versions and PPDU formats. Determining bandwidth necessitates first identifying the Wi-Fi version and PPDU format, leading to multiple demodulation processes, numerous processing steps, long processing times, complex logic, and complicated implementation. Furthermore, since a spectrum analyzer is a measurement tool, users can set its center frequency to any value, and it does not adhere to the logical protocol rules of Wi-Fi. Therefore, a spectrum analyzer cannot replace the Wi-Fi network card itself in determining the logical concept of the "main channel." Consequently, using the above method to determine the bandwidth of a Wi-Fi signal in spectrum analysis has certain limitations.

[0070] Alternatively, bandwidth can be obtained through spectrum analysis: First, calculate the signal power envelope to find the frame start point. Then, extract a segment of data after the frame start point to perform an FFT (Fast Fourier Transform) and calculate the power spectrum. Afterward, calculate the total signal energy. When the accumulated energy reaches 99% of the total energy, determine the corresponding frequency range. While spectrum analysis seems simple and direct, ensuring accurate bandwidth calculation requires extracting a sufficiently long data segment for FFT, and searching for the start and end frequencies of the power spectrum is time-consuming. Furthermore, it is susceptible to noise interference, leading to inaccurate bandwidth calculations. Most importantly, in situations with multiple devices coexisting, if adjacent channels are occupied by other devices, the calculated bandwidth will be directly incorrect.

[0071] Based on this, embodiments of this application provide a method for identifying signal bandwidth. This method detects the number of peak points in a target sequence and then determines the target signal bandwidth based on the number of peak points and a bandwidth reference template. Compared to traditional methods that analyze the bandwidth indicator bit in the SIGNAL field, the method provided in this application does not require subsequent fine synchronization, channel estimation, equalization, and SIGNAL bit recovery to know the bandwidth information in advance. It is simple to process and has a fast identification speed. Furthermore, it uses the same processing method for different frame formats, eliminating the need to design separate bandwidth indicator bit extraction methods for different frame formats, thus exhibiting good compatibility. Compared to methods that calculate bandwidth by analyzing the spectrum, the method provided in this application does not require time-consuming FFT operations. The calculation of peak points is very fast, resulting in a faster identification speed. Even if signals from other devices exist in adjacent channels, it will not affect the bandwidth identification process. It is unaffected by interference from other device signals in space, leading to more accurate bandwidth identification. It also maintains better compatibility with traditional WIFI demodulation. By simply processing the intermediate data from the synchronization steps of traditional demodulation, bandwidth information can be obtained with virtually no additional overhead.

[0072] Next, a method for identifying signal bandwidth provided in the embodiments of this application will be explained in detail.

[0073] Figure 1 This is a flowchart illustrating a method for identifying signal bandwidth according to an embodiment of this application. The execution entity of this method can be a spectrum analyzer or a host computer. Please refer to... Figure 1 The method includes the following steps:

[0074] Step 101: Receive the signal to be processed.

[0075] In some embodiments, the signal to be processed is a WIFI signal.

[0076] It should be noted that the above description is based on the assumption that the signal to be processed is a WIFI signal. Alternatively, in application, the signal to be processed can be other signals. This application does not limit this.

[0077] Step 102: Sample the signal to be processed using a preset sampling rate to obtain the sampled signal.

[0078] In some embodiments, when the signal to be processed is a WIFI signal, it is necessary to resample the WIFI signal (IQ sampling). Since the maximum bandwidth of the WIFI signal is 320MHz, theoretically, a minimum sampling rate of 320MHz is required to capture the signal without loss. Therefore, the preset sampling rate is greater than 320MHz.

[0079] It should be noted that the above description assumes a preset sampling rate greater than 320MHz. Alternatively, in application, the preset sampling rate can be determined based on actual conditions. This application does not limit this.

[0080] Step 103: Determine the target sequence from the sampled signal.

[0081] In some embodiments, the starting point of a specified field sequence can be identified in the sampled signal, and the sequence signal within a preset time period starting from the starting point of the specified field sequence can be determined as the target sequence.

[0082] In some embodiments, the specified field sequence is an L-STF sequence. Traditional Wi-Fi signal preambles include L-STF, L-LTF, and L-SIG. While theoretically, the peak counts of these three fields will differ for different bandwidths, L-STF has more repetition periods, typically 10, which better suppresses noise in subsequent processes. Furthermore, the L-STF sequence is located at the beginning of a frame, allowing for bandwidth identification and determination with fewer processing steps. Additionally, L-LTF generally has two periods, and L-SIG has one to two periods; theoretically, bandwidth identification can be performed by referring to the L-STF processing procedure.

[0083] Continuing from the previous description, when the specified field sequence is an L-STF sequence, the periodicity of the L-STF sequence can be used to detect the occurrence of repetitive patterns in the sampled signal through an autocorrelation algorithm. When the autocorrelation value is greater than the threshold, it is determined to be the starting point of the L-STF sequence, that is, the L-STF sequence is coarsely synchronized.

[0084] As an example, the autocorrelation value of the sampled signal can be calculated using the following formula (1);

[0085] (1)

[0086] Where d represents the starting position of the current detection, R(d) represents the autocorrelation value at d, r(d+k) represents the sampled value of the sampling signal at position d+k, which includes both I and Q signals and is in complex form, r*(d+k+N) represents the conjugate of the sampled value of the sampling signal at position d+k+N, and N represents the period length, which can be set to the number of sampling points in a single short sequence period (256 points) or an integer multiple of the number of sampling points in a single short sequence period.

[0087] Continuing from the previous description, after determining the starting point of a specified field sequence, the sequence signal within a preset time period starting from that starting point can be identified as the target sequence. As an example, a sequence signal starting from that starting point and lasting for 8 µs can be identified as the target sequence. Thus, a complete L-STF sequence containing 10 cycles can be used as the target sequence.

[0088] It should be noted that this explanation is based on a preset time period of 8µs. Alternatively, in practice, the preset time period can be set according to actual circumstances. This application does not impose any limitations on this.

[0089] In some embodiments, coarse synchronization may fail, that is, the starting point of the specified field sequence is not found. In this case, the starting point of the specified field sequence can be determined by sampling the signal of the next frame until the starting point of the specified field sequence is determined.

[0090] Step 104: Detect the number of peak points in the target sequence.

[0091] In some embodiments, the target sequence can be divided into multiple subsequences according to the periodicity of a specified field, with each subsequence having the same period length. Then, the number of valid peak points corresponding to each of the multiple subsequences is detected, and the sum of the number of valid peak points corresponding to the multiple subsequences is determined as the number of peak points of the target sequence.

[0092] As an example, the target sequence can be a complete L-STF sequence. Generally, an L-STF sequence has 10 periods. Therefore, the target sequence can be divided into 10 subsequences based on the periodicity of the L-STF, with each subsequence having an equal period length; that is, one subsequence corresponds to one period of the L-STF sequence. Then, the number of valid peak points in each of these 10 subsequences can be detected, and the sum of the valid peak point counts of the 10 subsequences is determined as the peak point count of the target sequence.

[0093] In some embodiments, preliminary peak detection can be performed on the sampling points in each of the plurality of subsequences to determine candidate peak points in the plurality of subsequences. Then, the plurality of subsequences are sequentially used as target subsequences. It is determined whether the sampling points at the same position as the candidate peak points in the target subsequences in the remaining subsequences are also candidate peak points in the remaining subsequences. The remaining subsequences are the sequences other than the target subsequences in the plurality of subsequences. When the number of times it is determined that the sampling points at the same position as the candidate peak points in the target subsequences in the remaining subsequences are also candidate peak points in the remaining subsequences is greater than a threshold, the candidate peak points in the target subsequences are determined as valid peak points. The threshold is positively correlated with the signal-to-noise ratio and the number of the plurality of subsequences.

[0094] In some embodiments, in order to perform preliminary peak detection on the sampling points of each of the plurality of subsequences and determine the candidate peak points in the plurality of subsequences, the value of the sampling point can be compared with the value of the previous sampling point and the value of the next sampling point, where the previous sampling point is the sampling point before the sampling point and the next sampling point is the sampling point after the sampling point; if the value of the sampling point is greater than the value of the previous sampling point and greater than the value of the next sampling point, then the sampling point is determined as a candidate peak point.

[0095] As an example, suppose the value of the current sampling point is X, the value of the previous sampling point is Y, and the value of the next sampling point is Z. If X is greater than both Y and Z, the current sampling point can be identified as a candidate peak point. If X is only greater than Y or only greater than Z, then the current sampling point is not a candidate peak point. If X is equal to Y and greater than Z, then the current sampling point is also not a candidate peak point.

[0096] As described above, the sampling is multiple sampling, meaning that both the I (in-phase) and Q (quadrature) signals will be sampled. Therefore, the corresponding candidate peak points need to be determined for both the I and Q signals.

[0097] Continuing from the previous description, after identifying the candidate peak points among the multiple subsequences, these multiple subsequences can be used sequentially as target subsequences for subsequent joint peak point calculation.

[0098] In some embodiments, in order to improve the accuracy of the determined number of peak points, taking advantage of the fact that the L-STF sequence contains 10 repetition periods, it is also necessary to determine the sampling points at the same positions in the other subsequences corresponding to the candidate peak points in the target subsequence, so as to determine whether the sampling points in the other subsequences other than the target subsequence corresponding to the current candidate peak points are also candidate sampling points.

[0099] As an example, suppose the current target subsequence is subsequence A, and the remaining subsequences include subsequence B. If subsequence A includes a candidate peak point X, and the sampling time point corresponding to X in subsequence A is the m-th second of subsequence A, and the sampling time point corresponding to X1 in subsequence B is also the m-th second of subsequence B, it means that within its own period, the sampling time point of X1 is the same as that of X. Therefore, X1 corresponds to X, that is, X1 is a sampling point at the same position as the candidate peak point X in the target subsequence.

[0100] Continuing from the previous description, after determining the sampling points in the remaining subsequences that correspond to the candidate peak points in the target subsequence, it is necessary to determine whether the sampling points in the remaining subsequences that correspond to the candidate peak points in the target subsequences are also candidate peak points in the remaining subsequences. Then, the number of times the corresponding sampling points in the remaining subsequences are determined to be candidate peak points determines whether the candidate peak points in the target subsequences are valid peak points.

[0101] If the number of times a corresponding sampling point in the remaining subsequence is identified as a candidate peak point is greater than the threshold, it indicates that most of the common points in the period of the target sequence are peak points. The possibility that this candidate peak point is a misjudged peak point is relatively small. Therefore, the corresponding candidate peak point in the target subsequence can be determined as a valid peak point. Conversely, if the number of times a corresponding sampling point in the remaining subsequence is identified as a candidate peak point is less than the threshold, it indicates that most of the common points in the period of the target sequence are not peak points. The possibility that this candidate peak point is a misjudged peak point is relatively large. Therefore, the corresponding candidate peak point in the target subsequence cannot be determined as a valid peak point. In other words, a joint peak point count must be performed for each candidate peak point in the target subsequence.

[0102] As an example, suppose the target subsequence is subsequence A, and the remaining subsequences include subsequences B and C. Subsequence A contains candidate peak points X, Y, and Z; in subsequence B, X1 corresponds to X, Y1 corresponds to Y, and Z1 corresponds to Z; in subsequence C, X2 corresponds to X, Y2 corresponds to Y, and Z2 corresponds to Z, with a frequency threshold of 1. If X1 is a candidate peak point in subsequence B, and X2 is not a candidate peak point in subsequence C, and the number of times it is judged as a candidate peak point is 1, which equals the frequency threshold, then X can be determined as a valid peak point. If X1 is not a candidate peak point in subsequence B, and X2 is not a candidate peak point in subsequence C, and the number of times it is judged as a candidate peak point is 0, which is less than the frequency threshold, then X cannot be determined as a valid peak point.

[0103] For example, if the target sequence has 10 subsequences, one of which is the target subsequence, and the target subsequence contains candidate peak points, for each candidate peak point in the target subsequence: it is necessary to determine whether the corresponding points in the other 9 subsequences are candidate peak points. If it is determined that the number of times the corresponding sampling point in the other subsequence is a candidate peak point is greater than 4, then the candidate peak point in the target subsequence is determined to be a valid peak point; if it is determined that the number of times the corresponding sampling point in the other subsequence is a candidate peak point is less than or equal to 4, then the candidate peak point is determined not to be a valid peak point.

[0104] In some embodiments, the frequency threshold needs to ensure that more than half of the subsequences in the target sequence correspond to candidate peak points; that is, the frequency threshold is positively correlated with the number of subsequences. For example, if there are 10 subsequences, the frequency threshold can be greater than 4; if there are 9 subsequences, the frequency threshold can be no less than 4; and if there are 7 subsequences, the frequency threshold can be no less than 3.

[0105] In addition, in some embodiments, the effective peak points of the I-channel signal and the Q-channel signal need to be determined separately according to the above process.

[0106] Continuing from the previous description, after determining the number of valid peak points for each of the multiple subsequences, the sum of the number of valid peak points for each of the multiple subsequences needs to be determined as the number of peak points for the target sequence in order to proceed with the subsequent processes.

[0107] In some embodiments, there may be a frequency deviation before the joint peak point count is calculated. Therefore, the frequency offset can also be estimated and corrected using the L-STF autocorrelation phase difference.

[0108] In some embodiments, to suppress noise and improve accuracy, before detecting the number of peak points in the target sequence, the target sequence can be segmented and periodically averaged. Segmentation and periodic averaging include: dividing the target sequence into multiple subsequences based on the periodicity of a specified field, with each subsequence having an equal period length; for each sampling point in these subsequences: calculating the average value of the corresponding sampling points in these subsequences; updating the sampling points based on the average value; and then integrating the multiple subsequences after updating the sampling points to obtain the target sequence after segmentation and periodic averaging. Thus, the number of peak points in the target sequence after segmentation and periodic averaging can be detected.

[0109] It should be noted that the process of dividing the target sequence into multiple subsequences according to the periodicity of the specified field is the same as the process of segmenting the target sequence when calculating the joint peak points mentioned above. It will not be repeated here. Please refer to the relevant content above.

[0110] Then, for each sampling point in the multiple subsequences, the average value of the corresponding sampling points in the multiple subsequences must be calculated.

[0111] As an example, assuming there are 10 periods of subsequence, the average value of each sampling point can be calculated according to the following formula (2);

[0112] (2)

[0113] in, is the average value of the sampled points, and n is the position index within a period. n ranges from 0 to N-1, which can traverse every sampled point in a complete period; i is the index of the period; r(n+i·N) represents the value of the nth sampled point in the 0th period when i=0, the value of the nth sampled point in the 1st period when i=1, and so on. Through the above formula (2), the final average value is the value of the averaged periodic subsequence at the nth position.

[0114] Continuing from the previous description, when calculating the average value of the corresponding samples in the multiple subsequences, it is necessary to update the value of the sampling point to the average value. Then, the multiple subsequences after updating the sampling points are integrated to obtain the target sequence after segmentation and periodic averaging.

[0115] In some embodiments, the number of peak points in the target sequence after segmentation and periodic averaging can be directly detected, and subsequent operations can be performed based on the number of peak points to determine the bandwidth of the target signal.

[0116] In some embodiments, there may be frequency deviations before segmentation and periodic averaging. Therefore, the frequency offset can also be estimated and corrected using the L-STF autocorrelation phase difference.

[0117] Step 105: Determine the target signal bandwidth based on the number of peak points and bandwidth reference template of the target sequence. The bandwidth reference template is used to indicate the correspondence between the bandwidth of multiple different signals and the number of peak points.

[0118] In some embodiments, the bandwidth reference template may be pre-configured, and the bandwidth reference template may store the correspondence between different signal bandwidths and peak points.

[0119] As an example, the bandwidth reference template can be as shown in Table 1 below:

[0120] Table 1

[0121] signal bandwidth Peak Points 20M （24，24） 40M （44，48） 80M （92，92） 160M （200，200） 320M （331，332）

[0122] As described above, since there is no resampling, the peak count is in complex form. The real part of the peak count in Table 1 represents the peak count of the I-channel signal, and the imaginary part represents the peak count of the Q-channel signal. Furthermore, since the complete L-STF sequence may contain a large number of peaks, the peak count corresponding to a portion of the cycles can be stored in the bandwidth reference template. For example, the peak count in Table 1 represents the total peak count of the four cycles (3.2 µs) of the L-STF sequence under ideal conditions.

[0123] As shown in Table 1 above, the larger the signal bandwidth, the more peak points there are. That is, when the bandwidth is extended to 40MHz, 80MHz, or higher, the subcarrier distribution of the L-STF sequence is replicated in each 20MHz subband, and the subcarriers in each subband undergo phase rotation to avoid interference between different subbands. The larger the bandwidth, the more subcarriers there are, the higher the frequency components the signal contains, and the faster the time-domain signal changes, thus resulting in more peak points per unit time.

[0124] It should be noted that the bandwidth reference template mentioned above is only an example. Alternatively, in applications, technicians can configure the bandwidth reference template according to actual needs.

[0125] In some embodiments, since the number of peak points in the determined target sequence may not be exactly the same as the number of peak points corresponding to the signal bandwidth stored in the bandwidth reference template, the target signal bandwidth can be determined by comparing the difference between the number of peak points in the target sequence and the number of peak points corresponding to multiple different signal bandwidths in the bandwidth reference template, and then determining the signal bandwidth corresponding to the number of peak points in the bandwidth reference template that has the smallest difference from the number of peak points in the target sequence.

[0126] For example, assuming the number of peak points in the target sequence is (m, n), we can calculate the Euclidean distances (m, n) with (24, 24), (44, 48), (92, 92), (200, 200), and (331, 332) in Table 1, i.e., the complex domain Euclidean distances. The signal bandwidth corresponding to the number of peak points with the smallest Euclidean distance in the bandwidth reference template is then determined as the target signal bandwidth. In other words, the smallest Euclidean distance indicates the smallest difference. For instance, if the number of peak points corresponding to the smallest Euclidean distance is (44, 48), then the target signal bandwidth is 40 MHz; if the number of peak points corresponding to the smallest Euclidean distance is (331, 332), then the target signal bandwidth is 320 MHz.

[0127] As another example, the target signal bandwidth can also be determined by the Euclidean distance of the amplitude values. That is, the target signal bandwidth can be determined by calculating the difference between the modulus of the number of peak points in the target sequence and the modulus of the number of peak points in the bandwidth reference template, and the signal bandwidth corresponding to the peak point with the smallest difference.

[0128] In some embodiments, the error may be large in a low signal-to-noise ratio environment. In order to ensure the accuracy of the determined signal bandwidth, the initial signal bandwidth can be determined from the bandwidth reference template based on the number of peak points. Then, the target sequence can be filtered based on the initial signal bandwidth to obtain the target signal bandwidth.

[0129] In some embodiments, the target sequence can be filtered based on the initial signal bandwidth according to the following steps (1)-(8) to obtain the target signal bandwidth;

[0130] (1) Use the initial signal bandwidth as the current cutoff frequency.

[0131] As an example, if the initial signal bandwidth determined from the bandwidth reference template is 20MHz, then 20MHz can be used as the current cutoff frequency.

[0132] (2) Filter the target sequence using the current cutoff frequency to obtain the filtered target sequence.

[0133] Then, the target sequence can be filtered using the current cutoff frequency to obtain the filtered target sequence. This removes high-frequency components and gradually approaches the actual bandwidth.

[0134] (3) Update the target sequence to the filtered target sequence.

[0135] (4) Detect the number of peak points in the target sequence.

[0136] In other words, the number of peak points is detected according to the filtered target sequence.

[0137] (5) Match alternative bandwidths from the bandwidth reference template based on the number of peak points.

[0138] It should be noted that the process of matching candidate bandwidths from the bandwidth reference template based on the number of peak points is similar to the process of determining the target signal bandwidth based on the number of peak points and the bandwidth reference template of the target sequence, as described above. Please refer to the relevant content above, and it will not be repeated here.

[0139] (6) Compare whether the alternative bandwidth is equal to the current cutoff frequency.

[0140] (7) If the candidate bandwidth is not equal to the current cutoff frequency, the current cutoff frequency is updated to the candidate bandwidth, and the target sequence is filtered using the current cutoff frequency until the candidate bandwidth is equal to the current cutoff frequency.

[0141] In other words, if the candidate bandwidth is not equal to the current cutoff frequency, the current cutoff frequency needs to be updated to the candidate bandwidth, and the process should return to the step of filtering the target sequence using the current cutoff frequency to filter the target sequence again until the candidate bandwidth is equal to the current cutoff frequency. This process is repeated multiple times to filter the target sequence, thereby removing high-frequency components during the multiple iterations and gradually approaching the actual bandwidth of the signal to be processed, i.e., the target signal bandwidth.

[0142] (8) If the alternative bandwidth is equal to the current cutoff frequency, then the alternative bandwidth shall be used as the target signal bandwidth.

[0143] In other words, if the candidate bandwidth is equal to the current cutoff frequency, it means that the current noise influence is already very small and the number of peak points in the target sequence remains basically unchanged. Correspondingly, the candidate bandwidth determined from the bandwidth reference template based on the number of peak points will not change. Therefore, the current candidate bandwidth can be used as the target signal bandwidth.

[0144] In some embodiments, in order to further reduce the number of peak points and improve the accuracy of the determined target signal bandwidth, after filtering the target sequence based on the initial signal bandwidth, the target sequence can also be segmented and periodically averaged. The segmentation and periodic averaging steps include: dividing the target sequence into multiple subsequences according to the periodic repetition of a specified field, with each subsequence having an equal period length; for each sampling point in the multiple subsequences: calculating the average value of the corresponding sampling points in the multiple subsequences; updating the sampling points based on the average value; and then integrating the multiple subsequences after updating the sampling points to obtain the target sequence after segmentation and periodic averaging.

[0145] It should be noted that the specific steps for segmentation and periodic averaging have been described in detail above, and will not be repeated here. Please refer to the relevant content above.

[0146] As an example, please refer to Figure 2 , Figure 2 This is a schematic diagram of an iterative filtering process provided in an embodiment of this application. Figure 2As can be seen, when the actual signal bandwidth of the signal to be processed is 40MHz, due to the extremely low signal-to-noise ratio environment (e.g., 4dB), although the joint peak point calculation can effectively suppress the increase in peak points caused by noise, it may still misjudge the candidate bandwidth as 160MHz due to the excessive number of peak points. Therefore, 160MHz can be used as the current cutoff frequency for filtering to filter out high-frequency noise outside the 160MHz bandwidth. After that, segmentation and periodic averaging can reduce the number of peak points. However, based on this number of peak points, it may still be misjudged as a candidate bandwidth of 80MHz, and the 80MHz bandwidth is not equal to the current 160MHz cutoff frequency. Therefore, it is necessary to update the current cutoff frequency to 80MHz, so as to use 80MHz as the cutoff frequency for filtering to filter out high-frequency noise outside the 80MHz bandwidth. After filtering out high-frequency noise, segmentation and periodic averaging are performed to further reduce the number of peak points. Based on this number of peak points, the candidate bandwidth can be determined to be 40MHz. However, since the 40MHz bandwidth is not equal to the current 80MHz cutoff frequency, the current cutoff frequency needs to be updated to 40MHz. Filtering is then performed using 40MHz as the cutoff frequency to filter out high-frequency noise outside the 40MHz bandwidth. After segmentation and periodic averaging, since the actual bandwidth of the signal is 40MHz, the noise impact is already very small, and the peak points remain basically unchanged. Therefore, the candidate bandwidth determined based on this peak point is still 40MHz, and this 40MHz candidate bandwidth is equal to the current 40MHz cutoff frequency. Therefore, 40MHz can be used as the target signal bandwidth to correctly determine the actual bandwidth of the signal to be processed.

[0147] Next, the signal bandwidth identification method provided in the embodiments of this application will be described again in a cyclical manner.

[0148] For example, please refer to Figure 3 , Figure 3 This is a flowchart of another signal bandwidth identification method provided in this application embodiment. First, the signal to be processed is acquired. Then, the signal is sampled, and L-STF coarse synchronization is used to determine the starting point of a specified field sequence (L-STF sequence). If synchronization fails, it indicates that no valid frame data was found, i.e., the starting point of the L-STF sequence was not found. In this case, the next frame can be searched, and the process returns to the signal sampling step. After successful synchronization (starting point identification), the target sequence, i.e., the L-STF sequence, is extracted, and the number of peak points in the L-STF sequence is detected. Then, the target signal bandwidth is determined based on the bandwidth reference template.

[0149] As another example, to reduce the impact of noise and improve the accuracy of the determined target signal bandwidth, segmented and periodic averaging, as well as iterative filtering, can be added. Please refer to... Figure 4 , Figure 4This is a flowchart of another signal bandwidth identification method provided in this application embodiment. First, the signal to be processed is acquired, then the signal to be processed is sampled, and L-STF coarse synchronization is used to determine the starting point of the L-STF sequence. If synchronization fails, it means that no valid frame data has been found. Then, the next frame can be searched, and the process returns to the signal sampling step. After successful synchronization, the L-STF sequence is extracted. The L-STF sequence may include a subsequence of 10 periods, and coarse frequency offset estimation and correction are performed on it. Then, the 10 periods of the L-STF sequence are segmented and periodically averaged to suppress noise interference, and the number of peak points of the obtained L-STF sequence is detected. A candidate bandwidth is matched from the bandwidth reference template. Then, it is determined whether the current cutoff frequency is equal to the candidate bandwidth. If they are not equal, the current cutoff frequency is updated to the candidate bandwidth, the L-STF sequence is filtered to remove high-frequency components, and the process returns to the segmentation and periodic averaging step. If they are equal, the candidate bandwidth is determined as the target signal bandwidth.

[0150] As another example, in situations with low signal-to-noise ratios, to improve the accuracy of the detected peak count and further enhance the accuracy of the determined target signal bandwidth, joint peak count calculation, iterative filtering, and segmented and periodic averaging can be combined. Furthermore, the initial signal bandwidth can be obtained through joint peak count calculation as the cutoff frequency for the first filter. Please refer to [reference needed]. Figure 5 , Figure 5This is a flowchart of another signal bandwidth identification method provided in an embodiment of this application. First, the signal to be processed is acquired, then the signal to be processed is sampled, and L-STF coarse synchronization is used to determine the starting point of the L-STF sequence. If synchronization fails, it means that no valid frame data has been found. Then, the next frame can be searched, and the process returns to the signal sampling step. After successful synchronization, the L-STF sequence is extracted, which may include a subsequence of 10 periods. Coarse frequency offset estimation and correction are performed on this subsequence. Then, the joint peak count of the 10 periods of the L-STF sequence is calculated. Based on the obtained peak count, a candidate bandwidth is matched from the bandwidth reference template. Since the frequency during the initial filtering is 0, the currently determined candidate bandwidth is definitely not equal to the current cutoff frequency. Therefore, the candidate bandwidth calculated using the joint peak count is updated to the current cutoff frequency. The L-STF sequence is then filtered to remove high-frequency components. The filtered L-STF sequence is then segmented and periodically averaged. The peak count of the L-STF sequence is detected, and a candidate bandwidth is matched from the bandwidth reference template based on this peak count. It is then determined whether the current cutoff frequency is equal to the candidate bandwidth. If they are not equal, the current cutoff frequency is updated to the candidate bandwidth, the L-STF sequence is filtered to remove high-frequency components, and the process returns to the segmentation and periodic averaging steps. If they are equal, the candidate bandwidth is determined as the target signal bandwidth.

[0151] This application embodiment detects the number of peak points in the target sequence and then determines the target signal bandwidth based on the number of peak points in the target sequence and a bandwidth reference template. The process is simple and can quickly determine the bandwidth of the signal to be processed for subsequent related steps, reducing time consumption. Furthermore, the target sequence can be divided into multiple subsequences according to the periodicity of a specified field, with each subsequence having an equal period length. Then, the number of effective peak points corresponding to each subsequence is detected, and the sum of the effective peak points corresponding to each subsequence is determined as the number of peak points in the target sequence. That is, joint peak point calculation improves the accuracy of the detected peak points, thereby improving the accuracy of the determined target signal bandwidth. Moreover, the target sequence can be segmented and periodically averaged to suppress noise interference, and iterative filtering can be performed to filter out high-frequency components. In cases of low signal-to-noise ratio, the joint peak method can be used to obtain the cutoff frequency of the initial filtering before iterative filtering, ensuring the accuracy of the identified target signal bandwidth.

[0152] Those skilled in the art will understand that all or part of the functions of the various methods in the above embodiments can be implemented by hardware or by computer programs. When all or part of the functions in the above embodiments are implemented by computer programs, the program can be stored in a computer-readable storage medium, which may include: read-only memory, random access memory, disk, optical disk, hard disk, etc., and the program is executed by a computer to achieve the above functions. For example, the program can be stored in the memory of a device, and when the program in the memory is executed by the processor, all or part of the above functions can be achieved. In addition, when all or part of the functions in the above embodiments are implemented by computer programs, the program can also be stored in a server, another computer, disk, optical disk, flash drive, or external hard drive, etc., and can be downloaded or copied to the memory of a local device, or the system of the local device can be updated. When the program in the memory is executed by the processor, all or part of the functions in the above embodiments can be achieved.

[0153] The above examples illustrate the present invention only to aid in understanding it and are not intended to limit the scope of the invention. Those skilled in the art can make various simple deductions, modifications, or substitutions based on the principles of this invention.

Claims

1. A method for identifying signal bandwidth, characterized in that, The method includes: Receive signals to be processed; The signal to be processed is sampled using a preset sampling rate to obtain a sampled signal; Determine the target sequence from the sampled signal; Detect the number of peak points in the target sequence; The target signal bandwidth is determined based on the number of peak points and the bandwidth reference template of the target sequence, wherein the bandwidth reference template is used to indicate the correspondence between multiple different signal bandwidths and the number of peak points; Determining the target sequence from the sampled signal includes: Identify the starting point of the specified field sequence in the sampled signal; The sequence signal within a preset time period, starting from the starting point of the specified field sequence, is determined as the target sequence; Wherein, the specified field sequence is an L-STF sequence; The number of peak points detected in the target sequence includes: The target sequence is divided into multiple subsequences according to the periodic repetition of a specified field, and the period length of each subsequence is equal. Detect the number of valid peak points corresponding to each of the plurality of subsequences; The sum of the effective peak points corresponding to the multiple subsequences is determined as the peak point number of the target sequence.

2. The signal bandwidth identification method as described in claim 1, characterized in that, The detection of the number of valid peak points corresponding to each of the plurality of subsequences includes: Preliminary peak detection is performed on the sampling points of each of the multiple subsequences to determine the candidate peak points in the multiple subsequences; The plurality of subsequences are sequentially used as the target subsequence; Determine whether the sampling point at the same position as the candidate peak point in the target subsequence in the remaining subsequence is also a candidate peak point in the remaining subsequence, wherein the remaining subsequence is the sequence other than the target subsequence among the plurality of subsequences; When the number of times that the sampling point at the same position as the candidate peak point in the target subsequence is also a candidate peak point in the remaining subsequence is greater than the number of times the candidate peak point in the remaining subsequence is determined to be a valid peak point, the candidate peak point in the target subsequence is determined to be a valid peak point. The number of times the threshold is positively correlated with the signal-to-noise ratio and the number of the multiple subsequences.

3. The signal bandwidth identification method as described in claim 2, characterized in that, The preliminary peak detection of sampling points in each of the plurality of subsequences, and the determination of candidate peak points in the plurality of subsequences, includes: The value of the sampling point is compared with the value of the previous sampling point and the value of the next sampling point, wherein the previous sampling point is the sampling point before the sampling point and the next sampling point is the sampling point after the sampling point; If the value of the sampling point is greater than the value of the previous sampling point and greater than the value of the next sampling point, then the sampling point is determined as the candidate peak point.

4. The signal bandwidth identification method as described in claim 1, characterized in that, The determination of the target signal bandwidth based on the peak point count and bandwidth reference template of the target sequence includes: Based on the number of peak points, the initial signal bandwidth is determined from the bandwidth reference template; The target signal bandwidth is obtained by filtering the target sequence based on the initial signal bandwidth.

5. The signal bandwidth identification method as described in claim 4, characterized in that, The step of filtering the target sequence based on the initial signal bandwidth to obtain the target signal bandwidth includes: Use the initial signal bandwidth as the current cutoff frequency; The target sequence is filtered using the current cutoff frequency to obtain a filtered target sequence. Update the target sequence with the filtered target sequence; Detect the number of peak points in the target sequence; Based on the peak point count, alternative bandwidths are matched from the bandwidth reference template; Compare whether the candidate bandwidth is equal to the current cutoff frequency; If the candidate bandwidth is not equal to the current cutoff frequency, the current cutoff frequency is updated to the candidate bandwidth, and the target sequence is filtered using the current cutoff frequency until the candidate bandwidth is equal to the current cutoff frequency. If the alternative bandwidth is equal to the current cutoff frequency, then the alternative bandwidth is used as the target signal bandwidth.

6. The signal bandwidth identification method as described in claim 5, characterized in that, After filtering the target sequence based on the initial signal bandwidth, the method further includes: The target sequence is segmented and periodically averaged, the segmentation and periodic averaging including: The target sequence is divided into multiple subsequences according to the periodic repetition of a specified field, and the period length of each subsequence is equal. For each sampling point in the plurality of subsequences: calculate the average value of the sampling points in the plurality of subsequences, and update the sampling point based on the average value; The multiple subsequences after updating the sampling points are integrated to obtain the target sequence after segmentation and periodic averaging.

7. The signal bandwidth identification method as described in claim 1, characterized in that, Before detecting the number of peak points in the target sequence, the method further includes: The target sequence is segmented and periodically averaged, the segmentation and periodic averaging including: The target sequence is divided into multiple subsequences according to the periodic repetition of a specified field, and the period length of each subsequence is equal. For each sampling point in the plurality of subsequences: calculate the average value of the sampling points in the plurality of subsequences, and update the sampling point based on the average value; The multiple subsequences after updating the sampling points are integrated to obtain the target sequence after segmentation and periodic averaging; The number of peak points detected in the target sequence includes: The number of peak points in the target sequence after segmentation and periodic averaging is detected.

8. The signal bandwidth identification method as described in claim 1, characterized in that, Determining the target signal bandwidth based on the peak point count and bandwidth reference template of the target sequence includes: Compare the number of peak points in the target sequence with the difference between the number of peak points corresponding to multiple different signal bandwidths in the bandwidth reference template; The signal bandwidth corresponding to the peak number that differs the least from the peak number of the target sequence in the bandwidth reference template is determined as the target signal bandwidth.

9. The signal bandwidth identification method as described in claim 1, characterized in that, The signal to be processed is a WIFI signal, and the preset sampling rate is greater than 320MHz.

10. 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 method as described in any one of claims 1 to 9.

11. A computer-readable storage medium, characterized in that, The medium stores a computer program that can be executed by a processor to implement the method as described in any one of claims 1-9.

Images