CN114389920A - Channel estimation result processing method, device, terminal and storage medium - Google Patents

Abstract

The embodiment of the application discloses a channel estimation result processing method, a channel estimation result processing device, a terminal and a storage medium, and belongs to the technical field of communication. The method comprises the following steps: acquiring channel state information, wherein the channel state information comprises first channel state information and second channel state information; the updating period of the first channel state information is a first period, and the updating period of the second channel state information is a second period; the first period is greater than the second period; in the updating period of the second channel state information, acquiring an initial wiener filter coefficient in the updating period of the second channel state information according to the first channel state information; acquiring a wiener filter coefficient in an update period of second channel state information according to the initial wiener filter coefficient and the second channel state information; and carrying out filtering processing on the channel estimation result according to the wiener filtering coefficient. The scheme reduces the real-time calculation amount of wiener filter coefficient calculation, and further reduces the power consumption of the terminal.

Description

Channel estimation result processing method, device, terminal and storage medium

technical field

The present disclosure relates to the field of communication technologies, and in particular, to a method, device, terminal and storage medium for processing a channel estimation result.

Background technique

The terminal needs to perform real-time channel estimation during the communication process, and needs to calculate the Wiener filter coefficient for processing the channel estimation result in real time before performing the channel estimation, so as to perform filtering, denoising and interpolation processing on the channel estimation result.

In the related art, the minimum period of channel state information change in a system used for coefficient calculation is usually a time slot as a unit. Therefore, when calculating the coefficients, the Wiener filter coefficients need to be calculated in units of the minimum period of the channel state information.

However, in the solution in the above-mentioned related art, the calculation amount of the Wiener filter coefficient calculation is relatively large, which causes a large waste of power consumption to the terminal.

SUMMARY OF THE INVENTION

Embodiments of the present application provide a method, device, terminal, and storage medium for processing a channel estimation result, which can reduce the power consumption of the terminal for channel estimation. The technical solution is as follows:

On the one hand, an embodiment of the present application provides a method for processing a channel estimation result, and the method includes:

Acquire channel state information, where the channel state information includes first channel state information and second channel state information; the update cycle of the first channel state information is the first cycle, and the update cycle of the second channel state information is the first cycle two periods; the first period is greater than the second period;

During the update period of the second channel state information, obtain the initial Wiener filter coefficient within the update period of the second channel state information according to the first channel state information;

According to the initial Wiener filter coefficient and the second channel state information, obtain the Wiener filter coefficient in the update period of the second channel state information;

According to the Wiener filter coefficient, filter processing is performed on the channel estimation result within the update period of the second channel state information.

On the other hand, an embodiment of the present application provides an apparatus for processing a channel estimation result, and the apparatus includes:

an information acquisition module, configured to acquire channel state information, where the channel state information includes first channel state information and second channel state information; the update cycle of the first channel state information is a first cycle, and the second channel state information The update period of the information is the second period; the first period is greater than the second period;

a first acquisition module, configured to acquire, within the update period of the second channel state information, an initial Wiener filter coefficient within the update period of the second channel state information according to the first channel state information;

a second obtaining module, configured to obtain the Wiener filter coefficient within the update period of the second channel state information according to the initial Wiener filter coefficient and the second channel state information;

The processing module is configured to perform filtering processing on the channel estimation result within the update period of the second channel state information according to the Wiener filter coefficient.

On the other hand, an embodiment of the present application provides a terminal, the terminal includes a processor and a memory; at least one computer instruction is stored in the memory, and the at least one computer instruction is loaded and executed by the processor to implement The channel estimation result processing method described in the above aspects.

On the other hand, an embodiment of the present application provides a computer-readable storage medium, where at least one computer instruction is stored in the computer-readable storage medium, and the computer instruction is loaded and executed by a processor to implement the above aspects The channel estimation result processing method.

In another aspect, a computer program product or computer program is provided, the computer program product or computer program comprising computer instructions stored in a computer-readable storage medium. The processor of the terminal reads the computer instruction from the computer-readable storage medium, and the processor executes the computer instruction, so that the terminal executes the channel estimation result processing method provided in various optional implementation manners of the foregoing aspects.

On the other hand, an embodiment of the present application provides a chip, where the chip is configured to implement the method for processing a channel estimation result as described in the foregoing aspect.

The beneficial effects of the technical solutions provided by the embodiments of the present application include at least:

By dividing the channel state information into the first channel state information and the second channel state information according to their respective update cycles, and by updating the first channel state information corresponding to the first cycle with a longer cycle, the corresponding channel state information in the first cycle is calculated. initial Wiener filter coefficients, and then calculate the Wiener filter coefficients in each second cycle by updating the second channel state information corresponding to the second cycle with a shorter period and the initial Wiener filter coefficients, so as to pass each Wiener filter coefficient Filter processing is performed on the channel estimation result in the second cycle. It avoids the situation that the terminal needs to calculate the Wiener filter coefficient corresponding to the time slot according to the channel state information obtained in the time slot in each time slot, thereby reducing the real-time calculation amount of the Wiener filter coefficient calculation, and then The power consumption of the terminal is reduced.

Description of drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description serve to explain the principles of the disclosure.

1 is a block diagram of a communication system according to an exemplary embodiment;

FIG. 2 is a flowchart of a method for processing a channel estimation result according to an exemplary embodiment;

FIG. 3 is a flowchart of a method for processing a channel estimation result according to another exemplary embodiment;

FIG. 4 is a schematic diagram of enabling a default mode for coefficient calculation according to the embodiment shown in FIG. 3;

FIG. 5 is a schematic diagram of performing coefficient calculation by enabling a power consumption reduction mode according to the embodiment shown in FIG. 3;

6 is a structural block diagram of an apparatus for processing a channel estimation result provided by an exemplary embodiment of the present application;

FIG. 7 shows a structural block diagram of a terminal provided by an exemplary embodiment of the present application.

The above-mentioned drawings have shown clear embodiments of the present disclosure, and will be described in more detail hereinafter. These drawings and written descriptions are not intended to limit the scope of the disclosed concepts in any way, but rather to illustrate the disclosed concepts to those skilled in the art by referring to specific embodiments.

Detailed ways

In order to make the objectives, technical solutions and advantages of the present application clearer, the embodiments of the present application will be further described in detail below with reference to the accompanying drawings.

As used herein, "plurality" refers to two or more. "And/or", which describes the association relationship of the associated objects, means that there can be three kinds of relationships, for example, A and/or B, which can mean that A exists alone, A and B exist at the same time, and B exists alone. The character "/" generally indicates that the associated objects are an "or" relationship.

FIG. 1 shows a block diagram of a communication system provided by an exemplary embodiment of the present application. The communication system may include: an access network 12 , a terminal device 14 and a core network 16 .

The access network 12 includes several access network devices 120 . The access network device 120 may be a base station, and the base station is a device deployed in an access network to provide a wireless communication function for a terminal. The base station may include various forms of macro base station, micro base station, relay station, access point and so on. In systems using different wireless access technologies, the names of devices with base station functions may be different. For example, in LTE (Long Term Evolution) systems, they are called eNodeB (Evolved Node B, base station) or Abbreviated as eNB; in the 5G NR-U (5G New Radio in Unlicensed Spectrum, 5G air interface operating in the unlicensed frequency band) system, it is called gNodeB (5G base station) or gNB. As communication technology evolves, the description of "base station" may change. For the convenience of the embodiments of the present application, the above-mentioned apparatuses for providing a wireless communication function for the terminal device 14 are collectively referred to as network devices.

The terminal device 14 may include various handheld devices with wireless communication functions, vehicle-mounted devices, wearable devices, computing devices or other processing devices connected to wireless modems, as well as various forms of user equipment, mobile stations (Mobile Station, MS) , Terminal (Terminal Device) and so on. For the convenience of description, the devices mentioned above are collectively referred to as terminals. The access network device 120 and the terminal device 14 communicate with each other through a certain air interface technology, such as a Uu interface.

As the top layer of the mobile communication network, the core network 16 completes the routing and exchange of data, and finally realizes the establishment of a channel between the end user and the Internet. After the channel is established, the end user can access the data center on the Internet, that is, the server of the service provider, So as to use the business and services provided by the service provider.

The technical solutions of the embodiments of the present application can be applied to various communication systems, for example: a Global System of Mobile Communication (GSM) system, a Code Division Multiple Access (CDMA) system, a Wideband Code Division Multiple Access (Wideband) system Code Division Multiple Access (WCDMA) system, General Packet Radio Service (GPRS), Long Term Evolution (Long Term Evolution, LTE) system, LTE Frequency Division Duplex (FDD) system, LTE Time Division Duplex (Time Division Duplex, TDD) system, Advanced Long Term Evolution (LTE-A) system, New Radio (New Radio, NR) system, evolution system of NR system, LTE (LTE- based access to Unlicensed spectrum, LTE-U) system, NR-U system, Universal Mobile Telecommunication System (UMTS), Worldwide Interoperability for Microwave Access (WiMAX) communication system, Wireless Local Area Network (Wireless Local Area Network) Area Networks, WLAN), Wireless Fidelity (Wireless Fidelity, WiFi), the 6th generation mobile communication technology (6-Generation, 6G) system, the next generation communication system or other communication systems.

Generally speaking, traditional communication systems support a limited number of connections and are easy to implement. However, with the development of communication technology, mobile communication systems will not only support traditional communication, but also support, for example, Device to Device (D2D). ) communication, Machine to Machine (M2M) communication, Machine Type Communication (MTC), Vehicle to Vehicle (V2V) communication and Vehicle to Everything (V2X) systems, etc. The embodiments of the present application can also be applied to these communication systems.

FIG. 2 shows a flowchart of a method for processing a channel estimation result provided by an exemplary embodiment of the present application. The method for processing the channel estimation result may be executed by a terminal, for example, the terminal may be the terminal device 14 in the communication system shown in FIG. 1 above. The channel estimation result processing method includes the following steps:

Step 201: Obtain channel state information, where the channel state information includes first channel state information and second channel state information; an update period of the first channel state information is a first period, and an update period of the second channel state information is a second period; The first period is greater than the second period.

In this embodiment of the present application, in the process of channel estimation, the terminal needs to calculate the Wiener filter coefficients used for channel estimation of each time slot, and the Wiener filter coefficient of each time slot is the channel obtained by the terminal based on each time slot. The state information is determined. Therefore, the terminal needs to obtain the channel state information of each time slot.

The channel state information may include first channel state information and second channel state information, and the first channel state information and the second channel state information may be distinguished according to their corresponding update periods, that is, the update period of the first channel state information may be Including the first cycle, the update cycle of the second channel state information may include the second cycle, and the update cycle of the first channel state information is greater than the update cycle of the second channel state information.

For example, the update cycle of the first channel state information may be updated once every x time slots, and the update cycle of the second channel state information may be updated once every y time slots, and x is greater than y.

In a possible implementation manner, the channel state information includes at least one of Doppler spread information, delay spread information, signal-to-noise ratio, timing offset, and frequency offset.

Wherein, when the terminal communicates in motion, the frequency of the received signal will change, this phenomenon can be called the Doppler effect, and the Doppler spread information can be the information of the signal frequency shift change determined by the terminal based on the Doppler effect . Since the distances of the radio waves passing through each path are different, the arrival times of the transmitted waves in each path are different, which may cause multipath delay expansion, thereby generating delay expansion information. The signal-to-noise ratio is the ratio of signal power to noise power, and can be used to indicate the ratio of signal-domain noise in the terminal.

Step 202: During the update period of the second channel state information, acquire the initial Wiener filter coefficients within the update period of the second channel state information according to the first channel state information.

In this embodiment of the present application, within the update period of the second channel state information, the terminal may acquire the initial Wiener filter coefficient within the update period of the second channel state information according to the first channel state information.

In a possible implementation manner, since the update period of the first channel state information is greater than the update period of the second channel state information, within the update period of the second channel state information, the first channel state information is updated in the corresponding update period The value corresponding to the period remains unchanged, and the terminal may calculate and obtain the initial Wiener filter coefficient according to the first channel state information.

Wherein, the initial Wiener filter coefficients may be coefficients calculated through Doppler extension information, delay extension information and signal-to-noise ratio.

Since the corresponding values of Doppler extension information, delay extension information and signal-to-noise ratio remain unchanged in their respective update periods, when calculating the initial Wiener filter coefficients, there are Doppler extension information in multiple time intervals, In this case, after the initial Wiener filter coefficient is calculated once, it is not necessary to repeat the calculation, thereby reducing the calculation amount of the initial Wiener filter coefficient.

For example, if the update cycle of the first channel state information is 100 time slots, and the update cycle of the second channel state information is 20 time slots, the initial Wiener filter coefficient can be calculated according to the first channel state information every 20 time slots. When the time slot is -20, the value of each channel state information in the first channel state information remains unchanged, then it can be determined that the initial Wiener filter coefficient of the time slot 0-20 is the same value. The initial Wiener filter coefficients of The filter coefficients are the same value, and no additional coefficient calculation is required, thereby reducing the calculation amount of the terminal.

Step 203: Acquire the Wiener filter coefficient in the update period of the second channel state information according to the initial Wiener filter coefficient and the second channel state information.

In this embodiment of the present application, after obtaining the initial Wiener filter coefficient of the current time slot, the terminal may calculate and obtain the Wiener filter coefficient within the update period of the second channel state information according to the second channel state information corresponding to the current time slot .

Wherein, the second channel state information can be used to perform phase rotation of the coefficients on the initial Wiener filter coefficients, and according to the update cycle of the second channel state information, perform phase rotation on the initial Wiener filter coefficients in each update cycle to obtain the second channel state information. The Wiener filter coefficients in the update period of the channel state information.

For example, if the update period of the first channel state information is 100 time slots, it can be determined that the initial Wiener filter coefficients in each 100 time slot interval are the same, that is, the initial Wiener filter coefficients in the 0-100 time slots can be a, The initial Wiener filter coefficient in time slots 101-200 may be b, and so on. If the update period of the second channel state information is 20 time slots, it can be determined that the values collected from the second channel state information in the interval of every 20 time slots are the same, that is, the value of the second channel state information in time slots 0-20 is the same. The values can be all p, and the values of the second channel state information in the 21-40 time slots can be all q. Since the initial Wiener filter coefficient in the 0-100 time slots can be a, according to the update period of 20 time slots The second channel state information can be calculated to determine the Wiener filter coefficient in each 20 time slot, that is, the Wiener filter coefficient in the 0-20 time slot interval can be calculated according to a and p, and the 21-40 time slot interval The inner Wiener filter coefficients can be calculated from a and q, and so on.

Step 204: Perform filtering processing on the channel estimation result within the update period of the second channel state information according to the Wiener filter coefficient.

In this embodiment of the present application, the terminal may perform filtering processing on the channel estimation result within the update period of the second channel state information according to the determined Wiener filter coefficient.

Since the Wiener filter coefficients calculated in each time slot in each update cycle of the second channel state information are the same, the corresponding Wiener filter coefficient pairs in each update cycle of the second channel state information can be paired The channel estimation results in the update period are filtered.

To sum up, in this embodiment of the present application, the channel state information is divided into the first channel state information and the second channel state information according to their respective update cycles, and the first channel corresponding to the first cycle with a longer update cycle state information, calculate the corresponding initial Wiener filter coefficient in the first cycle, and then calculate the Wiener filter coefficient in each second cycle by updating the second channel state information corresponding to the second cycle with a shorter cycle and the initial Wiener filter coefficient filtering coefficients, so as to implement filtering processing on the channel estimation result in the second cycle through each Wiener filtering coefficient. It avoids the situation that the terminal needs to calculate the Wiener filter coefficient corresponding to the time slot according to the channel state information obtained in the time slot in each time slot, thereby reducing the real-time calculation amount of the Wiener filter coefficient calculation, and then The power consumption of the terminal is reduced.

FIG. 3 shows a flowchart of a method for processing a channel estimation result provided by an exemplary embodiment of the present application. The method for processing the channel estimation result may be executed by a terminal, for example, the terminal may be the terminal device 14 in the communication system shown in FIG. 1 above. The channel estimation result processing method includes the following steps:

Step 301, acquiring channel state information.

In this embodiment of the present application, the terminal may acquire the value corresponding to each channel state information in each time slot.

The channel state information may include first channel state information and second channel state information. The update cycle of the first channel state information may include a first cycle, the update cycle of the second channel state information may include a second cycle, and the first cycle may be greater than the second cycle.

In a possible implementation manner, the first channel state information includes Doppler spread information, delay spread information, and signal-to-noise ratio; the second channel state information includes at least one of timing offset and frequency offset.

Exemplarily, in the process of calculating the Wiener filter coefficients, the channel state information needs to be acquired in real time, and the channel state information acquired in real time may include Doppler spread information, delay spread information, signal-to-noise ratio, timing deviation, and Frequency deviation, the obtained channel state information can be stored.

Wherein, the channel state information used in the process of calculating the Wiener filter coefficients may include frequency-domain related Doppler spread information, timing offset and signal-to-noise ratio, or the channel state information used in the process of calculating the Wiener filter coefficients may also include Time-domain related delay spread information, frequency deviation, and signal-to-noise ratio.

That is to say, the process of calculating Wiener filter coefficients can be calculated using Doppler spread information, timing offset and signal-to-noise ratio, or the process of calculating Wiener filter coefficients can also be calculated using delay spread information, frequency offset and signal-to-noise ratio. .

In a possible implementation manner, the first period includes at least one of an update period of the Doppler spread information and an update period of the delay spread information.

Wherein, when calculating the Wiener filter coefficients using Doppler spread information, timing offset and signal-to-noise ratio, the first period may include the update period of the Doppler spread information; when calculating the Wiener filter coefficients using the time delay When the extension information, the frequency deviation and the signal-to-noise ratio are calculated, the first period may include an update period of the delay extension information.

Step 302 , in the update period of the second channel state information, obtain a signal-to-noise ratio interval in which the signal-to-noise ratio in the first channel state information is located.

In the embodiment of the present application, in the update period of the second channel state information that is shorter than the update period of the first channel state information, the signal-to-noise ratio interval in which the signal-to-noise ratio in the first channel state information is located is acquired.

Among them, since the signal-to-noise ratio belongs to short-term state information, that is, unlike the Doppler spread information and the delay spread information, the value of the channel state information can be maintained in the first period, and the signal-to-noise ratio can only be maintained in a short period of time. The value of the channel state information remains unchanged for the period of time. In order to convert the signal-to-noise ratio from short-term state information to long-term state information, at least two signal-to-noise ratio intervals can be divided to obtain the position of the signal-to-noise ratio in the first channel state information. The signal-to-noise ratio range.

In a possible implementation manner, the terminal obtains the SNR value of each time slot in the historical record, determines the maximum value of the SNR value as the upper limit of the SNR interval, and determines the minimum value of the SNR value as The lower limit of the signal-to-noise ratio interval is obtained to obtain the signal-to-noise ratio range, and the signal-to-noise ratio range is equally divided according to the preset quantization threshold to obtain each signal-to-noise ratio interval.

Exemplarily, if the range of the signal-to-noise ratio value is determined by the terminal to be [-10, 40] according to the historical record, that is, the signal-to-noise ratio value is between -10dB and 40dB, if the preset quantization threshold is 8, the The range of [-10, 40] is divided into 8 equal parts, and 8 SNR intervals are obtained after the equal parts are obtained.

Step 303: Obtain a reference signal-to-noise ratio corresponding to the signal-to-noise ratio interval.

In this embodiment of the present application, the terminal determines a signal-to-noise ratio interval corresponding to the signal-to-noise ratio value according to the obtained signal-to-noise ratio value, and obtains a reference signal-to-noise ratio corresponding to the signal-to-noise ratio interval.

In a possible implementation manner, after acquiring each SNR interval, the terminal determines the median in each SNR interval as the reference SNR corresponding to the SNR interval.

The terminal may obtain the reference SNR corresponding to each SNR interval, and determine the reference SNR corresponding to the SNR interval according to the SNR interval corresponding to the obtained SNR value.

Exemplarily, if the signal-to-noise ratio range of [-10, 40] is divided into 8 equal parts, 8 signal-to-noise ratio intervals are obtained after the equal divisions are obtained, and the medians in the obtained signal-to-noise ratio intervals are -6, 0, 6, 12, 18, 24, 30, and 36 are used as the reference SNR corresponding to each SNR interval, and the SNR interval to which the current SNR value belongs is determined according to the obtained current SNR value. , and obtain the reference signal-to-noise ratio corresponding to the corresponding signal-to-noise ratio interval.

The entire SNR range is divided into multiple SNR intervals, and each SNR interval corresponds to a reference SNR, and each reference SNR, that is, the quantized SNR value, is used to characterize the entire SNR The individual SNR values in the range. The terminal only needs to calculate the initial Wiener filter coefficients corresponding to each reference SNR, and then the initial Wiener filter coefficients corresponding to each time slot in the entire first cycle can be obtained, which greatly reduces the amount of coefficient calculation and reduces to a certain extent. power consumption of the terminal.

Step 304: Acquire the initial Wiener filter coefficients in the update period of the second channel state information according to the reference signal-to-noise ratio.

In the embodiment of the present application, the terminal may calculate and obtain the initial Wiener filter coefficient on each time slot in the update period of the second channel state according to the obtained reference signal-to-noise ratio corresponding to each time slot.

In a possible implementation manner, in response to the terminal acquiring the reference signal-to-noise ratio corresponding to each signal-to-noise ratio interval, each reference signal-to-noise ratio is used in advance, and the Doppler spread information in the first channel state information and Timing deviation, the initial Wiener filter coefficient corresponding to each reference signal-to-noise ratio is calculated and obtained, and the reference signal-to-noise ratio and the corresponding initial Wiener filter coefficient are stored. When the terminal obtains the signal-to-noise ratio of the current time slot, determines the reference signal-to-noise ratio corresponding to the signal-to-noise ratio, and determines the reference signal-to-noise ratio from the initial Wiener filter coefficient corresponding to the stored reference signal-to-noise ratio according to the determined reference signal-to-noise ratio The initial Wiener filter coefficients corresponding to the signal-to-noise ratio.

Exemplarily, when it is determined that the reference signal-to-noise ratio corresponding to each signal-to-noise ratio interval includes -6, 0, 6, 12, 18, 24, 30 and 36, due to the Doppler spread information and delay spread in the first cycle The value of the information does not change, so the corresponding initial Wiener filter coefficients in the first cycle are pre-calculated according to each reference signal-to-noise ratio. When the coefficient calculation is started, the terminal obtains the current time slot in the first cycle. The corresponding signal-to-noise ratio value is determined based on the corresponding signal-to-noise ratio value in the current time slot to determine the signal-to-noise ratio interval to which it belongs, so as to determine the reference signal-to-noise ratio corresponding to the signal-to-noise ratio interval. The initial Wiener filter coefficient corresponding to the reference signal-to-noise ratio is selected from the stored initial Wiener filter coefficients as the initial Wiener filter coefficient obtained in the current time slot.

In a possible implementation manner, when the initial Wiener filter coefficient corresponding to the reference signal-to-noise ratio already exists within the update period of the first channel state information, the existing initial Wiener filter coefficient corresponding to the reference signal-to-noise ratio is coefficient, which is obtained as the initial Wiener filter coefficient in the update period of the second channel state information. When there is no initial Wiener filter coefficient corresponding to the reference signal-to-noise ratio within the update period of the first channel state information, according to the reference signal-to-noise ratio, the Doppler spread information in the first channel state information, and the first channel state The delay extension information in the information is used to obtain the initial Wiener filter coefficient in the update period of the second channel state information.

Wherein, when the terminal obtains the signal-to-noise ratio value in the current time slot, the terminal determines the corresponding signal-to-noise ratio interval according to the signal-to-noise ratio value in the current time slot, and determines the corresponding reference signal-to-noise ratio according to the determined signal-to-noise ratio interval , determine whether the initial Wiener filter coefficient corresponding to the reference SNR has been calculated, if the initial Wiener filter coefficient corresponding to the reference SNR has not been calculated before the current time slot, the obtained reference SNR Calculate the initial Wiener filter coefficient in the current time slot, and store the calculated initial Wiener filter coefficient and its corresponding reference signal-to-noise ratio in the terminal. If the reference signal-to-noise ratio has been calculated before the current time slot initial Wiener filter coefficients, the initial Wiener filter coefficients may be obtained from the stored initial Wiener filter coefficients according to the obtained reference signal-to-noise ratio.

Exemplarily, when the terminal acquires the signal-to-noise ratio value a in the first time slot in the first period, the signal-to-noise ratio value a belongs to the signal-to-noise ratio interval 1, and the reference corresponding to the signal-to-noise ratio interval 1 The signal-to-noise ratio is the reference signal-to-noise ratio A, and the initial Wiener filter coefficient corresponding to the calculated reference signal-to-noise ratio A is the initial Wiener filter coefficient in the first time slot. When the terminal obtains the signal-to-noise ratio value b in the second time slot in the first period, the signal-to-noise ratio value b still belongs to the signal-to-noise ratio interval 1, and the reference signal-to-noise ratio corresponding to the signal-to-noise ratio interval 1 In order to refer to the signal-to-noise ratio A, the initial Wiener filter coefficients calculated in the previous time slot can be directly used as the initial Wiener filter coefficients in the second time slot. When the terminal obtains the SNR value c in the third time slot in the first period, the SNR value c belongs to the SNR interval 2, and the reference SNR corresponding to the SNR interval 2 is With reference to the signal-to-noise ratio B, the initial Wiener filter coefficient corresponding to the reference signal-to-noise ratio B may be calculated and obtained as the initial Wiener filter coefficient in the third time slot.

In a possible implementation manner, obtaining the second The initial Wiener filter coefficients in the update period of the channel state information.

Wherein, in each time slot, the terminal can calculate and obtain the initial Wiener filter coefficient in each time slot according to the signal-to-noise ratio value, the Doppler extension information value and the time delay extension information value in the first channel state information.

In a possible implementation manner, the initial Wiener filter coefficients are determined according to the autocorrelation matrix and the cross-correlation matrix.

Wherein, the autocorrelation matrix can be calculated by the channel correlation coefficient, the signal-to-noise ratio value, and the distance of the pilot pattern, and the cross-correlation matrix can be calculated by the channel correlation coefficient and the distance of the pilot pattern.

The channel correlation coefficient related to the frequency domain can be obtained by calculating the distance information of the pilot pattern, the carrier spacing and the real-time estimated delay spread information. The channel correlation coefficient of the time domain correlation can be calculated from the distance information of the pilot pattern, the symbol time and the real-time estimated Doppler spread information.

Exemplarily, the formula of the initial Wiener filter coefficient W can be expressed as,

where the autocorrelation matrix is Φ _y and the cross-correlation matrix is Φ _hh' . The autocorrelation matrix is Φ _y The calculation method can be,

是噪声功率，I是一个N×N的单位矩阵。where R(Δk) is the channel correlation coefficient, Δk=k _j −k _i is the distance between RS RE j and RS RE i,

is the noise power, and I is an N×N identity matrix.

The calculation method of the cross-correlation matrix Φ _hh' can be,

Φ _hh' = [R(k ₀ -k _i )R(k ₁ -k _i )...R(k _N-1 -k _i )]

In the calculation process of the autocorrelation matrix and the cross-correlation matrix, the channel correlation coefficient R is used. The channel correlation coefficient R can use the Doppler spread information or delay spread information obtained by real-time estimation, and obtain the current channel correlation coefficient based on statistical correlation. The calculation method of the frequency domain correlation channel correlation coefficient R can be:

R(Δk)=sin c(π×Δk×Δf×Delay)

Among them, Δk is the distance information, Δf is the carrier spacing, and Delay is the delay spread information obtained by real-time estimation.

The calculation method of the channel correlation coefficient R of the time domain correlation can be,

R(Δn)=sinc(2π×Δn×N _symb ×Doppler)

where Δn is the distance information, _Nsymb is the symbol time, and Doppler is the Doppler spread information estimated in real time.

In a possible implementation manner, before obtaining the initial Wiener filter coefficient, the terminal reads the channel state information contained in the register to obtain the first period and the second period. When the first period and the second period meet the specified conditions, the During the update period of the second channel state information, the initial Wiener filter coefficients within the update period of the second channel state information are acquired according to the first channel state information.

Wherein, the specified condition may include that the ratio of the first period to the second period is greater than the proportional threshold.

That is to say, the Wiener filter coefficients obtained by the terminal can be calculated in two ways. One way is that by enabling the default mode, the terminal can determine the Doppler spread information and the delay spread information through the coefficient calculation module in the terminal. And the shortest change period in the signal-to-noise ratio information to calculate the Wiener filter coefficients in real time. Due to the influence of Beam Forming on the base station side in the 4G/5G system, the signal-to-noise ratio may vary for each time slot. Therefore, the cycle of coefficient calculation can only be performed with one time slot as the cycle. Case. Another way is that by enabling the power consumption reduction mode, the terminal can convert the short-term state information into long-term state information by quantizing the continuous signal-to-noise ratio into multiple states, that is, dividing the entire signal-to-noise ratio range into a specified threshold value Each state corresponds to a reference SNR value. In the process of coefficient calculation, the current first cycle Doppler spread information, delay spread information values, and the quantized reference SNR value are used to calculate The specified threshold initial Wiener filter coefficients common to the current first cycle, and the initial Wiener filter coefficients in the first cycle may constitute an initial coefficient set S.

Exemplarily, FIG. 4 is a schematic diagram of enabling a default mode to perform coefficient calculation according to an embodiment of the present application. As shown in Figure 4, the terminal calculates the coefficients using the ACF/SNR level set in the current slot, and then selects and rotates the coefficients in the current slot. Wherein, step 41 is the estimation process of Doppler extension information, time delay extension information and channel correlation coefficient, step 42 is the process of generating coefficients using signal-to-noise ratio, Doppler extension information and time delay extension information, step 43 is The process of coefficient selection (SNR estimation in the current slot) and phase rotation of the coefficients. FIG. 5 is a schematic diagram of performing coefficient calculation by enabling a power consumption reduction mode according to an embodiment of the present application. As shown in Figure 5, when the resource allocation is performed for the first time or the last time, the filtered signal-to-noise ratio remains unchanged, and the power consumption reduction mode can be enabled for coefficient calculation. The coefficients corresponding to each time slot are calculated to obtain the coefficients of each time slot. Wherein, step 51 is the estimation process of Doppler extension information, time delay extension information and channel correlation coefficient, step 52 is the process of generating coefficients using the signal-to-noise ratio, Doppler extension information and time delay extension information, step 53 is The process of coefficient selection (SNR estimation in the current slot) and phase rotation of the coefficients.

In a possible implementation manner, when the ratio of the first period to the second period is greater than a proportional threshold, the terminal enables a power reduction mode.

In order to ensure that the accuracy of the coefficients obtained by the calculation of the coefficients used for channel estimation does not affect the performance of the system, it is necessary to determine whether the first period corresponding to the first channel state information is much larger than the second period before selecting the power reduction mode for coefficient calculation. In the second cycle of the channel state information, if the ratio between the first cycle and the second cycle is greater than the proportional threshold, the terminal has better cost performance when using the power reduction mode for coefficient calculation, which can better maintain system performance and reduce power consumption. balance between consumption.

Step 305: Acquire the Wiener filter coefficient in the update period of the second channel state information according to the initial Wiener filter coefficient and the second channel state information.

In the embodiment of the present application, the terminal calculates the Wiener filter coefficient in the update period for acquiring the second channel state information according to the obtained initial Wiener filter coefficient and the second channel state information.

In a possible implementation manner, after obtaining the initial Wiener filter coefficient, the terminal needs to perform phase rotation on the coefficient according to the second channel state information of the current time slot, so as to obtain the Wiener filter coefficient in the time slot.

Wherein, the second channel state information includes at least one of timing offset and frequency offset.

In a possible implementation manner, when the second channel state information includes a timing offset, a rotation process is performed on the coefficients in the frequency domain direction in the initial Wiener filter coefficients according to the timing offset, and the second channel state information is obtained within the update period of the The Wiener filter coefficients of .

That is to say, when the terminal obtains the initial Wiener filter coefficient, the terminal performs phase rotation on the initial Wiener filter coefficient in the frequency domain direction according to the obtained timing deviation of the current update cycle of the second channel state information, to obtain the first Two Wiener filter coefficients in the update period of the channel state information.

In a possible implementation manner, when the second channel state information includes a frequency deviation, a rotation process is performed on the coefficients in the time domain direction in the initial Wiener filter coefficients according to the frequency deviation to obtain the second channel state information. Wiener filter coefficients in the update period.

That is, when the terminal acquires the initial Wiener filter coefficient, the terminal performs phase rotation on the initial Wiener filter coefficient in the time domain direction according to the acquired frequency deviation of the current update cycle of the second channel state information, to obtain the first Two Wiener filter coefficients in the update period of the channel state information.

Exemplarily, when the terminal acquires that the timing offset TO changes, it performs phase rotation on the channel correlation coefficient R(Δk), and multiplies R(Δk) by exp(2π×Δk×TO) to obtain the Wiener filter coefficient. When the terminal obtains the change of the frequency offset FO, it performs phase rotation on the channel correlation coefficient R(Δn), and multiplies R(Δn) by exp(2π×Δn×FO) to obtain the Wiener filter coefficient.

In a possible implementation manner, for different receiving antennas and different CDM groups (code division multiplexing groups), the Wiener filter coefficients of each receiving antenna and CDM group need to be determined respectively.

Wherein, in the process of phase rotation of the coefficients, firstly, the terminal can select the SNR coefficients of the current timeslot from the initial coefficient set S by using the instantaneous values of the signal-to-noise ratios of each receiving antenna of the current timeslot and the CDM group. If the update period of the timing offset is M timeslots, for the coefficients in the frequency domain direction, the timing offset TO can be used to perform a phase rotation every M timeslots; if the update period of the frequency offset FO is X timeslots, for the time domain Coefficient of direction, which can be phase rotated every X slots using the frequency offset FO. In order to simplify the high-level L1CC control process, in the process of coefficient rotation, the rotation of TO and FO can also adopt a scheme of performing phase rotation on the coefficients once per time slot.

Step 306: Perform filtering processing on the channel estimation result within the update period of the second channel state information according to the Wiener filter coefficient.

In this embodiment of the present application, the terminal may perform filtering processing on the channel estimation result within the update period of the second channel state information according to the acquired real-time Wiener filter coefficient.

The power reduction mode of the coefficient calculation process can be applied to the process of calculating the channel estimation coefficients of 4G LTE TM1 to TM10, and can also be applied to the process of calculating the coefficients of 5G NR PDSCH/PDCCH/PBCH DMRS.

Exemplarily, in the calculation process of the modem chip coefficients, the channel state information is classified according to the update period, and the coefficient calculation process is divided into two parts: coefficient generation and coefficient rotation, and the long-term channel information is used for coefficient generation, using The coefficient rotation of short-term information can effectively save the complexity of coefficient calculation, especially in the communication scenario of base station scheduling strategy and slow channel change, it can effectively reduce the amount of coefficient calculation without affecting the performance of channel estimation, so as to reduce The purpose of system power consumption.

Taking the calculation of filter coefficients for 5G NR PDSDCH DMRS pilots as an example, the coefficient calculation amount for each cycle can be shown in Table 1. For NR PDSDCH DMRS pilots, the coefficient generation process requires 63088 complex multiplications and 55156 complex additions. , 380 division operations.

Table 1

If 8 complex multiplications or complex multiplications and accumulations of sc16 (16bit I+16bit Q) can be completed in one cycle, and 8 complex additions and subtractions of sc16 (16bit I+16bit Q) can be completed in one cycle, one cycle can Completing the computing power of four divisions for conversion, the number of cycles for each period coefficient calculation is about 7886+6984+95=15000. The number of cycles for each cycle coefficient calculation can be shown in Table 2. The coefficient calculation is performed according to the power consumption reduction mode, and one coefficient calculation can be performed every N time slots, and the number of cycles saved can be 15000*(N-1) cycles . In a typical scenario, if N=40, the corresponding number of cycles is 600,000, and if N=100, the corresponding number of cycles is 1.5 million. Therefore, the power consumption can be greatly reduced by using the solution shown in this application.

complex multiplication complex addition division operation total computational complexity 63088 55156 380 cycle consumption 7886 6894 95

Table 2

To sum up, in this embodiment of the present application, the channel state information is divided into the first channel state information and the second channel state information according to their respective update cycles, and the first channel corresponding to the first cycle with a longer update cycle state information, calculate the corresponding initial Wiener filter coefficient in the first cycle, and then calculate the Wiener filter coefficient in each second cycle by updating the second channel state information corresponding to the second cycle with a shorter cycle and the initial Wiener filter coefficient filtering coefficients, so as to implement filtering processing on the channel estimation result in the second cycle through each Wiener filtering coefficient. It avoids the situation that the terminal needs to calculate the Wiener filter coefficient corresponding to the time slot according to the channel state information obtained in the time slot in each time slot, thereby reducing the real-time calculation amount of the Wiener filter coefficient calculation, and then The power consumption of the terminal is reduced.

FIG. 6 shows a structural block diagram of an apparatus for processing a channel estimation result provided by an exemplary embodiment of the present application. The channel estimation result processing device is used in a terminal, and the channel estimation result processing device includes:

An information acquisition module 610 is configured to acquire channel state information, where the channel state information includes first channel state information and second channel state information; an update cycle of the first channel state information is a first cycle, and the second channel state information The update period of the status information is the second period; the first period is greater than the second period;

a first obtaining module 620, configured to obtain, within the update period of the second channel state information, the initial Wiener filter coefficient within the update period of the second channel state information according to the first channel state information;

A second obtaining module 630, configured to obtain the Wiener filter coefficient within the update period of the second channel state information according to the initial Wiener filter coefficient and the second channel state information;

The processing module 640 is configured to perform filtering processing on the channel estimation result in the update period of the second channel state information according to the Wiener filter coefficient.

In one possible implementation,

The first channel state information includes: Doppler spread information, delay spread information, and signal-to-noise ratio;

The second channel state information includes at least one of timing offset and frequency offset.

In a possible implementation manner, the first obtaining module 620 includes:

an interval acquisition submodule, configured to acquire, within the update period of the second channel state information, the signal-to-noise ratio interval in which the signal-to-noise ratio in the first channel state information is located;

a reference acquisition sub-module for acquiring the reference signal-to-noise ratio corresponding to the signal-to-noise ratio interval;

The first obtaining sub-module is configured to obtain the initial Wiener filter coefficient in the update period of the second channel state information according to the reference signal-to-noise ratio.

In a possible implementation, the first acquisition submodule includes:

The first obtaining unit is configured to, when the initial Wiener filter coefficient corresponding to the reference signal-to-noise ratio already exists in the update period of the first channel state information, obtain the existing Wiener filter coefficient corresponding to the reference signal-to-noise ratio. The initial Wiener filter coefficient is obtained as the initial Wiener filter coefficient in the update period of the second channel state information.

In a possible implementation, the first acquisition submodule includes:

a second obtaining unit, configured to, when there is no initial Wiener filter coefficient corresponding to the reference SNR in the update period of the first channel state information, obtain the first channel according to the reference SNR The Doppler extension information in the state information and the delay extension information in the first channel state information are used to acquire the initial Wiener filter coefficients in the update period of the second channel state information.

In a possible implementation manner, the first obtaining module 620 includes:

The acquisition submodule is configured to obtain a sub-module according to the signal-to-noise ratio in the first channel state information, the Doppler spread information in the first channel state information, and all the information in the first channel state information. The delay extension information is obtained, and the initial Wiener filter coefficient in the update period of the second channel state information is acquired.

In a possible implementation manner, the second obtaining module 630 includes:

A first coefficient obtaining sub-module is configured to, when the second channel state information includes the timing deviation, perform rotation processing on the coefficients in the frequency domain direction in the initial Wiener filter coefficients according to the timing deviation, to obtain the obtained Wiener filter coefficients in the update period of the second channel state information.

In a possible implementation manner, the second obtaining module 630 includes:

The second coefficient obtaining sub-module is configured to, when the second channel state information includes the frequency deviation, perform rotation processing on the coefficients in the time domain direction in the initial Wiener filter coefficients according to the frequency deviation, to obtain Wiener filter coefficients in the update period of the second channel state information.

In a possible implementation manner, the first period includes at least one of an update period of the Doppler spread information and an update period of the delay spread information.

In a possible implementation, the apparatus further includes:

A cycle acquisition module, configured to read the register before acquiring the initial Wiener filter coefficient in the update cycle of the second channel state information according to the first channel state information during the update cycle of the second channel state information contains the channel state information, and obtains the first period and the second period;

The first obtaining module 620 includes:

a coefficient obtaining submodule, configured to obtain the second channel state information according to the first channel state information within the update cycle of the second channel state information when the first cycle and the second cycle meet a specified condition The initial Wiener filter coefficients in the update period of the channel state information.

In a possible implementation manner, the specified conditions include:

The ratio of the first period to the second period is greater than a proportional threshold.

To sum up, in this embodiment of the present application, the channel state information is divided into the first channel state information and the second channel state information according to their respective update cycles, and the first channel corresponding to the first cycle with a longer update cycle state information, calculate the corresponding initial Wiener filter coefficient in the first cycle, and then calculate the Wiener filter coefficient in each second cycle by updating the second channel state information corresponding to the second cycle with a shorter cycle and the initial Wiener filter coefficient filtering coefficients, so as to implement filtering processing on the channel estimation result in the second cycle through each Wiener filtering coefficient. It avoids the situation that the terminal needs to calculate the Wiener filter coefficient corresponding to the time slot according to the channel state information obtained in the time slot in each time slot, thereby reducing the real-time calculation amount of the Wiener filter coefficient calculation, and then The power consumption of the terminal is reduced.

FIG. 7 shows a structural block diagram of a terminal provided by an exemplary embodiment of the present application. The terminal may be an electronic device such as a smart phone, a tablet computer, an electronic book, a portable personal computer, etc., on which an application program is installed and run. The terminal in this application may include one or more of the following components: a processor 710 , a memory 720 and a screen 730 .

Processor 710 may include one or more processing cores. The processor 710 uses various interfaces and lines to connect various parts in the entire terminal, and executes the terminal's operation by running or executing the instructions, programs, code sets or instruction sets stored in the memory 720, and calling the data stored in the memory 720. Various functions and processing data. Optionally, the processor 710 may employ at least one of a digital signal processing (Digital Signal Processing, DSP), a Field-Programmable Gate Array (Field-Programmable Gate Array, FPGA), and a Programmable Logic Array (Programmable Logic Array, PLA). implemented in hardware. The processor 710 may integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU), a modem, and the like. Among them, the CPU mainly processes the operating system, user interface and application programs, etc.; the GPU is used for rendering and drawing the content that needs to be displayed on the screen 730; the modem is used for processing wireless communication. It can be understood that, the above-mentioned modem may not be integrated into the processor 710, and is implemented by a communication chip alone.

The memory 720 may include random access memory (Random Access Memory, RAM), or may include read-only memory (Read-Only Memory, ROM). Optionally, the memory 720 includes a non-transitory computer-readable storage medium. Memory 720 may be used to store instructions, programs, codes, sets of codes, or sets of instructions. The memory 720 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for implementing at least one function (such as a touch function, a sound playback function, an image playback function, etc.) , instructions for implementing the above method embodiments, etc., the operating system can be an Android (Android) system (including a system based on the deep development of the Android system), an IOS system developed by Apple (including a system based on the deep development of the IOS system) or other systems. The storage data area may also store data created by the terminal during use (such as phone book, audio and video data, chat record data) and the like.

The screen 730 may be a capacitive touch display screen for receiving a user's touch operation on or near it using any suitable object such as a finger, a stylus pen, etc., and displaying a user interface of various application programs. The touch display is usually located on the front panel of the terminal. The touch screen can be designed as a full screen, a curved screen or a special-shaped screen. The touch display screen can also be designed to be a combination of a full screen and a curved screen, or a combination of a special-shaped screen and a curved screen, which is not limited in the embodiments of the present application.

In addition, those skilled in the art can understand that the structure of the terminal shown in the above drawings does not constitute a limitation on the terminal, and the terminal may include more or less components than those shown in the drawings, or combine certain components, Or a different component arrangement. For example, the terminal further includes components such as a radio frequency circuit, a photographing component, a sensor, an audio circuit, a wireless fidelity (Wireless Fidelity, WiFi) component, a power supply, and a Bluetooth component, which will not be repeated here.

Embodiments of the present application further provide a computer-readable storage medium, where at least one computer instruction is stored in the computer-readable storage medium, and the at least one computer instruction is loaded and executed by a processor to implement the channel described in the above embodiments Estimated result processing method.

According to one aspect of the present application, there is provided a computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The processor of the terminal reads the computer instruction from the computer-readable storage medium, and the processor executes the computer instruction, so that the terminal executes the channel estimation result processing method provided in various optional implementation manners of the foregoing aspects.

An embodiment of the present application further provides a chip, which is configured to execute the method for processing a channel estimation result as described in each of the foregoing embodiments.

Those skilled in the art should realize that, in one or more of the above examples, the functions described in the embodiments of the present application may be implemented by hardware, software, firmware, or any combination thereof. When implemented in software, the functions may be stored in or transmitted over as one or more instructions or code on a computer-readable storage medium. Computer-readable storage media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage medium can be any available medium that can be accessed by a general purpose or special purpose computer.

The above descriptions are only optional embodiments of the present application, and are not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application shall be included in the protection of the present application. within the range.

Claims (16)

1. A method for processing a channel estimation result, wherein the method comprises: Acquire channel state information, where the channel state information includes first channel state information and second channel state information; the update cycle of the first channel state information is the first cycle, and the update cycle of the second channel state information is the first cycle two periods; the first period is greater than the second period; During the update period of the second channel state information, obtain the initial Wiener filter coefficient within the update period of the second channel state information according to the first channel state information; According to the initial Wiener filter coefficient and the second channel state information, obtain the Wiener filter coefficient in the update period of the second channel state information; According to the Wiener filter coefficient, filter processing is performed on the channel estimation result within the update period of the second channel state information. 2. The method according to claim 1, wherein The first channel state information includes: Doppler spread information, delay spread information, and signal-to-noise ratio; The second channel state information includes at least one of timing offset and frequency offset. 3 . The method according to claim 2 , wherein, within an update period of the second channel state information, within an update period of acquiring the second channel state information according to the first channel state information. 4 . The initial Wiener filter coefficients of , including: During the update period of the second channel state information, obtain the signal-to-noise ratio interval in which the signal-to-noise ratio in the first channel state information is located; obtaining a reference signal-to-noise ratio corresponding to the signal-to-noise ratio interval; According to the reference signal-to-noise ratio, an initial Wiener filter coefficient within an update period of the second channel state information is acquired. 4. The method according to claim 3, wherein the obtaining, according to the reference signal-to-noise ratio, an initial Wiener filter coefficient within an update period of the second channel state information comprises: When the initial Wiener filter coefficient corresponding to the reference signal-to-noise ratio already exists within the update period of the first channel state information, obtain the existing initial Wiener filter coefficient corresponding to the reference signal-to-noise ratio is the initial Wiener filter coefficient in the update period of the second channel state information. 5 . The method according to claim 3 , wherein the obtaining, according to the reference signal-to-noise ratio, an initial Wiener filter coefficient within an update period of the second channel state information comprises: 5 . When there is no initial Wiener filter coefficient corresponding to the reference signal-to-noise ratio within the update period of the first channel state information, according to the reference signal-to-noise ratio, the The Pler extension information and the delay extension information in the first channel state information are used to obtain the initial Wiener filter coefficients in the update period of the second channel state information. 6 . The method according to claim 2 , wherein, within an update period of the second channel state information, within an update period of acquiring the second channel state information according to the first channel state information. 7 . The initial Wiener filter coefficients of , including: According to the signal-to-noise ratio in the first channel state information, the Doppler spread information in the first channel state information, and the delay spread information in the first channel state information, Obtain the initial Wiener filter coefficients in the update period of the second channel state information. 7 . The method according to claim 2 , wherein, according to the initial Wiener filter coefficient and the second channel state information, the Wiener in the update period of the second channel state information is obtained. 8 . Filter coefficients, including: When the second channel state information includes the timing deviation, according to the timing deviation, rotate the coefficients in the frequency domain direction in the initial Wiener filter coefficients to obtain the update period of the second channel state information The Wiener filter coefficients in . 8 . The method according to claim 2 , wherein, according to the initial Wiener filter coefficient and the second channel state information, acquiring the Wiener in the update period of the second channel state information. 9 . Filter coefficients, including: When the second channel state information includes the frequency deviation, rotate the coefficients in the time domain direction in the initial Wiener filter coefficients according to the frequency deviation to obtain an update of the second channel state information Wiener filter coefficients in period. 9 . The method according to claim 2 , wherein the first period comprises at least one of an update period of the Doppler spread information and an update period of the delay spread information. 10 . The method according to any one of claims 1 to 8, wherein the second channel state information is acquired according to the first channel state information within an update period of the second channel state information The update period before the initial Wiener filter coefficients also includes: The channel state information is contained in the read register, and the first cycle and the second cycle are obtained; The obtaining, during the update period of the second channel state information, according to the first channel state information, the initial Wiener filter coefficients within the update period of the second channel state information includes: When the first period and the second period satisfy a specified condition, within the update period of the second channel state information, within the update period of acquiring the second channel state information according to the first channel state information The initial Wiener filter coefficients of . 11. The method according to claim 10, wherein the specified condition comprises: The ratio of the first period to the second period is greater than a proportional threshold. 12. An apparatus for processing a channel estimation result, wherein the apparatus comprises: an information acquisition module, configured to acquire channel state information, where the channel state information includes first channel state information and second channel state information; the update cycle of the first channel state information is a first cycle, and the second channel state information The update period of the information is the second period; the first period is greater than the second period; a first acquisition module, configured to acquire, within the update period of the second channel state information, an initial Wiener filter coefficient within the update period of the second channel state information according to the first channel state information; a second obtaining module, configured to obtain the Wiener filter coefficient within the update period of the second channel state information according to the initial Wiener filter coefficient and the second channel state information; The processing module is configured to perform filtering processing on the channel estimation result within the update period of the second channel state information according to the Wiener filter coefficient. 13. A terminal, characterized in that the terminal comprises a processor and a memory; at least one computer instruction is stored in the memory, and the at least one computer instruction is loaded and executed by the processor to realize the method as claimed in claim 1 . Any one of the channel estimation result processing methods described in to 11. 14. A computer-readable storage medium, wherein at least one computer instruction is stored in the computer-readable storage medium, and the computer instruction is loaded and executed by a processor to implement any one of claims 1 to 11. The channel estimation result processing method described above. 15. A computer program product, characterized in that the computer program product comprises computer instructions, and the computer instructions are executed by a processor of a terminal, so that the terminal performs the channel estimation according to any one of claims 1 to 11 Result processing method. 16 . A chip, characterized in that, the chip is configured to execute the channel estimation result processing method according to any one of claims 1 to 11 .

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