Phase tracking enhancement method, storage medium and product

Abstract

The invention provides a phase tracking enhancement method, a storage medium and a product. The method comprises the following steps: processing a received signal by a receiver to obtain a channel estimation value on each subcarrier; acquiring a first pilot signal inserted on a preset position subcarrier of each OFDM symbol based on the received signal, and performing initial phase tracking according to the first pilot signal and the channel estimation value to obtain an initial phase parameter; based on the first result after channel equalization, the second result after demapping or the third result after error correction decoding, reconstructing to obtain a second pilot signal; and performing enhanced phase tracking according to the first pilot signal, the second pilot signal and the channel estimation value to obtain an updated phase parameter. Therefore, phase tracking can be performed based on more pilot signals, the accuracy of phase tracking can be improved, and the phase parameter estimation error can be reduced.

Description

Technical Field

[0001] This application relates to the field of communication technologies, and particularly to a method, a storage medium, and a product for enhanced phase tracking. Background Art

[0002] Phase tracking is a commonly used synchronization technology in communication receivers. By estimating and compensating the phase error of the received signal in real time, the phase consistency between the received signal and the transmitted signal is maintained. The phase error is mainly caused by CFO, STO, circuit phase noise, etc., which will seriously affect the quality of the received signal. Common methods for phase error estimation: perform correlation operations using known pilot signals or two consecutive repeated signals.

[0003] In the WLAN scenario, pilot signals are inserted on the subcarriers at specific positions of each OFDM symbol. Phase tracking can be performed according to the pilot signals received in real time. However, to ensure throughput, the number of pilot signals is very small (for example, in the 20M OFDM symbol of 802.11n, only 4 subcarriers are inserted among a total of 64 subcarriers), which limits the performance of phase error estimation and phase tracking, especially in the low signal-to-noise ratio (SNR) receiving scenario. In the low SNR environment, the quality of the received signal deteriorates, and the interference of noise on the signal increases. At this time, the already scarce pilot signals are more vulnerable to noise, and their accuracy and reliability are further reduced. Summary of the Invention

[0004] In view of the above technical problems existing in the prior art, this application is proposed. This application aims to provide a method, a storage medium, and a product for enhanced phase tracking, which can solve the problem of large errors in phase error estimation due to the small number of pilot signals participating in the operation. By reducing the phase error, the probability of decoding misjudgment is reduced, packet loss is reduced, and thus the retransmission rate is reduced.

[0005] According to the first aspect of this application, a method for enhanced phase tracking is provided. The method includes: the receiver processes the received signal to obtain channel estimation values on each subcarrier; obtains the first pilot signal inserted on the subcarriers at the preset positions of each OFDM symbol based on the received signal, and performs initial phase tracking according to the first pilot signal and the channel estimation values to obtain initial phase parameters; reconstructs the second pilot signal based on the first result after channel equalization, the second result after demapping, or the third result after error correction decoding; performs enhanced phase tracking according to the first pilot signal, the second pilot signal, and the channel estimation values to obtain updated phase parameters.

[0006] According to a second aspect of the present application, there is provided a computer-readable storage medium storing computer instructions for causing a computer to execute the method for enhanced phase tracking as described in various embodiments of the present application.

[0007] According to a third aspect of the present application, there is provided a computer program product including computer instructions for causing a computer to execute the method for enhanced phase tracking as described in various embodiments of the present application.

[0008] Compared with the prior art, the beneficial effects of the embodiments of the present application are as follows:

[0009] The method for enhanced phase tracking provided by the embodiments of the present application reconstructs a second pilot signal based on a first result after channel equalization, a second result after demapping, or a third result after error correction decoding, and uses the second pilot signal and the first pilot signal simultaneously for enhanced phase tracking. In this way, the number of pilot signals for enhanced phase tracking is increased. Enhanced phase tracking based on the reconstructed second pilot signal and the first pilot signal can reduce the estimation error of phase parameters, improve the accuracy of phase error estimation, and make the updated phase parameters closer to the true values.

[0010] The above description is only an overview of the technical solution of the present application. In order to be able to understand the technical means of the present application more clearly, it can be implemented in accordance with the content of the specification. And in order to make the above description and other purposes, features, and advantages of the present application more obvious and understandable, the specific embodiments of the present application are specifically given below. Brief Description of the Drawings

[0011] In the drawings, which are not necessarily drawn to scale, the same reference numerals may describe similar components in different views. Similar reference numerals with alphabetical suffixes or different alphabetical suffixes may represent different examples of similar components. The drawings generally illustrate various embodiments by way of example and not by way of limitation, and are used together with the specification and the claims to explain the disclosed embodiments. Such embodiments are illustrative and exemplary and are not intended to be exhaustive or exclusive embodiments of the method, apparatus, system, or non-transitory computer-readable medium having instructions for implementing the method.

[0012] Figure 1 A flowchart showing the method for enhanced phase tracking according to an embodiment of the present application is shown.

[0013] Figure 2 A schematic diagram of a receiver for performing enhanced phase tracking according to an embodiment of the present application is shown.

[0014] Figure 3Shows another schematic diagram of a receiver for enhanced phase tracking according to an embodiment of the present application.

[0015] Figure 4 Shows a curve of the CFO parameter estimation error versus SNR according to an embodiment of the present application.

[0016] Figure 5 Shows a curve of the STO parameter estimation error versus SNR according to an embodiment of the present application.

[0017] Figure 6 Shows the ordinary phase tracking STO according to an embodiment of the present application l Parameter estimation result variation curve with the number of OFDM symbols.

[0018] Figure 7 Shows the enhanced phase tracking STO according to an embodiment of the present application l Parameter estimation result variation curve with the number of OFDM symbols. Detailed implementation manners

[0019] To enable those skilled in the art to better understand the technical solutions of the present application, the present application will be described in detail below in conjunction with the accompanying drawings and specific implementation manners. The embodiments of the present application will be further described in detail below in conjunction with the accompanying drawings and specific examples, but it is not a limitation to the present application.

[0020] The "first", "second" and similar terms used in the present application do not denote any order, quantity or importance, but are only used for distinction. The terms such as "including" or "comprising" used in the present application mean that the elements before the term cover the elements listed after the term, and do not exclude the possibility of also covering other elements. In the present application, the arrows shown in the figures for each step are only examples of the execution order and not limitations. The technical solutions of the present application are not limited to the execution order described in the embodiments. Each step in the execution order can be executed together, can be decomposed, and can be reordered, as long as it does not affect the logical relationship of the execution content.

[0021] All terms used in the present application (including technical terms or scientific terms) have the same meaning as understood by those of ordinary skill in the art to which the present application pertains, unless otherwise specifically defined. It should also be understood that terms defined in a general dictionary, such as those, should be interpreted as having a meaning consistent with their meaning in the context of the relevant art, and should not be interpreted in an idealized or overly formal sense, unless specifically defined as such here. Technologies and devices known to those of ordinary skill in the relevant art may not be discussed in detail, but where appropriate, such technologies and devices should be regarded as part of the specification.

[0022] In a communication system, a transmitter modulates an original transmitted signal, loads information onto a carrier wave for transmission. During the transmission process, the signal is affected by various factors, which cause phase offsets and jitters in the signal. The receiver needs to accurately recover a carrier wave that is in the same frequency and phase as the transmitter through phase tracking. By phase tracking, these phase changes can be estimated and compensated in real time, enabling the receiver to accurately recover the original signal.

[0023] As Figure 2 shown, the receiver processes the received baseband signal, searches for timing information in the signal through relevant algorithms (such as timing synchronization algorithms based on pilot signals or cyclic prefixes), determines the starting position and symbol boundaries of the signal, and ensures that subsequent operations can be carried out at the correct time points.

[0024] Then, using the pilot signal or specific structure in the received signal, algorithms such as those based on maximum likelihood estimation are used to estimate the carrier frequency offset. After estimating the frequency offset, the received signal is compensated by multiplying it with the corresponding complex exponential factor to eliminate the influence of the carrier frequency offset on the signal, bringing the signal to the correct carrier frequency to achieve frequency offset estimation and compensation.

[0025] Next, OFDM demodulation is performed. The signal after timing synchronization and frequency offset estimation and compensation is subjected to a discrete Fourier transform operation, converting the signal from the time domain to the frequency domain, and separating the information carried on different subcarriers in the OFDM symbol.

[0026] Furthermore, by means of the transmitted pilot signal, algorithms such as least squares (LS), linear minimum mean square error (LMMSE), etc. are used to estimate the channel characteristics, obtain the channel estimation values on each subcarrier, and based on the channel estimation results, the signal part carrying signaling information is processed to demodulate system-related control signaling, such as demodulation signaling parameters like modulation mode, coding rate, etc., providing necessary parameters for subsequent data demodulation.

[0027] According to the ordinary phase tracking method, after obtaining the demodulation signaling parameters, the previous processing results (including, for example, channel estimation values, demodulation signaling parameters, etc.) and the pilot signal can be used for ordinary phase tracking, and after ordinary phase tracking, an ordinary phase parameter estimation value is obtained. Then, channel equalization processing is carried out, and the result of the channel equalization processing is input into the decoding and verification module to execute the subsequent processing flow.

[0028] However, this application finds that the error between the ordinary phase parameter estimation value obtained based on the ordinary phase tracking method and the true value is relatively large, especially in low SNR (signal-to-noise ratio) scenarios (such as the SNR working threshold in the MCS0 scenario is around 2 dB), and an accurate ordinary phase parameter estimation value cannot be obtained.

[0029] As Figure 1As shown, the method with enhanced phase tracking provided by the embodiments of the present application can effectively solve the above problems. Specifically, in step S101, the receiver processes the received signal to obtain the channel estimation values on each subcarrier. Common implementation methods include channel estimation based on pilot signals, channel estimation based on blind estimation, and channel estimation based on semi-blind estimation, which are not limited herein.

[0030] For example, the transmitter inserts known pilot signals into the data sequence to be transmitted according to a preset rule. The position, quantity, and sequence design of the pilot signals need to be optimized according to the specific requirements of the communication system. For example, in an orthogonal frequency division multiplexing (OFDM) system, the pilot signals can be distributed in a block-like, comb-like manner in the frequency domain and time domain.

[0031] After the receiver receives the signal, it extracts the pilot signals from the received signal. Since the pilot signals are known at the transmitting end, the receiver can accurately find the pilot signals according to the position and sequence information of the pilot signals. And by comparing the received pilot signals with the known transmitted pilot signals, algorithms such as the least squares (LS) method and the minimum mean square error (MMSE) method are used to calculate the channel estimation values at the pilot positions.

[0032] This is only for illustrative purposes and does not constitute a limitation on the specific solution.

[0033] In step S102, a first pilot signal inserted on the subcarriers at the preset positions of each OFDM symbol is obtained based on the received signal, and initial phase tracking is performed according to the first pilot signal and the channel estimation values to obtain initial phase parameters.

[0034] Exemplarily, a simple introduction to the basic model for phase tracking is given.

[0035] Among them, the phase error model is as follows:

[0036] Φ l,k =CPE l +k×STO l ;

[0037] CPE l =l∈+∈0;

[0038] STO l =lμ+μ0;

[0039] Among them, l = 1,..., L represents the OFDM symbol number, and a total of L OFDM symbols are transmitted; k = 1,..., K represents the subcarrier number, and the total number of subcarriers used is K; Φ l,k represents the corresponding phase error value; CPE lDenote the common phase error of the \(l\) -th OFDM symbol, which is mainly caused by the residual carrier frequency offset (CFO). (The so - called "residual", the received signal will first pass through the frequency offset estimation and compensation module, and there is still a small amount of CFO when it reaches the phase tracking module). \(l\in\) represents the linear variation part of the common phase error (CPE) related to the \(l\) -th OFDM symbol caused by the residual carrier frequency offset (CFO). Due to the existence of the residual CFO, as the symbol index \(l\) increases, the CPE l linearly increases at a rate of \(\epsilon\), where \(\epsilon\) is determined by the residual CFO, and \(\epsilon_0\) represents the bias component; STO l Denote the timing deviation of the \(l\) -th OFDM symbol, which is mainly caused by the sampling frequency offset (SRO). \(l\mu\) represents the linear variation part of the timing error (STO) related to the \(l\) -th OFDM symbol caused by the sampling frequency offset (SRO). As the symbol index \(l\) increases, the timing error linearly increases at a rate of \(\mu\), where \(\mu\) is determined by the SRO, and \(\mu_0\) represents the bias component. l Here, \(G\) is the number of time - domain signal points of an OFDM symbol, \(\Delta f\)

[0040]

[0041] is the residual carrier frequency offset CFO, \(f\) r is the sampling rate, \(\Delta f\) s is the sampling frequency offset SRO. s The received signal model is as follows:

[0042] \[y

[0043] \]=\(H\) l,k \[x k \]+\(n\) l,k \]; l,k where

[0044] \(y\) l,k : the received signal, an \(N\) R -dimensional column vector, the number of receiving antennas is \(N\) R ;

[0045] \(H\) k : the channel matrix, an \(N\) R \(\times N\) T matrix, the number of transmitting antennas is \(N\) T ;

[0046] \(x\) l,k : the transmitted signal, an \(N\) T -dimensional column vector;

[0047] \(n\) l,k : the Gaussian white noise, an \(N\) R -dimensional random vector.

[0048] Note: Without loss of generality, assume \(N\) R \(\geq N\)T , ignoring the impact of precoding.

[0049] Specifically, the communication protocol pre - determines the parameters related to the first pilot signal, including the sub - carrier number corresponding to the first pilot signal and the first pilot signal value. Based on the sub - carrier number corresponding to the first pilot signal, the total number of the first pilot signals is obtained. Based on this information, the sub - carrier position where the first pilot signal is located can be located in the received signal. In the received signal, according to the determined sub - carrier number, the signal value is extracted from the corresponding sub - carrier, and a set of first pilot signals can be obtained. where k p is the sub - carrier number corresponding to the p - th first pilot signal, P is the total number of the first pilot signals (it is certain that P is not less than 2), k p the value and the set of the first pilot signals transmitted by the transmitter are both determined by the communication protocol, where represents the first pilot signal transmitted on the l - th OFDM symbol and the k p - th sub - carrier.

[0050] In this embodiment, the first pilot signal extracted from the received signal is used as a known reference signal, and its phase characteristics are clear. The channel estimation value contains information such as the phase offset caused by the channel to signal transmission. Based on the first pilot signal and the channel estimation value for initial phase tracking, the influence of the actual channel on the phase of the first pilot signal can be comprehensively considered.

[0051] Exemplarily, based on the first pilot signal and the channel estimation value, a specific phase tracking algorithm (such as the least - squares method) can be used to perform initial phase tracking and calculation on the phase of the received signal. In this process, the estimation of the phase parameters is continuously adjusted and optimized to adapt to the phase changes experienced by the signal during transmission.

[0052] After the initial phase tracking process, a set of initial phase parameters that can describe the initial phase state of the received signal is finally obtained. For example, the phase parameters include the common phase error CPE and the timing offset STO, which can be used for subsequent operations such as phase compensation of the received signal.

[0053] Exemplarily, according to the known first pilot signal and the channel estimation value the phase error estimation value on the l - th OFDM symbol and the k p - th sub - carrier can be obtained where is the channel estimation value on the k - th sub - carrier, k ranges from 1 to K, covering all used sub - carriers, is the channel estimation value on the k p - th sub - carrier.

[0054] According to the expression, a total of P linear equations can be obtained, and by combining them, a linear equation system is obtained:

[0055]

[0056] Generally, P > 2, and the weighted least squares method can be used to estimate the parameter vector Θ l , where the weight matrix W is a diagonal matrix with the two-norm of the channel estimate value as the diagonal elements, Initial Initial

[0057] Furthermore, the historical parameter estimation results can be comprehensively used for parameter smoothing to reduce the parameter estimation error. The common phase deviation after parameter smoothing on the l-th OFDM symbol The timing deviation after parameter smoothing on the l-th OFDM symbol where SF[·] represents the smoothing operator, and the smoothing method can be moving average, loop filtering, Kalman filtering, etc., which is not limited herein.

[0058] Based on the result of parameter smoothing, the phase error estimation value at any subcarrier position is obtained and error compensation is performed to obtain the signal on the l-th OFDM symbol and the k-th subcarrier after phase error compensation y l,k is the signal received on the l-th OFDM symbol and the k-th subcarrier before phase error compensation, is the compensation factor, which is constructed according to the phase error estimation value Φ l,k to adjust the phase of the received signal, cancel the phase deviation caused by factors such as the channel, and make the signal closer to the phase state of the original transmitter's transmitted signal, thereby improving the signal quality.

[0059] This is only for illustrative purposes and does not constitute a limitation on the specific solution.

[0060] For example Figure 2 , after initial phase tracking, channel equalization processing is performed. Equalization algorithms such as zero-forcing ZF and minimum mean square error MMSE are used to process the received signal in combination with the channel estimate value to eliminate the inter-symbol interference and other effects caused by the channel, and make the received signal closer to the transmitted signal of the original transmitter.

[0061] Among them, the transmitted signal vector estimated after zero-forcing equalization The goal of zero-forcing equalization is to make the total response of the channel equal to 1 at all frequencies, that is, to completely eliminate inter-symbol interference (ISI). It calculates the pseudo-inverse of the channel estimation matrix to process the received signal y l,k and obtain the estimated transmitted signal

[0062] The minimum mean square error (MMSE) equalization method can also be used to obtain the transmitted signal vector σ 2 represents the variance of the noise, reflecting the power of the noise in the channel and used to measure the degree of interference of the noise on the signal. N T ×N T identity matrix. The MMSE takes into account the combined effects of the channel and the noise. Compared with zero-forcing equalization, the MMSE can estimate the transmitted signal more accurately in a noisy environment and has better performance.

[0063] This is only an example and does not constitute a limitation on the specific solution.

[0064] In step S103, a second pilot signal is reconstructed based on the first result after channel equalization, the second result after demapping, or the third result after error correction decoding; in step S104, enhanced phase tracking is performed according to the first pilot signal, the second pilot signal, and the channel estimation value to obtain updated phase parameters.

[0065] Specifically, channel equalization is to compensate for signal distortion caused by the channel. After being processed by equalization algorithms such as zero-forcing (ZF) and minimum mean square error, the obtained signal (the first result) is closer to the original transmitted signal in terms of amplitude and phase, reducing the influence of inter-symbol interference and the like.

[0066] Demapping is the process of restoring the modulated signal (such as modulation methods like QAM, PSK, etc.) to a bit stream. The second result obtained after demapping is the information bits preliminarily extracted from the modulated signal.

[0067] Error correction decoding uses the redundant information added during encoding to detect and correct the error codes in the received signal. The third result is the more reliable information bits after error correction processing.

[0068] Using the first result after channel equalization, the second result after demapping, or the third result after error correction decoding, the second pilot signal is reconstructed through a specific algorithm or rule. The reconstructed second pilot signal is combined with the first pilot signal for enhanced phase tracking, and more pilot signals participate in the phase tracking operation process, greatly reducing the phase estimation error.

[0069] In some embodiments of the present application, an element in the QAM constellation symbol set that is closest to the first result in terms of Euclidean distance in the complex plane can be used as the reconstructed second pilot signal; wherein, the QAM constellation symbols are obtained based on the original transmitted signal transmitted by the transmitter.

[0070] Specifically, an element that is closest to the signal obtained after channel equalization in terms of Euclidean distance in the complex plane can be found within the set of QAM constellation symbols transmitted by the transmitter as the reconstructed second pilot signal wherein, n t is 1, …, N T , Ω is the set of transmitted QAM constellation symbols, S is an element in the set, and F is the F-norm.

[0071] The QAM constellation points are the standard positions of the signals transmitted by the transmitter. Finding the element in the QAM constellation symbol set that is closest to the first result after channel equalization in terms of Euclidean distance is because this element is most likely the constellation point corresponding to the original transmitted signal. The so-called “reconstruction” can be understood as reconstructing the original transmitted signal inferred from the first result into a new second pilot signal for use, so as to increase the number of pilot signals participating in the phase tracking operation and improve the accuracy of phase tracking.

[0072] wherein, the reconstructed second pilot signal and the first pilot signal are used together as new pilot signals wherein, k d is the subcarrier number corresponding to the d-th data signal, D is the total number of data signals, and D + P = K.

[0073] In some embodiments of the present application, when the number of elements in the QAM constellation symbol set that are closest to the first result in terms of Euclidean distance in the complex plane exceeds one and there is a discrimination ambiguity, the average value of each element is obtained as the reconstructed second pilot signal.

[0074] That is to say, the distances to more than one QAM constellation point are the same and the minimum value is taken simultaneously, which results in the inability to uniquely determine which QAM constellation point is transmitted according to the distance minimum principle, thus leading to a discrimination ambiguity. At this time, the average value of these QAM constellation points can be used as the reconstructed second pilot signal, which can comprehensively consider these possible QAM constellation points to a certain extent. The average value can reflect the central tendency of these possible QAM constellation points. Compared with randomly selecting one of the QAM constellation points, taking the average value can reduce the estimation deviation and improve the accuracy and reliability of the reconstructed second pilot signal.

[0075] In addition, since the distribution of some QAM constellation points in the complex plane may be relatively symmetric, their average value may happen to be 0. When the average value is 0, a random element is selected from among the elements that are closest in Euclidean distance to the first result in the complex plane as the second pilot signal.

[0076] When the average value is 0, it may not represent any actual QAM constellation point because, in the set of QAM constellation points, there is usually no actual QAM constellation point located at the origin (0,0) of the complex plane. At this time, if 0 is still used as the reconstructed second pilot signal, it may cause errors in subsequent signal processing because 0 is not a valid constellation point value. Therefore, in order to obtain a valid reconstructed second pilot signal, a random selection is made from among the elements that are closest in Euclidean distance (i.e., those QAM constellation points that cause discrimination ambiguity). In this way, the use of the unreasonable value 0 is avoided. This can ensure that subsequent signal demodulation, decoding, etc. are carried out based on correct signal values, maintaining the normal operation of the communication system.

[0077] In some embodiments of the present application, when enhanced phase tracking is performed and discrimination ambiguity occurs, the weight coefficient at the subcarrier position corresponding to the discrimination ambiguity in the weight matrix is reduced.

[0078] That is to say, since the probability of discrimination error is relatively large when discrimination ambiguity occurs, when subsequent enhanced phase tracking is performed, the weight coefficient at the corresponding position in the weight matrix W needs to be reduced, that is where k a represents the subcarrier position where discrimination ambiguity occurs, n a represents the number of ambiguous elements in the reconstructed signal vector and Q represents the number of information bits carried by each OFDM symbol.

[0079] When discrimination ambiguity occurs, the probability of discrimination error is relatively large, which means that the reliability of the received signal at the relevant subcarrier position is low. Reducing the weight coefficient can reduce the influence of the signal at the subcarrier position corresponding to the discrimination ambiguity in the subsequent enhanced phase tracking calculation, avoid large errors caused by misjudged signals, prevent the further spread of errors, and ensure the accuracy of phase tracking. Moreover, after the weight coefficient is reduced, subsequent calculations pay more attention to other signals with high reliability, enabling the enhanced phase tracking algorithm to focus on more accurate information, adjust the phase tracking result, improve the overall phase tracking performance, and make the tracking more conform to the actual signal phase change.

[0080] In some other embodiments of the present application, based on the new pilot signal Perform enhanced phase tracking, which is different from the initial phase tracking in that when performing enhanced phase tracking, the number of new pilot signals increases from P to K, so that the obtained updated phase parameters are more accurate.

[0081] Among them, when performing enhanced phase tracking, Solve the K-dimensional equation system by the weighted least squares method: Different from performing the initial phase tracking, (1) Becomes a K-dimensional vector, The number of rows of the matrix becomes K, Is a K-dimensional matrix; (2) The weight coefficient corresponding to the decision ambiguity subcarrier position in is reduced.

[0082] At this time, the updated phase parameters include And Among them,

[0083] Use the updated phase parameters to re-perform parameter smoothing and phase compensation, among which, Subsequently, perform phase compensation and channel equalization to obtain the updated result And send the updated result To the subsequent decoding and verification module.

[0084] That is to say, based on the updated common phase error and updated timing deviation obtained from the current enhanced phase tracking, perform parameter smoothing and phase compensation, and then perform channel equalization on the updated compensation result, and then send the result after channel equalization to the subsequent decoding and verification module.

[0085] Alternatively, the updated common phase error and updated timing deviation obtained from the current enhanced phase tracking can also be used for the parameter smoothing process during the next initial phase tracking, and there is no need to perform additional parameter smoothing, phase compensation, and decoding this time. In this way, the hardware cost and system delay can be reduced, and the system burden can be reduced.

[0086] In some embodiments of the present application, the second pilot signal is reconstructed based on the second result after demapping, specifically including: when demapping according to the QAM constellation diagram corresponding to the modulation method adopted by the transmitter, obtaining the soft bit information of each bit; using the soft bit information to perform hard decision to convert the soft bit information into a binary bit value, and reconstructing the second pilot signal according to the preset modulation mapping rule with the binary bit value.

[0087] Specifically, as Figure 3As shown, the post - equalization reconstruction (1) refers to the process of reconstructing a second pilot signal based on the first result after channel equalization. The soft - bit reconstruction (2) refers to reconstructing a second pilot signal based on the second result after demapping.

[0088] Specifically, for the soft - bit reconstruction (2), the modulated signal (such as a QAM - modulated signal) after channel equalization is restored from the QAM constellation - point mapping relationship to a bit - stream, that is, converted from a modulation symbol to the original soft - bit information. Among them, the soft - bit information is also called the "log - likelihood ratio", which is used to characterize the relative probability of each bit information being 0 or 1. For example, in a communication receiver, the soft - bit information can reflect whether a certain bit in the received signal is more likely to be 0 or 1, and the degree of this tendency. Compared with a simple 0 - 1 decision, it carries more reliability information of the signal.

[0089] After having the probability information of each bit being 0 or 1, a decision threshold can be set (for example, if the probability is greater than 0.5, it is judged as 1; if it is less than 0.5, it is judged as 0), and the soft - bit information is converted into a clear binary bit value (0 or 1) to complete the reconstruction of binary data at the bit level.

[0090] The binary bit value obtained by hard decision is reconstructed into the transmitted QAM symbol according to the modulation mapping rule (such as in QAM modulation, different binary combinations correspond to different constellation points) preset in the communication system, and used as the second pilot signal for subsequent enhanced phase tracking.

[0091] In some embodiments of the present application, reconstructing a second pilot signal based on the third result after error - correction decoding specifically includes: performing error - correction decoding on the first result after channel equalization to obtain the initially restored original bit information; subjecting the original bit information to the encoding and modulation process of the transmitter to reconstruct the QAM constellation - point symbol, and using the reconstructed QAM constellation - point symbol as the second pilot signal.

[0092] Exemplarily, as Figure 3 shown in the block - level reconstruction (3), specifically, the original bit information after error - correction decoding can be completely executed through the encoding and modulation process of the transmitter to restore the transmitted QAM symbol and use it as the second pilot signal.

[0093] In this embodiment, taking the reconstruction of the second pilot signal based on the first result after channel equalization as an embodiment of enhanced phase tracking, and taking the ordinary phase - tracking method without enhanced phase tracking as a comparative example, the phase - error parameter estimation is carried out.

[0094] The comparison results are as Figure 4 、 Figure 5As shown, it can be seen that based on the enhanced phase tracking method provided in the embodiments of the present application, the common phase error estimation error and the timing deviation estimation error can be significantly reduced, and more accurate phase tracking can be achieved.

[0095] The comparison results are as Figure 6 , Figure 7 shown. It can be seen that based on the enhanced phase tracking method provided in the embodiments of the present application, the value estimated is closer to the true value.

[0096] Moreover, through further verification, based on the enhanced phase tracking method provided in the embodiments of the present application, the estimation errors of CPE l and STO l are smaller, and it converges faster with the enhancement of OFDM symbols. And near the SNR threshold at which the receiver operates, the error vector magnitude of the received signal can be made smaller, improving the quality of the received signal. At the same time, due to the reduction of the phase estimation error, the probability of decoding misjudgment is reduced, the packet loss is reduced, and the retransmission probability is reduced. In addition, the enhanced phase tracking method provided in the embodiments of the present application can operate at a lower SNR threshold, which means a reduction in the power consumption of the receiver.

[0097] In some embodiments of the present application, the computer-readable storage medium stores computer instructions, and the computer instructions are used to cause the computer to execute the steps of the phase tracking enhancement method as described in the various embodiments of the present application.

[0098] The above computer-readable storage medium can be, for example, a read-only memory (ROM), a random access memory (RAM), a phase change random access memory (PRAM), a static random access memory (SRAM), a dynamic random access memory (DRAM), an electrically erasable programmable read-only memory (EEPROM), other types of random access memory (RAM), a flash drive or other forms of flash memory, a cache, a register, a static memory, a compact disc read-only memory (CD-ROM), a digital versatile disc (DVD) or other optical memory, a cassette tape or other magnetic storage device, or any other possible non-transitory medium used to store information or instructions that can be accessed by a computer device, etc.

[0099] According to an embodiment of the present application, there is also provided a computer program product, and the computer program product includes computer instructions, and the computer instructions are used to cause a computer to execute the steps in the phase tracking enhancement method as described in the various embodiments of the present application.

[0100] This application describes various operations or functions, which can be implemented as software code or instructions or be defined as software code or instructions. Such content can be source code that can be directly executed or differential code ("incremental" or "patch" code) ("object" or "executable" form). The software code or instructions can be stored in a computer-readable storage medium, and when executed, can cause a machine to perform the described functions or operations, and include any mechanism for storing information in a form accessible to a machine (e.g., a computing device, an electronic system, etc.), such as a recordable or non-recordable medium (e.g., read-only memory (ROM), random access memory (RAM), magnetic disk storage media, optical storage media, flash devices, etc.).

[0101] Moreover, although exemplary embodiments have been described herein, the scope includes any and all embodiments based on this application having equivalent elements, modifications, omissions, combinations (e.g., schemes that cross various embodiments), adaptations, or alterations. The elements in the claims will be broadly interpreted based on the language employed in the claims and are not limited to the examples described in this specification or during the implementation of this application, and the examples will be construed as non-exclusive. Thus, this specification and the examples are intended to be considered only as examples, and the true scope and spirit are indicated by the following claims and the full scope of their equivalents.

[0102] The above description is intended to be illustrative rather than restrictive. For example, the above examples (or one or more of their schemes) can be used in combination with each other. For example, other embodiments can be used by those of ordinary skill in the art upon reading the above description. Additionally, in the above detailed description, various features can be grouped together to simplify this application. This should not be construed as an intention that the disclosed features that are not claimed are necessary for any claim. On the contrary, the subject matter of this application can be less than all the features of a particular disclosed embodiment. Thus, the claims are incorporated herein as examples or embodiments into the detailed description, where each claim independently serves as a separate embodiment, and it is contemplated that these embodiments can be combined with each other in various combinations or permutations. The scope of this application should be determined with reference to the appended claims and the full scope of the equivalent forms empowered by these claims.

[0103] The above embodiments are only exemplary embodiments of this application and are not used to limit this application. The protection scope of this application is defined by the claims. Those skilled in the art can make various modifications or equivalent replacements within the essence and protection scope of this application, and such modifications or equivalent replacements should also be regarded as falling within the protection scope of this application.

Claims

1. A method for enhanced phase tracking, characterized in that, The method includes: The receiver processes the received signal to obtain channel estimation values on each subcarrier; Based on the received signal, obtain the first pilot signal inserted on the subcarriers at preset positions of each OFDM symbol, and perform initial phase tracking according to the first pilot signal and the channel estimation values to obtain initial phase parameters; Based on the first result after channel equalization, the second result after demapping, or the third result after error correction decoding, reconstruct the second pilot signal; Perform enhanced phase tracking according to the first pilot signal, the second pilot signal, and the channel estimation values to obtain updated phase parameters.

2. The method according to claim 1, wherein Reconstructing the second pilot signal based on the first result after channel equalization specifically includes: Taking the element in the QAM constellation symbol set that has the closest Euclidean distance to the first result in the complex plane as the reconstructed second pilot signal; Wherein, the QAM constellation symbols are obtained based on the original transmitted signal transmitted by the transmitter.

3. The method according to claim 2, wherein When the number of elements in the QAM constellation symbol set that have the closest Euclidean distance to the first result in the complex plane exceeds one and discrimination ambiguity occurs, obtain the average value of each element as the reconstructed second pilot signal.

4. The method according to claim 3, characterized in that, When the average value is 0, randomly select one of the elements that have the closest Euclidean distance to the first result in the complex plane as the second pilot signal.

5. The method according to claim 3 or 4, characterized in that, When performing enhanced phase tracking and judgment ambiguity occurs, reduce the weight coefficient of the subcarrier position corresponding to judgment ambiguity in the weight matrix.

6. The method according to claim 1, wherein Reconstructing the second pilot signal based on the second result after demapping specifically includes: When demapping according to the QAM constellation diagram corresponding to the modulation method adopted by the transmitter, obtain soft bit information for each bit; Perform hard decision using the soft bit information to convert the soft bit information into binary bit values, and reconstruct the second pilot signal according to the preset modulation mapping rule with the binary bit values.

7. The method according to claim 1, characterized in that, Reconstructing the second pilot signal based on the third result after error correction decoding specifically includes: Perform error correction decoding based on the first result after channel equalization to obtain the initially recovered original bit information; Reconstruct QAM constellation symbols by subjecting the original bit information to the encoding and modulation process of the transmitter, and use the reconstructed QAM constellation symbols as the second pilot signal.

8. The method according to claim 1, wherein The phase parameters include common phase error and timing deviation; the method further includes: Based on the updated common phase error and updated timing deviation obtained from the current enhanced phase tracking, perform parameter smoothing and phase compensation, and then perform channel equalization on the updated compensation result, and send the result after channel equalization to the subsequent decoding and verification module.

9. The method according to claim 1, wherein The method further includes: Using the updated common phase error and updated timing deviation obtained from the current enhanced phase tracking for the parameter smoothing process during the next initial phase tracking.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions, and the computer instructions are used to cause the computer to execute the method for enhanced phase tracking as described in any one of claims 1-9.

11. A computer program product, characterized in that, Comprising computer instructions for causing a computer to execute the method for enhanced phase tracking according to any one of claims 1-9.

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