WO2023138263A1

WO2023138263A1 - Channel estimation result processing method and device, terminal and storage medium

Info

Publication number: WO2023138263A1
Application number: PCT/CN2022/138683
Authority: WO
Inventors: 高宁泊; 雷立辉
Original assignee: 哲库科技(北京)有限公司
Priority date: 2022-01-21
Filing date: 2022-12-13
Publication date: 2023-07-27
Also published as: CN114389920A; CN114389920B

Abstract

Provided are a channel estimation result processing method and device, a terminal and a storage medium, belonging to the technical field of communications. The method comprises: acquiring channel state information, the channel state information comprising first channel state information and second channel state information, the update period of the first channel state information being a first period, the update period of the second channel state information being a second period, and the first period being greater than the second period (201); within the update period of the second channel state information, acquiring, according to the first channel state information, an initial Wiener filter coefficient in the update period of the second channel state information (202); according to the initial Wiener filter coefficient and the second channel state information, acquiring a Wiener filter coefficient in the update period of the second channel state information (203); and performing, according to the Wiener filter coefficient, filtering processing on a channel estimation result. According to the described solution, the real-time calculation amount of Wiener filter coefficient calculation is reduced, and then the power consumption of the terminal is reduced.

Description

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

This application claims the priority of the Chinese patent application filed on January 21, 2022, with application number 202210072813.6, and the title of the invention is "channel estimation result processing method, device, terminal and storage medium", the entire content of which is incorporated by reference in this application.

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 channel estimation results.

Background technique

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

In related technologies, the minimum period of channel state information change in the system used for coefficient calculation is usually in units of time slots. Therefore, when calculating the coefficients, it is necessary to calculate the Wiener filter coefficients in units of the minimum period of the channel state information.

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

Contents of the invention

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

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

Acquiring channel state information, the channel state information including first channel state information and second channel state information; the update period of the first channel state information is the first period, and the update period of the second channel state information is the second period; the first period is greater than the second period;

In the update period of the second channel state information, acquire the initial Wiener filter coefficients in the update period of the second channel state information according to the first channel state information;

Acquiring Wiener filter coefficients within an update period of the second channel state information according to the initial Wiener filter coefficients and the second channel state information;

Filtering is performed on channel estimation results within an update period of the second channel state information according to the Wiener filter coefficients.

On the other hand, an embodiment of the present application provides an apparatus for processing channel estimation results, the apparatus including:

An information acquisition module, configured to acquire channel state information, the channel state information including first channel state information and second channel state information; the update period of the first channel state information is the first period, and the update period of the second channel state information is the second period; the first period is greater than the second period;

A first acquiring module, configured to acquire the initial Wiener filter coefficients in the update period of the second channel state information according to the first channel state information within the update period of the second channel state information;

A second acquisition module, configured to acquire Wiener filter coefficients within an update period of the second channel state information according to the initial Wiener filter coefficients and the second channel state information;

A processing module, configured to perform filtering processing on channel estimation results within an update period of the second channel state information according to the Wiener filter coefficients.

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 as described in the above aspect.

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 channel estimation result processing method as described in the above aspect.

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, and 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 at least include:

By dividing the channel state information into the first channel state information and the second channel state information according to the respective update periods, and calculating the corresponding initial Wiener filter coefficients in the first period through the first channel state information corresponding to the first period with a longer update period, and then calculating the Wiener filter coefficients in each second period through the second channel state information corresponding to the second period with a shorter update period and the initial Wiener filter coefficients, so as to implement filtering processing on channel estimation results in the second period through each Wiener filter 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 for calculating the Wiener filter coefficient, thereby reducing the power consumption of the terminal.

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.

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

Fig. 2 is a flow chart showing a method for processing channel estimation results according to an exemplary embodiment;

Fig. 3 is a flow chart showing a method for processing channel estimation results according to another exemplary embodiment;

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

Fig. 5 is a schematic diagram of enabling the power consumption reduction mode to perform coefficient calculation related to the embodiment shown in Fig. 3;

FIG. 6 is a structural block diagram of an apparatus for processing channel estimation results 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.

Detailed ways

In order to make the purpose, technical solution and advantages of the present application clearer, the implementation manners of the present application will be further described in detail below in conjunction with the accompanying drawings.

The "plurality" mentioned herein means two or more. "And/or" describes the association relationship of associated objects, indicating that there may be three types of relationships, for example, A and/or B may indicate: A exists alone, A and B exist simultaneously, and B exists independently. The character "/" generally indicates that the contextual 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 stations, micro base stations, relay stations, access points 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, long-term evolution) systems, it is called eNodeB (Evolved Node B, base station) or eNB for short; ) or gNB. As communications technology evolves, the description "base station" may change. For convenience in this embodiment of the application, the above-mentioned devices that provide wireless communication functions 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 a wireless modem, as well as various forms of user equipment, mobile stations (Mobile Station, MS), terminals (Terminal Device) and the like. For 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 the 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 services and services provided by the service provider.

The technical solution of the embodiment of the present application can be applied to various communication systems, such as: Global System of Mobile Communication (GSM) system, Code Division Multiple Access (CDMA) system, Wideband Code Division Multiple Access (WCDMA) system, General Packet Radio Service (General Packet Radio Service, GPRS), Long Term Evolution (Long Te rm Evolution, LTE) system, LTE Frequency Division Duplex (Frequency Division Duplex, FDD) system, LTE Time Division Duplex (Time Division Duplex, TDD) system, Advanced Long Term Evolution (LTE-A) system, New Radio (NR) system, NR system evolution 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 Networks (WLAN), Wireless Fidelity (WiFi), 6th generation mobile communication Technology (6-Generation, 6G) system, next-generation communication system or other communication systems, etc.

Generally speaking, the number of connections supported by traditional communication systems is limited and 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 (Device to Device, D2D) communication, machine-to-machine (Machine to Machine, M2M) communication, machine type communication (Machine Type Communication, MTC), inter-vehicle (Vehicle to Vehicle, V2V) communication and Internet of Vehicles ( Vehicle to Everything, V2X) system, etc. The embodiments of the present application may also be applied to these communication systems.

Fig. 2 shows a flowchart of a method for processing channel estimation results provided by an exemplary embodiment of the present application. Wherein, the channel estimation result processing method 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, acquire channel state information, the channel state information includes first channel state information and second channel state information; the update period of the first channel state information is the first period, and the update period of the second channel state information is the second period; the first period is greater than the second period.

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

Wherein, 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 include the first period, the update period of the second channel state information may include the second period, and the update period of the first channel state information is greater than the update period of the second channel state information.

For example, the update period of the first channel state information may be updated every x time slots, the update period of the second channel state information may be updated 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, time delay spread information, signal-to-noise ratio, timing offset, and frequency offset.

Wherein, when the terminal communicates while moving, the frequency of the received signal will change. This phenomenon may be called the Doppler effect, and the Doppler extension information may be the information of the frequency shift change of the signal determined by the terminal based on the Doppler effect. Due to the different distances that radio waves pass through each path, the arrival time of the transmitted wave in each path is different, which can cause multipath delay extension, thereby generating delay extension information. The signal-to-noise ratio is the ratio of signal power to noise power, and can be used to indicate the proportion of noise in the signal domain in the terminal.

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

In the embodiment of the present application, within the update period of the second channel state information, the terminal may acquire the initial Wiener filter coefficients 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 values corresponding to the first channel state information in the corresponding update periods remain unchanged, and the terminal can calculate the initial Wiener filter coefficient according to the first channel state information.

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

Since the corresponding values of the Doppler spread information, time delay spread information and SNR are unchanged in the respective update periods, when calculating the initial Wiener filter coefficients, there are cases where the Doppler spread information, time delay spread information and SNR values of multiple time intervals remain unchanged.

For example, if the update period of the first channel state information is 100 time slots, and the update period of the second channel state information is 20 time slots, the initial Wiener filter coefficients can be calculated according to the first channel state information every 20 time slots. If the values remain unchanged, it can be determined that the initial Wiener filter coefficients in time slots 0-20 and the initial Wiener filter coefficients in time slots 21-40 are the same value, and there is no need to perform additional coefficient calculations, thereby reducing the calculation amount of the terminal.

Step 203, according to the initial Wiener filter coefficients and the second channel state information, acquire Wiener filter coefficients within an update period of the second channel state information.

In the embodiment of the present application, after acquiring the initial Wiener filter coefficients of the current time slot, the terminal may calculate the Wiener filter coefficients 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 may be used to perform coefficient phase rotation on the initial Wiener filter coefficients, perform phase rotation on the initial Wiener filter coefficients in each update cycle according to the update cycle of the second channel state information, and obtain the Wiener filter coefficients in the update cycle of the second channel state information.

For example, if the update cycle of the first channel state information is 100 time slots, it can be determined that the initial Wiener filter coefficients in each interval of 100 time slots are the same, that is, the initial Wiener filter coefficients in time slots 0-100 may be a, the initial Wiener filter coefficients 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 by the second channel state information in the interval of every 20 time slots are the same, that is, the values of the second channel state information in the 0-20 time slots can all be p, and the values of the second channel state information in the 21-40 time slots can all be q. Since the initial Wiener filter coefficient in the 0-100 time slots can be a, the Wiener filter coefficients in each 20 time slots can be calculated and determined according to the second channel state information whose update period is 20 time slots, that is to say , the Wiener filter coefficients in the 0-20 time slot interval can be calculated according to a and p, the Wiener filter coefficients in the 21-40 time slot interval can be calculated according to a and q, and so on.

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

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

Since the Wiener filter coefficients calculated on each time slot in each update period of the second channel state information are the same, the channel estimation results in the update period can be filtered according to the corresponding Wiener filter coefficients in each update period of the second channel state information.

To sum up, in the embodiment of the present application, the channel state information is divided into first channel state information and second channel state information according to their respective update periods, and the corresponding initial Wiener filter coefficients in the first period are calculated by using the first channel state information corresponding to the first period with a longer update period, and then the Wiener filter coefficients in each second period are calculated by using the second channel state information and the initial Wiener filter coefficients corresponding to the second period with a shorter update period, so as to implement filtering processing on the channel estimation results in the second period through each Wiener filter 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 for calculating the Wiener filter coefficient, thereby reducing the power consumption of the terminal.

Fig. 3 shows a flowchart of a method for processing channel estimation results provided by an exemplary embodiment of the present application. Wherein, the channel estimation result processing method 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, acquire channel state information.

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

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

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 a timing offset and a frequency offset.

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

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

That is to say, the process of calculating Wiener filter coefficients may use Doppler spread information, timing deviation and signal-to-noise ratio, or the process of calculating Wiener filter coefficients may also use time delay spread information, frequency deviation and signal-to-noise ratio.

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

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

Step 302 , within an update period of the second channel state information, acquire a SNR interval in which the SNR in the first channel state information is located.

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

Wherein, since the signal-to-noise ratio belongs to short-term state information, that is, unlike the Doppler spread information and time-delay spread information, which can maintain the channel state information value in the first cycle, the signal-to-noise ratio can only maintain the channel state information value in a relatively short period of time.

In a possible implementation manner, the terminal obtains the SNR value on each time slot in the history record, determines the maximum value of the SNR value as the upper limit of the SNR range, determines the minimum value of the SNR value as the lower limit of the SNR range, obtains the SNR range, and equally divides the SNR range according to a preset quantization threshold to obtain each SNR range.

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

Step 303, acquiring a reference SNR corresponding to the SNR interval.

In the embodiment of the present application, the terminal determines the SNR interval corresponding to the SNR value according to the obtained SNR value, and obtains the reference SNR corresponding to the SNR interval.

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

Wherein, 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 SNR range of [-10, 40] is divided into 8 equal parts, 8 SNR intervals are obtained after obtaining the equal parts, and the medians in each SNR interval are obtained as -6, 0, 6, 12, 18, 24, 30, and 36 as the reference SNR corresponding to each SNR interval, and according to the obtained current SNR value, determine the SNR interval to which the current SNR value belongs, and obtain the reference SNR corresponding to the SNR interval .

By dividing the entire SNR range into a plurality of SNR intervals, and each SNR interval corresponds to a reference SNR, each reference SNR, that is, a quantized SNR value, is used to characterize each SNR value in the entire SNR range. The terminal only needs to calculate the initial Wiener filter coefficients corresponding to each reference signal-to-noise ratio to obtain the initial Wiener filter coefficients corresponding to each time slot in the entire first cycle, which greatly reduces the calculation amount of coefficients and reduces the power consumption of the terminal to a certain extent.

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

In the embodiment of the present application, the terminal may calculate the initial Wiener filter coefficients 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 obtaining the reference signal-to-noise ratio corresponding to each signal-to-noise ratio interval, each reference signal-to-noise ratio, and the Doppler spread information and timing deviation in the first channel state information are used in advance to calculate the initial Wiener filter coefficient corresponding to each reference signal-to-noise ratio, and store the reference signal-to-noise ratio and the corresponding initial Wiener filter coefficient. When the terminal acquires the signal-to-noise ratio of the current time slot, determine a reference signal-to-noise ratio corresponding to the signal-to-noise ratio, and determine the initial Wiener filter coefficient corresponding to the reference signal-to-noise ratio from the stored initial Wiener filter coefficients corresponding to the reference signal-to-noise ratio according to the determined reference signal-to-noise ratio.

Exemplarily, when it is determined that the reference SNR corresponding to each SNR range includes -6, 0, 6, 12, 18, 24, 30, and 36, since the values of the Doppler spread information and the delay spread information in the first cycle remain unchanged, the corresponding initial Wiener filter coefficients in the first cycle are pre-calculated according to each reference SNR. According to the determined reference signal-to-noise ratio, the initial Wiener filter coefficient corresponding to the reference signal-to-noise ratio is directly selected from each initial Wiener filter coefficient stored in advance as the initial Wiener filter coefficient obtained under 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 in the update period of the first channel state information, the existing initial Wiener filter coefficient corresponding to the reference signal-to-noise ratio 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 in the update period of the first channel state information, the initial Wiener filter coefficient in the update period of the second channel state information is obtained according to the reference signal-to-noise ratio, Doppler spread information in the first channel state information, and delay spread information in the first channel state information.

Wherein, when the terminal obtains the SNR value under the current time slot, it determines the SNR interval according to the SNR value under the current time slot, determines the corresponding reference SNR according to the determined SNR interval, and determines whether the initial Wiener filter coefficient corresponding to the reference SNR has been calculated. The corresponding reference signal-to-noise ratio is stored in the terminal. If the initial Wiener filter coefficient corresponding to the reference signal-to-noise ratio is calculated before the current time slot, the initial Wiener filter coefficient can be obtained from each stored initial Wiener filter coefficient 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 signal-to-noise ratio corresponding to the signal-to-noise ratio interval 1 is the reference signal-to-noise ratio A, and the initial Wiener filter coefficient corresponding to the reference signal-to-noise ratio A is calculated as 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 is the reference signal-to-noise ratio A, and can directly use the initial Wiener filter coefficient calculated in the previous time slot as the initial Wiener filter coefficient in the second time slot. When the terminal acquires the signal-to-noise ratio value c in the third time slot in the first cycle, the signal-to-noise ratio value c belongs to the signal-to-noise ratio interval 2, and the reference signal-to-noise ratio corresponding to the signal-to-noise ratio interval 2 is the reference signal-to-noise ratio B, the initial Wiener filter coefficient corresponding to the reference signal-to-noise ratio B can be calculated as the initial Wiener filter coefficient in the third time slot.

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

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

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

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

Wherein, the channel correlation coefficient of the frequency domain correlation can be obtained by calculating the distance information of the pilot pattern, the carrier spacing, and the time delay spread information estimated in real time. The channel correlation coefficient of the time domain correlation can be obtained by calculating 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,

Among them, the autocorrelation matrix is Φ _y , and the cross-correlation matrix is Φ _hh′ . The autocorrelation matrix is Φ _y can be calculated as,

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 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 as follows:

R(Δk)＝sin c(π×Δk×Δf×Delay)

Wherein, Δk is the distance information, Δf is the carrier spacing, and Delay is the time delay spread information estimated in real time.

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

R(Δn)＝sin c(2π×Δn×N _symb ×Doppler)

Among them, Δn is the distance information, N _symb is the symbol time, and Doppler is the Doppler spread information estimated in real time.

In a possible implementation, before obtaining the initial Wiener filter coefficients, the terminal reads the channel state information contained in the register to obtain the first cycle and the second cycle, and when the first cycle and the second cycle meet specified conditions, within the update cycle of the second channel state information, the initial Wiener filter coefficients in the update cycle of the second channel state information are obtained 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 a ratio threshold.

That is to say, the terminal can obtain the Wiener filter coefficients in two ways. One way is that the terminal can calculate the Wiener filter coefficients in real time by using the coefficient calculation module in the terminal to determine the shortest change cycle in the Doppler spread information, delay spread information, and signal-to-noise ratio information by enabling the default mode. Due to the influence of beam forming on the base station side in the 4G/5G system, the signal-to-noise ratio may change for each time slot. Therefore, the cycle of coefficient calculation can only use one time slot as the cycle. Another way is that by enabling the power reduction mode, the terminal can convert the short-term state information into long-term state information by quantizing the continuous SNR into multiple states, that is, the entire SNR range is divided into states with a specified threshold value, and each state corresponds to a reference SNR value. During the coefficient calculation process, the Doppler spread information, the value of the delay spread information, and the quantized reference SNR value of the current first cycle are used to calculate the specified threshold initial Wiener filter coefficients common to the current first cycle. The initial Wiener filter coefficients in the first cycle An initial coefficient set S can be formed.

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 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 an estimation process of Doppler spread information, time delay spread information and channel correlation coefficient, step 42 is a process of generating coefficients using SNR, Doppler spread information and time delay spread information, and step 43 is a process of coefficient selection (SNR estimation under the current time slot) and coefficient phase rotation. FIG. 5 is a schematic diagram of enabling a power consumption reduction mode to perform coefficient calculation 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 reduction mode can be enabled to calculate the coefficients, and the coefficients obtained by retaining the historical calculations are retained, and then the corresponding coefficients of each time slot are selected and rotated to calculate the coefficients of each time slot. Wherein, step 51 is an estimation process of Doppler spread information, time delay spread information and channel correlation coefficient, step 52 is a process of generating coefficients using SNR, Doppler spread information and time delay spread information, and step 53 is a process of coefficient selection (signal-to-noise ratio estimation under the current time slot) and coefficient phase rotation.

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

In order to ensure that the coefficient accuracy obtained by the coefficient calculation used for channel estimation does not affect the performance of the system, it is necessary to determine whether the first cycle corresponding to the first channel state information is far greater than the second cycle of the second channel state information before choosing to perform coefficient calculation in the reduced power mode. If the ratio between the first cycle and the second cycle is greater than the ratio threshold, the terminal has better cost performance when adopting the reduced power mode for coefficient calculation, and better maintains the balance between system performance and reduced power consumption.

Step 305, according to the initial Wiener filter coefficients and the second channel state information, acquire the Wiener filter coefficients within the update period of the second channel state information.

In the embodiment of the present application, the terminal calculates the Wiener filter coefficients in the update period of acquiring the second channel state information according to the acquired initial Wiener filter coefficients 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 a timing offset and a frequency offset.

In a possible implementation manner, when the second channel state information includes a timing offset, according to the timing offset, the coefficients in the frequency domain direction in the initial Wiener filtering coefficients are rotated to obtain the Wiener filtering coefficients within the update period of the second channel state information.

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

In a possible implementation manner, when the second channel state information includes a frequency deviation, according to the frequency deviation, the coefficients in the time domain direction of the initial Wiener filter coefficients are rotated to obtain the Wiener filter coefficients in the update period of the second channel state information.

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 time domain direction according to the acquired frequency deviation of the current update period of the second channel state information, to obtain the Wiener filter coefficient in the update period of the second channel state information.

Exemplarily, when the terminal acquires a change in the timing offset TO, it performs phase rotation on the channel correlation coefficient R(Δk), and multiplies R(Δk) by exp(2π×Δk×TO) to obtain Wiener filter coefficients. When the terminal obtains the change of the frequency deviation 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), it is necessary to determine the Wiener filter coefficients of each receiving antenna and CDM group respectively.

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

Step 306: Filter the channel estimation results within the update period of the second channel state information according to the Wiener filter coefficients.

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

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

Exemplarily, in the calculation process of the modem chip coefficients, by classifying the channel state information according to the update cycle, the coefficient calculation process is divided into two parts: coefficient generation and coefficient rotation. Long-term channel information is used for coefficient generation, and short-term information is used for coefficient rotation, which can effectively save the complexity of coefficient calculation. Especially in communication scenarios where base station scheduling strategies and channel changes are slow, the coefficient calculation amount can be effectively reduced without affecting channel estimation performance, thereby achieving the purpose of reducing system power consumption.

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

Table 1

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

the	复杂乘法运算complex multiplication	复杂加法运算complex addition	除法运算division operation
总计算复杂度Total Computational Complexity	6308863088	5515655156	380380
循环消耗cycle consumption	78867886	68946894	9595

Table 2

Fig. 6 shows a structural block diagram of an apparatus for processing channel estimation results 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, configured to acquire channel state information, where the channel state information includes first channel state information and second channel state information; the update period of the first channel state information is a first period, and the update period of the second channel state information is a second period; the first period is greater than the second period;

The first acquiring module 620 is configured to acquire the initial Wiener filter coefficients in the update period of the second channel state information according to the first channel state information within the update period of the second channel state information;

The second acquiring module 630 is configured to acquire Wiener filter coefficients within an update period of the second channel state information according to the initial Wiener filter coefficients and the second channel state information;

The processing module 640 is configured to perform filtering processing on channel estimation results within an update period of the second channel state information according to the Wiener filter coefficients.

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 a timing offset and a frequency offset.

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

An interval acquisition submodule, configured to acquire the SNR interval in which the SNR in the first channel state information is located within the update period of the second channel state information;

a reference acquisition submodule, configured to acquire a reference signal-to-noise ratio corresponding to the signal-to-noise ratio interval;

The first acquiring submodule is configured to acquire initial Wiener filter coefficients within an update period of the second channel state information according to the reference signal-to-noise ratio.

In a possible implementation manner, the first acquiring submodule includes:

The first acquiring unit is configured to acquire the existing initial Wiener filter coefficient corresponding to the reference signal-to-noise ratio as the initial Wiener filter coefficient in the update period of the second channel state information 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.

In a possible implementation manner, the first acquiring submodule includes:

The second acquisition unit is configured to acquire the initial Wiener filter coefficients in the update period of the second channel state information according to the reference signal-to-noise ratio, the Doppler spread information in the first channel state information, and the delay spread information in the first channel state information when there is no initial Wiener filter coefficient corresponding to the reference signal-to-noise ratio in the update period of the first channel state information.

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

An acquisition submodule, configured to acquire initial Wiener filter coefficients within an update period of the second channel state information 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.

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

The first coefficient acquisition submodule is configured to perform rotation processing on coefficients in the frequency domain direction in the initial Wiener filter coefficients according to the timing deviation when the second channel state information includes the timing deviation, and obtain Wiener filter coefficients within an update period of the second channel state information.

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

The second coefficient acquisition sub-module is configured to, when the second channel state information includes the frequency deviation, perform rotation processing on coefficients in the time domain direction of the initial Wiener filter coefficients according to the frequency deviation, and obtain Wiener filter coefficients within an 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 manner, the device further includes:

A cycle acquisition module, configured to read the channel state information contained in the register before obtaining the initial Wiener filter coefficients in the update cycle of the second channel state information according to the first channel state information in the update cycle of the second channel state information, and obtain the first cycle and the second cycle;

The first acquisition module 620 includes:

The coefficient acquisition submodule is used to acquire the initial Wiener filter coefficients in the update period of the second channel state information according to the first channel state information in the update period of the second channel state information when the first period and the second period meet specified conditions.

In a possible implementation manner, the specified conditions include:

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

Fig. 7 shows a structural block diagram of a terminal provided by an exemplary embodiment of the present application. The terminal may be a smart phone, a tablet computer, an e-book, a portable personal computer, and other electronic devices installed and running application programs. 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 of the entire terminal, and executes various functions of the terminal and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 720, and calling data stored in the memory 720. Optionally, the processor 710 may be implemented in at least one hardware form of Digital Signal Processing (Digital Signal Processing, DSP), Field-Programmable Gate Array (Field-Programmable Gate Array, FPGA), and Programmable Logic Array (Programmable Logic Array, PLA). The processor 710 may integrate one or a combination of a central processing unit (Central Processing Unit, CPU), an image processor (Graphics Processing Unit, GPU), a modem, and the like. Among them, the CPU mainly processes the operating system, the user interface and application programs, etc.; the GPU is responsible 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, but may be realized by a communication chip alone.

The memory 720 may include random access memory (Random Access Memory, RAM), and may also 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 program storage area and a data storage area, wherein the program storage 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-mentioned various method embodiments, and the like. The operating system may be an Android (Android) system (including a deeply developed system based on the Android system), an IOS system developed by Apple Inc. (including a deeply developed system based on the IOS system) or other systems. The storage data area can also store data (such as phone book, audio and video data, and chat record data) created by the terminal during use.

The screen 730 may be a capacitive touch display screen, which is used for receiving user's touch operation on or near it with any suitable object such as a finger or a stylus, and displaying user interfaces of various application programs. The touch screen is usually set on the front panel of the terminal. Touch screens can be designed as full screens, curved screens or special-shaped screens. The touch display screen can also be designed as 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 this embodiment of the present application.

In addition, those skilled in the art can understand that the structure of the terminal shown in the above figures does not constitute a limitation on the terminal, and the terminal may include more or less components than those shown in the figure, or combine certain components, or arrange different components. For example, the terminal also 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.

The embodiment of the present application also provides a computer-readable storage medium, 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 estimation result processing method described in the above embodiments.

According to an 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 implement the method for processing a channel estimation result as described in the foregoing embodiments.

Those skilled in the art should be aware that, in the foregoing one or more 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 on 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 media may be any available media 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 within the protection scope of the present application.

Claims

A method for processing channel estimation results, characterized in that the method is executed by a terminal, and the method includes:

Acquiring channel state information, the channel state information including first channel state information and second channel state information; the update period of the first channel state information is the first period, and the update period of the second channel state information is the second period; the first period is greater than the second period;

In the update period of the second channel state information, acquire the initial Wiener filter coefficients in the update period of the second channel state information according to the first channel state information;

Acquiring Wiener filter coefficients within an update period of the second channel state information according to the initial Wiener filter coefficients and the second channel state information;

Filtering is performed on channel estimation results within an update period of the second channel state information according to the Wiener filter coefficients.
The method according to claim 1, characterized in that,

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 a timing offset and a frequency offset.
The method according to claim 2, wherein said acquiring the initial Wiener filter coefficients in the update period of the second channel state information according to the first channel state information within the update period of the second channel state information comprises:

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

Acquiring a reference signal-to-noise ratio corresponding to the signal-to-noise ratio interval;

Acquiring initial Wiener filter coefficients in an update period of the second channel state information according to the reference signal-to-noise ratio.
The method according to claim 3, wherein the obtaining the initial Wiener filter coefficients in the update period of the second channel state information according to the reference signal-to-noise ratio comprises:

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, acquire the existing initial Wiener filter coefficient corresponding to the reference signal-to-noise ratio as the initial Wiener filter coefficient in the update period of the second channel state information.
The method according to claim 3, wherein the obtaining the initial Wiener filter coefficients in the update period of the second channel state information according to the reference signal-to-noise ratio comprises:

When there is no initial Wiener filter coefficient corresponding to the reference signal-to-noise ratio in 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 delay spread information in the first channel state information, acquire the initial Wiener filter coefficient in the update period of the second channel state information.
The method according to claim 2, wherein said acquiring the initial Wiener filter coefficients in the update period of the second channel state information according to the first channel state information within the update period of the second channel state information comprises:

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, acquire the initial Wiener filter coefficients in the update period of the second channel state information.
The method according to claim 2, characterized in that, according to the initial Wiener filter coefficient and the second channel state information, obtaining the Wiener filter coefficient within the update period of the second channel state information includes:

When the second channel state information includes the timing offset, according to the timing offset, the coefficients in the frequency domain direction in the initial Wiener filter coefficients are rotated to obtain Wiener filter coefficients within an update period of the second channel state information.
The method according to claim 2, characterized in that, according to the initial Wiener filter coefficient and the second channel state information, obtaining the Wiener filter coefficient within the update period of the second channel state information includes:

When the second channel state information includes the frequency deviation, according to the frequency deviation, the coefficients in the time domain direction of the initial Wiener filter coefficients are rotated to obtain the Wiener filter coefficients within the update period of the second channel state information.
The method according to claim 2, wherein 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.
The method according to any one of claims 1 to 8, wherein the method further comprises:

Read the channel state information contained in the register to obtain the first cycle and the second cycle;

The acquiring the initial Wiener filter coefficients in the update period of the second channel state information according to the first channel state information 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, acquire initial Wiener filter coefficients within the update period of the second channel state information according to the first channel state information.
The method according to claim 10, wherein the specified conditions include:

A ratio of the first period to the second period is greater than a ratio threshold.
A device for processing channel estimation results, characterized in that the device includes:

An information acquisition module, configured to acquire channel state information, the channel state information including first channel state information and second channel state information; the update period of the first channel state information is the first period, and the update period of the second channel state information is the second period; the first period is greater than the second period;

A first acquiring module, configured to acquire the initial Wiener filter coefficients in the update period of the second channel state information according to the first channel state information within the update period of the second channel state information;

A second acquisition module, configured to acquire Wiener filter coefficients within an update period of the second channel state information according to the initial Wiener filter coefficients and the second channel state information;

A processing module, configured to perform filtering processing on channel estimation results within an update period of the second channel state information according to the Wiener filter coefficients.
A terminal, characterized in that 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, so that the terminal implements the channel estimation result processing method according to any one of claims 1 to 11.
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, so that the terminal implements the channel estimation result processing method according to any one of claims 1 to 11.
A computer program product, characterized in that the computer program product includes computer instructions, and the computer instructions are executed by a processor of the terminal, so that the terminal executes the channel estimation result processing method according to any one of claims 1 to 11.
A chip, characterized in that the chip is used to execute the channel estimation result processing method according to any one of claims 1 to 11.