WO2021036999A1

WO2021036999A1 - Channel estimation method and apparatus, and computer storage medium

Info

Publication number: WO2021036999A1
Application number: PCT/CN2020/110854
Authority: WO
Inventors: 黄静月; 魏浩; 李萍; 李�杰
Original assignee: 中兴通讯股份有限公司
Priority date: 2019-08-23
Filing date: 2020-08-24
Publication date: 2021-03-04
Also published as: CN112422458A; CN112422458B

Abstract

Disclosed are a channel estimation method and apparatus, and a computer storage medium. The method comprises: acquiring N pilot signals, wherein the N pilot signals are continuous pilot signals received by means of the same antenna, or the N pilot signals are continuous pilot signals received when pilot signals are sent at a sending end by means of the same antenna, and N is a positive integer less than the total number of the pilot signals; and calculating, using the N pilot signals, equivalent channels, at the sending end or a receiving end, corresponding to the N pilot signals.

Description

Channel estimation method, device and computer storage medium

This application claims the priority of a Chinese patent application filed with the Chinese Patent Office with an application number of 201910786241.6 on August 23, 2019, and the entire content of the application is incorporated into this application by reference.

Technical field

This application relates to the field of information processing, for example, to a channel estimation method, device, and computer storage medium.

Background technique

With the continuous increase of mobile data traffic, the shortage of frequency band resources has gradually become a bottleneck restricting the development of wireless communication systems. The introduction of the millimeter wave frequency band provides new opportunities for solving the problem of shortage of frequency bands. However, the high frequency characteristics of the millimeter wave channel make rain attenuation and path loss effects particularly serious, and it is necessary to deploy a large-scale antenna array at the base station to provide sufficient power gain. The deployment of antenna arrays greatly increases the complexity of channel estimation.

In the related art, the channel estimation schemes of the millimeter wave system are all based on decoupling the path gain and angle information, and after separately estimating the gain and angle, the channel is synthesized. Although the pilot signal overhead can be reduced, high-dimensional channels need to be calculated and processed. The requirements for hardware and software are relatively strict, and the use in actual scenarios is greatly restricted.

Summary of the invention

The embodiments of the present application provide a channel estimation method, device, and computer storage medium, which can reduce computational complexity.

The embodiment of the present application provides a channel estimation method, including:

Obtain N pilot signals, where N pilot signals are continuous pilot signals received using the same antenna, or N pilot signals are continuous pilot signals received by the transmitting end when using the same antenna to transmit pilot signals The pilot signal of, where N is a positive integer less than the total number of pilot signals;

Using the N pilot signals, calculate the equivalent channels of the transmitting end or the receiving end corresponding to the N pilot signals.

A channel estimation device includes a processor and a memory, the memory stores a computer program, and the processor is configured to call the computer program in the memory to implement any of the methods described above.

A computer storage medium in which one or more programs are stored in the computer-readable storage medium, and the one or more programs can be executed by one or more processors to implement any one of the above-mentioned methods.

The embodiment of the present application provides another channel estimation method, including:

Obtain K ₁ + K ₂ pilot signals, where K ₁ pilot signals are continuous pilot signals received using the same antenna, and K ₂ pilot signals are when the same antenna is used to transmit the pilot signal at the transmitting end , The received continuous pilot signal; where K ₁ and K ₂ are both positive integers;

Calculate the equivalent channels of the transmitting end corresponding to _{K 1} pilot signals and the equivalent channels of the receiving end corresponding to _{K 2} pilot signals by using any of the above-mentioned methods;

The equivalent channel of the transmitting end corresponding to the K ₁ _{pilot signals and the equivalent channel of the receiving end corresponding to the K 2} pilot signals are used to calculate the original channel estimation matrix.

A channel estimation device includes a processor and a memory, the memory stores a computer program, and the processor is configured to call the computer program in the memory to implement the method described above.

A computer storage medium in which one or more programs are stored in the computer-readable storage medium, and the one or more programs can be executed by one or more processors to implement the method described above.

Description of the drawings

The accompanying drawings are used to provide an understanding of the technical solution of the present application, and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the technical solution of the present application, and do not constitute a limitation to the technical solution of the present application.

FIG. 1 is a flowchart of a channel estimation method provided by an embodiment of the application;

FIG. 2 is a flowchart of another channel estimation method provided by an embodiment of the application;

Fig. 3 is a flowchart of a channel estimation method provided in exemplary embodiment 1 of this application.

detailed description

Hereinafter, embodiments of the present application will be described with reference to the drawings. The steps shown in the flowcharts of the drawings can be executed in a computer system such as a set of computer-executable instructions. And, although a logical sequence is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than here.

Fig. 1 is a flowchart of a channel estimation method provided by an embodiment of the application. The method shown in Figure 1 includes:

Step 110: Obtain N pilot signals, where N pilot signals are continuous pilot signals received using the same antenna, or N pilot signals are received when the transmitting end uses the same antenna to transmit pilot signals The received continuous pilot signal, where N is a positive integer less than the total number of pilot signals.

In an exemplary embodiment, the selection of the same antenna may be randomly selected, or an antenna may be determined according to a preset selection strategy, and the selection strategy may be a preset antenna usage order or antenna number calculation formula, etc.

Step 120: Use the N pilot signals to calculate equivalent channels of the transmitting end or the receiving end corresponding to the N pilot signals.

In an exemplary embodiment, the continuous pilot signals received using the same antenna can be used to estimate the equivalent channel of the pilot signal transmitting end; the continuous pilot signals received when the pilot signal is transmitted using the same antenna at the transmitting end The frequency signal can be used to estimate the equivalent channel at the receiving end of the pilot signal to achieve the purpose of decoupling the receiving end and the transmitting end.

In an exemplary embodiment, the number of obtained pilot signals is part of the pilot signals, and a part of the total number of pilot signals is used to calculate the equivalent channel of the transmitting end or the receiving end of the pilot signal. The original channel matrix is decoupled into two parts: the equivalent channel of the transmitting end and the equivalent channel of the receiving end, which controls the calculation scale and effectively reduces the calculation complexity.

The method provided in the embodiment of this application obtains N pilot signals, where the N pilot signals are continuous pilot signals received using the same antenna, or the continuous pilot signals received when the same antenna is used to transmit the pilot signal at the transmitting end Using the N pilot signals to calculate the equivalent channel of the transmitting end or the receiving end corresponding to the N pilot signals, to realize the channel decoupling between the receiving end and the transmitting end, and use the part of the total number of pilot signals to send Separate calculation of equivalent channels at the end or the receiving end, effectively reducing the computational complexity.

The following describes the method provided by the embodiment of the present application:

In an exemplary embodiment, the calculating the equivalent channels of the receiving end or the transmitting end corresponding to the N pilot signals by using the N pilot signals includes: obtaining the equivalent channel corresponding to the equivalent sparse channel to be corrected An angle domain correction matrix, wherein the equivalent sparse channel to be corrected is calculated by using the N pilot signals; and the equivalent sparse channel to be corrected is processed according to the obtained angle domain correction matrix to obtain The corrected equivalent sparse channel in the angle domain; the equivalent sparse channel in the corrected angle domain is used to obtain the equivalent channel of the transmitting end or the receiving end.

In this exemplary embodiment, the equivalent sparse channel to be corrected can be obtained by the calculation method of the sparse channel in the related technology; after the equivalent sparse channel to be corrected is obtained, the angle domain correction matrix is obtained, and the angle domain correction matrix is used. The obtained equivalent sparse channel is corrected, and based on the corrected equivalent sparse channel in the angle domain, channel reconstruction is performed to obtain the original channel estimate.

Compared with the processing method in the related art based on decoupling the path gain and angle information and separately estimating the gain and angle, this application decouples the receiving end and the transmitting end when the pilot signal is received, and only calculates the angle domain. Information, to achieve the purpose of separately estimating the equivalent sparse channel of the receiving end and the transmitting end, the processing method is obviously different, and the calculation amount is significantly reduced.

In an exemplary embodiment, the obtaining the angle domain correction matrix corresponding to the equivalent sparse channel to be corrected includes: obtaining a rotation matrix; using the rotation matrix to process the angle domain transformation matrix obtained in advance to obtain the angle Domain correction matrix.

In this exemplary embodiment, the angle domain information is calculated by using the changed rotation angle, which effectively solves the problem of low dimensional estimation accuracy of the antenna array in the related art, and improves the processing accuracy of the channel estimation operation.

In an exemplary embodiment, said using the equivalent sparse channel of the corrected angle domain to obtain the equivalent channel of the transmitting end or the receiving end includes: calculating the equivalent sparse channel corresponding to the corrected angle domain The estimated channel; using the pre-acquired angle domain inverse transformation matrix, the estimated channel is processed to obtain the equivalent channel of the transmitting end or the receiving end, wherein the angle domain inverse transformation matrix is the inverse of the angle domain transformation matrix Transformation matrix.

In this exemplary embodiment, by calculating the estimated channel corresponding to the equivalent sparse channel in the angle domain after the correction, and then using the angle domain inverse transformation matrix to obtain the equivalent channel at the transmitting end or the receiving end, the calculation operation is a channel estimation operation And matrix inverse transformation operation, low computational complexity.

In an exemplary embodiment, the rotation matrix includes a changed angle parameter; calculating the estimated channel corresponding to the equivalent sparse channel in the angle domain after correction includes: under the angle domain correction matrix corresponding to different angle parameters, Calculate the estimated channel corresponding to the equivalent sparse channel in the corrected angle domain; according to the preset estimation channel selection strategy, from the calculated estimation channels, select the estimation channel that meets the estimation channel selection strategy as the required estimation channel Estimate the channel.

In this exemplary embodiment, a plurality of angle domain correction matrices can be obtained by using the angle parameters changed in the rotation matrix. Under each angle domain correction matrix, the corresponding estimated channel can be obtained respectively, thereby obtaining multiple sets of channel estimation values. , Select the estimated channel as the final equivalent channel estimation to meet different design needs.

In an exemplary embodiment, the selection strategy of the estimated channel is determined according to the calculation accuracy and the calculation complexity of the calculation operation of the estimated channel.

In this exemplary embodiment, setting the selection strategy of the estimated channel based on the channel estimation accuracy and implementation complexity can achieve a compromise and adjustment between hardware cost and processing efficiency.

In an exemplary embodiment, the angle domain transformation matrix is an inverse Fourier transform (Discrete Fourier Transformation, DFT) matrix.

The angle domain inverse transformation matrix is an inverse discrete Fourier transform (Inverse Discrete Fourier Transforamation, IDFT) matrix.

In this exemplary embodiment, the DFT matrix is used to transform the angle domain, and the operation is highly versatile.

Fig. 2 is a flowchart of another channel estimation method provided by an embodiment of the application. The method shown in Fig. 2 includes:

Step 210: Obtain K ₁ + K ₂ pilot signals, where K ₁ pilot signals are continuous pilot signals received by using the same antenna, and K ₂ pilot signals are transmitted by using the same antenna at the transmitting end. The continuous pilot signal received when the frequency signal is used.

In an exemplary embodiment, the upstream system is taken as an example, the total number of pilot signals is K ₁ +K ₂ , and both the receiving end and the transmitting end adopt the antenna switch strategy. When the first K ₁ pilot signals are sent, the transmitting end is at Each time slot enables one antenna for transmission according to a certain strategy, and the receiving end _{fixes one antenna for reception in the first K 1} time slot; when sending K ₂ pilot signals, the transmitting end _{fixes one in the next K 2} time slots. The antenna transmits, and the receiving end enables an antenna to receive in each time slot according to a certain strategy.

Step 220: Calculate the equivalent channels of the transmitting end corresponding to the _{K 1} pilot signals and the equivalent channels of the receiving end corresponding to the _{K 2} pilot signals by using any of the above-mentioned methods.

Step 230: Use the equivalent channels of the transmitting end corresponding to the _{K 1} _{pilot signals and the equivalent channels of the receiving end corresponding to the K 2} pilot signals to calculate the original channel estimation matrix.

In the method provided by the embodiment of the application, by obtaining K ₁ + K ₂ pilot signals, the channels of the receiving end and the transmitting end are decoupled, the high-dimensional overall channel matrix is split into two parts, and then K ₁ pilot signals are calculated separately. The equivalent channel corresponding to the frequency signal and the equivalent channel corresponding to the K ₂ pilot signals are obtained, and the equivalent channels corresponding to the transmitting end and the receiving end are obtained. After the equivalent channels of the receiving end and the transmitting end are estimated, the original channel is synthesized , Can significantly reduce the computational complexity and pilot signal overhead, while ensuring extremely high accuracy.

Hereinafter, the method provided by the embodiment of this application will be described with the embodiment of this application:

Exemplary embodiment one

Fig. 3 is a flowchart of a channel estimation method provided in exemplary embodiment 1 of this application. The method shown in Figure 3 includes the following steps:

Step one is to receive the pilot signal based on the antenna switch strategy. In the same time slot, only one antenna is enabled on the receiving end and the transmitting end, and the other antennas are in the off state. The received signal of the first M ₁ time slot, defined as y _r , can be used to estimate the equivalent channel of the receiving end; _{the received signal of the last M 2} time slots, defined as y _t , can be used to estimate the equivalent channel of the transmitting end.

As shown in Figure 3, the reception of pilot signals is controlled in the following ways, including:

Initialize the pilot index, where m _r =0 and m _t =0.

The transmitting end fixes an antenna to send the pilot signal m _r , and the receiving end enables an antenna to receive the pilot signal m _r . After successfully receiving 1 pilot signal, _{the value of m r} is increased by 1, that is, m _r = m _r +1, And so on, until m _r =M ₁ .

The transmitting end enables one antenna to transmit the pilot signal m _t , and the receiving end fixes an antenna to receive the pilot signal m _t . Each time a pilot signal is successfully received, _{the value of m t} is increased by 1, that is, m _t = m _t +1, And so on, until m _t =M ₂ .

Step 2: Perform channel sparsity extraction based on the phase rotation corrected DFT matrix, use Orthogonal Matching Pursuit (OMP) algorithm to estimate the sparse channel, and then perform channel reconstruction.

As shown in Figure 3, taking the estimation of the equivalent channel η _r at the receiving end as an example, the description is as follows:

The DFT matrix is F. Since the accuracy of the DFT matrix is limited by the dimensions of the antenna array, in order to improve the estimation accuracy, the rotation matrix Φ(x) is introduced, and the angle-corrected DFT matrix is

x represents the angle of rotation.

Using the angle-corrected DFT matrix

Transform the equivalent channel η _r at the receiving end to the angle domain to explore its sparsity.

Obtain the corresponding angle domain estimation channel based on OMP algorithm

In this process, the value of x can be adjusted continuously to improve the estimation accuracy.

Use the angle-corrected IDFT matrix

Find the final estimated channel

Similarly, the equivalent channel of the sender

It can be obtained by the above method.

Step 3: Use the estimated equivalent channels of the receiving end and the transmitting end

with

Get the original channel estimation matrix

The method provided in the first embodiment of the application, based on the sparsity of the millimeter wave channel, decouples the receiving end and the transmitting end, and estimates the channels separately, which effectively reduces the computational complexity, and continuously modifies the DFT matrix by adjusting the granularity of the rotation angle , It is possible to compromise and adjust the channel estimation accuracy and implementation complexity.

Exemplary embodiment two

A channel estimation method provided by the second exemplary embodiment of the present application includes the following steps:

Step 1: Set the number of pilot signals M ₁ =M ₂ =16, and both the receiving end and the transmitting end deploy antenna arrays with dimensions of 8×8. In the process of sending the pilot signal, the Media Access Control (MAC) layer needs to indicate the position of the antenna that is currently enabled on the transmitting end and the position of the antenna that is enabled on the receiving end. The received signal y _{r of the} first M ₁ time slot can be used to estimate the equivalent channel of the receiving end; the received signal y _{t of the} _{last M 2} time slots can be used to estimate the equivalent channel of the transmitting end. In order to simulate the linkage between the MAC layer and the physical layer, in the first M ₁ time slots, the transmitter fixes any antenna for transmission, and the antenna position enabled by the receiver in each time slot is generated based on a pseudo-random sequence; In M ₂ time slots, the position of the antenna enabled for each time slot at the transmitting end is generated based on a pseudo-random sequence, and the receiving end fixes any antenna for reception.

Step 2: Taking the estimation of the equivalent channel η _{r at the} receiving end as an example, set the rotation angle range of the receiving end and the sending end

Rotation factor δ = 0.1, 0.05, 0.02, the corresponding rotation step length is

Using the angle-corrected DFT matrix

Transform η _r into the angle domain, each item of the DFT matrix F is

And there are p, q=0,...,7. The rotation matrix Φ(x) is an 8×8 diagonal matrix, Φ(x)=diag{[1,e ^jx ,...,e ^j7x ]}. Use OMP algorithm to find the corresponding angle domain estimation channel

In this process, x can be adjusted continuously to improve the estimation accuracy. Finally, the IDFT matrix after angle correction is used

Find the final estimated channel

The equivalent channel of the sender

It can be estimated by similar methods.

with

Get the original channel estimation matrix

The performance simulation results of Normalized Mean Square Error (Normalized Mean Square Error, NMSE) are shown in Table 1. As shown in Table 1, the smaller the rotation step size, the higher the accuracy of the channel estimation obtained, and the computational complexity will increase accordingly. It is necessary to compromise between accuracy and implementation complexity by adjusting the rotation angle.

The method provided in the second embodiment of the application, based on the sparsity of the millimeter wave channel, decouples the receiving end and the transmitting end, and estimates the channels separately, effectively reducing the computational complexity, and continuously modifying the DFT matrix by adjusting the granularity of the rotation angle , It is possible to compromise and adjust the channel estimation accuracy and implementation complexity. The smaller the rotation step size, the higher the accuracy of the channel estimation obtained, and the computational complexity will increase accordingly. It is necessary to compromise between accuracy and implementation complexity by adjusting the rotation angle.

Table 1 NMSE performance under different rotation factors (dB)

Exemplary embodiment three

A channel estimation method provided by the third exemplary embodiment of the present application includes the following steps:

Step 1: Set the number of pilot signals M ₁ =M ₂ =8, 10, 12, 14, 16, and both the receiving end and the transmitting end deploy antenna arrays with dimensions of 8×8. In the process of sending the pilot signal, the MAC layer needs to indicate the position of the antenna that is currently enabled on the transmitting end and the position of the antenna that is enabled on the receiving end. The received signal y _{r of the} first M ₁ time slot can be used to estimate the equivalent channel of the receiving end; the received signal y _{t of the} _{last M 2} time slots can be used to estimate the equivalent channel of the transmitting end. In order to simulate the linkage between the MAC layer and the physical layer, in the first M ₁ time slots, the transmitting end fixes any antenna for transmission, and the antenna position enabled for each time slot at the receiving end is generated based on a pseudo-random sequence; _{In the two} time slots, the antenna position enabled by the transmitting end is generated based on a pseudo-random sequence, and the receiving end fixes any antenna for transmission.

Rotation factor δ = 0.1, the corresponding rotation step length is

Using the angle-corrected DFT matrix

Transform η _r into the angle domain, each item of the DFT matrix F is

And there are p, q=0,...,7. The rotation matrix Φ(x) is an 8×8 diagonal matrix, Φ(x)=diag{[1,e ^jx ,...,e ^j7x ]}. Use the OMP algorithm to find the angle domain estimation channel corresponding to _{η r}

Find the final estimated channel

The equivalent channel of the sender

It can be estimated by similar methods.

with

Get the original channel estimation matrix

The NMSE performance simulation results are shown in Table 2. It can be seen from Table 2 that when δ=0.1, when the channel estimation operation is performed, the number of pilot signals M≥8 can already meet the channel estimation requirements.

The method provided in the third embodiment of the application, based on the sparsity of the millimeter wave channel, decouples the receiving end and the transmitting end, and estimates the channels separately, effectively reducing the computational complexity, and continuously modifying the DFT matrix by adjusting the granularity of the rotation angle , It is possible to compromise and adjust the channel estimation accuracy and implementation complexity. When the rotation factor δ=0.1, the number of pilot signals M≥14 can already meet the channel estimation requirement.

Table 2 NMSE performance under different pilot numbers (dB)

An embodiment of the present application provides a channel estimation device, including a processor and a memory, the memory stores a computer program, and the processor is used to call the computer program in the memory to implement the following operations, including: obtaining N pilots Signal, where N pilot signals are continuous pilot signals received using the same antenna, or N pilot signals are continuous pilot signals received when the transmitting end uses the same antenna to transmit pilot signals , Where N is a positive integer smaller than the total number of pilot signals; the N pilot signals are used to calculate the equivalent channels of the transmitting end or the receiving end corresponding to the N pilot signals.

In an exemplary embodiment, the processor invokes a computer program in the memory to realize the use of the N pilot signals to calculate the equivalent of the transmitting end or the receiving end corresponding to the N pilot signals. Channel operations include: obtaining an angle domain correction matrix corresponding to the equivalent sparse channel to be corrected, where the equivalent sparse channel to be corrected is calculated by using the N pilot signals; and according to the obtained angle domain The correction matrix processes the equivalent sparse channel to be corrected to obtain the equivalent sparse channel in the angle domain after correction; using the equivalent sparse channel in the angle domain after the correction to obtain the equivalent channel at the transmitting end or the receiving end .

In an exemplary embodiment, the processor calls a computer program in the memory to implement the operation of obtaining the angle domain correction matrix corresponding to the equivalent sparse channel to be corrected, including: obtaining a rotation matrix; using the The rotation matrix processes the angle domain transformation matrix obtained in advance to obtain the angle domain correction matrix.

In an exemplary embodiment, the processor calls a computer program in the memory to implement the operation of using the equivalent sparse channel of the modified angle domain to obtain the equivalent channel of the transmitting end or the receiving end, It includes: calculating the estimated channel corresponding to the equivalent sparse channel in the corrected angle domain; processing the estimated channel by using a pre-acquired angle domain inverse transform matrix to obtain the equivalent channel at the transmitting end or the receiving end, wherein, The angle domain inverse transformation matrix is an inverse transformation matrix of the angle domain transformation matrix.

In an exemplary embodiment, the processor invoking a computer program in the memory to implement the calculation of the estimated channel corresponding to the equivalent sparse channel in the corrected angle domain includes: When changing the angle parameter, under the multiple angle domain correction matrices corresponding to the changed angle parameter, calculate the multiple estimated channels corresponding to the equivalent sparse channels of the multiple corrected angle domains; according to the preset estimation channel selection The strategy is to select an estimated channel that conforms to the preset estimation channel selection strategy from the multiple estimated channels obtained by calculation as the required estimated channel.

In an exemplary embodiment, the preset estimation channel selection strategy implemented by the processor calling the computer program in the memory is determined according to the calculation accuracy and the calculation complexity of the calculation operation of the estimation channel.

In an exemplary embodiment, the processor invokes a computer program in the memory to implement the angle domain transformation matrix as a DFT matrix.

The device provided in the embodiment of the present application obtains N pilot signals, where the N pilot signals are continuous pilot signals received using the same antenna, or the N pilot signals are transmitted using the same antenna at the transmitting end The continuous pilot signal received when the pilot signal is used, the N pilot signals are used to calculate the equivalent channel of the transmitting end or the receiving end corresponding to the N pilot signals, and the channel decoupling between the receiving end and the transmitting end is realized , Effectively reduce the computational complexity.

An embodiment of the present application provides a channel estimation device, including a processor and a memory, the memory stores a computer program, and the processor is used to call the computer program in the memory to implement the following operations, including: obtaining K ₁ +K ₂ pilot signals, of which K ₁ pilot signal is the continuous pilot signal received by the same antenna, and K ₂ pilot signals are the continuous pilot signal received when the transmitting end uses the same antenna to transmit the pilot signal Pilot signal; where K ₁ and K ₂ are both positive integers; using any of the methods described above, respectively calculate the equivalent channel of the transmitting end corresponding to _{K 1} _{pilot signals and the corresponding corresponding to K 2} pilot signals The equivalent channel of the receiving end; the equivalent channel of the transmitting end corresponding to _{K 1} _{pilot signals and the equivalent channel of the receiving end corresponding to K 2} pilot signals are used to calculate the original channel estimation matrix.

The device provided in this embodiment of the application obtains K ₁ + K ₂ pilot signals, decouples the channels of the receiving end and the transmitting end, splits the high-dimensional overall channel matrix into two parts, and then calculates K ₁ pilot signals respectively. The equivalent channel of the transmitting end corresponding to the frequency signal and the equivalent channel _{of the receiving end corresponding to the K 2} pilot signals. After the equivalent channels of the receiving end and the transmitting end are estimated, the original channel is synthesized, which can significantly reduce the computational complexity and The overhead of the pilot signal while ensuring extremely high accuracy.

An embodiment of the present application provides a computer storage medium, the computer-readable storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the following methods, including: Obtain N pilot signals, where N pilot signals are continuous pilot signals received using the same antenna, or N pilot signals are continuous pilot signals received when the transmitting end uses the same antenna to transmit pilot signals Wherein, N is a positive integer less than the total number of pilot signals; the N pilot signals are used to calculate the equivalent channels of the transmitting end or the receiving end corresponding to the N pilot signals.

In an exemplary embodiment, the one or more programs may be executed by one or more processors to realize the use of the N pilot signals to calculate the sending end corresponding to the N pilot signals Or the equivalent channel at the receiving end, including: obtaining an angle domain correction matrix corresponding to the equivalent sparse channel to be corrected, wherein the equivalent sparse channel to be corrected is calculated by using the N pilot signals; The angle domain correction matrix processes the equivalent sparse channel to be corrected to obtain the equivalent sparse channel in the angle domain after correction; the equivalent sparse channel in the angle domain after the correction is used to obtain the Equivalent channel.

In an exemplary embodiment, the one or more programs may be executed by one or more processors to implement the obtaining the angle domain correction matrix corresponding to the equivalent sparse channel to be corrected, including: obtaining a rotation matrix; Using the rotation matrix, the pre-acquired angle domain transformation matrix is processed to obtain the angle domain correction matrix.

In an exemplary embodiment, the one or more programs may be executed by one or more processors to implement the equivalent sparse channel using the modified angle domain to obtain information on the transmitting end or the receiving end. The effective channel includes: calculating the estimated channel corresponding to the corrected equivalent sparse channel in the angle domain; processing the estimated channel by using the pre-acquired angle domain inverse transformation matrix to obtain the equivalent channel at the transmitting end or the receiving end , Wherein the angle domain inverse transformation matrix is an inverse transformation matrix of the angle domain transformation matrix.

In an exemplary embodiment, the one or more programs may be executed by one or more processors to implement the following method, including: the rotation matrix includes a changed angle parameter; and calculating the corrected angle domain The estimated channel corresponding to the equivalent sparse channel includes: under the multiple angle domain correction matrices corresponding to the changed angle parameter, calculate the multiple estimated channels corresponding to the multiple corrected angle domain equivalent sparse channels; The set estimation channel selection strategy is to select an estimation channel that conforms to the preset estimation channel selection strategy from the multiple estimation channels obtained by calculation as the required estimation channel.

In an exemplary embodiment, the one or more programs may be executed by one or more processors to implement the following method, including: the preset estimation channel selection strategy is based on the calculation operation of the estimation channel The calculation accuracy and calculation complexity are determined.

In an exemplary embodiment, the one or more programs may be executed by one or more processors to implement the following method, including: the angle domain transformation matrix is a DFT matrix.

The computer storage medium provided in this embodiment of the application obtains N pilot signals, where the N pilot signals are continuous pilot signals received by the same antenna, or the N pilot signals are the same at the transmitting end. The continuous pilot signal received when the antenna transmits the pilot signal, and the N pilot signals are used to calculate the transmitting end or the equivalent channel of the receiving end corresponding to the N pilot signals to realize the channels of the receiving end and the transmitting end Decoupling effectively reduces computational complexity.

The embodiment of the present application provides another computer storage medium, the computer-readable storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the following methods, including : Obtain K ₁ +K ₂ pilot signals, where K ₁ pilot signals are continuous pilot signals received by the same antenna, and K ₂ pilot signals are pilot signals that are sent using the same antenna at the transmitting end The continuous pilot signal received at time; using any of the methods described above, respectively calculate the equivalent channel of the transmitting end corresponding to _{K 1} pilot signals and the equivalent channel of the receiving end corresponding to _{K 2 pilot signals; using} The equivalent channels of the transmitting end corresponding to the K ₁ _{pilot signals and the equivalent channels of the receiving end corresponding to the K 2} pilot signals are calculated to obtain the original channel estimation matrix.

The computer storage medium provided by the embodiment of the application obtains K ₁ +K ₂ pilot signals, decouples the channels of the receiving end and the transmitting end, splits the high-dimensional overall channel matrix into two parts, and then calculates K _{1 respectively.} The equivalent channel of the transmitting end corresponding to two pilot signals and the equivalent channel _{of the receiving end corresponding to K 2} pilot signals. After the equivalent channels of the receiving end and the transmitting end are estimated, the original channel is synthesized, which can significantly reduce the computational complexity It also guarantees extremely high accuracy while maintaining the overhead of the pilot signal.

A person of ordinary skill in the art can understand that all or some of the steps, functional modules/units in the system, and apparatus in the methods disclosed above can be implemented as software, firmware, hardware, and appropriate combinations thereof. In the hardware implementation, the division between functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may consist of multiple The physical components are executed cooperatively. Some or all of the components may be implemented as software executed by a processor, such as a digital signal processor or a microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on a computer-readable medium, and the computer-readable medium may include a computer storage medium (or a non-transitory medium) and a communication medium (or a transitory medium). As is well known to those of ordinary skill in the art, the term computer storage medium includes volatile and non-volatile data implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Sexual, removable and non-removable media. Computer storage media include, but are not limited to, Random Access Memory (RAM), Read-Only Memory (ROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), and flash memory Or other memory technologies, Compact Disc Read-Only Memory (CD-ROM), Digital versatile disc (DVD) or other optical disc storage, magnetic cassettes, magnetic tapes, disk storage or other A magnetic storage device or any other medium that can be used to store desired information and can be accessed by a computer. In addition, as is well known to those of ordinary skill in the art, communication media usually contain computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as carrier waves or other transmission mechanisms, and may include any information delivery media. .

Claims

A channel estimation method includes:

Obtain N pilot signals, where N pilot signals are continuous pilot signals received using the same antenna, or N pilot signals are continuous pilot signals received when the transmitting end uses the same antenna to transmit pilot signals The pilot signal of, where N is a positive integer less than the total number of pilot signals;

Using the N pilot signals, calculate the equivalent channels of the transmitting end or the receiving end corresponding to the N pilot signals.
The method according to claim 1, wherein the calculating equivalent channels of the transmitting end or the receiving end corresponding to the N pilot signals by using the N pilot signals comprises:

Acquiring an angle domain correction matrix corresponding to the equivalent sparse channel to be corrected, where the equivalent sparse channel to be corrected is calculated by using the N pilot signals;

Processing the equivalent sparse channel to be modified according to the obtained angle domain correction matrix to obtain the equivalent sparse channel in the angle domain after correction;

The equivalent sparse channel in the angle domain after the correction is used to obtain the equivalent channel of the transmitting end or the receiving end.
The method according to claim 2, wherein said obtaining the angle domain correction matrix corresponding to the equivalent sparse channel to be corrected comprises:

Get the rotation matrix;

Using the rotation matrix, the pre-acquired angle domain transformation matrix is processed to obtain the angle domain correction matrix.
The method according to claim 3, wherein said using the equivalent sparse channel of the corrected angle domain to obtain the equivalent channel of the transmitting end or the receiving end comprises:

Calculating the estimated channel corresponding to the equivalent sparse channel in the corrected angle domain;

The estimated channel is processed by using a pre-acquired angle domain inverse transformation matrix to obtain the equivalent channel of the transmitting end or the receiving end, wherein the angle domain inverse transformation matrix is the inverse transformation matrix of the angle domain transformation matrix.
The method of claim 4, wherein:

The rotation matrix includes varying angle parameters;

Calculating the estimated channel corresponding to the equivalent sparse channel in the corrected angle domain includes:

Under multiple angle domain correction matrices corresponding to different angle parameters, calculate multiple estimated channels corresponding to the multiple corrected equivalent sparse channels in the angle domain;

According to a preset estimation channel selection strategy, an estimation channel conforming to the preset estimation channel selection strategy is selected as the required estimation channel from among the plurality of estimation channels obtained by calculation.
The method according to claim 5, wherein the preset selection strategy of the estimated channel is determined according to the calculation accuracy and the calculation complexity of the calculation operation of the estimated channel.
The method according to any one of claims 3 to 6, wherein the angle domain transformation matrix is a discrete Fourier transform (DFT) matrix.
A channel estimation method, including:

Obtain K 1 + K 2 pilot signals, where K 1 pilot signals are continuous pilot signals received using the same antenna, and K 2 pilot signals are when the same antenna is used to transmit the pilot signal at the transmitting end , The received continuous pilot signal; where K 1 and K 2 are both positive integers;

Using the method according to any one of claims 1 to 7, respectively calculating the equivalent channels of the transmitting end corresponding to K 1 pilot signals and the equivalent channels of the receiving end corresponding to K 2 pilot signals;

The equivalent channel of the transmitting end corresponding to the K 1 pilot signals and the equivalent channel of the receiving end corresponding to the K 2 pilot signals are used to calculate the original channel estimation matrix.
A channel estimation device includes a processor and a memory, the memory stores a computer program, and the processor is configured to call the computer program in the memory to implement the method according to any one of claims 1 to 7.
A channel estimation device includes a processor and a memory, the memory stores a computer program, and the processor is configured to call the computer program in the memory to implement the method according to claim 8.
A computer storage medium storing at least one program, and the at least one program can be executed by at least one processor to implement the method according to any one of claims 1 to 7.
A computer storage medium storing at least one program, and the at least one program can be executed by at least one processor to implement the method according to claim 8.