OFDM signal parameter estimation method, program product and equipment

Abstract

The invention discloses an OFDM (Orthogonal Frequency Division Multiplexing) signal parameter estimation method, a program product and equipment. The method comprises the following steps: receiving a signal to be tested; determining whether the to-be-measured signal is an orthogonal frequency division multiplexing (OFDM) signal based on the to-be-measured signal, and acquiring a target data length estimated for one OFDM signal under the condition that the to-be-measured signal is determined to be the OFDM signal; obtaining an initial minimum cyclic prefix length and an initial maximum cyclic prefix length, and estimating the initial cyclic prefix length by using a dichotomy based on the initial minimum cyclic prefix length, the initial maximum cyclic prefix length and the target data length; acquiring a correction factor; and based on the correction factor, correcting the initial cyclic prefix length to obtain a target cyclic prefix length of the signal to be measured.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to an OFDM signal parameter estimation method, a computer program product and an OFDM signal parameter estimation device. Background Art

[0002] In recent years, the technology of some signal source devices (such as drones) has developed rapidly, and the threats they bring have also penetrated into various fields: aviation safety threats, public safety threats, infrastructure safety threats, network security threats, etc. Therefore, it is urgent to respond to the challenges brought by drones. In order to accurately discover and identify signal source devices in complex electromagnetic environments, it is necessary to receive the signals of signal source devices and perform various analysis and processing to explore their unique signal characteristics.

[0003] Currently, some signal source devices (such as drones) mostly use orthogonal frequency division multiplexing (OFDM) signal transmission system. There are many methods for OFDM signal identification, such as time-frequency analysis, wavelet transform, carrier modulation method identification and envelope correlation spectrum, but these methods can only identify whether the signal is an OFDM signal, lack more detailed characteristic parameters, and cannot distinguish the image transmission signals of different types of signal source devices. Summary of the invention

[0004] In order to solve the existing technical problems, the present invention provides an OFDM signal parameter estimation method, a computer program product and an OFDM signal parameter estimation device, which can accurately estimate signal parameters and greatly reduce search time, improve calculation speed and save calculation resources.

[0005] In a first aspect, a method for estimating parameters of an OFDM signal is provided, comprising: receiving a signal to be tested; determining whether the signal to be tested is an orthogonal frequency division multiplexing (OFDM) signal based on the signal to be tested, and obtaining a target data length estimated for the OFDM signal when it is determined that the signal to be tested is an OFDM signal; obtaining an initial minimum cyclic prefix length and an initial maximum cyclic prefix length, and estimating the initial cyclic prefix length using a binary search method based on the initial minimum cyclic prefix length, the initial maximum cyclic prefix length and the target data length; obtaining a correction factor; and correcting the initial cyclic prefix length based on the correction factor to obtain a target cyclic prefix length of the signal to be tested.

[0006] In a second aspect, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, the OFDM signal parameter estimation method as described in any one of the first aspect of the present application is implemented.

[0007] In a third aspect, an OFDM signal parameter estimation device is provided, comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the OFDM signal parameter estimation method as described in any one of the first aspects of the present application.

[0008] The present application receives a signal to be tested, first determines whether the signal to be tested is an orthogonal frequency division multiplexing (OFDM) signal, and when it is determined that the signal to be tested is an OFDM signal, obtains a target data length estimated for one of the OFDM signals, obtains an initial minimum cyclic prefix length and an initial maximum cyclic prefix length, searches for an initial cyclic prefix length based on the target data length within an initial cyclic prefix length range formed based on the initial minimum cyclic prefix length and the initial maximum cyclic prefix length, and then corrects the initial cyclic prefix length based on a correction factor to obtain a final cyclic prefix length, that is, the signal parameters of the signal to be tested can be obtained, so that the signal parameters can be more accurately identified and different types of image transmission signals can be more accurately identified based on the signal parameters; since the cyclic prefix lengths are diverse and a priori unknown, the amount of traversal calculations is large, and in order to address the problem of large amount of traversal calculations, a binary search method is used for traversal, which can greatly reduce the search time, reduce the amount of calculations, and save system resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 1. is a diagram showing an application environment of an OFDM signal parameter estimation method in an embodiment;

[0010] Figure 2 is a flow chart of an OFDM signal parameter estimation method in one embodiment;

[0011] Figure 3 is a schematic diagram of two OFDM symbols in one embodiment;

[0012] Figure 4 is a schematic diagram of a first signal and a second signal in an embodiment;

[0013] Figure 5 is a schematic diagram of a mutual function value and a threshold value in one embodiment;

[0014] Figure 6 A flowchart of determining an initial cyclic prefix length in one embodiment;

[0015] Figure 7 A schematic diagram of a trend between a cyclic prefix length and a judgment parameter value in an embodiment;

[0016] Figure 8 A flowchart of searching for a cyclic prefix length estimation value corresponding to a minimum value of a judgment parameter using a binary search method in an embodiment;

[0017] Fig. 9is a cross-correlation function diagram corresponding to different cyclic prefix length estimation values ​​in one embodiment;

[0018] Fig.10 An example diagram of estimating the initial cyclic prefix length by a binary method in one embodiment;

[0019] Fig.11 is a schematic diagram of an OFDM signal parameter estimation device in one embodiment;

[0020] Fig.12 Schematic diagram of an OFDM signal parameter estimation device in an embodiment. DETAILED DESCRIPTION

[0021] The technical solution of the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0022] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by those skilled in the art of the technical field of the present invention. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the scope of protection of the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items.

[0023] In the following description, reference is made to “some embodiments”, which describes a subset of all possible embodiments, but it should be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0024] See also Figure 1 , is an application environment diagram of an OFDM signal parameter estimation method in an embodiment. The application environment diagram includes 10 and a signal source device 20, the signal source device 20 can transmit a communication signal, for example, the signal source device 20 is a drone device. The OFDM signal parameter estimation device 10 is used to receive a signal transmitted by the signal source device 20 when working, and process the received signal to be tested, determine whether the received signal is an OFDM signal, and if the received signal is an OFDM signal, estimate the signal parameters of the received signal.

[0025] In recent years, drone technology has developed rapidly, and the threats it brings have also penetrated into various fields: aviation safety threats, public safety threats, infrastructure security threats, network security threats, etc. Therefore, it is urgent to respond to the challenges brought by drones. In order to accurately detect and identify drones in complex electromagnetic environments, it is necessary to receive drone signals and perform various analysis and processing to explore their unique signal characteristics.

[0026] Most current drones use the OFDM signal transmission system. There are many methods for OFDM signal identification, such as time-frequency analysis, wavelet transform, carrier modulation method identification and envelope correlation spectrum, but these methods can only identify whether the signal is an OFDM signal. They lack more detailed feature parameters and cannot distinguish different types of drone image transmission signals. Therefore, the method based on feature extraction is particularly effective. It can not only identify unmanned image transmission signals, but also has the potential to distinguish different models. In 2018, the Information Engineering University of the Strategic Support Force of the Chinese People's Liberation Army proposed a patent for "OFDM Signal Identification Method and System Based on Signal Structural Characteristics", which detects and identifies the cyclic prefix of the OFDM signal, but it does not estimate the length of the signal cyclic prefix.

[0027] Orthogonal frequency division multiplexing (OFDM): Current NR terminal devices, or IoT terminal devices that support standard features such as NB-IoT, all use OFDM as the basic mechanism for signal transmission. OFDM is essentially a frequency division system that uses multiple carriers (called subcarriers) to transmit information streams. Multiple subcarriers are mutually orthogonal in the time domain and overlap in the frequency domain, dividing the channel into several orthogonal subchannels, converting high-speed data signals into parallel low-speed sub-data streams, and modulating them to each subchannel for transmission. Each subcarrier channel of OFDM can be considered as flat fading, which can improve the anti-multipath fading performance. In engineering, OFDM waveforms can be realized through FFT and its inverse process. At the same time, in order to resist the memory of the channel and eliminate inter-symbol interference and inter-code interference, OFDM usually introduces a cyclic prefix (CP) as a protection interval. In a general NR system, the transmitter maps the information bit stream into a phase shift keying (PSK) or quadrature amplitude modulation (QAM) symbol for modulation. The working principle of the cyclic prefix is ​​to copy the tail of the OFDM symbol and place it at the head of the OFDM symbol to form a cyclic structure. The reason for this is that in a multipath environment, the signal may propagate on different paths, resulting in different times for the signal to arrive at the receiving end. Without a cyclic prefix, the earlier arriving path may overlap with the subsequent OFDM symbol, causing interference. By adding a cyclic prefix, it can be ensured that the delay caused by the multipath effect will not exceed one OFDM symbol period during the entire duration of the OFDM symbol before the FFT (Fast Fourier Transform) processing is performed at the receiving end, thereby avoiding interference between symbols.

[0028] See also Figure 2, is a flow chart of an OFDM signal parameter estimation method provided in an embodiment of the present application. The OFDM signal parameter estimation method is applied to an OFDM signal parameter estimation device, and the OFDM signal parameter estimation method includes the following steps:

[0029] S11. Receive a signal to be tested.

[0030] In this embodiment, the signal to be tested is a signal received by the OFDM signal parameter estimation device 10. For example, the signal source device 20 is a drone. When the drone flies within the search range of the OFDM signal parameter estimation device 10, the OFDM signal parameter estimation device 10 can receive the signal of the drone.

[0031] S12: Based on the signal to be tested, determine whether the signal to be tested is an orthogonal frequency division multiplexing (OFDM) signal. If it is determined that the signal to be tested is an OFDM signal, obtain a target data length estimated for an OFDM signal.

[0032] In this embodiment, before determining whether the signal to be tested is an orthogonal frequency division multiplexing (OFDM) signal, a preprocessing operation may be performed on the signal to be tested to obtain a preprocessed signal s(n). The preprocessing operation includes but is not limited to: filtering, down-converting, and down-sampling the signal to be tested, wherein the filter bandwidth and the center frequency point used for down-conversion are output parameters of the spectrum sensing algorithm, and the sampling rate of down-sampling refers to the standard protocol. Then, based on the preprocessed signal, it is determined whether the signal to be tested is an OFDM signal. Figure 3 As shown, it is a schematic diagram of two OFDM symbols, one OFDM symbol is one OFDM signal, one OFDM symbol includes a cyclic prefix and a valid signal data part, wherein the valid signal data part is the data actually transmitted. The target data length indicates the estimated length of the valid signal data part.

[0033] S13, obtaining an initial minimum cyclic prefix length and an initial maximum cyclic prefix length, and estimating the initial cyclic prefix length by using a dichotomy method based on the initial minimum cyclic prefix length, the initial maximum cyclic prefix length and the target data length.

[0034] In this embodiment, this step is the D parameter estimation part, that is, used to estimate the cyclic prefix length, the initial minimum cyclic prefix length and the initial maximum cyclic prefix length are preset values, and the initial cyclic prefix length is calculated by binary division in the initial cyclic prefix length range formed by the initial minimum cyclic prefix length and the initial maximum cyclic prefix length. Since the length of the useful signal data part has been determined, that is, the target data length, the cyclic prefix length needs to be estimated at this time.

[0035] The initial minimum cyclic prefix length and the initial maximum cyclic prefix length are preset values. In the initial cyclic prefix length range formed by the initial minimum cyclic prefix length and the initial maximum cyclic prefix length, multiple search points are obtained by using the binary search method, each search point corresponds to a cyclic prefix length estimation value, and the cyclic prefix length estimation value corresponding to the minimum judgment parameter value is searched in the initial cyclic prefix length range, and the cyclic prefix length estimation value corresponding to the minimum judgment parameter value is used as the initial cyclic prefix length estimation value of the preliminary estimation, wherein each search point corresponds to a judgment parameter value, and the judgment parameter value measures the maximum peak value among multiple cross-correlation values ​​corresponding to the cyclic prefix length estimation value under the search point in the binary search method, and the larger the cross-correlation value, the smaller the judgment parameter value, wherein the cross-correlation value represents the value of the degree of correlation between two segments of signal data. For the cyclic prefix length estimation value corresponding to each search point in the binary search method, the cyclic prefix length estimation value is used as the window length, the target data length is used as the data interval, and the cyclic prefix length estimation value is slid in the preprocessed signal to obtain multiple groups of two segments of signal data, and a cross-correlation value is calculated based on each group of two segments of signal data. Therefore, the initial cyclic prefix length obtained by the binary search indicates an approximate value based on the preliminary estimation of the cyclic prefix length range.

[0036] S14. Obtain correction factor.

[0037] In this embodiment, since the cyclic prefix length is greatly affected by the signal-to-noise ratio, a correction factor needs to be added to correct the preliminarily estimated initial cyclic prefix length, thereby obtaining the final cyclic prefix length.

[0038] S15. Based on the correction factor, correct the initial cyclic prefix length to obtain a target cyclic prefix length of the signal to be measured.

[0039] In this embodiment, the correction factor may be a positive value or a negative value, and the target cyclic prefix length is the sum of the correction factor and the initial cyclic prefix length.

[0040] In the above embodiment, a signal to be tested is received, and it is first determined whether the signal to be tested is an orthogonal frequency division multiplexing (OFDM) signal. When it is determined that the signal to be tested is an OFDM signal, a target data length estimated for one of the OFDM signals is obtained, and an initial minimum cyclic prefix length and an initial maximum cyclic prefix length are obtained. Within the range of an initial cyclic prefix length formed based on the initial minimum cyclic prefix length and the initial maximum cyclic prefix length, an initial cyclic prefix length is searched based on the target data length, and then the initial cyclic prefix length is corrected based on a correction factor to obtain a final cyclic prefix length, that is, a signal parameter of the signal to be tested can be obtained, so that the signal parameter can be more accurately identified and different types of image transmission signals can be more accurately identified according to the signal parameter. Since the cyclic prefix length is diverse and a priori unknown, the amount of traversal calculation is large. To address the problem of large amount of traversal calculation, a binary search method is used to greatly reduce the search time, reduce the amount of calculation, and save system resources.

[0041] In some embodiments, determining whether the signal to be tested is an OFDM signal based on the signal to be tested includes:

[0042] Obtain a set of candidate data lengths, an initial window length, and a sliding length;

[0043] Acquire multiple candidate data lengths from the candidate data length set, for each of the candidate data lengths, use the candidate data length as a data interval, use the initial window length as a data segment length, and based on the sliding length and the signal to be measured, slide and select multiple groups of first signals and second signals, and calculate the cross-correlation value between each group of first signals and second signals, to obtain multiple cross-correlation values ​​corresponding to each candidate data length;

[0044] Calculating a peak threshold value corresponding to the signal to be measured;

[0045] Based on a plurality of cross-correlation values ​​corresponding to each candidate data length and the peak threshold value, it is determined whether the signal to be tested is an OFDM signal.

[0046] In this embodiment, this part belongs to the P parameter estimation part in OFDM signal parameter estimation, and the P parameter estimation belongs to the length estimation part of the effective signal data. Since the preprocessed signal has a limited number of possible data lengths, the data length that may appear in the current downsampling is L data(i), i = 1, 2, ..., I, the data length represents the length of the valid signal data part, wherein the candidate data length set represents a set of multiple possible data lengths, for example, there are I candidate data lengths, wherein i represents the i-th case, and the initial window length represents the length of the initialized data segment. For the first I candidate data lengths, under each candidate data length, based on the configured sliding length, multiple groups of first signals and second signals are sequentially selected from the preprocessed signal s(n) by sliding. Figure 4 As shown, Figure 4 FIG. 1 is a schematic diagram of a first signal and a second signal in an embodiment. The figure only illustrates a schematic diagram of signals under two time units. Under a candidate data length, the candidate data length is used as the data interval, and the initial window length is used as the data segment length to select the first signal and the second signal. Figure 4 A group of first signals and second signals are shown in FIG. After obtaining the two segments of the signal, the cross-correlation value of the two segments of the signal is calculated, wherein the length of the two segments of the signal is the initial window length. The sliding length is moved in the timing direction, and another group of first signals and second signals are taken, and the cross-correlation value of the two segments of the signal is continued to be calculated. The sliding is continued until the sliding is terminated, and multiple cross-correlation values ​​are obtained under one candidate data length. For example, if the sliding is performed 100 times, there will be 100 cross-correlation values ​​under one candidate data length. For example, if there are 20 candidate data lengths in total, 2000 cross-correlation values ​​will be obtained.

[0047] Based on the first cross-correlation function, the cross-correlation value between the two signals is calculated. The calculation formula of the first cross-correlation function is as follows:

[0048]

[0049] In the first cross-correlation function formula, L slide is the sliding length, L data is the candidate data length, x(n) is the first cross-correlation function, n is the sliding length index, i is the index of the signal point, s[i+(n-1)] is the first signal, s*[i+L data +(n-1)] represents the second signal, and Lwin represents the initial window length.

[0050] In this embodiment, the peak threshold value represents the maximum amplitude threshold of the signal to be tested, which can be calculated using a peak decision method, for example, using OS-CFAR (selected small unit average constant false alarm detection) to calculate the maximum amplitude threshold η.

[0051] Optionally, the determining whether the signal to be tested is an OFDM signal based on the multiple cross-correlation values ​​corresponding to each candidate data length and the peak threshold value includes:

[0052] Obtaining a maximum cross-correlation value from a plurality of cross-correlation values ​​corresponding to each candidate data length, and determining that the signal to be tested is an OFDM signal when the maximum cross-correlation value is greater than the peak threshold value;

[0053] The obtaining of a target data length estimated for one of the OFDM signals comprises:

[0054] The data length corresponding to the maximum cross-correlation value is used as the target data length.

[0055] In this embodiment, the maximum cross-correlation value MAX_Value of x(n) is then found, and MAX_Value is compared with η. If MAX_Value>η, the signal is judged as an OFDM signal, and the target data length is estimated to be the current L corresponding to the maximum cross-correlation value. data (i). like Figure 5 As shown, Figure 5 Schematic diagram of mutual function value and threshold value in an embodiment, different first mutual correlation functions and decision thresholds, the blue curve in the figure is the first mutual correlation function, the yellow is the peak threshold value, when a candidate data length matches the actual data length, the multiple mutual correlation values ​​corresponding to the candidate data length are taken as the ordinate, and the number of sliding points is taken as the abscissa, and the following is obtained: Figure 5 The figure shown on the left shows that the maximum cross-correlation value is greater than the peak threshold value. The peak threshold value can be determined to obtain an estimated value of the data length. After obtaining the accurate length of the valid signal data part, the data segment length can be traversed to estimate the cyclic prefix length.

[0056] In the above embodiment, multiple candidate data lengths are obtained from a set of candidate data lengths. For each candidate data length, the sliding length is moved multiple times in the timing direction to obtain multiple groups of first signals and second signals. The cross-correlation value between each group of first signals and second signals is calculated to obtain multiple cross-correlation values ​​corresponding to each candidate data length. The maximum cross-correlation value is found. When the maximum cross-correlation value is greater than the peak threshold value, it indicates that the candidate data length corresponding to the maximum cross-correlation value matches the actual data length, so that the length of the effective signal data portion in an OFDM symbol can be accurately estimated, thereby improving the basis for the subsequent accurate estimation of the cyclic prefix length.

[0057] In some embodiments, Figure 6 As shown, Figure 6 This is a flow chart of determining an initial cyclic prefix length in an embodiment, wherein step S13 further includes:

[0058] S131. Form an initial cyclic prefix length range based on an initial minimum cyclic prefix length and an initial maximum cyclic prefix length.

[0059] S132. Based on the target data length, in the initial cyclic prefix length range, use the binary search method to search for the estimated cyclic prefix length corresponding to the minimum value of the evaluation parameter, and use the estimated cyclic prefix length corresponding to the minimum value of the evaluation parameter as the preliminary estimated initial cyclic prefix length.

[0060] In this embodiment, in the binary method, one search point corresponds to one cyclic prefix length estimation value, and one cyclic prefix length estimation value corresponds to one evaluation parameter value, so that one search point corresponds to one evaluation parameter value. Figure 7 As shown, Figure 7 A schematic diagram of a trend between a cyclic prefix length and a judgment parameter value in an embodiment; Figure 7 The peak decision parameter in the ordinate is the judgment parameter value, and the abscissa is the cyclic prefix length estimation value. Different cyclic prefix length estimation values ​​correspond to different judgment parameter values. On the whole, the judgment parameter value first decreases and then increases with the increase of the cyclic prefix length; then on the whole, the maximum cross-correlation peak value first increases and then decreases with the increase of the cyclic prefix length. When the judgment parameter value is the minimum, the cyclic prefix length estimation value is closest to the actual cyclic prefix length of the signal to be measured.

[0061] In the above embodiment, the binary search method is used to search for a cyclic prefix length estimate in the initial cyclic prefix length range, and the cyclic prefix length estimate corresponding to the cyclic prefix length estimate corresponding to the minimum value of the judgment parameter is used as the preliminary estimated initial cyclic prefix length. The cyclic prefix lengths are diverse and a priori unknown, so the traversal calculation amount is large. To address the problem of large traversal calculation amount, the binary search method is used to greatly reduce the search time, reduce the amount of calculation, and save system resources.

[0062] In some embodiments, Figure 8 As shown, step S132 further includes:

[0063] S1321. Initialize a current cyclic prefix length range based on an initial minimum cyclic prefix length and an initial maximum cyclic prefix length, wherein the current cyclic prefix length range includes three current length points, which are a current minimum length point, a current middle length point, and a current maximum length point.

[0064] In this embodiment, during the first cycle, that is, during the initialization process, the current cyclic prefix length range is the initial cyclic prefix length range, that is, the initialization parameter is [Min_Lcp Middle_Lcp Max_Lcp], where Min_Lcp, Middle_Lcp and Max_Lcp respectively represent the current minimum length point, the current middle length point and the current maximum length point in the initial cyclic prefix length range. The estimated cyclic prefix length corresponding to the current minimum length point is the initial minimum cyclic prefix length, the estimated cyclic prefix length corresponding to the current maximum length point is the initial maximum cyclic prefix length, and the estimated cyclic prefix length corresponding to the current middle length point is the average of the initial minimum cyclic prefix length and the initial maximum cyclic prefix length.

[0065] In the subsequent cycle process, the binary division method is used to continue to update the binary interval range, that is, to update the current cyclic prefix length range.

[0066] S1322. Calculate the evaluation parameter values ​​corresponding to the three current length points.

[0067] In some embodiments, the calculating the evaluation parameter values ​​corresponding to the three current length points includes:

[0068] For each of the current length points, the target data length is used as the data interval, the estimated value of the cyclic prefix length corresponding to the current length point is used as the data segment length, and based on the preset sliding length and the signal to be measured, multiple groups of third signals and fourth signals are selected by sliding, and the cross-correlation value between each group of the third signal and the fourth signal is calculated to obtain multiple cross-correlation values ​​corresponding to each of the current length points;

[0069] Based on the multiple cross-correlation values ​​corresponding to each of the current length points, the evaluation parameter value corresponding to each of the current length points is calculated.

[0070] In this embodiment, the current length point is the search point in the binary search method. For each cyclic prefix length estimation value, the target data length is used as the data interval, and the cyclic prefix length estimation value is used as the data segment length. Multiple groups of third signals and fourth signals under the cyclic prefix length estimation value are selected by sliding. Under each cyclic prefix length estimation value, the data segment length of the third signal and the fourth signal is each cyclic prefix length estimation value. Then, the cross-correlation value between each group of the third signal and the fourth signal is calculated to obtain multiple cross-correlation values ​​corresponding to each cyclic prefix length estimation value. For example, if the slide is 200 times, there are 200 cross-correlation values ​​under one cyclic prefix length estimation value. Then, the cyclic prefix length estimation value corresponds to 200 cross-correlation values.

[0071] Based on the second cross-correlation function, the cross-correlation value between the third signal and the fourth signal is calculated. The calculation formula of the second cross-correlation function is as follows:

[0072]

[0073] In the second cross-correlation function formula, L slide is the sliding length, L data1 is the target data length, x1(m) is the second cross-correlation function, m represents the sliding length index, j represents the index of the signal point, s[j+(m-1)] represents the third signal, s*[j+L data1 +(m-1)] represents the fourth signal, and Lwin represents the window length, that is, a cyclic prefix length estimation value. Therefore, according to the above method, multiple cross-correlation values ​​corresponding to the cyclic prefix length estimation value at each current length point can be obtained, thereby obtaining the evaluation parameter value corresponding to each current length point.

[0074] like Fig. 9 As shown, Fig. 9 is a cross-correlation function diagram corresponding to different cyclic prefix length estimation values ​​in an embodiment, Fig. 9 The window length in is the estimated value of the cyclic prefix length. Under different estimated values ​​of the cyclic prefix length, the corresponding cross-correlation function is different. The corresponding cross-correlation functions are shown when the estimated values ​​of the cyclic prefix length are 72 units, 144 units, and 512 units. Under each cyclic prefix length, multiple cross-correlation values ​​are obtained. Fig. 9 It can be seen that for any cyclic prefix length estimate, during the sliding process, the trend of the cross-correlation function value increases first and then decreases. This is related to the working principle of the cyclic prefix. The working principle of the cyclic prefix copies the tail of the OFDM symbol and places it at the head of the OFDM symbol to form a cyclic structure. Then, when the cyclic prefix length estimate is closest to the actual cyclic prefix length, during the sliding process, the corresponding cross-correlation function value can present the sharpest peak, and the two signal segments with the maximum cross-correlation value can be found, namely the tail of the OFDM symbol and the head of the OFDM symbol.

[0075] In this embodiment, the cross-correlation functions calculated based on different cyclic prefix length estimation values ​​have different shapes. Generally, the closer the cyclic prefix length estimation value is to the actual cyclic prefix length, the sharper the peak of the cross-correlation function is. Figure 7 As shown in the figure, when the window length is 144, that is, the estimated value of the cyclic prefix length is 144 units, the peak is the sharpest, and 144 units are closer to the actual cyclic prefix length. Therefore, by judging the parameter value, the sharpest peak can be found from the cross-correlation functions corresponding to multiple cyclic prefix length estimates, thereby finding the cyclic prefix length estimate corresponding to the sharpest peak.

[0076] In some embodiments, the calculating the evaluation parameter value corresponding to each current length point based on the multiple cross-correlation values ​​corresponding to each current length point comprises:

[0077] For any of the current length points, based on a plurality of cross-correlation values ​​corresponding to the current length point, obtaining a maximum cross-correlation peak value corresponding to the current length point;

[0078] Based on the maximum cross-correlation peak, the half-peak width corresponding to the current length point is calculated;

[0079] The absolute value of the difference between the half-peak width and the current length point is calculated, and the sum of the absolute value of the difference and the half-peak width is used as the evaluation parameter value.

[0080] In this embodiment, for a cross-correlation function, the half-peak width is the index difference corresponding to half of the maximum cross-correlation peak value in the cross-correlation function. For example, in a cross-correlation function, the maximum cross-correlation peak value is 100, and half of the maximum cross-correlation peak value is 50. For 50 corresponding to two signal point positions, namely the position of the 100th signal point and the position of the 300th signal point, the index difference is 200. For a cyclic prefix length estimate, its corresponding evaluation parameter value is the half-peak width corresponding to the cyclic prefix length estimate + abs (the half-peak width corresponding to the cyclic prefix length estimate - the cyclic prefix length estimate), where abs represents the absolute value. The smaller the evaluation parameter value, the sharper the corresponding maximum cross-correlation peak value. Therefore, the size of the evaluation parameter value corresponding to the cyclic prefix length estimate is used to indicate the sharpness of the maximum cross-correlation peak value corresponding to the cyclic prefix length estimate. The maximum mutual peak value is the maximum value among multiple mutual values.

[0081] S1323. Based on the judgment parameter values ​​corresponding to the three current length points, update the current cyclic prefix length range, continue to calculate the judgment parameter values ​​corresponding to the three updated current length points until the loop termination condition is met, obtain the cyclic prefix length estimation value corresponding to the target length point after the loop termination condition is met, and determine the initial cyclic prefix length based on the cyclic prefix length estimation value corresponding to the target length point.

[0082] In the above embodiment, the estimated value of the cyclic prefix length is searched for in the initial cyclic prefix length range by using the binary search method, and the current cyclic prefix length range is continuously updated based on the evaluation parameter values ​​corresponding to each search point in the current cyclic prefix length range until the loop termination condition is met to obtain the initial cyclic prefix length. Since the cyclic prefix length is diverse and unknown a priori, the amount of traversal calculation is large. To address the problem of large amount of traversal calculation, the binary search method is used to greatly reduce the search time, reduce the amount of calculation, and save system resources.

[0083] Optionally, S1323 specifically includes:

[0084] When it is determined based on the judgment parameter values ​​corresponding to the three current length points that the judgment parameter value shows an upward trend, and the absolute value of the difference between the judgment parameter values ​​corresponding to two adjacent current length points is greater than a first preset difference, updating the current maximum length point to the current intermediate length point, calculating a first average length value of the cyclic prefix length estimation value corresponding to the current minimum length point and the cyclic prefix length estimation value corresponding to the current intermediate length point, and updating the current intermediate length point based on the first average length value;

[0085] When it is determined based on the judgment parameter values ​​corresponding to the three current length points that the judgment parameter value is in a downward trend and the absolute value of the difference between the judgment parameter values ​​corresponding to two adjacent current length points is greater, the current minimum length point is updated to the current intermediate length point, a second average length value of the cyclic prefix length estimation value corresponding to the current maximum length point and the cyclic prefix length estimation value corresponding to the current intermediate length point is calculated, and the current intermediate length point is updated based on the second average length value;

[0086] When the absolute value of the difference between the evaluation parameter value corresponding to the current minimum length point and the evaluation parameter value corresponding to the current intermediate length point is less than a second preset difference, and / or the absolute value of the difference between the evaluation parameter value corresponding to the current intermediate length point and the evaluation parameter value corresponding to the current maximum length point is less than a second preset difference, the current cyclic prefix length range is further subdivided into two partitions to obtain two current sub-intervals, and the current cyclic prefix length range is updated based on the two current sub-intervals until the loop termination condition is met.

[0087] In this embodiment, when the evaluation parameter value is on an upward trend, in order to find the minimum evaluation parameter value more quickly, it is necessary to retain the first half of the current cyclic prefix length range, that is, to update the first half of the current cyclic prefix length range to the current cyclic prefix range. Specifically, [Min_Lcp Middle_Lcp Max_Lcp], where Min_Lcp, Middle_Lcp and Max_Lcp respectively represent the current minimum length point, the current middle length point and the current maximum length point in the initial cyclic prefix length range, the evaluation parameter value of Min_Lcp is less than the evaluation parameter value of Middle_Lcp, and the evaluation parameter value of Middle_Lcp is less than the evaluation parameter value of Max_Lcp, then the next value is [Min_Lcp Middle_Lcp1 Middle_Lcp], where Middle_Lcp1 represents the median of Min_Lcp and Middle_Lcp, and the cycle is repeated in sequence. When the evaluation parameter value is on a downward trend, in order to find the minimum evaluation parameter value more quickly, it is necessary to retain the second half of the current cyclic prefix length range, that is, to update the second half of the current cyclic prefix length range to the current cyclic prefix range. Specifically, [Min_Lcp Middle_LcpMax_Lcp], where Min_Lcp, Middle_Lcp and Max_Lcp respectively represent the current minimum length point, the current middle length point and the current maximum length point in the initial cyclic prefix length range, and the evaluation parameter value of Min_Lcp is greater than the evaluation parameter value of Middle_Lcp, and the evaluation parameter value of Middle_Lcp is greater than the evaluation parameter value of Max_Lcp, then the next value will be taken in [Middle_Lcp Middle_Lcp1 Max_Lcp], where Middle_Lcp1 represents the average of Max_Lcp and Middle_Lcp, and the cycle is repeated in sequence.

[0088] like Fig.10 As shown, in Fig.10 In (a), A1 is the current minimum length point, A2 is the current middle length point, and A3 is the current maximum length point. The judgment parameter value of A1 is less than the judgment parameter value of A2, and the judgment parameter value of A2 is less than the judgment parameter value of A3. Then continue to divide the range formed by A1 and A2 into two parts. In the next cycle, we get the following Fig.10 In (b), A1 is taken as the current minimum length point, A2 is taken as the current maximum length point, and the point corresponding to the average of the cyclic prefix length estimates corresponding to A1 and A2 is taken as A4, and A4 is the current intermediate length point. According to the method here, Fig.10 (b) in the above method continues to retain the first half, that is, retain the range formed by A1 and A4, and use the range formed by A1 and A4 as the current cyclic prefix length range, such as Fig.10In (c), A1 is taken as the current minimum length point, A4 is taken as the current maximum length point, and the point corresponding to the average of the cyclic prefix length estimation values ​​corresponding to A1 and A4 is taken as A5, and A5 is the current intermediate length point. Since the judgment parameter value corresponding to A5 is very close to the judgment parameter value corresponding to A1, decision ambiguity will occur. In order to better search for the cyclic prefix length estimation value corresponding to the minimum judgment parameter value, it is necessary to subdivide the range formed by A1 and A4 into two partitions.

[0089] Optionally, the further subdividing the current cyclic prefix length range into two partitions to obtain two current sub-intervals, and updating the current cyclic prefix length range based on the two current sub-intervals until a loop termination condition is met, includes:

[0090] Determining a first current subinterval based on the current minimum length point and the current intermediate length point;

[0091] Based on the current maximum length point and the current middle length point, determining a second current sub-interval; wherein each of the current sub-intervals includes three sub-length points, the three sub-length points being a current minimum sub-length point, a current middle sub-length point, and a current maximum sub-length point;

[0092] Based on the judgment parameters corresponding to the three sub-length points in the first current sub-interval and the judgment parameters corresponding to the three sub-length points in the second current sub-interval, the current cyclic prefix length range is updated, and the updated current cyclic prefix length range is continued to be subdivided into two partitions to obtain two current sub-intervals, until the absolute values ​​of the differences between the cyclic prefix length estimation values ​​corresponding to the multiple sub-length points in the two current sub-intervals are all less than the third preset difference, and it is determined that the loop termination condition is satisfied.

[0093] Optionally, updating the current cyclic prefix length range based on the evaluation parameters corresponding to the three sub-length points in the first current sub-interval and the evaluation parameters corresponding to the three sub-length points in the second current sub-interval includes:

[0094] From the judgment parameters corresponding to the three sub-length points in the first current sub-interval and the judgment parameters corresponding to the three sub-length points in the second current sub-interval, select a local minimum judgment parameter value, and use the target sub-length point corresponding to the local minimum judgment parameter value as the current middle length point of the updated current cyclic prefix length range, and use the two sub-length points adjacent to the target sub-length point as the current minimum length point and the current maximum length point of the updated current cyclic prefix length range, respectively.

[0095] In this embodiment, the second preset difference is smaller than the first preset difference, and the third preset difference is smaller than the second preset difference. Fig.10 In (d), the current cyclic prefix length range formed by the range formed by A1 and A4 is further subdivided into two partitions to obtain the first current sub-interval, that is, the range formed by A1 and A5, and the second current sub-interval is the range formed by A5 and A4. In the first current sub-interval, three search points are included, namely A1 is the current minimum sub-length point, A6 is the point corresponding to the average of the cyclic prefix length estimates corresponding to A1 and A5, A6 is the current intermediate sub-length point, and A5 is the current maximum sub-length point. In the second current sub-interval, three search points are included, namely A5 is the current minimum sub-length point, A7 is the point corresponding to the average of the cyclic prefix length estimates corresponding to A4 and A5, A7 is the current intermediate sub-length point, and A4 is the current maximum sub-length point. From Fig.10 It can be seen from (d) in that the evaluation parameter value of A5 is the smallest, and A5 is the local minimum evaluation parameter value. Based on A5, the adjacent search points are found to be A6 and A7. The range formed by A6, A5 and A7 is used as the current cyclic prefix length range, and then the next step of subdivision between the two partitions is performed to obtain Fig.10 (e) in the Fig.10 The treatment method of (d) in Fig.10 After processing (e) in the above formula, we can get Fig.10 In (f). Fig.10 In (f), the evaluation parameter values ​​of A5, A10, A9 and A11 are very close. The estimated cyclic prefix lengths corresponding to A5, A10, A9 and A11 can be accumulated and averaged to obtain the initial cyclic prefix length. In the case of high signal-to-noise ratio, the estimated result can be obtained with good accuracy after a few operations, which greatly reduces the amount of calculation in the system.

[0096] In the above embodiment, the estimated value of the cyclic prefix length is searched for in the initial cyclic prefix length range by using the binary search method, and the current cyclic prefix length range is continuously updated based on the evaluation parameter values ​​corresponding to each search point in the current cyclic prefix length range. When the evaluation parameters in the current cyclic prefix length range are very close, the current cyclic prefix length range is subdivided into two binary sub-intervals to obtain two binary sub-interval ranges, and the current cyclic prefix length range is cyclically updated until the loop termination condition is met to obtain the initial cyclic prefix length. Since the cyclic prefix length is diverse and a priori unknown, the traversal calculation amount is large. To address the problem of large traversal calculation amount, the binary search method is used to traverse, which can greatly reduce the search time, reduce the amount of calculation, and save system resources.

[0097] In some embodiments, obtaining the correction factor comprises:

[0098] Acquire a signal to be tested, a configured signal-to-noise ratio, and a real test cyclic prefix length corresponding to the signal to be tested;

[0099] Based on the test signal and the signal-to-noise ratio, perform a cyclic prefix length estimation operation multiple times to determine multiple estimated test cyclic prefix lengths corresponding to the multiple estimated test signals;

[0100] The correction factor is calculated based on a plurality of estimated test cyclic prefix lengths and the actual test cyclic prefix length.

[0101] In this embodiment, in the process of estimating the initial cyclic prefix length, it will be affected by the signal-to-noise ratio, so the initial cyclic prefix length needs to be corrected by a correction factor. The correction factor is related to the signal-to-noise ratio. The lower the signal-to-noise ratio, the greater the noise, the greater the value of the correction factor, and the value trend of the correction factor is negatively correlated with the signal-to-noise ratio. For a signal to be tested, after setting the signal-to-noise ratio, the OFDM signal parameter estimation method provided in the embodiment of the present application can be used to estimate the estimated cyclic prefix length corresponding to the signal to be tested multiple times, and the multiple estimated test cyclic prefix lengths estimated multiple times are averaged to obtain the average cyclic prefix length, and the average cyclic prefix length is compared with the actual test cyclic prefix length, and the difference between the actual test cyclic prefix length and the average cyclic prefix length is used as the correction factor. For example, this simulation uses SNR=10dB, correction factor=4, and the estimated cyclic prefix length corresponding to the signal to be tested is 141, so the target cyclic prefix length is 141+4=145, and the actual cyclic prefix length is 144, so the corrected cyclic prefix length is closer to the actual cyclic prefix length.

[0102] In the above embodiment, by estimating multiple estimated test cyclic prefix lengths of the signal to be tested multiple times, the correction factor is calculated based on the multiple estimated test cyclic prefix lengths and the actual test cyclic prefix length, thereby reducing the impact of noise on parameter estimation and improving the accuracy of signal parameter estimation.

[0103] In some embodiments, the method further comprises:

[0104] Outputting an estimation result of the signal to be measured;

[0105] The outputting of the estimation result of the signal to be tested includes at least one of the following:

[0106] Outputting whether the signal to be tested is the OFDM signal;

[0107] In a case where the signal to be tested is the OFDM signal, the target data length and the target cyclic prefix length corresponding to the signal to be tested are output.

[0108] In the above embodiment, the estimation result of the signal to be measured may be output through the user interface so that the user can intuitively understand the estimation result, thereby improving the user experience.

[0109] On the other hand, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the OFDM signal parameter estimation method described in any embodiment of the present application.

[0110] Among them, in the computer program product, an optional implementation form of the program module architecture of the computer program that implements each step of the OFDM signal parameter estimation method can be an OFDM signal parameter estimation device.

[0111] See also Fig.11 An embodiment of the present application provides an OFDM signal parameter estimation device, including: a receiving module 1101, used to receive a signal to be tested; a determining module 1102, used to determine whether the signal to be tested is an orthogonal frequency division multiplexing OFDM signal based on the signal to be tested, and when it is determined that the signal to be tested is an OFDM signal, obtain a target data length estimated for the OFDM signal; an estimating module 1103 is used to obtain an initial minimum cyclic prefix length and an initial maximum cyclic prefix length, and based on the initial minimum cyclic prefix length, the initial maximum cyclic prefix length and the target data length, the initial cyclic prefix length is estimated using a binary search method; the obtaining module 1102 is also used to obtain a correction factor; and a correcting module 1104 is used to correct the initial cyclic prefix length based on the correction factor to obtain a target cyclic prefix length of the signal to be tested.

[0112] Optionally, the determination module 1102 is further configured to:

[0113] Obtain a set of candidate data lengths, an initial window length, and a sliding length;

[0114] Acquire multiple candidate data lengths from the candidate data length set, for each of the candidate data lengths, use the candidate data length as a data interval, use the initial window length as a data segment length, and based on the sliding length and the signal to be measured, slide and select multiple groups of first signals and second signals, and calculate the cross-correlation value between each group of first signals and second signals, to obtain multiple cross-correlation values ​​corresponding to each candidate data length;

[0115] Calculating a peak threshold value corresponding to the signal to be measured;

[0116] Based on a plurality of cross-correlation values ​​corresponding to each candidate data length and the peak threshold value, it is determined whether the signal to be tested is an OFDM signal.

[0117] Optionally, the determination module 1102 is further configured to:

[0118] Obtaining a maximum cross-correlation value from a plurality of cross-correlation values ​​corresponding to each candidate data length, and determining that the signal to be tested is an OFDM signal when the maximum cross-correlation value is greater than the peak threshold value;

[0119] The obtaining of a target data length estimated for one of the OFDM signals comprises:

[0120] The data length corresponding to the maximum cross-correlation value is used as the target data length.

[0121] Optionally, the estimation module 1103 is further used for:

[0122] Based on the initial minimum cyclic prefix length and the initial maximum cyclic prefix length, forming an initial cyclic prefix length range;

[0123] Based on the target data length, in the initial cyclic prefix length range, a cyclic prefix length estimation value corresponding to a minimum judgment parameter value is searched using a binary search method, and the cyclic prefix length estimation value corresponding to the minimum judgment parameter value is used as a preliminary estimated initial cyclic prefix length.

[0124] Optionally, the estimation module 1103 is further used for:

[0125] Initialize a current cyclic prefix length range based on the initial minimum cyclic prefix length and the initial maximum cyclic prefix length, wherein the current cyclic prefix length range includes three current length points, which are a current minimum length point, a current middle length point, and a current maximum length point;

[0126] Calculate the evaluation parameter values ​​corresponding to the three current length points;

[0127] Based on the judgment parameter values ​​corresponding to the three current length points, the current cyclic prefix length range is updated, and the judgment parameter values ​​corresponding to the three updated current length points are continuously calculated until the loop termination condition is met, and the cyclic prefix length estimation value corresponding to the target length point after the loop termination condition is met is obtained, and the initial cyclic prefix length is determined based on the cyclic prefix length estimation value corresponding to the target length point.

[0128] Optionally, the estimation module 1103 is further used for:

[0129] For each of the current length points, the target data length is used as the data interval, the estimated value of the cyclic prefix length corresponding to the current length point is used as the data segment length, and based on the preset sliding length and the signal to be measured, multiple groups of third signals and fourth signals are selected by sliding, and the cross-correlation value between each group of the third signal and the fourth signal is calculated to obtain multiple cross-correlation values ​​corresponding to each of the current length points;

[0130] Based on the multiple cross-correlation values ​​corresponding to each of the current length points, the evaluation parameter value corresponding to each of the current length points is calculated.

[0131] Optionally, the estimation module 1103 is further used for:

[0132] For any of the current length points, based on a plurality of cross-correlation values ​​corresponding to the current length point, obtaining a maximum cross-correlation peak value corresponding to the current length point;

[0133] Based on the maximum cross-correlation peak, the half-peak width corresponding to the current length point is calculated;

[0134] The absolute value of the difference between the half-peak width and the current length point is calculated, and the sum of the absolute value of the difference and the half-peak width is used as the evaluation parameter value.

[0135] Optionally, the estimation module 1103 is further used for:

[0136] When it is determined based on the judgment parameter values ​​corresponding to the three current length points that the judgment parameter value shows an upward trend, and the absolute value of the difference between the judgment parameter values ​​corresponding to two adjacent current length points is greater than a first preset difference, updating the current maximum length point to the current intermediate length point, calculating a first average length value of the cyclic prefix length estimation value corresponding to the current minimum length point and the cyclic prefix length estimation value corresponding to the current intermediate length point, and updating the current intermediate length point based on the first average length value;

[0137] When it is determined based on the judgment parameter values ​​corresponding to the three current length points that the judgment parameter value is in a downward trend and the absolute value of the difference between the judgment parameter values ​​corresponding to two adjacent current length points is greater, the current minimum length point is updated to the current intermediate length point, a second average length value of the cyclic prefix length estimation value corresponding to the current maximum length point and the cyclic prefix length estimation value corresponding to the current intermediate length point is calculated, and the current intermediate length point is updated based on the second average length value;

[0138] When the absolute value of the difference between the evaluation parameter value corresponding to the current minimum length point and the evaluation parameter value corresponding to the current intermediate length point is less than a second preset difference, and / or the absolute value of the difference between the evaluation parameter value corresponding to the current intermediate length point and the evaluation parameter value corresponding to the current maximum length point is less than a second preset difference, the current cyclic prefix length range is further subdivided into two partitions to obtain two current sub-intervals, and the current cyclic prefix length range is updated based on the two current sub-intervals until the loop termination condition is met.

[0139] Optionally, the estimation module 1103 is further used for:

[0140] Determining a first current subinterval based on the current minimum length point and the current intermediate length point;

[0141] Based on the current maximum length point and the current middle length point, determining a second current sub-interval; wherein each of the current sub-intervals includes three sub-length points, the three sub-length points being a current minimum sub-length point, a current middle sub-length point, and a current maximum sub-length point;

[0142] Based on the judgment parameters corresponding to the three sub-length points in the first current sub-interval and the judgment parameters corresponding to the three sub-length points in the second current sub-interval, the current cyclic prefix length range is updated, and the updated current cyclic prefix length range is continued to be subdivided into two partitions to obtain two current sub-intervals, until the absolute values ​​of the differences between the cyclic prefix length estimation values ​​corresponding to the multiple sub-length points in the two current sub-intervals are all less than the third preset difference, and it is determined that the loop termination condition is satisfied.

[0143] Optionally, the estimation module 1103 is further used for:

[0144] From the judgment parameters corresponding to the three sub-length points in the first current sub-interval and the judgment parameters corresponding to the three sub-length points in the second current sub-interval, select a local minimum judgment parameter value, and use the target sub-length point corresponding to the local minimum judgment parameter value as the current middle length point of the updated current cyclic prefix length range, and use the two sub-length points adjacent to the target sub-length point as the current minimum length point and the current maximum length point of the updated current cyclic prefix length range, respectively.

[0145] Optionally, the correction module 1104 is further used for:

[0146] Acquire a signal to be tested, a configured signal-to-noise ratio, and a real test cyclic prefix length corresponding to the signal to be tested;

[0147] Based on the test signal and the signal-to-noise ratio, perform a cyclic prefix length estimation operation multiple times to determine multiple estimated test cyclic prefix lengths corresponding to the multiple estimated test signals;

[0148] The correction factor is calculated based on a plurality of estimated test cyclic prefix lengths and the actual test cyclic prefix length.

[0149] Optionally, an OFDM signal parameter estimation device further includes an output module 1105, which is used to:

[0150] Outputting an estimation result of the signal to be measured;

[0151] The outputting of the estimation result of the signal to be tested includes at least one of the following:

[0152] Outputting whether the signal to be tested is the OFDM signal;

[0153] In a case where the signal to be tested is the OFDM signal, the target data length and the target cyclic prefix length corresponding to the signal to be tested are output.

[0154] It can be understood by those skilled in the art that Fig.11 The structure of the OFDM signal parameter estimation device does not constitute a limitation on the OFDM signal parameter estimation device, and the various modules can be implemented in whole or in part by software, hardware, and a combination thereof. The above modules can be embedded in or independent of the processor in the OFDM signal parameter estimation device in the form of hardware, or can be stored in the memory in the OFDM signal parameter estimation device in the form of software, so that the processor can call and execute the operations corresponding to the above modules. In other embodiments, the OFDM signal parameter estimation device may include more or fewer modules than those shown in the figure.

[0155] See also Fig.12 On the other hand, an embodiment of the present application further provides an OFDM signal parameter estimation device 10, including a processor 13 and a memory 14, wherein the memory 14 stores a computer program, and when the computer program is executed by the processor, the processor 13 executes the steps of the OFDM signal parameter estimation method provided in any of the above embodiments of the present application.

[0156] The processor 13 is the control center, which uses various interfaces and lines to connect various parts of the entire OFDM signal parameter estimation device, and executes various functions and processes data of the OFDM signal parameter estimation device by running or executing software programs and / or modules stored in the memory 14, and calling data stored in the memory 14. Optionally, the processor 13 may include one or more processing cores; preferably, the processor 13 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user pages and applications, etc., and the modem processor mainly processes wireless communications. It can be understood that the above-mentioned modem processor may not be integrated into the processor 13.

[0157] The memory 14 can be used to store software programs and modules. The processor 13 executes various functional applications and data processing by running the software programs and modules stored in the memory 14. The memory 14 can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data created according to the use of the OFDM signal parameter estimation device, etc. In addition, the memory 14 can include a high-speed random access memory, and can also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices. Accordingly, the memory 14 can also include a memory processor to provide the processor 13 with access to the memory 14.

[0158] On the other hand, an embodiment of the present application further provides a storage medium storing a computer program. When the computer program is executed by a processor, the processor executes the steps of the OFDM signal parameter estimation method provided in any of the above embodiments of the present application.

[0159] In another aspect of an embodiment of the present application, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the OFDM signal parameter estimation method as described in any embodiment of the present application is implemented.

[0160] Those skilled in the art can understand that all or part of the processes in the methods provided in the above embodiments can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in the present application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0161] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. The protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for estimating OFDM signal parameters, characterized in that: include: receiving a signal to be tested; Based on the signal to be tested, determining whether the signal to be tested is an orthogonal frequency division multiplexing (OFDM) signal, and if it is determined that the signal to be tested is an OFDM signal, obtaining a target data length estimated for the OFDM signal; Acquire an initial minimum cyclic prefix length and an initial maximum cyclic prefix length, and estimate the initial cyclic prefix length by using a dichotomy method based on the initial minimum cyclic prefix length, the initial maximum cyclic prefix length and the target data length; Get the correction factor; Based on the correction factor, the initial cyclic prefix length is corrected to obtain a target cyclic prefix length of the signal to be tested.

2. The OFDM signal parameter estimation method according to claim 1, wherein: The determining, based on the signal to be tested, whether the signal to be tested is an OFDM signal comprises: Obtain a set of candidate data lengths, an initial window length, and a sliding length; Acquire multiple candidate data lengths from the candidate data length set, for each of the candidate data lengths, use the candidate data length as a data interval, use the initial window length as a data segment length, and based on the sliding length and the signal to be measured, slide and select multiple groups of first signals and second signals, and calculate the cross-correlation value between each group of first signals and second signals, to obtain multiple cross-correlation values ​​corresponding to each candidate data length; Calculating a peak threshold value corresponding to the signal to be measured; Based on a plurality of cross-correlation values ​​corresponding to each candidate data length and the peak threshold value, it is determined whether the signal to be tested is an OFDM signal.

3. The OFDM signal parameter estimation method according to claim 2, characterized in that: The determining whether the signal to be tested is an OFDM signal based on the multiple cross-correlation values ​​corresponding to each candidate data length and the peak threshold value comprises: Obtaining a maximum cross-correlation value from a plurality of cross-correlation values ​​corresponding to each candidate data length, and determining that the signal to be tested is an OFDM signal when the maximum cross-correlation value is greater than the peak threshold value; The obtaining of a target data length estimated for one of the OFDM signals comprises: The data length corresponding to the maximum cross-correlation value is used as the target data length.

4. The OFDM signal parameter estimation method according to claim 1, wherein: The estimating the initial cyclic prefix length by using a dichotomy method based on the initial minimum cyclic prefix length, the initial maximum cyclic prefix length and the target data length comprises: Based on the initial minimum cyclic prefix length and the initial maximum cyclic prefix length, forming an initial cyclic prefix length range; Based on the target data length, in the initial cyclic prefix length range, a cyclic prefix length estimation value corresponding to a minimum judgment parameter value is searched using a binary search method, and the cyclic prefix length estimation value corresponding to the minimum judgment parameter value is used as a preliminary estimated initial cyclic prefix length.

5. The OFDM signal parameter estimation method according to claim 4, characterized in that: The step of searching, based on the target data length, in the initial cyclic prefix length range, for an estimated cyclic prefix length corresponding to a minimum value of a judgment parameter by using a binary search method, and using the estimated cyclic prefix length corresponding to the minimum value of the judgment parameter as a preliminary estimated initial cyclic prefix length comprises: Initialize a current cyclic prefix length range based on the initial minimum cyclic prefix length and the initial maximum cyclic prefix length, wherein the current cyclic prefix length range includes three current length points, which are a current minimum length point, a current middle length point, and a current maximum length point; Calculate the evaluation parameter values ​​corresponding to the three current length points; Based on the judgment parameter values ​​corresponding to the three current length points, the current cyclic prefix length range is updated, and the judgment parameter values ​​corresponding to the three updated current length points are continuously calculated until the loop termination condition is met, and the cyclic prefix length estimation value corresponding to the target length point after the loop termination condition is met is obtained, and the initial cyclic prefix length is determined based on the cyclic prefix length estimation value corresponding to the target length point.

6. The OFDM signal parameter estimation method according to claim 5, characterized in that: The calculation of the evaluation parameter values ​​corresponding to the three current length points includes: For each of the current length points, the target data length is used as the data interval, the estimated value of the cyclic prefix length corresponding to the current length point is used as the data segment length, and based on the preset sliding length and the signal to be measured, multiple groups of third signals and fourth signals are selected by sliding, and the cross-correlation value between each group of the third signal and the fourth signal is calculated to obtain multiple cross-correlation values ​​corresponding to each of the current length points; Based on a plurality of cross-correlation values ​​corresponding to each of the current length points, a judgment parameter value corresponding to each of the current length points is calculated.

7. The OFDM signal parameter estimation method according to claim 6, characterized in that: The calculating, based on the multiple cross-correlation values ​​corresponding to each current length point, the evaluation parameter value corresponding to each current length point comprises: For any of the current length points, based on a plurality of cross-correlation values ​​corresponding to the current length point, obtaining a maximum cross-correlation peak value corresponding to the current length point; Based on the maximum cross-correlation peak, the half-peak width corresponding to the current length point is calculated; The absolute value of the difference between the half-peak width and the current length point is calculated, and the sum of the absolute value of the difference and the half-peak width is used as the evaluation parameter value.

8. The OFDM signal parameter estimation method according to claim 5, characterized in that: The updating of the current cyclic prefix length range based on the evaluation parameter values ​​corresponding to the three current length points, and continuing to calculate the evaluation parameter values ​​corresponding to the three updated current length points until the loop termination condition is met includes: When it is determined based on the judgment parameter values ​​corresponding to the three current length points that the judgment parameter value shows an upward trend, and the absolute value of the difference between the judgment parameter values ​​corresponding to two adjacent current length points is greater than a first preset difference, updating the current maximum length point to the current intermediate length point, calculating a first average length value of the cyclic prefix length estimation value corresponding to the current minimum length point and the cyclic prefix length estimation value corresponding to the current intermediate length point, and updating the current intermediate length point based on the first average length value; When it is determined based on the judgment parameter values ​​corresponding to the three current length points that the judgment parameter value is in a downward trend and the absolute value of the difference between the judgment parameter values ​​corresponding to two adjacent current length points is greater, the current minimum length point is updated to the current intermediate length point, a second average length value of the cyclic prefix length estimation value corresponding to the current maximum length point and the cyclic prefix length estimation value corresponding to the current intermediate length point is calculated, and the current intermediate length point is updated based on the second average length value; When the absolute value of the difference between the evaluation parameter value corresponding to the current minimum length point and the evaluation parameter value corresponding to the current intermediate length point is less than a second preset difference, and / or the absolute value of the difference between the evaluation parameter value corresponding to the current intermediate length point and the evaluation parameter value corresponding to the current maximum length point is less than a second preset difference, the current cyclic prefix length range is further subdivided into two partitions to obtain two current sub-intervals, and the current cyclic prefix length range is updated based on the two current sub-intervals until the loop termination condition is met.

9. The OFDM signal parameter estimation method according to claim 8, characterized in that: The step of continuing to subdivide the current cyclic prefix length range into two partitions to obtain two current sub-intervals, and updating the current cyclic prefix length range based on the two current sub-intervals until a loop termination condition is satisfied includes: Determining a first current subinterval based on the current minimum length point and the current intermediate length point; Based on the current maximum length point and the current middle length point, determining a second current sub-interval; wherein each of the current sub-intervals includes three sub-length points, the three sub-length points being a current minimum sub-length point, a current middle sub-length point, and a current maximum sub-length point; Based on the judgment parameters corresponding to the three sub-length points in the first current sub-interval and the judgment parameters corresponding to the three sub-length points in the second current sub-interval, the current cyclic prefix length range is updated, and the updated current cyclic prefix length range is continued to be subdivided into two partitions to obtain two current sub-intervals, until the absolute values ​​of the differences between the cyclic prefix length estimation values ​​corresponding to the multiple sub-length points in the two current sub-intervals are all less than the third preset difference, and it is determined that the loop termination condition is satisfied.

10. The OFDM signal parameter estimation method according to claim 9, characterized in that: The updating of the current cyclic prefix length range based on the evaluation parameters corresponding to the three sub-length points in the first current sub-interval and the evaluation parameters corresponding to the three sub-length points in the second current sub-interval includes: From the judgment parameters corresponding to the three sub-length points in the first current sub-interval and the judgment parameters corresponding to the three sub-length points in the second current sub-interval, select a local minimum judgment parameter value, and use the target sub-length point corresponding to the local minimum judgment parameter value as the current middle length point of the updated current cyclic prefix length range, and use the two sub-length points adjacent to the target sub-length point as the current minimum length point and the current maximum length point of the updated current cyclic prefix length range, respectively.

11. The OFDM signal parameter estimation method according to claim 1, wherein: The obtaining of the correction factor comprises: Acquire a signal to be tested, a configured signal-to-noise ratio, and a real test cyclic prefix length corresponding to the signal to be tested; Based on the test signal and the signal-to-noise ratio, perform a cyclic prefix length estimation operation multiple times to determine multiple estimated test cyclic prefix lengths corresponding to the multiple estimated test signals; The correction factor is calculated based on a plurality of estimated test cyclic prefix lengths and the actual test cyclic prefix length.

12. The OFDM signal parameter estimation method according to claim 1, wherein: The method further comprises: Outputting an estimation result of the signal to be measured; The outputting of the estimation result of the signal to be tested includes at least one of the following: Outputting whether the signal to be tested is the OFDM signal; In a case where the signal to be tested is the OFDM signal, the target data length and the target cyclic prefix length corresponding to the signal to be tested are output.

13. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the OFDM signal parameter estimation method according to any one of claims 1 to 11 is implemented.

14. An OFDM signal parameter estimation device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the OFDM signal parameter estimation method according to any one of claims 1 to 11.

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