A channel parameter joint estimation method, system, device, medium and product

Abstract

The application provides a channel parameter joint estimation method, system, device, medium and product, relates to the technical field of communication, and different first sampling periods and second sampling periods are preset to process a channel estimation sequence, so that a first estimation value and a second estimation value with a deviation of a first channel parameter are correspondingly obtained, an estimation method is constructed based on a quantitative relationship between the first estimation value, the second estimation value and the sampling period, each estimation value obtained is input into the constructed estimation method, and estimation values of real first channel parameters and second channel parameters of a current communication link are respectively determined. The application realizes the technical effect that multiple channel parameters are estimated with high precision by using a single estimator in an extremely low signal-to-noise ratio and high-speed mobile scene.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a method, system, device, medium and product for joint estimation of channel parameters. Background Technology

[0002] In the field of mobile communications, using the horizontal crossover rate (LCR) for Doppler shift estimation is a classic existing technique. In existing technologies, Doppler shift estimators are typically based on the theoretical foundation that, in a Rayleigh fading channel without additive noise, the horizontal crossover rate of the received signal envelope has a strict proportional relationship with the maximum Doppler shift. The estimation steps are typically set up as follows: 1. Signal Preprocessing and Envelope Detection: The receiver first synchronizes and estimates the channel of the received signal, obtaining a complex-valued channel impulse response sequence. Then, the magnitude of this sequence is calculated to extract the envelope signal characterizing the signal strength decay over time.

[0003] 2. Horizontal Crossover Rate Measurement: A fixed amplitude threshold is set. To simplify analysis, this threshold is typically set to the long-term root mean square value of the envelope signal. The estimator uses a counting circuit or software algorithm to accurately count the total number of times the envelope signal crosses the threshold from top to bottom within a unit of time; this statistical result is the measured horizontal crossover rate (LCR).

[0004] 3. Linear Conversion Estimation: The measured horizontal crossover rate value is directly substituted into a fixed linear conversion formula derived in advance based on a noiseless channel model to calculate and output the final Doppler frequency shift estimate. This process does not include any compensation or correction mechanism for noise effects.

[0005] Existing Doppler shift estimation methods are widely used due to their simple structure, but their theoretical models are based on the ideal assumption of noise-free environments, which severely limits their performance in real communication environments. In summary, existing solutions suffer from at least the following drawbacks: In extremely low signal-to-noise ratio (SNR) environments, the performance of existing channel parameter (especially Doppler shift) estimators is severely degraded by additive white Gaussian noise interference; traditional estimation methods based on autocorrelation functions or series approximations have inherent approximation errors, resulting in a small estimation range and low accuracy in high-speed shift scenarios; existing joint estimation methods involve large real-time computational loads and poor stability, making them difficult to implement in practical systems, and Doppler shift and SNR typically require two independent estimators, increasing the system's implementation cost and complexity. Summary of the Invention

[0006] The purpose of this application is to provide a method, system, device, medium, and product for joint estimation of channel parameters to improve the above-mentioned problems in the prior art.

[0007] For the purposes mentioned above, this application provides the following technical solution: The first aspect of this application provides a joint channel parameter estimation method, including: Obtain the channel estimation sequence for the current communication link; A first subsequence is obtained by sampling the channel estimation sequence based on a first sampling period, and a second subsequence is obtained by sampling the channel estimation sequence based on a second sampling period, wherein the first sampling period and the second sampling period are different; A first estimated value corresponding to the first subsequence and a second estimated value corresponding to the second subsequence are obtained respectively, wherein the first estimated value and the second estimated value are both deviation estimates of the first channel parameters; The first sampling period, the second sampling period, the first estimated value, and the second estimated value are input into a preset estimation strategy to determine the estimated values ​​of the first channel parameter and the second channel parameter corresponding to the current communication link, respectively.

[0008] Preferably, the second sampling period is greater than the first sampling period, and the second sampling period is set to an integer multiple of the first sampling period.

[0009] Further, obtaining the first estimated value corresponding to the first subsequence and the second estimated value corresponding to the second subsequence respectively includes: Obtain the first horizontal crossover rate corresponding to the first subsequence, and obtain the first estimated value based on the first horizontal crossover rate; Obtain the second horizontal cross rate corresponding to the second subsequence, and obtain the second estimated value based on the second horizontal cross rate.

[0010] Furthermore, the estimation strategy includes a first estimation strategy and a second estimation strategy, wherein the first estimation strategy is used to estimate the first channel parameter, and the second estimation strategy is used to estimate the second channel parameter; The first estimation strategy obtains the estimated value of the first channel parameter based on the set adjustment parameter, the first estimated value, and the second estimated value. The first channel parameter is the Doppler frequency shift, and the adjustment parameter is determined based on the first sampling period, the first estimated value, and the second estimated value. The second estimation strategy determines the estimated value of the second channel parameter based on the estimated value of the first channel parameter, the first estimated value, and the first sampling period; the second channel parameter is the signal-to-noise ratio.

[0011] Furthermore, the estimation strategy includes a first estimation strategy and a second estimation strategy, wherein the first estimation strategy is used to estimate the first channel parameter, and the second estimation strategy is used to estimate the second channel parameter; The first estimation strategy obtains the estimated value of the first channel parameter based on the set adjustment parameter, the first estimated value, and the second estimated value. The first channel parameter is the Doppler frequency shift, and the adjustment parameter is determined based on the first sampling period, the first estimated value, and the second estimated value. The second estimation strategy determines the estimated value of the second channel parameter based on the estimated value of the first channel parameter, the second estimated value, and the second sampling period; the second channel parameter is the signal-to-noise ratio.

[0012] Optionally, the adjustment parameter is determined based on the first sampling period, the first estimated value, and the second estimated value.

[0013] Optionally, the adjustment parameter is determined based on the second sampling period, the first estimate, and the second estimate.

[0014] Furthermore, there is a first correspondence between the first estimated value and the estimated values ​​of the first channel parameters and the second channel parameters; and there is a second correspondence between the second estimated value and the estimated values ​​of the first channel parameters and the second channel parameters. By jointly solving the first correspondence and the second correspondence, a first estimation strategy for estimating the first channel parameters and a second estimation strategy for estimating the second channel parameters are obtained.

[0015] Furthermore, the first estimation strategy includes:

[0016] in, The first estimated value, This is the second estimated value. This is an estimated value for the first channel parameter. The adjustment parameter is referred to here.

[0017] Optionally, the second estimation strategy determines the estimated value of the second channel parameter based on the estimated value of the first channel parameter, the first estimated value, and the first sampling period.

[0018] Optionally, the second estimation strategy determines the estimated value of the second channel parameter based on the estimated value of the first channel parameter, the second estimated value, and the second sampling period.

[0019] Preferably, the second sampling period is greater than the first sampling period, and the second sampling period is set to an integer multiple of the first sampling period.

[0020] Furthermore, the method also includes: Based on the estimated values ​​of the first channel parameter and the second channel parameter, the pre-stored first error correction table is queried to obtain the corrected value of the estimated value of the first channel parameter. The estimated value of the first channel parameter is corrected based on the correction value of the estimated value of the first channel parameter to obtain the corrected estimated value of the first channel parameter.

[0021] Furthermore, the method also includes: Based on the estimated value of the second channel parameter and the corrected estimated value of the first channel parameter, the pre-stored second error correction table is queried to obtain the corrected value of the estimated value of the second channel parameter. The estimated value of the second channel parameter is corrected based on the correction value of the estimated value of the second channel parameter to obtain the corrected estimated value of the second channel parameter.

[0022] Furthermore, the method for generating the first error correction table and the second error correction table includes: Based on the known true values ​​of the first channel parameters and the true values ​​of the second channel parameters, the relationship between the average relative error of the first channel parameters and the true value of the first channel parameters in different intervals of the second channel parameters is subjected to polynomial fitting through simulation to obtain the first polynomial coefficient set. Each interval of the second channel parameters and the corresponding first polynomial coefficient set are stored as a first error correction table. By performing polynomial fitting on the relationship between the average relative error of the second channel parameter and the true value of the second channel parameter in different first channel parameter intervals through simulation, a second polynomial coefficient set is obtained, and each first channel parameter interval and the corresponding second polynomial coefficient set are stored as a second error correction table.

[0023] A second aspect of this application provides a joint channel parameter estimation system, the system being used to implement the joint channel parameter estimation method described in the first aspect of this application, the system comprising: The periodic sampling module is used to acquire the channel estimation sequence of the current communication link, sample the channel estimation sequence based on a first sampling period to obtain a first subsequence, and sample the channel estimation sequence based on a second sampling period to obtain a second subsequence, wherein the first sampling period and the second sampling period are different; The preliminary estimation module is used to obtain a first estimated value corresponding to the first subsequence and a second estimated value corresponding to the second subsequence, wherein the first estimated value and the second estimated value are both estimated values ​​of the first channel parameters; The joint estimation module is used to input the first sampling period, the second sampling period, the first estimated value, and the second estimated value into a preset estimation strategy to determine the estimated values ​​of the first channel parameter and the second channel parameter corresponding to the current communication link, respectively.

[0024] A third aspect of this application provides an electronic device, comprising: a processor; and a memory for storing processor-executable instructions; wherein the processor is used for the instructions to implement a joint channel parameter estimation method as described in the first aspect of this application.

[0025] The fourth aspect of this application provides a storage medium, which is a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the joint channel parameter estimation method described in the first aspect of this application.

[0026] The fifth aspect of this application provides a computer program product comprising a computer program that, when executed by a processor, implements the steps of a joint channel parameter estimation method as described in the first aspect of this application.

[0027] This application, through the channel parameter joint estimation method described above, can achieve at least the following technical effects: This application acquires signals by setting a "dual sampling rate" and constructs an estimation method by utilizing the estimation deviation of the first channel parameter caused by noise and the quantitative relationship between the second channel parameter and the dual sampling rate. This transforms the adverse effects of noise into beneficial information and enables the high-precision estimation of multiple channel parameters using a single estimator. Attached Figure Description

[0028] To more clearly illustrate the technical solutions in the specific embodiments of this application or the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0029] Figure 1 A schematic flowchart of a joint channel parameter estimation method provided in this application embodiment; Figure 2 A schematic diagram of a joint channel parameter estimation system provided in this application embodiment; Figure 3 This is a schematic diagram of a computer device provided in an embodiment of this application.

[0030] Reference numerals: 200, a joint channel parameter estimation system; 201, periodic sampling module; 202, preliminary estimation module; 203, joint estimation module; 301, memory; 302, processor. Detailed Implementation

[0031] The technical solutions of this application will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0032] This application acquires signals by setting a "dual sampling rate" and constructs an estimation method using the quantitative relationship between the Doppler frequency shift estimation deviation caused by noise and the signal-to-noise ratio and dual sampling rate, thereby transforming the adverse effects of noise into beneficial information. Figure 1 As shown, the joint channel parameter estimation method provided in this embodiment specifically includes the following steps: Step S100: Obtain the channel estimation sequence of the current communication link; Specifically, the transmitting end sends a known pilot signal in the current communication link. After receiving the signal, the receiving end performs synchronization and preliminary processing, extracting a channel estimation sequence of the channel state from the mixed signal containing noise. This channel estimation sequence is used to reflect the fading changes of the channel over time.

[0033] Specifically, in this embodiment, the receiver first removes the CP (Cyclic Prefix) from the received signal and performs a Fast Fourier Transform (IFFT) on the remaining valid data block (containing known pilot signals and unknown data) to transform it from the time domain to the frequency domain. Then, in the frequency domain, the received pilot signal is compared with the locally stored original known pilot signal, and the channel frequency response at the pilot position is directly calculated using the least squares method. Finally, for Doppler estimation, the channel information in the frequency domain needs to be converted back to the time domain. Therefore, after performing an Inverse Fast Fourier Transform (IFFT) on the set of channel frequency responses calculated above, the output of the IFFT is the channel impulse response, which is a time-domain sequence. Each point in this sequence represents the complex gain (including amplitude and phase information) of a multipath component within the current OFDM (Orthogonal Frequency Division Multiplexing) symbol time. To perform further Doppler shift estimation, the most powerful complex gain sequence is traced, and the complex gains of all multipath components are processed (e.g., weighted average or selection of the path with the highest energy) to form a complex numerical sequence that characterizes the overall channel change over time, i.e., the channel estimation sequence described in step S100.

[0034] Step S200: Sample the channel estimation sequence based on a first sampling period to obtain a first sub-sequence, and sample the channel estimation sequence based on a second sampling period to obtain a second sub-sequence, wherein the first sampling period and the second sampling period are different; Specifically, the receiving end copies the same channel estimation sequence obtained in step S100 into two paths, and processes them differently according to a preset first sampling period and a second sampling period: 1. The first path uses a preset first sampling period T. s1 The channel estimation sequence is sampled to obtain a first subsequence. The first sampling period is the same as the original symbol period of the channel estimation sequence, that is, the first subsequence is obtained using all the estimated values ​​of the channel estimation sequence described in step S200. The horizontal crossover rate of the signal envelope is calculated, that is, the number of times the signal envelope crosses a preset reference threshold from top to bottom within one second is counted, and the value of this number is recorded as the first horizontal crossover rate LCR1.

[0035] 2. The second path uses a preset second sampling period to sample the channel estimation sequence (corresponding to period T). s2 The second sampling period is downsampling relative to the first sampling period. Downsampling is mainly achieved through decimation. For a sampling period T... sThe original channel estimation sequence [C1, C2, C3, C4, C5, C6, ...] is obtained. If downsampling by 2x is used, one sample is extracted every other sample to obtain a new sequence [C1, C3, C5, ...]. The second horizontal cross rate of the signal envelope of the sequence obtained after sampling according to the second sampling period is calculated to obtain LCR2.

[0036] Step S300: Obtain the first estimated value corresponding to the first subsequence and the second estimated value corresponding to the second subsequence, respectively. The first estimated value and the second estimated value are both estimated values ​​of the first channel parameters. Further, a first horizontal crossover rate corresponding to the first subsequence is obtained, and a first estimated value is obtained based on the first horizontal crossover rate; a second horizontal crossover rate corresponding to the second subsequence is obtained, and a second estimated value is obtained based on the second horizontal crossover rate.

[0037] Specifically, the category of the first channel parameter is Doppler frequency shift. Based on LCR1 and LCR2 obtained in step S200, the corresponding first estimated value is calculated according to the following formulas (1) and (2). Compared with the second estimate : (1) (2) In this embodiment, the first estimate and the second estimate are both deviation estimates of the Doppler frequency shift; formulas (1) and (2) are simplified formulas derived under the Rayleigh channel from the mathematical relationship between the Doppler frequency shift estimate and the horizontal crossover rate in the noiseless case. In formula (1), Let e ​​be the first estimated value, e be the base of the natural logarithm, and π be pi. The first level of crossover rate, This is the normalized value of the first level crossover rate; in formula (2), This is the second estimate, where e is the base of the natural logarithm, and π is pi. The second level crossover rate, This is the normalized value of the second-level crossover rate. Due to noise in the real environment, the above calculations yield... and This is a biased Doppler frequency shift estimate. In step S300, since two different sampling rates are set, the deviation caused by noise on the second estimate is different from the deviation caused by noise on the first estimate. Therefore, this embodiment uses the biased first and second estimates obtained through double sampling to transform the adverse effects of noise into beneficial information for higher-precision Doppler frequency shift estimation and signal-to-noise ratio estimation.

[0038] Step S400: Input the first sampling period, the second sampling period, the first estimated value, and the second estimated value into a preset estimation strategy to determine the estimated values ​​of the first channel parameter and the second channel parameter corresponding to the current communication link, respectively.

[0039] Specifically, the first estimate obtained in step S300 The magnitude of the deviation is compared with the true second channel parameter estimate SNR and the true first channel parameter estimate. and the first sampling period used It has a first correspondence; the second estimated value The magnitude of the deviation is compared with the true second channel parameter estimate SNR and the true first channel parameter estimate. and the second sampling period used There is a second correspondence. Therefore, in this embodiment, and It can be viewed as two equations containing two unknowns (the first channel parameter and the second channel parameter). The following formula (3) represents the first correspondence, and formula (4) is used to represent the second correspondence: (3) (4) This embodiment uses the above two formulas (3) and (4) to jointly solve the first correspondence and the second correspondence to obtain a first estimation strategy for estimating the first channel parameter and a second estimation strategy for estimating the second channel parameter, so as to realize the joint estimation of Doppler frequency shift and signal-to-noise ratio according to clear and direct calculation instructions. The preset estimation strategies in step S400 include the first estimation strategy (as shown in formula 5 below) and the second estimation strategy (as shown in formula 6 below): (5) (6) In formula (5), The first estimated value, This is the second estimated value. The first channel parameter is an estimated value; in formula (6), For the first sampling period, For the second sampling period, To adjust the parameters, Based on the first sampling period With the second sampling period Sure, The first channel parameter is an estimated value of the second channel parameter; where the category of the first channel parameter is Doppler frequency shift, and the category of the second channel parameter is signal-to-noise ratio. In this embodiment, the receiver does not need to perform complex iterations or searches, but only needs to... , and two known sampling periods , Substituting these values ​​into equations (5) and (6) above, we can directly and synchronously calculate the estimated values ​​of the first channel parameters. The algorithm estimates the SNR of the second channel parameter, thereby achieving high-precision estimation of the Doppler frequency shift and signal-to-noise ratio of the channel through a single estimator. The estimation strategy avoids real-time nonlinear solutions, and the algorithm structure is simple, stable, and easy to implement in hardware.

[0040] Optionally, the second estimation strategy can be based on the estimated value of the first channel parameter. The first estimated value With the first sampling period Determine the estimated value of the second channel parameter. (Equation 6); or, based on the estimated value of the first channel parameter. The second estimated value With the second sampling period Determine the estimated value of the second channel parameter. The second channel parameter is the signal-to-noise ratio (SNR) (Equation 7). Determine the estimated value of the second channel parameter. The method also includes the following formula (7): (7) Wherein, SNR is the estimated value of the second channel parameter. This is the second estimated value. This is an estimated value for the first channel parameter. For the second sampling period, the SNR value calculated based on equation (7) is theoretically the same as the SNR value calculated based on equation (6). If the actual estimation is different, the SNR can be calculated separately and then the average value is taken to reduce the error.

[0041] Preferably, the adjustment parameter The methods for determining it include the following formula (8): (8) In formula (8), The first estimated value, This is the second estimated value. This is an estimated value for the first channel parameter. This is the first sampling period.

[0042] In some embodiments, if the first estimate is calculated The corresponding first sampling period Greater than the second estimate The corresponding second sampling period Then the first sampling period The corresponding first level cross rate Less than the second sampling period The corresponding second level cross rate Thus, the first estimated value Less than the second estimate Therefore, the estimated value of the first channel parameter is... Alternatively, it can be calculated based on the following formula (9): (9) In formula (9), The first estimated value, This is the second estimated value. This is an estimated value for the first channel parameter; To adjust the parameters, The method for determining the value is as follows , The second sampling period is defined as follows. Based on equation (9) above, and combined with the second estimation strategy described in equation (6) or (7), the estimated value of the first channel parameter is used. First estimate With the first sampling period Determine the estimated values ​​of the second channel parameters. (Equation 6); or, based on the estimated value of the first channel parameter. Second estimate With the second sampling period Determine the estimated value of the second channel parameter. (Equation 7). The SNR value calculated based on equation (7) is theoretically the same as the SNR value calculated based on equation (6). If the actual estimation is different, the SNR can be calculated separately and then the average value is taken to reduce the error. Preferably, in step S200, parameters are first preset, setting the second sampling period to be greater than the first sampling period, and the second sampling period to be an integer multiple of the first sampling period. Parameter preset also includes presetting a reference threshold for calculating the horizontal crossover rate, typically selected as the average amplitude level of the signal envelope.

[0043] Specifically, the first sampling period is set. For faster sampling, the second sampling period Slow sampling, and the second sampling period The first sampling period The integer multiple of the value can be any integer multiple of the deviation difference that satisfies the Nyquist theorem and can produce a deviation difference sufficient to support a stable solution.

[0044] Furthermore, step S400 also includes: Step S401: Based on the estimated values ​​of the first channel parameters and the second channel parameters, query the pre-stored first error correction table to obtain the correction value of the estimated value of the first channel parameters; Step S402: Correct the estimated value of the first channel parameter according to the correction value of the estimated value of the first channel parameter to obtain the corrected estimated value of the first channel parameter. Step S403: Based on the estimated value of the second channel parameter and the corrected estimated value of the first channel parameter, query the pre-stored second error correction table to obtain the corrected value of the estimated value of the second channel parameter. Step S404: Correct the estimated value of the second channel parameter according to the correction value of the estimated value of the second channel parameter to obtain the corrected estimated value of the second channel parameter.

[0045] Specifically, to address minor errors caused by non-ideal factors such as limited sample size in reality, this embodiment introduces an intelligent correction method. By setting up a first error correction table and a second error correction table, the estimated value of the first channel parameters obtained in step S400 is corrected in real time through table lookup. The estimated SNR of the second channel parameter is corrected. First, the estimated value of the first channel parameter is corrected: based on the predefined interval of the SNR of the second channel parameter, such as less than 5dB, 5dB to 15dB, and greater than 15dB, the first polynomial coefficient set corresponding to its interval is selected from the first error correction table. Then, the correction values ​​of the estimated first channel parameters are calculated using the following formulas (10) and (11): (10) (11) In formulas (10) and (11), This is a correction value for the estimated value of the first channel parameter. The coefficient set of the first polynomial. This is an estimated value for the first channel parameter. This is the estimated value of the first channel parameter after correction. The subtraction operation is used because the Doppler estimates exhibit a positive bias.

[0046] After obtaining the corrected estimate of the first channel parameters Based on this, this embodiment further iteratively corrects the estimated value SNR of the second channel parameter to achieve a synergistic improvement in parameter estimation accuracy. Based on the corrected estimated value of the first channel parameter... The predefined interval in which it is located, such as less than 100Hz, 100Hz to 200Hz, 200Hz to 400Hz, and greater than 400Hz, is selected from the second error correction table as the corresponding set of the second polynomial coefficients. Then, based on the following formulas (12) and (13), the corrected values ​​of the estimated values ​​of the second channel parameters are obtained: (12) (13) In equations (12) and (13) above, This is a correction value for the estimated value of the second channel parameter. Here, SNR is the estimated value of the second channel parameter, representing the coefficient set of the second polynomial. This is the estimated value of the corrected second channel parameter. Based on the above formula, the final estimated value of the corrected second channel parameter is calculated. The addition operation is used here, also based on the principle that the signal-to-noise ratio estimate has a negative bias.

[0047] Further, in steps S401 and S403, the methods for generating the first error correction table and the second error correction table include: Step S4011: Based on the true values ​​of multiple known first channel parameters and the true values ​​of second channel parameters, a polynomial fitting is performed on the relationship between the average relative error of Doppler frequency shift and the true value of Doppler frequency shift in different signal-to-noise ratio intervals through simulation to obtain a first polynomial coefficient set. Each signal-to-noise ratio interval and the corresponding first polynomial coefficient set are stored as a first error correction table. Step S4012: By simulation, the relationship between the average relative error of the signal-to-noise ratio in different Doppler frequency shift intervals and the true value of the signal-to-noise ratio is fitted by a polynomial to obtain a second polynomial coefficient set. Each Doppler frequency shift interval and the corresponding second polynomial coefficient set are stored as a second error correction table.

[0048] Specifically, in equations (10) and (12) above, the first polynomial coefficient set used to correct the estimation error of the first channel parameters The second polynomial coefficient set used to correct the estimation error of the second channel parameters All parameters are predetermined through offline simulation and data fitting. The specific process includes: First, in the simulation environment, a series of known and accurate true signal-to-noise ratio (SNR) and true Doppler frequency shift values ​​are traversed within the system's operating range. Through numerous Monte Carlo simulations, the average estimation error data generated under these true parameter combinations is obtained based on the joint estimation method provided in this embodiment. Then, for each predetermined SNR estimation interval, a quadratic polynomial fitting is performed on the data with the true Doppler frequency shift as the independent variable and the corresponding average Doppler estimation relative error as the dependent variable to obtain a dedicated first polynomial coefficient set for that SNR interval. Combining the preset signal-to-noise ratio ranges with the corresponding first polynomial coefficient set Obtain the first error correction table; similarly, for each preset Doppler frequency shift estimation interval, perform a quadratic polynomial fitting on the data with the true signal-to-noise ratio as the independent variable and the corresponding average signal-to-noise ratio estimation relative error as the dependent variable to obtain the dedicated second polynomial coefficient set within that Doppler interval. Combining each preset Doppler frequency shift interval with the corresponding second polynomial coefficient set Obtain the second error correction table. Finally, store the first and second error correction tables in the device memory for use during real-time correction.

[0049] This embodiment establishes an error correction table to correct the initial Doppler frequency shift estimate and signal-to-noise ratio estimate, thereby obtaining more accurate results.

[0050] As an optional implementation, the joint estimation method provided in this embodiment can also be used to estimate two or more channel parameters, including the estimation of other channel parameters such as delay spread or multipath quantity. In specific implementation, when estimating three or more channel parameters, at least three different observation conditions (such as three sampling rates) are required. Under each condition, a set of initial, biased estimates is obtained. Finally, a set of bias equations under these three observation conditions is established, which contains three unknowns, and then the estimated values ​​are obtained by solving the equations.

[0051] Based on the same inventive concept, this invention also provides a joint channel parameter estimation system 200, as described in the following embodiments. Since the principle of the joint channel parameter estimation system 200 in solving the problem is similar to that of a joint channel parameter estimation method, the implementation of the joint channel parameter estimation system 200 can refer to the implementation of a joint channel parameter estimation method, and repeated details will not be elaborated further. As used below, the terms "unit" or "module" can refer to a combination of software and / or hardware that implements a predetermined function. Although the apparatus described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0052] Figure 2 This is a structural block diagram of a channel parameter joint estimation system 200 according to an embodiment of this application, such as... Figure 2 As shown, it includes: The periodic sampling module 201 is used to acquire the channel estimation sequence of the current communication link, sample the channel estimation sequence based on a first sampling period to obtain a first subsequence, and sample the channel estimation sequence based on a second sampling period to obtain a second subsequence, wherein the first sampling period and the second sampling period are different; The preliminary estimation module 202 is used to obtain a first estimated value corresponding to the first subsequence and a second estimated value corresponding to the second subsequence, wherein the first estimated value and the second estimated value are both deviation estimates of the first channel parameters; The joint estimation module 203 is used to input the first sampling period, the second sampling period, the first estimated value and the second estimated value into a preset estimation strategy to determine the estimated values ​​of the first channel parameter and the second channel parameter corresponding to the current communication link, respectively.

[0053] Furthermore, the periodic sampling module 201 is also configured to: the second sampling period is greater than the first sampling period, and the second sampling period is set to an integer multiple of the first sampling period.

[0054] Furthermore, the preliminary estimation module 202 is also used for: obtaining the first estimated value corresponding to the first subsequence and the second estimated value corresponding to the second subsequence, respectively, including: Obtain the first horizontal crossover rate corresponding to the first subsequence, and obtain the first estimated value based on the first horizontal crossover rate; Obtain the second horizontal cross rate corresponding to the second subsequence, and obtain the second estimated value corresponding to the second subsequence based on the second horizontal cross rate.

[0055] Furthermore, the joint estimation module 203 is also used to: the estimation strategy includes a first estimation strategy and a second estimation strategy, the first estimation strategy is used to estimate the first channel parameter, and the second estimation strategy is used to estimate the second channel parameter; The first estimation strategy obtains the estimated value of the first channel parameter based on the set adjustment parameter, the first estimated value, and the second estimated value. The first channel parameter is the Doppler frequency shift, and the adjustment parameter is determined based on the first sampling period, the first estimated value, and the second estimated value. The second estimation strategy determines the estimated value of the second channel parameter based on the estimated value of the first channel parameter, the first estimated value, and the first sampling period; the second channel parameter is the signal-to-noise ratio.

[0056] The estimation strategy includes a first estimation strategy and a second estimation strategy. The first estimation strategy is used to estimate the first channel parameter, and the second estimation strategy is used to estimate the second channel parameter. The first estimation strategy obtains the estimated value of the first channel parameter based on the set adjustment parameter, the first estimated value, and the second estimated value. The first channel parameter is the Doppler frequency shift, and the adjustment parameter is determined based on the first sampling period, the first estimated value, and the second estimated value. The second estimation strategy determines the estimated value of the second channel parameter based on the estimated value of the first channel parameter, the second estimated value, and the second sampling period; the second channel parameter is the signal-to-noise ratio.

[0057] Furthermore, the joint estimation module 203 is also used for: determining the adjustment parameter based on the first sampling period, the first estimated value, and the second estimated value, including:

[0058] in, The first estimated value, This is an estimated value for the first channel parameter. For the first sampling period, The adjustment parameter is referred to here.

[0059] Furthermore, the joint estimation module 203 is also used for: There is a first correspondence between the first estimated value and the estimated values ​​of the first channel parameter and the second channel parameter; there is a second correspondence between the second estimated value and the estimated values ​​of the first channel parameter and the second channel parameter. By jointly solving the first correspondence and the second correspondence, a first estimation strategy for estimating the first channel parameters and a second estimation strategy for estimating the second channel parameters are obtained.

[0060] Furthermore, the joint estimation module 203 is also used for: the first estimation strategy including:

[0061] in, The first estimated value, This is the second estimated value. This is an estimated value for the first channel parameter. The adjustment parameter is referred to here.

[0062] Furthermore, the joint estimation module 203 is also used to: determine the estimated value of the second channel parameter based on the estimated value of the first channel parameter, the first estimated value and the first sampling period of the second estimation strategy.

[0063] Furthermore, the joint estimation module 203 is also used to: determine the estimated value of the second channel parameter based on the estimated value of the first channel parameter, the second estimated value and the second sampling period.

[0064] Furthermore, the second sampling period is greater than the first sampling period, and the second sampling period is set to an integer multiple of the first sampling period.

[0065] Furthermore, the joint estimation module 203 is also used for: Based on the estimated values ​​of the first channel parameter and the second channel parameter, the pre-stored first error correction table is queried to obtain the corrected value of the estimated value of the first channel parameter. The estimated value of the first channel parameter is corrected based on the correction value of the estimated value of the first channel parameter to obtain the corrected estimated value of the first channel parameter.

[0066] Furthermore, the joint estimation module 203 is also used for: Based on the estimated value of the second channel parameter and the corrected estimated value of the first channel parameter, the pre-stored second error correction table is queried to obtain the corrected value of the estimated value of the second channel parameter. The estimated value of the second channel parameter is corrected based on the correction value of the estimated value of the second channel parameter to obtain the corrected estimated value of the second channel parameter.

[0067] Furthermore, the method for generating the first error correction table and the second error correction table includes: Based on the known true values ​​of the first channel parameters and the true values ​​of the second channel parameters, the relationship between the average relative error of the first channel parameters and the true value of the first channel parameters in different intervals of the second channel parameters is subjected to polynomial fitting through simulation to obtain the first polynomial coefficient set. Each interval of the second channel parameters and the corresponding first polynomial coefficient set are stored as a first error correction table. By performing polynomial fitting on the relationship between the average relative error of the second channel parameter and the true value of the second channel parameter in different first channel parameter intervals through simulation, a second polynomial coefficient set is obtained, and each first channel parameter interval and the corresponding second polynomial coefficient set are stored as a second error correction table.

[0068] In this embodiment, a computer device is also provided, such as... Figure 3As shown, it includes a memory 301, a processor 302, and a computer program stored in the memory 301 and executable on the processor 302. When the processor 302 executes the computer program, it implements any of the above-mentioned joint channel parameter estimation methods.

[0069] Specifically, the computer device can be a computer terminal, a server, or a similar computing device.

[0070] In this embodiment, a storage medium is provided, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the channel parameter joint estimation method described above in this embodiment.

[0071] In this embodiment, a computer program product is provided, which includes a computer program. When the computer program is executed by a processor, it implements the steps of the image rotation angle detection method described above in this embodiment.

[0072] In this embodiment, a computer-readable storage medium is provided, which stores a computer program that executes any of the above-described joint channel parameter estimation methods.

[0073] Specifically, computer-readable storage media, including both permanent and non-permanent, removable and non-removable media, can store information using any method or technology. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer-readable storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, and optical disc read-only memory (CD-ROM). ROM, digital multifunction optical disc (DVD) or other optical storage, magnetic cassette tape, magnetic magnetic disk storage or other magnetic storage devices or any other non-transfer medium, may be used to store information that can be accessed by a computing device. As defined herein, computer-readable storage media does not include transient media such as modulated data signals and carrier waves.

[0074] The embodiments of the present invention achieve the following technical effects: 1. This application sets up "dual sampling rate" for signal acquisition, and transforms the adverse effects of noise into beneficial information for estimation. Thus, even in extremely low signal-to-noise ratio and high-speed moving scenarios, it can still maintain high-precision estimation of Doppler frequency shift and SNR, with performance significantly better than traditional methods, and has high accuracy and robustness. 2. This application utilizes the quantitative relationship between the Doppler frequency shift estimation bias caused by noise and the signal-to-noise ratio and dual sampling rate to construct an estimation method, avoiding real-time nonlinear solutions. The algorithm structure is simple and stable, easy to implement in hardware, and suitable for mobile devices that are sensitive to power consumption and computing resources. 3. This application simultaneously achieves high-precision estimation of the channel's Doppler frequency shift and signal-to-noise ratio using a single estimator, simplifying receiver design and reducing system complexity and cost; 4. This application does not rely on series approximation, and its effective Doppler estimation range is larger, which can adapt to various mobile scenarios from low speed to high speed; 5. This application improves the accuracy of channel parameter estimation by introducing an error correction table to further correct the estimated values.

[0075] Finally, it should be noted that 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 or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A joint estimation method for channel parameters, characterized in that, include: Obtain the channel estimation sequence for the current communication link; A first subsequence is obtained by sampling the channel estimation sequence based on a first sampling period, and a second subsequence is obtained by sampling the channel estimation sequence based on a second sampling period, wherein the first sampling period and the second sampling period are different; A first estimated value corresponding to the first subsequence and a second estimated value corresponding to the second subsequence are obtained respectively, wherein the first estimated value and the second estimated value are both deviation estimates of the first channel parameters; The first sampling period, the second sampling period, the first estimated value, and the second estimated value are input into a preset estimation strategy to determine the estimated values ​​of the first channel parameter and the second channel parameter corresponding to the current communication link, respectively.

2. The joint channel parameter estimation method according to claim 1, characterized in that, The step of obtaining the first estimated value corresponding to the first subsequence and the second estimated value corresponding to the second subsequence includes: Obtain the first horizontal crossover rate corresponding to the first subsequence, and obtain the first estimated value based on the first horizontal crossover rate; Obtain the second horizontal cross rate corresponding to the second subsequence, and obtain the second estimated value based on the second horizontal cross rate.

3. The joint channel parameter estimation method according to claim 1, characterized in that, The estimation strategy includes a first estimation strategy and a second estimation strategy. The first estimation strategy is used to estimate the first channel parameter, and the second estimation strategy is used to estimate the second channel parameter. The first estimation strategy obtains the estimated value of the first channel parameter based on the set adjustment parameter, the first estimated value, and the second estimated value. The first channel parameter is the Doppler frequency shift, and the adjustment parameter is determined based on the first sampling period, the first estimated value, and the second estimated value. The second estimation strategy determines the estimated value of the second channel parameter based on the estimated value of the first channel parameter, the first estimated value, and the first sampling period. The second channel parameter is the signal-to-noise ratio.

4. The joint channel parameter estimation method according to claim 1, characterized in that, The estimation strategy includes a first estimation strategy and a second estimation strategy. The first estimation strategy is used to estimate the first channel parameter, and the second estimation strategy is used to estimate the second channel parameter. The first estimation strategy obtains the estimated value of the first channel parameter based on the set adjustment parameter, the first estimated value, and the second estimated value. The first channel parameter is the Doppler frequency shift, and the adjustment parameter is determined based on the first sampling period, the first estimated value, and the second estimated value. The second estimation strategy determines the estimated value of the second channel parameter based on the estimated value of the first channel parameter, the second estimated value, and the second sampling period; the second channel parameter is the signal-to-noise ratio.

5. A joint channel parameter estimation method according to claim 3 or 4, characterized in that, The adjustment parameters are determined based on the first sampling period, the first estimated value, and the second estimated value.

6. A joint channel parameter estimation method according to claim 3 or 4, characterized in that, The adjustment parameter is determined based on the second sampling period, the first estimated value, and the second estimated value.

7. The joint channel parameter estimation method according to claim 1, characterized in that, There is a first correspondence between the first estimated value and the estimated values ​​of the first channel parameter and the second channel parameter; there is a second correspondence between the second estimated value and the estimated values ​​of the first channel parameter and the second channel parameter. By jointly solving the first correspondence and the second correspondence, a first estimation strategy for estimating the first channel parameters and a second estimation strategy for estimating the second channel parameters are obtained.

8. The joint channel parameter estimation method according to claim 7, characterized in that, The first estimation strategy includes: in, The first estimated value, This is the second estimated value. This is an estimated value for the first channel parameter. To adjust the parameters.

9. The joint channel parameter estimation method according to claim 7, characterized in that, The second estimation strategy determines the estimated value of the second channel parameter based on the estimated value of the first channel parameter, the first estimated value, and the first sampling period.

10. The joint channel parameter estimation method according to claim 7, characterized in that, The second estimation strategy determines the estimated value of the second channel parameter based on the estimated value of the first channel parameter, the second estimated value, and the second sampling period.

11. The joint channel parameter estimation method according to claim 1, characterized in that, The second sampling period is greater than the first sampling period, and the second sampling period is set to an integer multiple of the first sampling period.

12. The joint channel parameter estimation method according to claim 1, characterized in that, The method further includes: Based on the estimated values ​​of the first channel parameter and the second channel parameter, the pre-stored first error correction table is queried to obtain the corrected value of the estimated value of the first channel parameter. The estimated value of the first channel parameter is corrected based on the correction value of the estimated value of the first channel parameter to obtain the corrected estimated value of the first channel parameter.

13. The joint channel parameter estimation method according to claim 12, characterized in that, The method further includes: Based on the estimated value of the second channel parameter and the corrected estimated value of the first channel parameter, the pre-stored second error correction table is queried to obtain the corrected value of the estimated value of the second channel parameter. The estimated value of the second channel parameter is corrected based on the correction value of the estimated value of the second channel parameter to obtain the corrected estimated value of the second channel parameter.

14. The joint channel parameter estimation method according to claim 13, characterized in that, The methods for generating the first error correction table and the second error correction table include: Based on the known true values ​​of the first channel parameters and the true values ​​of the second channel parameters, the relationship between the average relative error of the first channel parameters and the true value of the first channel parameters in different intervals of the second channel parameters is subjected to polynomial fitting through simulation to obtain the first polynomial coefficient set. Each interval of the second channel parameters and the corresponding first polynomial coefficient set are stored as a first error correction table. By performing polynomial fitting on the relationship between the average relative error of the second channel parameter and the true value of the second channel parameter in different first channel parameter intervals through simulation, a second polynomial coefficient set is obtained, and each first channel parameter interval and the corresponding second polynomial coefficient set are stored as a second error correction table.

15. A joint channel parameter estimation system, characterized in that, include: The periodic sampling module is used to acquire the channel estimation sequence of the current communication link, sample the channel estimation sequence based on a first sampling period to obtain a first subsequence, and sample the channel estimation sequence based on a second sampling period to obtain a second subsequence, wherein the first sampling period and the second sampling period are different; The preliminary estimation module is used to obtain the first estimated value corresponding to the first subsequence and the second estimated value corresponding to the second subsequence, respectively. The first estimated value and the second estimated value are both deviation estimates of the first channel parameters. The joint estimation module is used to input the first sampling period, the second sampling period, the first estimated value, and the second estimated value into a preset estimation strategy to determine the estimated values ​​of the first channel parameter and the second channel parameter corresponding to the current communication link, respectively.

16. An electronic device, characterized in that, include: processor; Memory used to store the processor's executable instructions; The processor is used for the instructions to implement a joint channel parameter estimation method as described in any one of claims 1 to 14.

17. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the steps of a joint channel parameter estimation method as described in any one of claims 1 to 14.

18. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the steps of a joint channel parameter estimation method as described in any one of claims 1 to 14.

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