A filtering method, device, electronic equipment and storage medium

Abstract

The present application provides a filtering method, device, electronic device and storage medium, wherein the filtering method comprises: obtaining a channel parameter estimation value of the current channel according to a pilot signal of a current wireless resource, filtering the channel parameter estimation value using a currently configured filter, and obtaining the filtered channel parameter estimation value; reconfiguring the filter coefficient and filtering times of the filter according to the filtered channel parameter estimation value, and the filter enters a stable state after completing the filtering times according to the reconfigured filter coefficient. The above scheme uses a filter to filter the channel parameter estimation value, and reconfigures the filter coefficient and filtering times of the filter according to the filtered channel parameter estimation value, so as to realize adaptive adjustment of the filter parameters, and uses the filter after adaptively adjusting the filter parameters to filter the channel parameter estimation value, which is conducive to improving the accuracy of channel parameter estimation.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a filtering method, device, electronic device and storage medium. Background Art

[0002] In the related art, the filtering-based channel parameter estimation method usually starts filtering the channel parameter estimation value obtained according to the pilot signal after the terminal and the base station establish a stable link, until the terminal and the base station lose synchronization.

[0003] In the above filtering process, a fixed filtering coefficient is always used to filter the channel parameter estimation value. This solution has poor adaptability to changes in terminal scenarios, resulting in low accuracy of channel parameter estimation. Summary of the invention

[0004] The purpose of the embodiments of the present application is to provide a filtering method, device, electronic device and storage medium to improve the accuracy of channel parameter estimation.

[0005] In the first aspect, an embodiment of the present application provides a filtering method, which includes: obtaining a channel parameter estimation value of a current channel according to a pilot signal of a current wireless resource, filtering the channel parameter estimation value using a currently configured filter, and obtaining the filtered channel parameter estimation value; reconfiguring the filtering coefficient and filtering times of the filter according to the filtered channel parameter estimation value, and the filter entering a stable state after completing filtering the filtering times according to the reconfigured filtering coefficient.

[0006] In the implementation process of the above scheme, a filter is used to filter the channel parameter estimation value, and the filter coefficient and the number of filtering times of the filter are reconfigured according to the filtered channel parameter estimation value to realize adaptive adjustment of the filter parameters. The channel parameter estimation value is filtered by the filter after adaptively adjusting the filter parameters, which is beneficial to improving the accuracy of channel parameter estimation.

[0007] In an implementation of the first aspect, the method further includes: after the filter enters a stable state, at every preset update interval, executing the step of reconfiguring the filter coefficients and filtering times of the filter according to the filtered channel parameter estimation values.

[0008] In the implementation process of the above scheme, after the filter reaches a stable state, the filter coefficient and filtering times of the filter are periodically reconfigured to achieve adaptive adjustment of the filter parameters. The filter after adaptively adjusting the filter parameters is used to filter the channel parameter estimation value, which is beneficial to improving the accuracy of channel parameter estimation.

[0009] In an implementation of the first aspect, reconfiguring the filter coefficient and the number of filtering times of the filter according to the filtered channel parameter estimation value includes: determining the signal-to-noise ratio and Doppler spread of the current channel according to the filtered channel parameter estimation value; determining the compensation parameter of the coherence time according to the signal-to-noise ratio; determining the coherence time according to the Doppler spread and the compensation parameter; and reconfiguring the filter coefficient and the number of filtering times of the filter according to the coherence time, the period of the current wireless resource, and a preset minimum number of filtering times.

[0010] In the process of implementing the above scheme, the compensation parameters are taken into account when determining the coherence time, so that the determined coherence time has higher accuracy, so that the above filtering method can use the high-accuracy coherence time to reconfigure the filter coefficients and filtering times of the filter, thereby improving the accuracy of the above filtering method when reconfiguring the filter coefficients and filtering times of the filter, and using the filter after the reconfigured filter parameters to filter the channel parameter estimation value, which is beneficial to improving the accuracy of channel parameter estimation.

[0011] In an implementation of the first aspect, determining the compensation parameter of the coherence time according to the signal-to-noise ratio includes: determining a target preset signal-to-noise ratio corresponding to the signal-to-noise ratio in a preset signal-to-noise ratio list, the preset signal-to-noise ratio list including multiple preset signal-to-noise ratios; determining a target preset compensation parameter corresponding to the target preset signal-to-noise ratio in a preset compensation parameter list, the preset compensation parameter list including multiple preset compensation parameters, and the preset compensation parameters in the preset compensation parameter list correspond one-to-one to the preset signal-to-noise ratios in the preset signal-to-noise ratio list;

[0012] The determining of the coherence time according to the Doppler spread and the compensation parameter includes: calculating the intermediate coherence time of the current channel according to the target preset compensation parameter and the Doppler spread; determining the target preset coherence time corresponding to the intermediate coherence time in a preset coherence time list, wherein the preset coherence time list includes multiple preset coherence times.

[0013] In the implementation process of the above scheme, the signal-to-noise ratio, compensation parameter and coherence time are divided into gears in advance and stored in the form of a preset signal-to-noise ratio list, a preset compensation parameter list and a preset coherence time list. When determining the coherence time of the current channel, the coherence time of the current channel can be quickly obtained by looking up a table, which is beneficial to improving the configuration efficiency of the above filtering method for reconfiguring the filter coefficients and filtering times of the filter.

[0014] In an implementation method of the first aspect, the reconfiguration of the filter coefficient and the number of filtering times of the filter according to the coherence time, the period of the current wireless resource and the preset minimum number of filtering times includes: taking the period of the current wireless resource, the coherence time of the current channel and the preset minimum number of filtering times as inputs of a preset function, obtaining new filter coefficients and new filtering times output by the preset function; and reconfiguring the filter using the new filter coefficients and the new number of filtering times.

[0015] In the implementation process of the above scheme, the period of the current wireless resource, the coherence time of the channel and the preset minimum number of filtering times are used as the input of the preset function, and the new filtering coefficient and the new number of filtering times output by the preset function are directly obtained. The preset function takes into account the preset minimum number of filtering times. The new filtering coefficient and the new number of filtering times calculated by the preset function can enable the filter to enter a stable state as soon as possible. On the one hand, it is beneficial to improve the configuration efficiency of the filter coefficient and the number of filtering times of the filter by the above filtering method. On the other hand, using the filter with the reconfigured filter parameters to filter the channel parameter estimation value is beneficial to improving the accuracy of the channel parameter estimation.

[0016] In an implementation of the first aspect, the method also includes: periodically monitoring preset special events, and if the occurrence of the special event is monitored, reconfiguring the filtering coefficient and filtering times of the filter according to the filtering strategy corresponding to the special event; wherein the filtering strategy also includes the filtering object of the filter.

[0017] In the process of implementing the above scheme, by monitoring the preset special events, when the special events occur, the filter coefficients and filtering times of the filter are reconfigured according to the filtering strategy corresponding to the special events, so that the above filtering method can have the ability to cope with special events, thereby making the above filtering method applicable to more application scenarios, which is conducive to improving the adaptability of the above filtering method.

[0018] In an implementation manner of the first aspect, the filtering strategy further includes: whether to reset the filter state when entering the special event, and / or whether to reset the filter state after completing the filtering times.

[0019] The filtering strategy in the above scheme may include at least one of the filtering object, the special event filtering coefficient, the special event filtering times, whether to reset the filter state when entering the special event, and whether to reset the filter state after completing the filtering times. On the one hand, the above filtering method has a high degree of customization, so that the above filtering method can be applicable to more application scenarios, thereby improving the adaptability of the above filtering method. On the other hand, the filtering strategy corresponding to the special event can be customized, which is conducive to improving the special event handling capability of the above filtering method.

[0020] In a second aspect, an embodiment of the present application provides a filtering device, the device comprising:

[0021] A channel parameter estimation value acquisition module, used to obtain a channel parameter estimation value of a current channel according to a pilot signal of a current wireless resource, filter the channel parameter estimation value using a currently configured filter, and obtain the filtered channel parameter estimation value;

[0022] The filter configuration module is used to reconfigure the filter coefficient and the number of filtering times of the filter according to the estimated value of the channel parameter after filtering, and the filter enters a stable state after completing the filtering times according to the reconfigured filter coefficient.

[0023] In a third aspect, an embodiment of the present application provides an electronic device, comprising: a processor, a memory, and a communication bus, wherein the processor and the memory communicate with each other through the communication bus; the memory stores computer program instructions that can be executed by the processor, and when the computer program instructions are read and run by the processor, the method provided by the first aspect or any possible implementation of the first aspect is executed.

[0024] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which computer program instructions are stored. When the computer program instructions are read and executed by a processor, the method provided by the first aspect or any possible implementation of the first aspect is executed.

[0025] Other features and advantages of the present application will be described in the following description, and partly become apparent from the description, or be understood by practicing the embodiments of the present application. The purpose and other advantages of the present application can be realized and obtained by the structures specifically pointed out in the written description, claims, and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments of the present application will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0027] Figure 1 A flowchart of a filtering method provided in an embodiment of the present application;

[0028] Figure 2 A schematic diagram of the structure of a channel parameter estimation device provided in an embodiment of the present application;

[0029] Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0030] The following will describe the technical solutions in the embodiments of the present application in conjunction with the accompanying drawings in the embodiments of the present application. The following embodiments are only used to more clearly illustrate the technical solutions of the present application, and are therefore only used as examples, and cannot be used to limit the scope of protection of the present application.

[0031] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by technicians in the technical field to which this application belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" in the specification and claims of this application and the above-mentioned figure descriptions and any variations thereof are intended to cover non-exclusive inclusions.

[0032] In the description of the embodiments of the present application, the technical terms "first", "second", etc. are only used to distinguish different objects, and cannot be understood as indicating or implying relative importance or implicitly indicating the number, specific order or primary and secondary relationship of the indicated technical features. In the description of the embodiments of the present application, the meaning of "multiple" is more than two, unless otherwise clearly and specifically defined.

[0033] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0034] When the related technology performs channel parameter estimation, due to the small number of receiving antennas of the terminal, there are fewer available pilots, so in a single measurement, the sample size of the channel parameter estimation is small, which leads to a large variance or more noise in the estimated parameters, and it is impossible to converge to the expected value quickly. In order to make up for this defect, the related technology can use filters such as IIR (Infinite Impulse Response) filters to filter the channel parameter estimation values ​​obtained according to the pilot signal, thereby smoothing the estimation results and reducing the estimation variance and noise.

[0035] The channel parameter estimation method in the related art generally starts filtering the parameter estimation value after the terminal establishes a stable link with the base station, until the terminal loses synchronization with the base station, and the whole process uses one or a group of fixed filter coefficients to filter the parameter estimation value. In this scheme, if the terminal has a situation such as terminal movement that changes the terminal usage scenario and causes the channel environment to change, the fixed filter coefficient cannot adapt to the time-varying or even sudden channel environment. At this time, if the fixed filter coefficient is continued to be used to filter the parameter estimation value, the channel parameter estimation accuracy will be low.

[0036] Based on this, an embodiment of the present application provides a filtering method, which uses a filter to filter the channel parameter estimation value, and reconfigures the filter coefficient and the number of filtering times of the filter according to the filtered channel parameter estimation value, thereby realizing adaptive adjustment of the filter parameters. The channel parameter estimation value is filtered by the filter after adaptively adjusting the filter parameters, which is beneficial to improving the accuracy of channel parameter estimation.

[0037] The following is a detailed description of the above filtering methods. Figure 1 , the present application embodiment provides a filtering method, the method comprising:

[0038] Step S110: obtaining a channel parameter estimation value of the current channel according to the pilot signal of the current wireless resource, filtering the channel parameter estimation value using the currently configured filter, and obtaining a filtered channel parameter estimation value;

[0039] Step S120: reconfigure the filter coefficient and filtering times of the filter according to the estimated value of the filtered channel parameter, and the filter enters a stable state after completing filtering times according to the reconfigured filtering coefficient.

[0040] It can be understood that the wireless resources in the above step S110 refer to the wireless signals carried in the above channels.

[0041] In addition, it can be understood that the above filtering method can periodically reconfigure the filter coefficient and the number of filtering times of the filter after reconfiguring the filter coefficient and the number of filtering times of the filter. The specific scheme can be:

[0042] As an optional implementation of the above filtering method, the above filtering method further includes: after the filter enters a stable state, a preset update interval Q is set every interval. max , executing the step of reconfiguring the filter coefficients and filtering times of the filter according to the filtered channel parameter estimation value.

[0043] After the filter reaches a stable state, the above scheme periodically reconfigures the filter coefficient and filtering times of the filter, thereby realizing adaptive adjustment of the filter parameters. The filter after adaptively adjusting the filter parameters is used to filter the channel parameter estimation value, which is beneficial to improving the accuracy of channel parameter estimation.

[0044] The scheme of reconfiguring the filter coefficient and filtering times of the filter according to the estimated value of the filtered channel parameter in step S120 is described in detail below:

[0045] As an optional implementation of the above-mentioned filtering method, the above-mentioned step S120 includes: determining the signal-to-noise ratio and Doppler spread of the current channel according to the filtered channel parameter estimation value; determining the compensation parameter of the coherence time according to the signal-to-noise ratio; determining the coherence time according to the Doppler spread and the compensation parameter; reconfiguring the filter coefficient and the number of filtering times of the filter according to the coherence time, the period of the current wireless resource and the preset minimum number of filtering times.

[0046] It can be understood that the period of the above-mentioned wireless resources can be directly determined by the period pre-configured for the wireless signal, or the electronic device that executes the above-mentioned filtering method can obtain the period of the wireless resources by executing the wireless resource period calculation step, wherein the wireless resource period calculation step can be: calculating the wireless resource period by the propagation time and arrival time of the wireless signal, or: calculating the wireless resource period by the arrival time difference of the wireless signal, or: calculating the wireless resource period by the sending and arrival time of the wireless signal.

[0047] It is understandable that the above coherence time refers to the maximum time difference range within which the channel remains constant. The longer the coherence time, the smaller the change in the channel state and the higher the quality of signal transmission. The method for obtaining the channel coherence time in the embodiment of the present application will be described in detail in the following description.

[0048] In addition, it can be understood that the above-mentioned preset minimum number of filtering times is used to characterize the minimum number of filtering times that makes the filter reach a stable state under the performance conditions of the current terminal. The preset minimum number of filtering times can be customized by the user, and the user can determine the preset minimum number of filtering times by testing the performance of the terminal. It can be understood that the stronger the performance of the terminal, the stronger its data processing capability, and the faster it can make the filter reach a stable state, so the smaller the minimum number of filtering times required, and vice versa, if the performance of the terminal is poor, the larger the minimum number of filtering times required. Accordingly, the above-mentioned number of filtering times reconfigured according to the channel parameter estimation value is also the number of filtering times that makes the filter reach a stable state under the current terminal performance conditions. The filter enters a stable state after completing the filtering of the filtering times according to the reconfigured filtering coefficients.

[0049] It is understandable that there may be a multipath effect when calculating the channel coherence time, thereby affecting the calculation accuracy of the channel coherence time, so the above scheme can be compensated by compensation parameters. The setting of compensation parameters can make the transmission characteristics of the channel closer to the ideal single-path transmission characteristics, thereby improving the calculation accuracy of the channel coherence time. In addition, the setting method of the compensation parameters can refer to the relevant technology, and the embodiments of this application will not be repeated.

[0050] The above scheme takes into account the compensation parameters when determining the coherence time, so that the determined coherence time has higher accuracy, so that the above filtering method can use the high-accuracy coherence time to reconfigure the filter coefficients and filtering times of the filter, thereby improving the accuracy of the above filtering method when reconfiguring the filter coefficients and filtering times of the filter, and using the filter after the reconfigured filter parameters to filter the channel parameter estimation value is beneficial to improving the accuracy of channel parameter estimation.

[0051] The following is an introduction to the specific scheme of determining the channel coherence time based on the signal-to-noise ratio, Doppler spread and compensation parameters of the current channel:

[0052] As an optional implementation manner of the above-mentioned filtering method, the above-mentioned determination of the compensation parameter of the coherence time according to the signal-to-noise ratio includes: determining a target preset signal-to-noise ratio corresponding to the signal-to-noise ratio in a preset signal-to-noise ratio list, the preset signal-to-noise ratio list including multiple preset signal-to-noise ratios; determining a target preset compensation parameter corresponding to the target preset signal-to-noise ratio in a preset compensation parameter list, the preset compensation parameter list including multiple preset compensation parameters, and the preset compensation parameters in the preset compensation parameter list correspond one-to-one to the preset signal-to-noise ratio in the preset signal-to-noise ratio list.

[0053] The above-mentioned determination of the coherence time according to the Doppler spread and the compensation parameter includes: calculating the intermediate coherence time of the current channel according to the target preset compensation parameter and the Doppler spread; determining the target preset coherence time corresponding to the intermediate coherence time in the preset coherence time list, wherein the preset coherence time list includes multiple preset coherence times. This implementation example:

[0054] The above preset signal-to-noise ratio list stores signal-to-noise ratio values ​​at different gears, and the preset compensation parameter list stores compensation parameter values ​​at different gears. The compensation parameter gears in the preset compensation parameter list correspond to the signal-to-noise ratio gears in the preset signal-to-noise ratio list one by one. The gear division method is, for example:

[0055] The preset signal-to-noise ratio list stores L signal-to-noise ratio gears, and the preset compensation parameter list also stores corresponding L compensation parameter gears. The division of each gear is as follows:

[0056] 0≤SNR0≤SNR1≤…≤SNR l ≤…≤SNR L-1

[0057] β0≥β1≥…≥β l ≥…≥β L-1 ≥0

[0058] Wherein, SNR represents signal-to-noise ratio, and β represents compensation parameter.

[0059] The scheme for determining the target preset signal-to-noise ratio in the preset signal-to-noise ratio list and determining the target preset compensation parameter corresponding to the target signal-to-noise ratio in the preset compensation parameter list may be:

[0060] If the signal-to-noise ratio SNR meets the following conditions, the target preset signal-to-noise ratio is determined to be SNR l :

[0061] SNR l ≤SNR <SNR l+1

[0062] The target preset signal-to-noise ratio is SNR l (that is, the target preset signal-to-noise ratio is at level l), then determine the target preset compensation parameter β at the same level l. l ;

[0063] In addition, the preset coherence time list also stores coherence time values ​​under different gears, and the gears divided are, for example:

[0064] 0≤T0≤T1≤…≤T k ≤…

[0065] Preset compensation parameter β according to the target l and Doppler spread fD , the solution for calculating the intermediate coherence time of the current channel can be:

[0066]

[0067] The scheme for determining the target preset coherence time in the preset coherence time list according to the intermediate coherence time may be:

[0068] Select k ≥ 0 so that:

[0069] T k ≤T <T k+1

[0070] The above T k This is the target preset coherence time.

[0071] In order to further understand the above gear division method, the embodiment of the present application provides a gear division scheme for signal-to-noise ratio, compensation parameter and coherence time in a certain application scenario:

[0072] The signal-to-noise ratio is divided into three levels as follows:

[0073] 0≤SNR0=-15dB≤SNR1=1dB≤SNR2=25dB

[0074] The compensation parameters are divided into three levels as follows:

[0075] β0=1185.9≥β1=293.1≥β2=20.5≥0

[0076] The coherence time can be divided as follows:

[0077] 0≤T0=0≤T1=640ms

[0078] The above scheme divides the signal-to-noise ratio, compensation parameter and coherence time into gears in advance, and stores them in the form of a preset signal-to-noise ratio list, a preset compensation parameter list and a preset coherence time list. When determining the coherence time of the current channel, the coherence time of the current channel can be quickly obtained by looking up the table, which is beneficial to improving the configuration efficiency of the above filtering method for reconfiguring the filter coefficients and filtering times of the filter.

[0079] It can be understood that the above scheme of determining the channel coherence time by compensating the parameters is only one implementation method of obtaining the coherence time, and the above coherence time can also be obtained by the following implementation methods:

[0080] The Doppler spread of the pilot signal is directly used to determine the coherence time of the channel.

[0081] It can be understood that in some methods for calculating the coherence time of a channel, the coherence time and the Doppler spread are reciprocals of each other. Therefore, in this embodiment, the coherence time of the channel can be determined by directly calculating the reciprocal of the Doppler spread.

[0082] It should be noted that the Doppler spread mentioned above can be obtained by estimating the channel parameters when estimating the channel parameters of the pilot signal.

[0083] In this implementation, the channel coherence time is directly calculated by the Doppler spread of the pilot signal, which is conducive to improving the configuration efficiency of the above filtering method when configuring the filter coefficient and the number of filtering times of the filter.

[0084] The following is an introduction to the above scheme of reconfiguring the filter coefficient and the number of filtering times of the filter according to the coherence time, the cycle of the current wireless resource and the preset minimum number of filtering times:

[0085] It can be understood that the method for reconfiguring the filter coefficient and the number of filtering times of the filter according to the coherence time, the cycle of the current wireless resource and the preset minimum number of filtering times in the above scheme can be:

[0086] (1) adopting a machine learning model, using the machine learning model to learn the mapping relationship between the period of the wireless resource, the coherence time of the channel, and the preset minimum filtering times and the filter coefficient and the filtering times of the filter, taking the period of the wireless resource, the coherence time of the channel, and the preset minimum filtering times as inputs of the machine learning model, and obtaining a new filtering coefficient and a new filtering times output by the machine learning model;

[0087] (2) A mapping table of the relationship between the wireless resource period, the channel coherence time, the preset minimum filtering times, the filter coefficient of the filter, and the filtering times is pre-set. After obtaining the wireless resource period, the channel coherence time, and the preset minimum filtering times, the corresponding new filtering coefficient and filtering times are directly determined by looking up the table.

[0088] Of course, in addition to the above two solutions, the embodiment of the present application also provides another solution, specifically:

[0089] As an optional implementation manner of the above-mentioned filtering method, the above-mentioned reconfiguration of the filter coefficient and the number of filtering times of the filter according to the coherence time, the period of the current wireless resource and the preset minimum number of filtering times includes: taking the period of the current wireless resource, the coherence time of the current channel and the preset minimum number of filtering times as inputs of a preset function, obtaining new filter coefficients and new number of filtering times output by the preset function; and reconfiguring the filter using the new filter coefficients and the new number of filtering times.

[0090] The expression of the above preset function is:

[0091] (α,N)=g(T k ,T cyc ,N min )

[0092] Among them, T k is the coherence time of the channel; T cyc is the period of the current wireless resource; N min is the preset minimum filtering order; α is the filtering coefficient, which can be a coefficient or a group of coefficients; N is the steady-state filtering order; g(·) is the preset function.

[0093] It can be understood that the purpose of the above preset function g(·) is to try to obtain the channel coherence time T k The filter is configured to complete as many filterings as possible within a certain period of time, so that the filter enters a stable state after completing N filterings. It can be understood that the stable state of the filter means that the output of the filter to the input signal does not change with time, or the degree of change of the output of the filter to the input signal with time is within a preset threshold range.

[0094] It is understandable that the expression of the preset function g(·) may be different for different filters; the expression of the preset function g(·) may also be different for different stable states in the same filter (for example, in some scenarios, the filter is required to have a more stringent stable state, that is, the filter's output to the input signal is required not to change with time, while in some scenarios, the filter is required to have a more relaxed stable state, that is, the filter's output to the input signal is required to change with time within a preset threshold range), the expression of the preset function g(·) may also be different.

[0095] If the filter adopts a first-order IIR filter, its filter coefficient α is a scalar. In this case, g(·) can be expressed in the following three ways:

[0096]

[0097]

[0098]

[0099] The above function g1(·) can be applied to the filtering method when the channel scenario remains unchanged, for example, the terminal is in a stationary state and the minimum filtering number cannot be configured; the application scenario of function g2(·) is similar to that of function g1(·), but the minimum filtering number is allowed to be configured in the application scenario of function g2(·); the application scenario of function g3(·) takes into account the minimum filtering number, measurement signal period and coherence time, and can be applied to more scenarios.

[0100] The above N minThe value of can be 4; for different wireless resources, T cyc The value of can be 20ms, 40ms, 80ms or other possible configurations. It can be understood that in a communication system such as an NR system, T cyc The value of can be configured by high-level signaling of the base station, so it is not controlled by the electronic device that executes the above filtering method.

[0101] It can be understood that the three implementation methods of the preset function g(·) shown in the above content are just three examples, which are not limitations of the preset function g(·).

[0102] The above scheme uses the current wireless resource period, the coherence time of the channel and the preset minimum number of filtering times as the input of the preset function, and directly obtains the new filtering coefficient and the new number of filtering times output by the preset function. The preset function takes into account the preset minimum number of filtering times. The new filtering coefficient and the new number of filtering times calculated by the preset function can enable the filter to enter a stable state as soon as possible. On the one hand, it is conducive to improving the configuration efficiency of the filter coefficient and the number of filtering times of the filter by the above filtering method. On the other hand, using the filter with the reconfigured filter parameters to filter the channel parameter estimation value is conducive to improving the accuracy of channel parameter estimation.

[0103] It is understood that, in addition to the preset update interval Q max In addition to reconfiguring the filter regularly, the filter coefficient and filtering times can also be reconfigured when a preset special event is detected. The scheme can be:

[0104] As an optional implementation of the above-mentioned filtering method, the above-mentioned filtering method also includes: periodically monitoring preset special events, and if a special event is monitored to occur, reconfiguring the filtering coefficient and filtering times of the filter according to the filtering strategy corresponding to the special event; wherein the filtering strategy also includes the filtering object of the filter.

[0105] It is understandable that the above-mentioned special event may be a user-defined event or a default special event in the terminal.

[0106] It is understandable that the above-mentioned preset special events may be:

[0107] P={E0,E1,E2,…,}

[0108] Each special event i The filtering strategy may include the following:

[0109] (1) Filter object A i, used to indicate the parameters that need to be filtered by the filter after the special event occurs, for example: for the special event E0, A0 only contains the delay spread estimate, while for the special event E1, A1 contains the delay spread and signal-to-noise ratio estimate;

[0110] (2) Special event filter coefficient α i , used to indicate the filter coefficients used when the filter is reconfigured after a special event occurs;

[0111] (3) Special event filtering times N i , used to indicate the number of filtering times used when the filter is reconfigured after a special event occurs;

[0112] It is understandable that the electronic device executing the above filtering method can monitor whether a preset special event occurs by monitoring interruption.

[0113] In addition, the terminal may use a table storage method to store special events and the filtering strategy corresponding to each special event. When a special event is monitored, the terminal may obtain the filtering strategy corresponding to the special event by looking up the table.

[0114] The above scheme monitors preset special events, and when a special event occurs, reconfigures the filter coefficient and filtering times of the filter according to the filtering strategy corresponding to the special event, so that the above filtering method can have the ability to cope with special events, thereby making the above filtering method applicable to more application scenarios, which is conducive to improving the adaptability of the above filtering method.

[0115] As an optional implementation of the above filtering method, the above filtering strategy also includes: whether to reset the filter state when entering a special event, and / or whether to reset the filter state after completing filtering for a certain number of times.

[0116] That is, the above filtering strategy may also include the following:

[0117] (4) Whether to reset the filter state when entering this special event;

[0118] (5) Whether to reset the filter state after completing the filtering times.

[0119] It can be understood that the above filter state refers to the relationship between the input signal and the output signal of the filter. For an IIR filter, its filter state is composed of the filter coefficient and the state at the previous moment.

[0120] It is understandable that if the filtering strategy for a particular event does not fully specify the above (1) to (5), the unspecified parameters may adopt the preset default parameters.

[0121] It is understandable that when a special event E occurs i After that, the terminal will estimate the parameter set A i All parameters in the E i The filter is filtered according to the configuration of the filtering strategy, and the filter state is reset at the specified reset time; after completing the given number of filtering times N i After filtering, the special event processing steps are completed.

[0122] In the implementation process of the above scheme, the filtering strategy may include at least one of the filtering object, the special event filtering coefficient, the special event filtering times, whether to reset the filter state when entering the special event, and whether to reset the filter state after completing the filtering times. On the one hand, the above filtering method has a high degree of customization, so that the above filtering method can be applied to more application scenarios, improving the adaptability of the above filtering method. On the other hand, the filtering strategy corresponding to the special event can be customized, which is conducive to improving the special event handling capability of the above filtering method.

[0123] It is understandable that the operation mode of the terminal can be set to a normal operation mode or a special event mode. When the terminal is operating in the normal operation mode, the step of reconfiguring the filter coefficient and the number of filtering times of the filter according to the filtered channel parameter estimation value is performed at a preset update interval. When a special event is detected, the terminal switches to the special event mode, and after dealing with the special event, the mode is switched back to the normal operation mode.

[0124] The normal operation mode and special event mode are described in detail below:

[0125] 1. Normal operation mode

[0126] In normal operating mode, the channel parameter estimation value is filtered using the currently configured filter to obtain the filtered channel parameter estimation value; the filter coefficient and filtering times of the filter are reconfigured according to the filtered channel parameter estimation value, and the filter enters a stable state after completing the filtering times according to the reconfigured filtering coefficient.

[0127] After the filter enters a stable state, the step of reconfiguring the filter coefficient and the number of filtering times of the filter according to the estimated values ​​of the filtered channel parameters is performed at every preset update interval.

[0128] It can be understood that in normal operation mode, the filter coefficient update step can be divided into three stages:

[0129] Phase 1: scene selection phase, in which the current scene of the channel (i.e., the corresponding gear position) can be determined by the signal-to-noise ratio and Doppler spread of the channel, and the new filter coefficient and filtering times of the filter can be determined according to the preset function g(·).

[0130] Phase 2: Filter transition phase, in which the channel parameter estimation value is filtered according to the new filter coefficients obtained in phase 1, and the state of the current filter is not reset until the filtering of the new filtering times is completed;

[0131] Stage 3: Filter stabilization stage. In this stage, the filtering of the new filtering times has been completed, and it can be considered that the filter has entered a stable state.

[0132] It is understandable that after the filter enters a stable state (ie, enters stage three), it will return from stage three to stage one at every preset update interval, thereby achieving adaptive configuration of the filter coefficient and filtering times of the filter.

[0133] 2. Special Event Mode

[0134] After entering the special event mode, determine the special event E i The filtering strategy includes the following:

[0135] (1) Filter object A i ;

[0136] (2) Special event filter coefficient α i ;

[0137] (3) Special event filtering times N i ;

[0138] (4) Whether to reset the filter state when entering this special event;

[0139] (5) Whether to reset the filter state after completing filtering for a special event filtering number of times.

[0140] Then, for special event E i , for the filter object A i All parameters in the E i The special event filter coefficient is used for filtering, and the filter state is reset at the specified reset time.

[0141] After completing the filtering of the special event filtering times, you can switch from the special event mode to the normal operation mode.

[0142] The following is an example of how to set up a special event:

[0143] The set of preset special events is:

[0144] P={E0,E1}

[0145] Among them, special event E0 represents the RF chip restart event; special event E1 represents the neighboring cell measurement event;

[0146] The filtering strategy for special event E0 is set as follows:

[0147] (1) Filter object A0: contains the set of all filter parameters;

[0148] (2) Special event filter coefficient α0: not set;

[0149] (3) Special event filtering times N0: not set;

[0150] (4) When this event occurs, all IIR filter states are reset immediately and then return to phase 1 in normal operating mode.

[0151] The filtering strategy for special event E1 is set as follows:

[0152] (1) Filter object A1: contains the set of all power-related parameters;

[0153] (2) Special event filter coefficient α1: fixed to 1 / 2;

[0154] (3) Special event filtering times N1: fixed to 2;

[0155] (4) When this event occurs, all IIR filter states are not reset;

[0156] (5) After completing the special event filtering times N1, there is no need to reset the current state of the IIR filter.

[0157] Based on the same inventive concept, see Figure 2 The present application also provides a filtering device 200, which includes:

[0158] A channel parameter estimation value acquisition module 210 is used to acquire a channel parameter estimation value of a current channel according to a pilot signal of a current wireless resource, and filter the channel parameter estimation value using a currently configured filter to acquire the filtered channel parameter estimation value;

[0159] The filter configuration module 220 is used to reconfigure the filter coefficient and filtering times of the filter according to the filtered channel parameter estimation value, and the filter enters a stable state after completing the filtering times according to the reconfigured filtering coefficient.

[0160] As an optional implementation of the above-mentioned filtering device, the above-mentioned filtering device also includes:

[0161] The periodic configuration module is used to perform the step of reconfiguring the filter coefficient and filtering times of the filter according to the estimated value of the filtered channel parameter at every preset update interval after the filter enters a stable state.

[0162] As an optional implementation of the above-mentioned filtering device, the above-mentioned filter configuration module 220 is specifically used to: determine the signal-to-noise ratio and Doppler spread of the current channel according to the channel parameter estimation value after filtering; determine the compensation parameter of the coherence time according to the signal-to-noise ratio; determine the coherence time according to the Doppler spread and the compensation parameter; reconfigure the filter coefficient and the number of filtering times of the filter according to the coherence time, the period of the current wireless resource and the preset minimum number of filtering times.

[0163] As an optional implementation manner of the above-mentioned filtering device, the above-mentioned filter configuration module 220 determines the compensation parameter of the coherence time according to the signal-to-noise ratio, including: determining a target preset signal-to-noise ratio corresponding to the signal-to-noise ratio in a preset signal-to-noise ratio list, wherein the preset signal-to-noise ratio list includes multiple preset signal-to-noise ratios; determining a target preset compensation parameter corresponding to the target preset signal-to-noise ratio in a preset compensation parameter list, wherein the preset compensation parameter list includes multiple preset compensation parameters, and the preset compensation parameters in the preset compensation parameter list correspond to the preset signal-to-noise ratio in the preset signal-to-noise ratio list one-to-one;

[0164] The filter configuration module 220 determines the coherence time according to the Doppler expansion and the compensation parameters, including: calculating the intermediate coherence time of the current channel according to the target preset compensation parameters and the Doppler expansion; determining the target preset coherence time corresponding to the intermediate coherence time in the preset coherence time list, wherein the preset coherence time list includes multiple preset coherence times.

[0165] As an optional implementation of the above-mentioned filtering device, the above-mentioned filter configuration module 220 reconfigures the filter coefficient and the number of filtering times of the filter according to the coherence time, the period of the current wireless resource and the preset minimum number of filtering times, including: taking the period of the current wireless resource, the coherence time of the current channel and the preset minimum number of filtering times as inputs of a preset function, obtaining new filter coefficients and new filtering times output by the preset function; and reconfiguring the filter using the new filter coefficients and the new number of filtering times.

[0166] As an optional implementation of the above-mentioned filtering device, the above-mentioned filtering device 200 further includes:

[0167] The special event processing module is used to periodically monitor the preset special events. If the special event is monitored, the filter coefficient and filtering times of the filter are reconfigured according to the filtering strategy corresponding to the special event; wherein the filtering strategy also includes the filtering object of the filter.

[0168] As an optional implementation manner of the above-mentioned filtering device, the above-mentioned filtering strategy also includes: whether to reset the filter state when entering the special event, and / or whether to reset the filter state after completing the filtering of the filtering times.

[0169] Figure 3 A schematic diagram of an electronic device provided in an embodiment of the present application. Figure 3 The electronic device 300 includes: a processor 310, a memory 320 and a communication interface 330. These components are interconnected and communicate with each other through a communication bus 340 and / or other forms of connection mechanisms (not shown).

[0170] The memory 320 includes one or more (only one is shown in the figure), which may be, but not limited to, a random access memory (RAM), a read only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), etc. The processor 310 and other possible components may access the memory 320 and read and / or write data therein.

[0171] The processor 310 includes one or more (only one is shown in the figure), which can be an integrated circuit chip with signal processing capabilities. The above-mentioned processor 310 can be a general-purpose processor, including a central processing unit (CPU), a micro controller unit (MCU), a network processor (NP) or other conventional processors; it can also be a special-purpose processor, including a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components.

[0172] The communication interface 330 includes one or more (only one is shown in the figure), which can be used to communicate directly or indirectly with other devices to exchange data. For example, the communication interface 330 can be an Ethernet interface; it can be a mobile communication network interface, such as an interface of a 3G, 4G, or 5G network; or it can be other types of interfaces with data transceiving functions.

[0173] One or more computer program instructions may be stored in the memory 320 , and the processor 310 may read and execute these computer program instructions to implement the filtering method and other desired functions provided in the embodiments of the present application.

[0174] Understandably, Figure 3 The structure shown is for illustration only. The electronic device 300 may also include Figure 3 More or fewer components as shown, or with Figure 3 Different configurations shown. Figure 3 Each component shown in the figure can be implemented by hardware, software or a combination thereof. For example, the electronic device 300 can be a single server (or other device with computing processing capabilities), a combination of multiple servers, a cluster of a large number of servers, etc., and can be both a physical device and a virtual device.

[0175] The present application also provides a computer-readable storage medium, which stores computer program instructions. When the computer program instructions are read and executed by a computer processor, the filtering method provided by the present application is executed. For example, the computer-readable storage medium can be implemented as Figure 3 The memory 320 in the electronic device 300.

[0176] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0177] In addition, the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0178] Furthermore, the functional modules in the various embodiments of the present application may be integrated together to form an independent part, or each module may exist independently, or two or more modules may be integrated to form an independent part.

[0179] The above description is only an embodiment of the present application and is not intended to limit the protection scope of the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A filtering method, It is characterized in that The method comprises: Acquire a channel parameter estimation value of a current channel according to a pilot signal of a current wireless resource, and filter the channel parameter estimation value using a currently configured filter to acquire the filtered channel parameter estimation value; Reconfiguring the filter coefficient and filtering times of the filter according to the filtered channel parameter estimation value, wherein the filter enters a stable state after completing filtering times according to the reconfigured filtering coefficient; The method further comprises: after the filter enters a stable state, performing a step of reconfiguring the filter coefficient and the number of filtering times of the filter according to the filtered channel parameter estimation value at every preset update interval; The reconfiguring of the filter coefficient and the number of filtering times of the filter according to the filtered channel parameter estimation value comprises: determining the signal-to-noise ratio and Doppler spread of the current channel according to the filtered channel parameter estimation value; determining the compensation parameter of the coherence time according to the signal-to-noise ratio; determining the coherence time according to the Doppler spread and the compensation parameter; reconfiguring the filter coefficient and the number of filtering times of the filter according to the coherence time, the cycle of the current wireless resource and the preset minimum number of filtering times; wherein the preset minimum number of filtering times is used to represent the minimum number of filtering times that enables the filter to reach a stable state under the performance conditions of the current terminal; The reconfiguring of the filter coefficient and the number of filtering times of the filter according to the coherence time, the period of the current wireless resource and the preset minimum number of filtering times includes: taking the period of the current wireless resource, the coherence time of the current channel and the preset minimum number of filtering times as inputs of a preset function, obtaining new filter coefficients and new filtering times output by the preset function; and reconfiguring the filter using the new filter coefficients and the new number of filtering times.

2. The filtering method according to claim 1, It is characterized in that The determining of the compensation parameter of the coherence time according to the signal-to-noise ratio comprises: Determine a target preset signal-to-noise ratio corresponding to the signal-to-noise ratio in a preset signal-to-noise ratio list, wherein the preset signal-to-noise ratio list includes multiple preset signal-to-noise ratios; Determine a target preset compensation parameter corresponding to the target preset signal-to-noise ratio in a preset compensation parameter list, wherein the preset compensation parameter list includes multiple preset compensation parameters, and the preset compensation parameters in the preset compensation parameter list correspond one-to-one to the preset signal-to-noise ratios in the preset signal-to-noise ratio list; Determining the coherence time according to the Doppler spread and the compensation parameter comprises: Calculating the intermediate coherence time of the current channel according to the target preset compensation parameter and the Doppler spread; A target preset coherence time corresponding to the intermediate coherence time in a preset coherence time list is determined, wherein the preset coherence time list includes a plurality of preset coherence times.

3. The filtering method according to any one of claims 1 to 2, It is characterized in that The method further comprises: Perform periodic monitoring on preset special events, and if the occurrence of the special event is monitored, reconfigure the filter coefficient and filtering times of the filter according to the filtering strategy corresponding to the special event; wherein the filtering strategy also includes the filtering object of the filter.

4. The filtering method according to claim 3, It is characterized in that The filtering strategy also includes: whether to reset the filter state when entering the special event, and / or whether to reset the filter state after completing the filtering times.

5. A filtering device, It is characterized in that The device comprises: A channel parameter estimation value acquisition module, used to obtain a channel parameter estimation value of a current channel according to a pilot signal of a current wireless resource, filter the channel parameter estimation value using a currently configured filter, and obtain the filtered channel parameter estimation value; A filter configuration module, used for reconfiguring the filter coefficient and the number of filtering times of the filter according to the estimated value of the filtered channel parameter, wherein the filter enters a stable state after completing the filtering times according to the reconfigured filter coefficient; The filtering device further comprises: a periodic configuration module, which is used to execute the step of reconfiguring the filter coefficient and the number of filtering times of the filter according to the estimated value of the filtered channel parameter at every preset update interval after the filter enters a stable state; The filter configuration module is specifically used to: determine the signal-to-noise ratio and Doppler spread of the current channel according to the estimated value of the channel parameter after filtering; determine the compensation parameter of the coherence time according to the signal-to-noise ratio; determine the coherence time according to the Doppler spread and the compensation parameter; reconfigure the filter coefficient and the number of filtering times of the filter according to the coherence time, the cycle of the current wireless resource and the preset minimum number of filtering times; wherein the preset minimum number of filtering times is used to represent the minimum number of filtering times that enables the filter to reach a stable state under the performance conditions of the current terminal; The filter configuration module reconfigures the filter coefficient and the number of filtering times of the filter according to the coherence time, the period of the current wireless resource and the preset minimum number of filtering times, including: taking the period of the current wireless resource, the coherence time of the current channel and the preset minimum number of filtering times as inputs of a preset function, obtaining new filter coefficients and new filtering times output by the preset function; and reconfiguring the filter using the new filter coefficients and the new number of filtering times.

6. An electronic device, It is characterized in that include: A processor, a memory and a communication bus, wherein the processor and the memory communicate with each other via the communication bus; The memory stores program instructions executable by the processor, and the processor can execute the method according to any one of claims 1 to 4 by calling the program instructions.

7. A computer-readable storage medium, It is characterized in that The computer-readable storage medium stores computer instructions, and when the computer instructions are executed by a computer, the computer is caused to execute the method according to any one of claims 1 to 4.

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