Orthogonal frequency division multiplexing sampling frequency offset estimation method based on pilot multi-step difference

Abstract

The application provides a pilot multi-step differential-based orthogonal frequency division multiplexing sampling frequency offset estimation method. The method comprises: selecting two time domain symbols containing equally spaced pilot subcarriers in the allocated resource block, and removing the cyclic prefix of the received signals of the two time domain symbols respectively; based on the known pilot symbols, demodulating the pilot subcarrier sequences on the two time domain symbols to obtain a first pilot sequence and a second pilot sequence; performing multi-step differential correlation on the pilot index dimension of the complex exponential sequence, normalizing the correlation sums under each step length according to the effective item number to obtain a corresponding correlation quantity sequence; performing vector summation on the correlation quantity sequence and performing an angle operation once, and calculating an intermediate quantity based on the maximum differential step length; and determining the sampling frequency offset estimation value of the receiver relative to the transmitter according to the intermediate quantity. The application can reduce the calculation complexity, avoid phase folding processing and facilitate fixed-point implementation.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of communication systems, and in particular to a pilot multi-step differential-based orthogonal frequency division multiplexing sampling frequency offset estimation method. BACKGROUND

[0002] In an orthogonal frequency division multiplexing system, a transmitter and a receiver usually use independent crystal oscillators as clock sources. Due to crystal manufacturing tolerance, aging or temperature drift, the receiver inevitably has sampling frequency offset and carrier frequency offset relative to the transmitter. Taking a typical time-frequency grid of a cellular system as an example, each user is allocated a plurality of resource blocks that are continuous in the frequency domain, and each resource block contains fourteen time domain symbols and twelve subcarriers. The second symbol and the eleventh symbol are arranged with equally spaced pilot subcarriers (two subcarriers between adjacent pilots), which are used for parameter and channel estimation. Sampling frequency offset mainly leads to two types of effects in the frequency domain: inter-subcarrier crosstalk and additional phase rotation varying with the subcarrier index.

[0003] The existing method usually takes the pilot samples at the same frequency domain position of the second symbol and the eleventh symbol, point-by-point calculates the phase difference, considers that the phase difference is approximately linear with respect to the subcarrier index, then uses the least squares method to fit the slope, and converts the sampling frequency offset according to the time interval of the second symbol and the eleventh symbol, the frequency domain interval of adjacent pilot subcarriers and the number of fast Fourier transform points.

[0004] However, the existing method has the following problems: first, the frequent calculation of the argument is complex and not conducive to fixed-point implementation; second, when the offset is large, the phase difference is easy to exceed the main value interval and cause phase folding, which requires additional unwrapping processing and is sensitive to noise; third, the robustness is insufficient when the pilot is sparse or the interference is enhanced, and the estimation stability is limited. SUMMARY

[0005] Therefore, the embodiments of the present application provide a pilot multi-step differential-based orthogonal frequency division multiplexing sampling frequency offset estimation method to solve the problems of frequent calculation of the argument, complex calculation, cumbersome unwrapping processing and sensitivity to noise in the prior art.

[0006] The first aspect of the embodiment of the present application provides a pilot multi-step differential based orthogonal frequency division multiplexing sampling frequency offset estimation method, comprising: selecting two time domain symbols containing equally spaced pilot subcarriers in an allocated resource block, and removing a cyclic prefix from received signals of the two time domain symbols respectively; performing fast Fourier transform on the two time domain data sequences after removing the cyclic prefix to obtain frequency domain received signals, and extracting pilot subcarrier sequences at the same frequency domain position on the two time domain symbols; performing demodulation processing on the pilot subcarrier sequences on the two time domain symbols based on known pilot symbols to obtain a first pilot sequence and a second pilot sequence; performing conjugate complex multiplication on the first pilot sequence and the second pilot sequence at corresponding frequency points to obtain a complex exponential sequence varying with pilot indexes; performing multi-step differential correlation on the pilot index dimension of the complex exponential sequence, normalizing correlation sums at each step length according to effective item numbers to obtain a corresponding correlation quantity sequence; performing vector summation on the correlation quantity sequence and performing an angle operation once, and calculating an intermediate quantity based on a maximum differential step length; and determining a sampling frequency offset estimation value of a receiver relative to a transmitter according to the intermediate quantity.

[0007] The second aspect of the embodiment of the present application provides a pilot multi-step differential based orthogonal frequency division multiplexing sampling frequency offset estimation device, comprising: a selection module, configured to select two time domain symbols containing equally spaced pilot subcarriers in an allocated resource block, and remove a cyclic prefix from received signals of the two time domain symbols respectively; a transformation module, configured to perform fast Fourier transform on the two time domain data sequences after removing the cyclic prefix to obtain frequency domain received signals, and extract pilot subcarrier sequences at the same frequency domain position on the two time domain symbols; a demodulation module, configured to perform demodulation processing on the pilot subcarrier sequences on the two time domain symbols based on known pilot symbols to obtain a first pilot sequence and a second pilot sequence; a conjugate complex multiplication module, configured to perform conjugate complex multiplication on the first pilot sequence and the second pilot sequence at corresponding frequency points to obtain a complex exponential sequence varying with pilot indexes; a normalization module, configured to perform multi-step differential correlation on the pilot index dimension of the complex exponential sequence, normalize correlation sums at each step length according to effective item numbers to obtain a corresponding correlation quantity sequence; an angle operation module, configured to perform vector summation on the correlation quantity sequence and perform an angle operation once, and calculate an intermediate quantity based on a maximum differential step length; and a linear conversion module, configured to determine a sampling frequency offset estimation value of a receiver relative to a transmitter according to the intermediate quantity.

[0008] The third aspect of the embodiment of the present application provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the steps of the above method.

[0009] The above at least one technical scheme adopted by the embodiment of the present application can achieve the following beneficial effects:

[0010] The two time domain symbols containing equally-spaced pilot subcarriers are selected in the allocated resource block, the cyclic prefix is removed from the received signals of the two time domain symbols respectively, the fast Fourier transform is performed on the two time domain data sequences after the cyclic prefix is removed to obtain frequency domain received signals, and the pilot subcarrier sequences at the same frequency domain position are extracted on the two time domain symbols; the pilot subcarrier sequences on the two time domain symbols are demodulated based on the known pilot symbols to obtain a first pilot sequence and a second pilot sequence; the first pilot sequence and the second pilot sequence are conjugate multiplied at the corresponding frequency points to obtain a complex exponential sequence varying with the pilot index; multi-step differential correlation is performed on the pilot index dimension of the complex exponential sequence, the correlation sums at each step length are normalized according to the effective item number to obtain a corresponding correlation quantity sequence; vector summation is performed on the correlation quantity sequence and once angle operation is performed, and an intermediate quantity is calculated based on the maximum differential step length; and the sampling frequency offset estimation value of the receiver relative to the transmitter is determined according to the intermediate quantity. The application can reduce the calculation complexity, avoid phase folding processing and facilitate fixed-point implementation. BRIEF DESCRIPTION OF DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0012] Figure 1 is a typical time-frequency signal structure diagram in the prior art;

[0013] Figure 2 is a time domain symbol structure diagram in an orthogonal frequency division multiplexing system;

[0014] Figure 3 is a straight line diagram in the prior art varying with the subcarrier index ;

[0015] Figure 4 is a phase difference variation curve diagram in the prior art relative to the subcarrier index ;

[0016] Figure 5 is a flowchart of the orthogonal frequency division multiplexing sampling frequency offset estimation method based on pilot multi-step differential provided by the embodiments of the present application;

[0017] Figure 6 is a flowchart of the orthogonal frequency division multiplexing sampling frequency offset estimation method provided by the embodiments of the present application in an actual scene;

[0018] Figure 7 is a flowchart of calculating an intermediate quantity provided by an embodiment of the present application

[0019] Figure 8 is a flowchart of calculating an intermediate quantity provided by an embodiment of the present application is a flowchart of calculating an intermediate quantity provided by an embodiment of the present application is a flowchart of calculating an intermediate quantity provided by an embodiment of the present application

[0020] Figure 9 is a structural diagram of a pilot-based multi-step differential orthogonal frequency division multiplexing sampling frequency offset estimation device provided by an embodiment of the present application

[0021] Figure 10 is a structural diagram of an electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0022] In the following description, for the purpose of explanation and not limitation, specific details are set forth, such as particular system configurations, techniques, etc., in order to provide a thorough understanding of the present embodiments. However, it will be apparent to one skilled in the art that the present embodiments can be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present embodiments.

[0023] Common orthogonal frequency division multiplexing systems all contain pilot subcarriers that are equally spaced in the frequency domain. Taking the 5G NR system as an example, when the subcarrier spacing is equal to 30 kHz, a typical time-frequency signal structure is as shown in Figure 1 Figure 1 is a typical time-frequency signal structure diagram in the prior art): a plurality of resource blocks that are continuous in the frequency domain are allocated to each user. Along the time domain direction, each resource block contains 14 continuous time domain symbols, numbered in turn as 0, 1, …, 13; along the frequency domain direction, each resource block contains 12 continuous subcarriers. Figure 1 A complete resource block is boxed in thick lines in the figure. In each resource block, time domain symbol 2 and time domain symbol 11 contain pilot subcarriers that are equally spaced in the frequency domain (the grid filled with shading in the figure), and the pilot subcarriers adjacent in the frequency domain are spaced 2 subcarriers apart. The pilot subcarriers carry pilot symbols known to the receiver. Figure 1

[0024] Let be the sampling frequency offset of the receiver relative to the transmitter, then, as observed on time domain symbol 2 and time domain symbol 11, the frequency domain received signals on the subcarriers with the same frequency domain position differ by a phase rotation factor:

[0025] ​​​

[0026] in, Indicates the subcarrier index. Indicates carrier frequency deviation. Indicates noise. The time interval corresponding to time domain symbol 2 and time domain symbol 11, Indicates the length of a time-domain symbol. For example... Figure 2 As shown ( Figure 2 (This is a schematic diagram of the time-domain symbol structure in an orthogonal frequency division multiplexing system.) , and These represent the length of the cyclic prefix and the number of points in the Fast Fourier Transform, respectively.

[0027] remember ,but It appears as a subcarrier index Changing straight lines (e.g.) Figure 3 As shown, Figure 3 In existing technology Subcarrier index (A schematic diagram of a changing straight line), the slope of the straight line is equal to... The intercept of the line at zero frequency is equal to .

[0028] Existing sampling frequency deviation estimation methods generally estimate the following steps: :

[0029] Step 1: Extract the phase difference between pilot subcarriers with the same frequency domain position in time domain symbol 2 and time domain symbol 11. ;

[0030] Step 2: Estimate the phase difference using the least squares method. Relative to subcarrier subscript The slope of the curve representing the change in is denoted as . ;

[0031] Step 3, from estimate :

[0032]

[0033] exist The reason for dividing by 2 in the estimation formula is that adjacent pilot subcarriers in the frequency domain are spaced by 2 subcarriers.

[0034] However, the aforementioned prior art has the following drawbacks:

[0035] 1. Frequent calls to the argument function are required. Extracting phase difference The computational complexity is high.

[0036] 2. When the carrier frequency deviation or sampling frequency deviation is large, because of the argument function... It can only indicate radians within the interval, Relative to subcarrier subscript The change curve will appear as follows Figure 4 ( Figure 4 It is the phase difference in existing technology Relative to subcarrier subscript The phase folding problem shown in the schematic diagram of the change curve requires solving before applying the least squares method.

[0037] In view of the problems existing in the prior art, this application provides a sampling frequency deviation estimation method for orthogonal frequency division multiplexing systems. The purpose of this application is to reduce the number of argument calculations and avoid the phase folding problem.

[0038] This application selects two time-domain symbols containing equally spaced pilot subcarriers within the allocated resource block, and sequentially performs cyclic prefix removal, fast Fourier transform, and pilot decimation. Using known pilot symbols, the pilot samples of the two symbols are demodulated to construct two pilot sequences. Conjugate complex multiplication is then performed at corresponding frequency points to form a complex exponential sequence that varies with the pilot index. Multi-step differential correlation is performed along the pilot index dimension, and the correlation sums at each step size are normalized and converged into a vector sum. Only one argument operation is performed, and intermediate quantities are calculated based on the maximum differential step size. Finally, the sampling frequency deviation estimate is obtained through linear conversion. This scheme reduces the number of argument operations, avoids phase folding and unwinding, improves fixed-point implementation friendliness, and maintains good estimation stability and engineering usability under pilot sparsity and noise interference conditions.

[0039] The technical solution of this application will now be described in detail with reference to the accompanying drawings and specific embodiments.

[0040] Figure 5 This is a flowchart illustrating the orthogonal frequency division multiplexing sampling frequency deviation estimation method based on pilot multi-step differential provided in an embodiment of this application. Figure 5 As shown, the orthogonal frequency division multiplexing sampling frequency deviation estimation method based on pilot multi-step differential can specifically include:

[0041] S501, select two time-domain symbols containing equally spaced pilot subcarriers within the allocated resource block, and remove the cyclic prefix from the received signals of the two time-domain symbols respectively;

[0042] S502, perform Fast Fourier Transform on the two time-domain data sequences after removing the cyclic prefix to obtain the frequency-domain received signal, and extract the pilot subcarrier sequence at the same frequency domain position from the two time-domain symbols;

[0043] S503, based on the known pilot symbols, the pilot subcarrier sequences on the two time-domain symbols are demodulated to obtain the first pilot sequence and the second pilot sequence;

[0044] S504, perform conjugate complex multiplication of the first pilot sequence and the second pilot sequence at corresponding frequency points to obtain a complex exponential sequence that varies with the pilot index;

[0045] S505 performs multi-step differential correlation on the pilot index dimension of the complex exponential sequence, normalizes the correlation sum at each step size according to the number of effective terms, and obtains the corresponding correlation quantity sequence.

[0046] S506 performs vector summation on the relevant quantity sequence and performs an argument operation, and calculates the intermediate quantity based on the maximum difference step size;

[0047] S507 determines the estimated sampling frequency deviation of the receiver relative to the transmitter based on the intermediate quantity.

[0048] In some embodiments, two time-domain symbols containing equally spaced pilot subcarriers are selected within the allocated resource block, and the cyclic prefix is ​​removed from the received signals of the two time-domain symbols respectively, including:

[0049] Based on the system's time-frequency grid configuration, a first time-domain symbol and a second time-domain symbol containing equally spaced pilot subcarriers are determined within the allocated resource block. The equal spacing is a preset pilot spacing, and the first time-domain symbol and the second time-domain symbol are separated by a preset symbol spacing.

[0050] Perform timing synchronization on the received time-domain baseband signal to locate the starting positions of the first and second time-domain symbols;

[0051] According to the cyclic prefix length configured by the system, the corresponding cyclic prefix samples are truncated and discarded from the beginning of the first and second time domain symbols, while the symbol body samples are retained, resulting in two time domain data sequences after removing the cyclic prefix.

[0052] Specifically, in one embodiment, the receiver first obtains the pilot pattern within the resource block based on the time-frequency grid configuration sent by the system side, and determines two time-domain symbols containing equally spaced pilot subcarriers in the allocated resource block, designated as the first time-domain symbol and the second time-domain symbol. The spacing between adjacent pilot subcarriers in the frequency domain is given by the system configuration, and the symbol spacing between the first and second time-domain symbols is also given by the system configuration. In a typical configuration of a cellular system, the first time-domain symbol may correspond to symbol two, and the second time-domain symbol may correspond to symbol eleven. The pilot subcarriers within the two symbols are equally spaced in the frequency domain with a fixed subcarrier spacing.

[0053] In this embodiment, the receiver performs timing synchronization on the continuously received time-domain baseband data to locate the starting positions of the first time-domain symbol and the second time-domain symbol.

[0054] After determining the starting positions of the first and second time-domain symbols, the corresponding cyclic prefix samples are truncated and discarded from the beginning of the first and second time-domain symbols according to the cyclic prefix length configured by the system, while the symbol body samples are retained, resulting in two time-domain data sequences after removing the cyclic prefix. For both ordinary cyclic prefix and extended cyclic prefix configurations, the corresponding cyclic prefix length parameters are read and truncated in this embodiment.

[0055] In this embodiment, to improve the reliability of subsequent processing, the receiver performs a consistency check after acquiring the two time-domain data sequences: recording the time-domain coordinates, time interval, pilot index set, and their respective starting sampling indexes of the two time-domain symbols as input parameters for subsequent frequency-domain transformation and pilot decimation. Through the above process, a first time-domain data sequence and a second time-domain data sequence that are consistent with the time-frequency grid, have had their cyclic prefix removed, and are aligned at the boundaries are obtained, providing a clear data foundation for subsequent frequency-domain transformation and equal-interval pilot decimation.

[0056] In some embodiments, performing Fast Fourier Transform on the two time-domain data sequences after removing the cyclic prefix to obtain the frequency-domain received signal, and extracting pilot subcarrier sequences at the same frequency domain position from the two time-domain symbols, includes:

[0057] Based on the system configuration, determine the number of transform points, frequency domain subcarrier mapping relationship, and pilot spacing of the Fast Fourier Transform, and determine the frequency domain index set of equally spaced pilot subcarriers;

[0058] The two time-domain data sequences are subjected to Fast Fourier Transform to obtain the corresponding two frequency-domain received signals.

[0059] According to the frequency domain index set, pilot subcarriers that are located at the same frequency domain position and are equally spaced are extracted from the two frequency domain received signals, and the index order of the pilot subcarriers is kept consistent, so as to obtain two pilot subcarrier sequences for subsequent demodulation processing.

[0060] Specifically, in one embodiment, after acquiring two time-domain data sequences, the receiver first determines the number of Fast Fourier Transform points for frequency-domain processing, the mapping relationship from resource blocks to frequency-domain indices, and the equal spacing parameters of pilot subcarriers based on the system-side bandwidth configuration, subcarrier spacing, and resource mapping rules. To facilitate subsequent unified extraction, the receiver establishes a set of frequency-domain indices for pilot subcarriers within the allocated resource block, using the starting subcarrier position of the allocated resource block as a reference, and sets the spacing between adjacent pilots to a preset pilot spacing. In a typical cellular system configuration, pilot subcarriers are sampled every two subcarriers in the frequency domain until all pilot positions within the allocated resource block are covered.

[0061] First, the receiver performs Fast Fourier Transform on the first time-domain data sequence and the second time-domain data sequence respectively to obtain two corresponding frequency-domain received signals.

[0062] Subsequently, according to the established frequency domain index set, the receiver extracts pilot subcarrier samples that are located at the same frequency domain position and are equally spaced from the two received signals in the frequency domain, while strictly maintaining the consistent index order of the pilot subcarriers, forming two pilot subcarrier sequences for subsequent demodulation processing. For scenarios crossing resource block boundaries, this embodiment uses the relative starting point within the resource block as a unified reference to avoid the impact of changes in the full bandwidth coordinate system on extraction consistency.

[0063] In some examples, the subcarrier spacing is 30 kHz, and the user allocates only one resource block containing 12 consecutive subcarriers. The first time-domain symbol is symbol 2, and the second time-domain symbol is symbol 11, respectively. The receiver uses the starting frequency of this resource block as a reference and selects a pilot signal every two subcarriers, sequentially extracting samples from the received signals in both frequency domains at the pilot positions. This forms two pilot subcarrier sequences of equal length and with the same index order. Each element of the sequence corresponds to the same frequency domain position within the resource block, and there is no repetition, omission, or position mismatch between the two sequences.

[0064] Through the above implementation method, the receiver obtains two pilot subcarrier sequences within the allocated resource block range that are consistent with the system configuration, have a determined number of Fast Fourier Transform points and mapping relationship, and have aligned frequency domain positions and consistent index order of the pilots. This provides a unified and unambiguous input basis for subsequent known pilot demodulation, corresponding frequency point conjugate complex multiplication, and multi-step differential correlation in the pilot index dimension, reducing the accumulation of errors caused by invalid frequency interference and index mismatch.

[0065] In some embodiments, the pilot subcarrier sequences in two time-domain symbols are demodulated based on known pilot symbols to obtain a first pilot sequence and a second pilot sequence, including:

[0066] Generate or read a known pilot symbol sequence that corresponds to two time-domain symbols and is one-to-one with the frequency domain position of the pilot subcarrier based on the system configuration;

[0067] The pilot subcarrier sequences on the two time-domain symbols are conjugately multiplied with the pilot symbol sequences of the corresponding known pilot symbols to obtain the demodulated pilot samples;

[0068] Arrange the demodulated pilot samples according to the pilot index order to obtain the first pilot sequence corresponding to the first time domain symbol and the second pilot sequence corresponding to the second time domain symbol.

[0069] Specifically, in one embodiment, after determining the frequency domain index set of the pilot subcarriers, the receiver first generates or reads the known pilot symbol sequence corresponding to the two time-domain symbols according to the system-side configuration. The generation or reading process takes the resource block index set, time-domain symbol subscripts, pilot patterns, and cell-related parameters as input to obtain a complex symbol sequence with a one-to-one correspondence between the frequency domain positions of the pilot subcarriers and an amplitude of unit modulus. When the system-side buffer is enabled, the known pilot symbol sequence of the corresponding symbol can be directly read from the local buffer and a consistency check can be performed. The check includes the matching of the sequence length with the pilot index set, and the consistency of the sequence's unit modulus constraint and mapping order.

[0070] In this embodiment, to ensure a one-to-one correspondence, the receiver uses the pilot index set as a reference to align the known pilot symbol sequences of the two time-domain symbols, so that the symbols in the sequences strictly correspond to the frequency domain positions of the pilot subcarriers.

[0071] Subsequently, the receiver performs demodulation processing on the pilot subcarrier sequences of the two time-domain symbols respectively. Specifically, at the frequency domain position of each pilot subcarrier, the pilot subcarrier sequence is multiplied by the conjugate of the pilot symbol sequence of the corresponding known pilot symbol to obtain the demodulated pilot sample. After performing the above operations on the two time-domain symbols respectively, the receiver arranges the demodulated pilot samples in sequence according to the pilot index order to form the first pilot sequence corresponding to the first time-domain symbol and the second pilot sequence corresponding to the second time-domain symbol.

[0072] In one example, the subcarrier spacing is 30kHz, and the user is allocated only one resource block containing 12 consecutive subcarriers with a pilot spacing of 2. The first and second time-domain symbols are symbol 2 and symbol 11, respectively. The receiver obtains a set of indices for the six pilot frequency domain positions based on the pilot pattern within the resource block, and generates a sequence of known pilot symbols corresponding one-to-one with this set. For the pilot subcarrier sequences on the two time-domain symbols, each of the six pilot positions is multiplied by the conjugate of the corresponding known pilot symbol sequence to obtain six demodulated pilot samples. These samples are then arranged sequentially according to their pilot indices to form the first and second pilot sequences, each of length 6.

[0073] Through the above implementation method, the receiver completes the demodulation of the known pilot symbols in the frequency domain, so that the first pilot sequence and the second pilot sequence retain only the channel amplitude change and the additional phase terms introduced by the sampling frequency deviation and carrier frequency deviation between the two time domain symbols; at the same time, it ensures strict alignment of the two sequences in length and index, providing a consistent and unambiguous input basis for the subsequent conjugate complex multiplication of corresponding frequency points and the multi-step differential correlation in the pilot index dimension.

[0074] In some embodiments, the first pilot sequence and the second pilot sequence are multiplied by their conjugate at corresponding frequency points to obtain a complex exponential sequence that varies with the pilot index, including:

[0075] The first pilot sequence and the second pilot sequence are paired one by one according to the pilot index to ensure that each pair of samples corresponds to the same frequency domain position.

[0076] The complex multiplication result is obtained by conjugate complex multiplication of each sample in the second pilot sequence with the corresponding sample in the first pilot sequence;

[0077] The complex multiplication results are arranged sequentially according to the pilot index to form a complex exponential sequence that varies with the pilot index. This complex exponential sequence is used for subsequent multi-step difference correlation processing along the pilot index dimension.

[0078] Specifically, in one embodiment, after obtaining the first pilot sequence and the second pilot sequence, the receiver first establishes a one-to-one pairing relationship based on the pilot index set. The pairing process uses the relative frequency domain coordinates within the allocated resource block as a unified reference, and matches samples in the two sequences at the same frequency domain position one by one in ascending order of pilot index, resulting in a length of... M The pairing list.

[0079] In this embodiment, a conjugate complex multiplication operation is performed on each pair of samples. Specifically, the samples in the second pilot sequence are conjugate complex multiplied with the corresponding samples in the first pilot sequence to obtain the complex multiplication result.

[0080] Subsequently, the receiver arranges the complex multiplication results of each frequency point sequentially according to the pilot index, forming a complex exponential sequence that varies with the pilot index. To ensure the alignment of the sequence with subsequent differential correlations, this embodiment also records the starting pilot index and length of the sequence. M The relative frequency domain coordinate range within the allocated resource block is used as the parameter input for subsequent multi-step differential correlation.

[0081] In one example, the subcarrier spacing is 30kHz, and the user allocates only one resource block containing 12 consecutive subcarriers with a pilot spacing of 2. The first and second time-domain symbols correspond to symbol 2 and symbol 11, respectively. The pilot index set contains 6 frequency domain positions. The receiver pairs the two sequences one by one at these 6 positions, performs the operation of "second sample × complex conjugate of first sample" at each position, and obtains 6 complex multiplication results; then arranges them in ascending index order to form a complex exponential sequence of length 6.

[0082] Through the above implementation method, the receiver aggregates the pilot samples aligned on two time-domain symbols into a single sequence representation point by point in the frequency domain. This sequence eliminates the pilot modulation and intra-symbol common phase terms in phase, retaining only the linear phase increment related to the pilot index. At the same time, it retains the squared channel amplitude term in amplitude, which facilitates subsequent multi-step differential correlation and one argument operation in the pilot index dimension to achieve stable extraction of the phase slope.

[0083] In some embodiments, multi-step differential correlation is performed on the pilot index dimension of the complex exponential sequence, and the correlation sum at each step size is normalized according to the number of effective terms to obtain the corresponding correlation quantity sequence, including:

[0084] Determine the preset maximum differential step size and the index offset mapping relationship between the pilot interval and the differential step size;

[0085] For each difference step size, a sample pair with a pilot index difference of a preset index offset is selected in the complex exponential sequence. The preset index offset is determined by the mapping relationship between the difference step size and the pilot interval. The conjugate complex multiplication of the subsequent sample and the previous sample is calculated to form the difference correlation term.

[0086] The differential correlation terms are summed within the pilot index range that meets the pairing conditions to obtain the correlation sum corresponding to the differential step size. The correlation sum is then normalized according to the effective pairing number of the differential step size to obtain the correlation quantity corresponding to the differential step size.

[0087] Arrange the relevant quantities corresponding to each difference step size in order of difference step size to form a sequence of relevant quantities for subsequent vector summation and argument calculation.

[0088] Specifically, the input in this embodiment is a complex exponential sequence arranged in pilot index order, and the sequence length is denoted as . M This corresponds to the result of demodulating and multiplying the two time-domain symbols at the same frequency position within the allocated resource block by their conjugate. The receiver determines the preset maximum differential step size based on the system configuration and establishes an index offset mapping relationship between the pilot spacing and the differential step size to guide the selection of sample pairs and boundary clipping.

[0089] Subsequently, for each difference step, sample pairs satisfying the index offset relationship are extracted on the pilot index dimension of the complex exponential sequence. The conjugate complex multiplication of the next sample and the previous sample is calculated to form a difference correlation term. The difference correlation term is summed within the effective pairing range to obtain the correlation sum, and normalized according to the effective pairing number corresponding to the difference step to obtain the correlation quantity corresponding to the difference step. The correlation quantities of each difference step are arranged in order of difference step to form a correlation quantity sequence, and output together with the effective pairing number, start and end pilot index and other parameters of each difference step for subsequent vector summation and argument calculation.

[0090] Furthermore, multi-step differential correlation refers to constructing sample pairs in parallel with multiple differential step sizes along the pilot index dimension and aggregating the correlation quantity, thereby suppressing slowly varying amplitude terms and some frequency domain interference while maintaining phase increment information. A preset index offset is used to establish a one-to-one mapping relationship between the differential step size and the pilot spacing, ensuring that the index spacing of the sample pairs is strictly consistent with the system pilot grid, avoiding phase distortion introduced by index mismatch.

[0091] For example, in some examples, the subcarrier spacing is 30kHz, the user allocates only one resource block containing 12 consecutive subcarriers, with two time-domain symbols, symbol 2 and symbol 11, and pilots are evenly spaced in the frequency domain, with a pilot position count of 6. After preprocessing, the length is... M = 6 and the index is a complex exponential sequence with monotonically increasing. The maximum difference step size is preset to 3, and the mapping relationship between the pilot interval and the difference step size is established. Under the pilot index expression in this example, the preset index offset corresponds one-to-one with the difference step size. For difference step size 1, sample pairs with an index difference of 1 are selected in the sequence to form 5 effective pairs; the conjugate complex multiplication of the next sample with the previous sample is calculated for each pair and summed, and the number of effective pairs is recorded as 5. The normalization is completed by multiplying by the reciprocal to obtain the correlation quantity of difference step size 1. For difference step size 2, 4 pairs are formed and the correlation quantity of this step size is obtained in the same way; for difference step size 3, 3 pairs are formed and normalization is completed to obtain the corresponding correlation quantity. Finally, three complex correlation quantities are output in the order of difference step size 1, 2, and 3 to form a correlation quantity sequence, and the effective pair size and start and end index of each difference step size are output for subsequent vector summation and argument calculation.

[0092] Through the above implementation method, multi-step differential correlation and unified normalization are completed in the pilot index dimension. The output correlation sequence is not sensitive to the slowly varying amplitude term, which facilitates subsequent one-time aggregation and argument calculation. This provides a structured input for the stable extraction of phase increment information with the pilot index and subsequent sampling frequency deviation estimation.

[0093] In some embodiments, vector summation is performed on the relevant quantity sequences, followed by an argument operation, and intermediate quantities are calculated based on the maximum difference step size, including:

[0094] The vector sum is obtained by vector summing of the complex correlation quantities in the correlation quantity sequence in order of difference step size.

[0095] Perform an argument operation on the vector sum to obtain the angle.

[0096] The normalization coefficient is determined based on the maximum difference step size, and the angle quantity is normalized according to the normalization coefficient to obtain the intermediate quantity.

[0097] Specifically, the input in this embodiment is a sequence of correlation quantities arranged in differential step size order. Each correlation quantity is a complex quantity formed in the pilot index dimension with a corresponding differential step size and normalized by the effective pairing number. The receiver first performs vector summation on the correlation quantity sequence, that is, performs complex addition on each complex correlation quantity in differential step size order to obtain a vector sum; then performs an argument operation on the vector sum to obtain an angle quantity; finally, determines the normalization coefficient according to the maximum differential step size, and uses the coefficient to normalize the angle quantity to obtain an intermediate quantity. In the implementation, the normalization process replaces division by pre-stored reciprocals of the normalization coefficients and performing multiplication.

[0098] Vector summation refers to adding the correlation quantities under different difference step sizes in the complex plane as a vector, so that the dominant phase increment related to the pilot index dominates in coherent superposition, while weakening the random deflection caused by noise and slowly varying amplitude.

[0099] A single argument operation refers to calculating the argument only for the vector sum, mapping the composite orientation of all related quantities to a single angular quantity, thus avoiding the phase folding and unfolding problems caused by taking the argument point by point at each frequency or each differential step.

[0100] The normalization coefficient is used to convert angular quantities to a scale consistent with system parameters. The normalization coefficient is related to the maximum difference step size. In engineering implementation, this coefficient is treated as a constant and can be pre-calculated and stored with system configuration.

[0101] In some examples, the subcarrier spacing is 30kHz, and the user allocates only one resource block containing 12 consecutive subcarriers with a pilot spacing of 2. The two time-domain symbols are symbol 2 and symbol 11. After preprocessing, a set of correlation quantities with three differential step sizes is obtained, which are denoted as three complex correlation quantities in the order of differential step sizes 1, 2, and 3.

[0102] The receiver performs a complex addition of the three values ​​to obtain a vector sum, and then performs an argument operation on this vector sum to obtain the angle. Subsequently, it determines a normalization coefficient based on the maximum difference step size, and normalizes the angle value according to this normalization coefficient to obtain an intermediate value.

[0103] In implementation, the normalization step replaces division by multiplying by a pre-stored reciprocal. The intermediate value obtained in this way serves as the input for subsequent sampling frequency deviation estimation. The intermediate value has completed the one-time aggregation of relevant information from multiple steps, avoiding the complexity and implementation difficulties caused by point-by-point argument taking and multiple divisions.

[0104] In some embodiments, determining an estimated sampling frequency offset of the receiver relative to the transmitter based on an intermediate quantity includes:

[0105] The sampling frequency deviation conversion factor is determined based on the preset pilot interval, the time interval between two time domain symbols, and the number of points in the fast Fourier transform.

[0106] The reciprocal of the sampling frequency deviation conversion coefficient is pre-stored in the form of a lookup table, and the corresponding reciprocal is read during calculation;

[0107] The intermediate value is multiplied by the reciprocal to complete the linear conversion, and the estimated value of the sampling frequency deviation is obtained.

[0108] Among them, the estimated value of sampling frequency deviation is linearly proportional to the intermediate value, and the proportional relationship is determined by the sampling frequency deviation conversion coefficient.

[0109] Specifically, in this embodiment, the intermediate quantities output from the preceding steps are used as inputs, and the system parameters are the pilot interval, the symbol interval between two time-domain symbols, the number of Fast Fourier Transform points, and the cyclic prefix length. The receiver determines the sampling frequency deviation conversion factor based on the above parameters. The conversion factor is proportional to the pilot interval, proportional to the symbol interval, and related to the ratio of the cyclic prefix length to the number of Fast Fourier Transform points.

[0110] In the specific implementation, the receiver pre-stores the reciprocal of the conversion coefficient in the form of a lookup table, and uses the pilot spacing, symbol spacing, number of Fast Fourier Transform points, and cyclic prefix length as search keys for indexing. During real-time calculation, the receiver reads the corresponding reciprocal, performs a multiplication operation between the intermediate quantity and the reciprocal to complete the linear conversion, and obtains the estimated value of the sampling frequency deviation.

[0111] Furthermore, the sampling frequency deviation conversion factor is used to map the intermediate quantity obtained from one argument calculation to the actual sampling frequency deviation. Its composition is determined by the system pilot grid and symbol span, and is affected by the configuration of the number of fast Fourier transform points and the cyclic prefix length.

[0112] The lookup table reciprocal is an engineering technique introduced to avoid division. It pre-calculates and stores the reciprocals of the conversion coefficients corresponding to all possible system configurations offline. At runtime, linear conversion can be completed by only looking up the table and multiplying, thus meeting the constraints of low power consumption.

[0113] The linear conversion relationship indicates that the estimated sampling frequency deviation is proportional to the intermediate value, and the proportionality constant is the reciprocal of the conversion factor. When system parameters change, only the lookup table index needs to be switched; the main process structure remains unchanged.

[0114] In one example, the subcarrier spacing is 30kHz, and the user allocates only one resource block containing 12 consecutive subcarriers, with a pilot spacing of 2 and a symbol spacing of 9 between two time-domain symbols. The system side provides the Fast Fourier Transform (FFT) points and cyclic prefix length for the current bandwidth. The receiver calculates the sampling frequency deviation conversion factor based on these four parameters and calculates its reciprocal offline during device initialization. A multi-key index entry is created based on <pilot spacing, symbol spacing, FFT points, and cyclic prefix length>, and stored in non-volatile memory and a high-speed buffer. To adapt to different bandwidths or cyclic prefix modes, the lookup table contains several version identifiers, which are used to select the correct entry during configuration switching.

[0115] In another example, the intermediate value obtained from the preceding steps is already limited to the main value range. The receiver reads the reciprocal of the conversion factor that matches the current configuration, and multiplies the intermediate value by this reciprocal to obtain the estimated sampling frequency deviation. If a momentary configuration switch is detected that causes a change in the lookup table index, the entry is updated at the frame boundary and a configuration timestamp is added to the current estimate to avoid inconsistencies caused by the overlap between the old and new configurations.

[0116] Through the above implementation method, the process of this embodiment replaces the division operation with a single multiplication and table lookup, which completes the linear conversion from intermediate quantity to the estimated value of sampling frequency deviation while ensuring the adaptiveness of system parameters.

[0117] Based on the technical solutions of the preceding embodiments of this application, the following describes the specific implementation process of the sampling frequency deviation estimation method for orthogonal frequency division multiplexing systems in a specific scenario.

[0118] Because of the aforementioned phase rotation factor The phase difference can be considered as a complex exponential signal superimposed with noise. In an orthogonal frequency division multiplexing system containing pilot subcarriers with equal frequency spacing, the problem of estimating the sampling frequency deviation is highly similar to the problem of estimating the carrier frequency deviation. This invention uses the L&R algorithm in carrier frequency deviation estimation methods to estimate the phase difference. Relative to subcarrier subscript The slope of the curve representing the change in frequency is used to estimate the sampling frequency deviation, but in this process, it is not necessary to explicitly extract the phase difference. The overall estimation process is as follows: Figure 6 As shown, Figure 6 This is a schematic diagram of the sampling frequency deviation estimation algorithm in an orthogonal frequency division multiplexing system provided in a real-world scenario according to an embodiment of this application, specifically including the following steps:

[0119] Step 1: Remove the cyclic prefix from the time-domain received signals on time-domain symbols 2 and 11 respectively;

[0120] Step 2: Transform the time-domain received signal (with the cyclic prefix removed) to the frequency domain using a Fast Fourier Transform.

[0121] Step 3: Extract pilot subcarriers that are evenly distributed in the frequency domain;

[0122] Step 4: Remove the known pilot symbols. This is done by multiplying the frequency-domain received signal on the pilot subcarrier by the conjugate of the known pilot symbols. The frequency-domain received signals with the known pilot symbols removed on time-domain symbols 2 and 11 are denoted as follows: and ;

[0123] Step 5, Calculation and Conjugate complex multiplication: ;

[0124] Step 6, as follows Figure 8 As shown ( Figure 8 The calculation provided in the embodiments of this application In the frequency domain (Flowchart of the normalized difference correlation function) Calculation In the frequency domain Step-normalized difference correlation function:

[0125]

[0126] This represents the maximum difference step size, which is generally taken as 1. .if If it is an odd number, then .

[0127] Step 7, as follows Figure 7 As shown ( Figure 7 This is the intermediate computational quantity provided in the embodiments of this application. (Flowchart of the process) Estimating intermediate quantities :

[0128]

[0129] Step 8: Estimate the sampling frequency deviation :

[0130]

[0131] On the surface, calculation and estimates In practice, division is always performed by various constants. However, in implementation, division can be replaced by equivalent multiplication. The method is to pre-calculate the reciprocals of these constants and store them in a lookup table. When division by a constant is required, the product of the reciprocal of the constant and the reciprocal is calculated instead.

[0132] It should be noted that, although the embodiments of this application use the L&R algorithm to estimate the phase difference Relative to subcarrier subscript The slope of the change curve is used, but in practical applications, other carrier frequency deviation estimation algorithms can also be used to estimate the slope of this change curve. This embodiment does not constitute a limitation on the technical solution of this application.

[0133] The following are embodiments of the apparatus described in this application, which can be used to execute the embodiments of the method described in this application. For details not disclosed in the apparatus embodiments of this application, please refer to the embodiments of the method described in this application.

[0134] Figure 9 This is a schematic diagram of the orthogonal frequency division multiplexing sampling frequency deviation estimation device based on pilot multi-step differential provided in an embodiment of this application. Figure 9 As shown, the orthogonal frequency division multiplexing sampling frequency deviation estimation device based on pilot multi-step differential includes:

[0135] The selection module 901 is used to select two time-domain symbols containing equally spaced pilot subcarriers within the allocated resource block, and to remove the cyclic prefix from the received signals of the two time-domain symbols respectively.

[0136] The transformation module 902 is used to perform fast Fourier transform on the two time-domain data sequences after removing the cyclic prefix to obtain the frequency-domain received signal, and extract the pilot subcarrier sequence at the same frequency domain position from the two time-domain symbols.

[0137] Demodulation module 903 is used to perform demodulation processing on pilot subcarrier sequences in two time domain symbols based on known pilot symbols to obtain a first pilot sequence and a second pilot sequence;

[0138] The conjugate complex multiplication module 904 is used to perform conjugate complex multiplication of the first pilot sequence and the second pilot sequence at corresponding frequency points to obtain a complex exponential sequence that varies with the pilot index.

[0139] The normalization module 905 is used to perform multi-step differential correlation on the pilot index dimension of the complex exponential sequence, normalize the correlation sum at each step size according to the number of effective terms, and obtain the corresponding correlation quantity sequence.

[0140] Argument calculation module 906 is used to perform vector summation on the relevant quantity sequence and perform an argument calculation, and calculate intermediate quantities based on the maximum difference step size;

[0141] The linear conversion module 907 is used to determine the estimated sampling frequency deviation of the receiver relative to the transmitter based on the intermediate quantity.

[0142] In some embodiments, Figure 9 The selection module 901 determines, based on the system's time-frequency grid configuration, a first time-domain symbol and a second time-domain symbol containing equally spaced pilot subcarriers within the allocated resource block. The equal spacing is a preset pilot interval, and the first time-domain symbol and the second time-domain symbol are separated by a preset symbol interval. The module performs timing synchronization on the received time-domain baseband signal to locate the starting positions of the first time-domain symbol and the second time-domain symbol. According to the cyclic prefix length configured by the system, the module trims and discards the corresponding cyclic prefix samples from the beginning of the first time-domain symbol and the second time-domain symbol, while retaining the symbol body samples, to obtain two time-domain data sequences after removing the cyclic prefix.

[0143] In some embodiments, Figure 9 The transformation module 902 determines the number of transformation points, frequency domain subcarrier mapping relationship, and pilot spacing of the Fast Fourier Transform according to the system configuration, and determines the frequency domain index set of equally spaced pilot subcarriers; it performs Fast Fourier Transform on the two time domain data sequences respectively to obtain the corresponding two frequency domain received signals; according to the frequency domain index set, it extracts pilot subcarriers that are in the same frequency domain position and equally spaced from the two frequency domain received signals, and keeps the index order of the pilot subcarriers consistent, to obtain two pilot subcarrier sequences for subsequent demodulation processing.

[0144] In some embodiments, Figure 9 The demodulation module 903 generates or reads known pilot symbol sequences that correspond to the two time-domain symbols and are one-to-one with the frequency domain positions of the pilot subcarriers, based on the system configuration; it multiplies the pilot subcarrier sequences on the two time-domain symbols by the pilot symbol sequences of the corresponding known pilot symbols, respectively, to obtain demodulated pilot samples; it arranges the demodulated pilot samples according to the pilot index order to obtain the first pilot sequence corresponding to the first time-domain symbol and the second pilot sequence corresponding to the second time-domain symbol.

[0145] In some embodiments, Figure 9 The conjugate complex multiplication module 904 pairs the first pilot sequence and the second pilot sequence one by one according to the pilot index to ensure that each pair of samples corresponds to the same frequency domain position; it performs conjugate complex multiplication on each sample in the second pilot sequence and the corresponding sample in the first pilot sequence to obtain the complex multiplication result; it arranges the complex multiplication results in sequence according to the pilot index order to form a complex exponential sequence that varies with the pilot index. The complex exponential sequence is used for subsequent multi-step differential correlation processing in the pilot index dimension.

[0146] In some embodiments, Figure 9The normalization module 905 determines the preset maximum differential step size and the index offset mapping relationship between the pilot interval and the differential step size. For each differential step size, a sample pair with a preset index offset difference between the pilot indices is selected from the complex exponential sequence. The preset index offset is determined by the mapping relationship between the differential step size and the pilot interval. The conjugate complex multiplication of the subsequent sample and the previous sample is calculated to form a differential correlation term. The differential correlation term is summed within the pilot index range that satisfies the pairing condition to obtain the correlation sum corresponding to the differential step size. The correlation sum is normalized according to the effective pairing number of the differential step size to obtain the correlation quantity corresponding to the differential step size. The correlation quantities corresponding to each differential step size are arranged in the order of the differential step size to form a correlation quantity sequence for subsequent vector summation and first argument operation.

[0147] In some embodiments, Figure 9 The argument calculation module 906 performs vector summation on each complex correlation quantity in the correlation quantity sequence according to the difference step size to obtain a vector sum; performs an argument calculation on the vector sum to obtain an angle quantity; determines the normalization coefficient according to the maximum difference step size, and normalizes the angle quantity according to the normalization coefficient to obtain an intermediate quantity.

[0148] In some embodiments, Figure 9 The linear conversion module 907 determines the sampling frequency deviation conversion coefficient based on the preset pilot interval, the time interval between two time domain symbols, and the number of points of the fast Fourier transform; it pre-stores the reciprocal of the sampling frequency deviation conversion coefficient in the form of a lookup table and reads the corresponding reciprocal during calculation; it performs a linear conversion by multiplying the intermediate quantity with the reciprocal to obtain the estimated value of the sampling frequency deviation; wherein, the estimated value of the sampling frequency deviation is linearly proportional to the intermediate quantity, and the proportional relationship is determined by the sampling frequency deviation conversion coefficient.

[0149] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0150] Figure 10 This is a schematic diagram of the structure of the electronic device 10 provided in an embodiment of this application. Figure 10 As shown, the electronic device 10 of this embodiment includes: a processor 1001, a memory 1002, and a computer program 1003 stored in the memory 1002 and executable on the processor 1001. When the processor 1001 executes the computer program 1003, it implements the steps in the various method embodiments described above. Alternatively, when the processor 1001 executes the computer program 1003, it implements the functions of each module / unit in the various device embodiments described above.

[0151] For example, computer program 1003 may be divided into one or more modules / units, which are stored in memory 1002 and executed by processor 1001 to complete this application. The one or more modules / units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of computer program 1003 in electronic device 10.

[0152] Electronic device 10 may be a desktop computer, laptop, handheld computer, cloud server, or other electronic device. Electronic device 10 may include, but is not limited to, a processor 1001 and a memory 1002. Those skilled in the art will understand that... Figure 10 This is merely an example of electronic device 10 and does not constitute a limitation on electronic device 10. It may include more or fewer components than shown, or combine certain components, or different components. For example, electronic device may also include input / output devices, network access devices, buses, etc.

[0153] The processor 1001 can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0154] The memory 1002 can be an internal storage unit of the electronic device 10, such as a hard disk or RAM of the electronic device 10. The memory 1002 can also be an external storage device of the electronic device 10, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, FlashCard, etc., equipped on the electronic device 10. Furthermore, the memory 1002 can include both internal and external storage units of the electronic device 10. The memory 1002 is used to store computer programs and other programs and data required by the electronic device. The memory 1002 can also be used to temporarily store data that has been output or will be output.

[0155] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0156] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0157] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0158] In the embodiments provided in this application, it should be understood that the disclosed apparatus / computer devices and methods can be implemented in other ways. For example, the apparatus / computer device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. Multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0159] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0160] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0161] If an integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program may include computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. A computer-readable medium may include: any entity or device capable of carrying computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0162] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for estimating sampling frequency deviation in orthogonal frequency division multiplexing based on pilot multi-step differential, characterized in that, include: Within the allocated resource block, select two time-domain symbols containing equally spaced pilot subcarriers, and remove the cyclic prefix from the received signals of the two time-domain symbols respectively; The frequency domain received signal is obtained by performing Fast Fourier Transform on the two time domain data sequences after removing the cyclic prefix, and the pilot subcarrier sequences at the same frequency domain position are extracted from the two time domain symbols. Based on the known pilot symbols, the pilot subcarrier sequences on the two time-domain symbols are demodulated to obtain the first pilot sequence and the second pilot sequence. Perform conjugate complex multiplication of the first pilot sequence and the second pilot sequence at corresponding frequency points to obtain a complex exponential sequence that varies with the pilot index; Perform multi-step differential correlation on the pilot index dimension of the complex exponential sequence, and normalize the correlation sum at each step size according to the number of effective terms to obtain the corresponding correlation quantity sequence; The relevant quantity sequence is vector summed and an argument operation is performed. The intermediate quantity is calculated based on the maximum difference step size. The estimated sampling frequency deviation of the receiver relative to the transmitter is determined based on the intermediate value.

2. The method according to claim 1, characterized in that, The step of selecting two time-domain symbols containing equally spaced pilot subcarriers within the allocated resource block, and removing the cyclic prefix from the received signals of the two time-domain symbols respectively, includes: Based on the system's time-frequency grid configuration, a first time-domain symbol and a second time-domain symbol containing equally spaced pilot subcarriers are determined within the allocated resource block. The equal spacing is a preset pilot spacing, and the first time-domain symbol and the second time-domain symbol are separated by a preset symbol spacing. Perform timing synchronization on the received time-domain baseband signal to locate the starting positions of the first time-domain symbol and the second time-domain symbol; According to the cyclic prefix length configured by the system, the corresponding cyclic prefix samples are truncated and discarded from the beginning of the first time domain symbol and the second time domain symbol, while the symbol body samples are retained, resulting in two time domain data sequences after removing the cyclic prefix.

3. The method according to claim 1, characterized in that, The step of performing Fast Fourier Transform on the two time-domain data sequences after removing the cyclic prefix to obtain the frequency-domain received signal, and extracting pilot subcarrier sequences at the same frequency position from the two time-domain symbols, includes: Based on the system configuration, determine the number of transform points, frequency domain subcarrier mapping relationship, and pilot spacing of the Fast Fourier Transform, and determine the frequency domain index set of equally spaced pilot subcarriers; The two time-domain data sequences are subjected to Fast Fourier Transform to obtain the corresponding two frequency-domain received signals. According to the frequency domain index set, pilot subcarriers that are located at the same frequency domain position and are equally spaced are extracted from the two frequency domain received signals, and the index order of the pilot subcarriers is kept consistent to obtain two pilot subcarrier sequences for subsequent demodulation processing.

4. The method according to claim 1, characterized in that, The process of demodulating the pilot subcarrier sequences on the two time-domain symbols based on known pilot symbols to obtain a first pilot sequence and a second pilot sequence includes: Generate or read a known pilot symbol sequence that corresponds to two time-domain symbols and is one-to-one with the frequency domain position of the pilot subcarrier based on the system configuration; The pilot subcarrier sequences on the two time-domain symbols are conjugately multiplied with the pilot symbol sequences of the corresponding known pilot symbols to obtain the demodulated pilot samples; Arrange the demodulated pilot samples according to the pilot index order to obtain the first pilot sequence corresponding to the first time domain symbol and the second pilot sequence corresponding to the second time domain symbol.

5. The method according to claim 4, characterized in that, The step of performing a conjugate complex multiplication of the first pilot sequence and the second pilot sequence at corresponding frequency points to obtain a complex exponential sequence that varies with the pilot index includes: The first pilot sequence and the second pilot sequence are paired one by one according to the pilot index to ensure that each pair of samples corresponds to the same frequency domain position. The sample in the second pilot sequence is multiplied by the corresponding sample in the first pilot sequence by conjugate complex multiplication to obtain the complex multiplication result; The complex multiplication results are arranged sequentially according to the pilot index order to form a complex exponential sequence that varies with the pilot index. This complex exponential sequence is used for subsequent multi-step difference correlation processing along the pilot index dimension.

6. The method according to claim 1, characterized in that, The process involves performing multi-step differential correlation along the pilot index dimension of the complex exponential sequence, normalizing the correlation sum at each step size according to the number of effective terms, and obtaining the corresponding correlation quantity sequence, including: Determine the preset maximum differential step size and the index offset mapping relationship between the pilot interval and the differential step size; For each differential step size, a sample pair in the complex exponential sequence is selected whose pilot index differs by a preset index offset. The preset index offset is determined by the mapping relationship between the differential step size and the pilot interval. The conjugate complex multiplication of the subsequent sample and the previous sample is calculated to form a differential correlation term. The differential correlation terms are summed within the pilot index range that meets the pairing conditions to obtain the correlation sum corresponding to the differential step size. The correlation sum is then normalized according to the effective pairing number of the differential step size to obtain the correlation quantity corresponding to the differential step size. The relevant quantities corresponding to each difference step size are arranged in order of difference step size to form a sequence of relevant quantities for subsequent vector summation and argument calculation.

7. The method according to claim 1, characterized in that, The step of performing vector summation and argument operation on the relevant quantity sequence, and calculating intermediate quantities based on the maximum difference step size, includes: The vector sum is obtained by vector summing of each complex correlation quantity in the correlation quantity sequence in order of difference step size. Perform an argument operation on the vector to obtain the angle. The normalization coefficient is determined based on the maximum difference step size, and the angle quantity is normalized according to the normalization coefficient to obtain the intermediate quantity.

8. The method according to claim 1, characterized in that, Determining the estimated sampling frequency deviation of the receiver relative to the transmitter based on the intermediate quantity includes: The sampling frequency deviation conversion factor is determined based on the preset pilot interval, the time interval between two time domain symbols, and the number of points in the fast Fourier transform. The reciprocal of the sampling frequency deviation conversion coefficient is pre-stored in the form of a lookup table, and the corresponding reciprocal is read during calculation; The intermediate value is multiplied by the reciprocal to complete the linear conversion, and the estimated value of the sampling frequency deviation is obtained. The estimated value of the sampling frequency deviation is linearly proportional to the intermediate quantity, and the proportional relationship is determined by the sampling frequency deviation conversion coefficient.

9. A sampling frequency deviation estimation device based on pilot multi-step differential, characterized in that, include: The selection module is used to select two time-domain symbols containing equally spaced pilot subcarriers within the allocated resource block, and to remove the cyclic prefix from the received signals of the two time-domain symbols respectively; The transformation module is used to perform fast Fourier transform on the two time-domain data sequences after removing the cyclic prefix to obtain the frequency-domain received signal, and extract the pilot subcarrier sequence at the same frequency position on the two time-domain symbols. The demodulation module is used to perform demodulation processing on the pilot subcarrier sequences on the two time-domain symbols based on the known pilot symbols, to obtain the first pilot sequence and the second pilot sequence; The conjugate complex multiplication module is used to perform conjugate complex multiplication of the first pilot sequence and the second pilot sequence at corresponding frequency points to obtain a complex exponential sequence that varies with the pilot index; The normalization module is used to perform multi-step differential correlation on the pilot index dimension of the complex exponential sequence, normalize the correlation sum at each step size according to the number of effective terms, and obtain the corresponding correlation quantity sequence. The argument calculation module is used to perform vector summation on the relevant quantity sequence and perform an argument calculation, and calculate intermediate quantities based on the maximum difference step size; A linear conversion module is used to determine the estimated value of the sampling frequency deviation of the receiver relative to the transmitter based on the intermediate quantity.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 8.

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