A method and apparatus for channel estimation

Abstract

The application provides a channel estimation method and device, which are used for solving the problems of low channel estimation accuracy and large interactive data volume in a multi-antenna distributed architecture scenario. In the application, a first communication device performs domain transformation processing on first channel information to obtain first transformed domain information; the first communication device receives second compressed information from a second communication device, the second compressed information being information obtained by performing domain transformation processing and compression on second channel information; the first communication device merges the first transformed domain information and the second compressed information to obtain first merged information; the first communication device can obtain first channel estimation information based on the first merged information; in addition, the first communication device further compresses the first merged information to obtain first compressed merged information, and sends the first compressed merged information to the second communication device.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a method and apparatus for channel estimation. Background Technology

[0002] Multi-antenna systems can provide higher throughput and reliability while consuming the same time-frequency resources, and have been widely studied by academia and industry. However, to fully utilize the spatial multiplexing gain and array gain of multi-antenna systems, accurate channel estimation and key physical algorithms, such as power allocation and precoding design, are required.

[0003] Multi-antenna systems can be centralized or distributed. Centralized architectures require aggregating all antenna data for channel estimation, resulting in high data processing complexity and significant bus bandwidth requirements. Distributed architectures divide antennas into clusters, with each cluster equipped with a separate processing unit. Each cluster performs channel estimation independently, but this approach often suffers from low performance and may require multiple iterations and data exchanges, further increasing channel estimation complexity.

[0004] Therefore, designing a channel estimation method that can improve the channel estimation accuracy and reduce the amount of interactive data in a distributed architecture of a multi-antenna system has become an urgent problem to be solved. Summary of the Invention

[0005] This application provides a channel estimation method and apparatus to solve problems such as low channel estimation accuracy and large amount of interactive data in multi-antenna distributed architecture scenarios.

[0006] In a first aspect, embodiments of this application provide a channel estimation method. This method can be executed by a first communication device, by a component of the first communication device (e.g., a processor, a chip, or a chip system), or by a logic module or software capable of implementing all or part of the functions of the first communication device. The method includes: performing domain transformation processing on first channel information to obtain first transformed domain information; receiving second compressed information from a second communication device, the second compressed information being information obtained by domain transformation processing and compression of the second channel information; merging the first transformed domain information and the second compressed information to obtain first merged information; obtaining first channel estimation information based on the first merged information; furthermore, compressing the first merged information to obtain first compressed merged information, and sending the first compressed merged information to the second communication device.

[0007] According to the configuration method provided in the embodiments of this application, the first communication device in a distributed architecture of a multi-antenna system can perform channel estimation based on combined information, thereby improving the accuracy of channel estimation. Furthermore, since both the first and second communication devices transmit compressed information, the amount of channel estimation data exchange can be reduced.

[0008] In conjunction with the first aspect, in some embodiments of the first aspect, the first channel information is frequency domain information and the first transform domain information is time delay domain information.

[0009] In conjunction with the first aspect, in some embodiments of the first aspect, the first channel information is antenna domain information and the first transform domain information is angle domain information.

[0010] In conjunction with the first aspect, in some embodiments of the first aspect, compressing the first merged information to obtain first compressed merged information includes: comparing the first merged information with a first threshold, retaining values ​​in the first merged information that are higher than the first threshold, and setting values ​​in the first merged information that are lower than the first threshold to zero.

[0011] In conjunction with the first aspect, in some embodiments of the first aspect, the first merged information is subjected to soft-window processing.

[0012] In conjunction with the first aspect, in some embodiments of the first aspect, obtaining first channel estimation information based on the first merging information includes: transforming the first merging information from the time delay domain to the frequency domain.

[0013] In conjunction with the first aspect, in some embodiments of the first aspect, obtaining first channel estimation information based on the first merging information includes: transforming the first merging information from the angle domain to the antenna domain.

[0014] Secondly, embodiments of this application provide a channel estimation method. This method can be executed by a second communication device, by a component of the second communication device (e.g., a processor, chip, or chip system), or by a logic module or software capable of implementing all or part of the functions of the second communication device. The method includes: performing domain transformation processing on second channel information to obtain second transform domain information; compressing the second transform domain information to obtain second compressed information; sending the second compressed information to a first communication device; receiving first compressed merging information from the first communication device; merging the second transform domain information with the first compressed merging information to obtain second merged information; and obtaining second channel estimation information based on the second merged information.

[0015] According to the configuration method provided in the embodiments of this application, the second communication device in a distributed architecture of a multi-antenna system can perform channel estimation based on combined information, thereby improving the accuracy of channel estimation. Furthermore, since both the first and second communication devices transmit compressed information, the amount of channel estimation data exchange can be reduced.

[0016] In conjunction with the second aspect, in some embodiments of the second aspect, the second channel information is frequency domain information and the second transform domain information is time delay domain information.

[0017] In conjunction with the second aspect, in some embodiments of the second aspect, the second channel information is antenna domain information and the second transform domain information is angle domain information.

[0018] In conjunction with the second aspect, in some embodiments of the second aspect, the second transform domain information is merged with the first compression merging information to obtain the second merged information, including: deleting the second compression information from the first compression merging information and then adding the second transform domain information.

[0019] In conjunction with the second aspect, in some embodiments of the second aspect, the second merged information is subjected to soft-window processing.

[0020] In conjunction with the second aspect, in some implementations of the second aspect, obtaining the second channel estimation information based on the second merging information includes: transforming the second merging information from the time delay domain to the frequency domain.

[0021] In conjunction with the second aspect, in some embodiments of the second aspect, obtaining second channel estimation information based on second merging information includes: transforming the second merging information from the angle domain to the antenna domain.

[0022] Thirdly, embodiments of this application provide a communication device including a module for performing the methods described in the first aspect or any possible implementation of the first aspect.

[0023] Fourthly, embodiments of this application provide a communication device including a module for performing the methods described in the second aspect or any possible implementation of the second aspect.

[0024] Fifthly, embodiments of this application provide a communication device, including a processor and an interface circuit. The interface circuit is used to receive signals from other devices outside the device and transmit them to the processor, or to send signals from the processor to other devices outside the device. The processor is used to implement the methods described in the first aspect or possible implementations of the first aspect, or to implement the methods described in the second aspect or possible implementations of the second aspect, through logic circuits or execution code instructions.

[0025] In a sixth aspect, embodiments of this application provide a computer-readable storage medium storing a computer program or instructions that, when executed by a computing device, implement the method described in the first aspect or possible implementations of the first aspect, or implement the method described in the second aspect or possible implementations of the second aspect.

[0026] In a seventh aspect, embodiments of this application provide a computer program product comprising a computer program or instructions that, when executed by a computing device, implement the method described in the first aspect or possible implementations of the first aspect, or implement the method described in the second aspect or possible implementations of the second aspect.

[0027] Eighthly, embodiments of this application provide a communication system comprising one or more of the following: a communication device as provided in the third, fourth, or fifth aspect; a computer-readable storage medium as provided in the sixth aspect; and a computer program product as provided in the seventh aspect. Attached Figure Description

[0028] Figure 1 A schematic diagram of a possible communication architecture provided for an embodiment of this application;

[0029] Figure 2 This application provides a schematic diagram of a possible centralized architecture.

[0030] Figure 3 This application provides a schematic diagram of a possible distributed architecture for an embodiment of the present application.

[0031] Figure 4 A schematic flowchart illustrating a channel estimation method provided in this application embodiment;

[0032] Figure 5 Another schematic flowchart of a channel estimation method provided in this application embodiment;

[0033] Figure 6 Another schematic flowchart of a channel estimation method provided in this application embodiment;

[0034] Figure 7 A schematic block diagram of a communication device provided in an embodiment of this application;

[0035] Figure 8 This is another schematic block diagram of a communication device provided in an embodiment of this application. Detailed Implementation

[0036] The technical solutions in this application will now be described with reference to the accompanying drawings.

[0037] It should be understood that, in the embodiments of this application, the sequence number of each process does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0038] It should be understood that in the embodiments of this application, the numbering of terms is generally for the convenience of differentiation. The numbering does not mean that the terms have a difference in order or priority. For example, "first channel information" and "second channel information" are usually only used to distinguish between the two sets of information, and should not limit the implementation process of the embodiments of this application.

[0039] It should be understood that in the embodiments of this application, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of a single item or a plurality of items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be a single item or multiple items.

[0040] It should be understood that, in the embodiments of this application, the terms "system" and "network" are often used interchangeably herein.

[0041] It should be understood that in the embodiments of this application, the term "and / or" is generally used to describe the relationship between associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. It should be understood that the character " / " appearing in the embodiments of this application generally indicates that the preceding and following associated objects have an "or" relationship.

[0042] The methods and apparatus provided in this application can be applied to communication systems. Figure 1 This is a schematic diagram of the architecture of the communication system 100 used in an embodiment of this application. Figure 1 As shown, the communication system includes a wireless access network 110 and a core network 120. Optionally, the communication system 100 may also include an Internet 130. The wireless access network 110 may include at least one wireless access network device (such as...). Figure 1 111a and 111b in the above), may also include at least one terminal (such as Figure 1 (Referring to sections 112a-112j). Terminals connect wirelessly to the wireless access network (WLAN) equipment, which in turn connects to the core network via wireless or wired connections. The core network equipment and the WLAN equipment can be independent physical devices, or they can integrate the functions of the core network equipment and the logical functions of the WLAN equipment onto the same physical device. Alternatively, a single physical device can integrate some of the functions of both the core network equipment and the WLAN equipment. Terminals and WLAN equipment can connect to each other via wired or wireless connections. Figure 1This is just an illustration; the communication system may also include other network devices, such as wireless repeaters and wireless backhaul devices. Figure 1 It is not shown in the middle.

[0043] Radio access network equipment can be a base station, an evolved NodeB (eNodeB), a transmission reception point (TRP), a next-generation NodeB (gNB) in a 5G mobile communication system, a next-generation base station in a 6G mobile communication system, a base station in a future mobile communication system, or an access node in a WiFi system; it can also be a module or unit that performs some of the functions of a base station, for example, it can be a central unit (CU) or a distributed unit (DU). Radio access network equipment can be a macro base station (such as... Figure 1 111a) in the text can also be a micro base station or an indoor station (such as...). Figure 1 111b) in the above can also be a relay node or a donor node, etc. It is understood that all or part of the functions of the wireless access network device in this application can also be implemented through software functions running on hardware, or through virtualization functions instantiated on a platform (e.g., a cloud platform). The embodiments of this application do not limit the specific technology or specific device form used in the wireless access network device. For ease of description, a base station is used as an example of a wireless access network device in the following description.

[0044] A terminal can also be called a terminal device, user equipment (UE), mobile station, mobile terminal, etc. Terminals can be widely used in various scenarios, such as device-to-device (D2D), vehicle-to-everything (V2X) communication, machine-type communication (MTC), Internet of Things (IoT), virtual reality, augmented reality, industrial control, autonomous driving, telemedicine, smart grids, smart furniture, smart offices, smart wearables, smart transportation, smart cities, etc. Terminals can be mobile phones, tablets, computers with wireless transceiver capabilities, wearable devices, vehicles, drones, helicopters, airplanes, ships, robots, robotic arms, smart home devices, etc. The embodiments of this application do not limit the specific technologies or device forms used in the terminals.

[0045] Base stations and terminals can be fixed or mobile. They can be deployed on land, including indoors or outdoors, handheld or vehicle-mounted; they can also be deployed on water; and they can be deployed in the air on aircraft, balloons, and artificial satellites. The embodiments of this application do not limit the application scenarios of base stations and terminals.

[0046] The roles of base stations and terminals can be relative, for example, Figure 1 The helicopter or drone 112i can be configured as a mobile base station. For terminals 112j that access the wireless access network 110 via 112i, terminal 112i is a base station; however, for base station 111a, 112i is a terminal, meaning that 111a and 112i communicate via a wireless air interface protocol. Of course, 111a and 112i can also communicate via a base station-to-base station interface protocol; in this case, relative to 111a, 112i is also a base station. Therefore, both base stations and terminals can be collectively referred to as communication devices. Figure 1 111a and 111b in the diagram can be referred to as communication devices with base station functionality. Figure 1 The 112a-112j in the text can be referred to as communication devices with terminal functions.

[0047] Communication between base stations and terminals, between base stations, and between terminals can be conducted using licensed spectrum, unlicensed spectrum, or both simultaneously. Communication can be conducted using spectrum below 6 GHz, spectrum above 6 GHz, or both simultaneously. The embodiments of this application do not limit the spectrum resources used for wireless communication.

[0048] In the embodiments of this application, the functions of the base station can be executed by modules (such as chips) within the base station, or by a control subsystem that includes base station functions. This control subsystem, including base station functions, can be a control center in the application scenarios of the aforementioned terminals, such as smart grids, industrial control, intelligent transportation, and smart cities. Similarly, the functions of the terminal can be executed by modules (such as chips or modems) within the terminal, or by a device that includes terminal functions.

[0049] In this application, the base station sends downlink signals or downlink information to the terminal, and the downlink information is carried on the downlink channel; the terminal sends uplink signals or uplink information to the base station, and the uplink information is carried on the uplink channel.

[0050] It is understandable that as the network evolves, the names of the aforementioned network elements may change, and the functions of the network elements may be merged, separated, or even changed. However, these changes do not mean that they are no longer within the scope of application of this application.

[0051] The methods and apparatus provided in this application can be applied to wireless access network devices as well as terminal devices.

[0052] Multi-antenna systems can provide higher throughput and reliability while consuming the same time-frequency resources, and have been widely studied by academia and industry. However, to fully utilize the spatial multiplexing gain and array gain of multi-antenna systems, accurate channel estimation and key physical algorithms, such as power allocation and precoding design, are required.

[0053] Multi-antenna systems have centralized and distributed architectures, such as... Figure 2 As shown, Figure 2 This diagram illustrates a possible centralized architecture for an embodiment of this application. A centralized architecture requires aggregating all antenna data for channel estimation, resulting in high data processing complexity and a large bus bandwidth requirement for data aggregation. Under a centralized architecture, as the number of antennas increases, both the data processing complexity and the bus bandwidth required for data aggregation increase dramatically, posing a significant challenge to chip design. Therefore, centralized processing architectures may become a bottleneck restricting the application of larger-scale antennas in the future. Figure 3 As shown, Figure 3 This is a schematic diagram of a possible distributed architecture provided in an embodiment of this application. The distributed architecture divides the antennas into clusters, with each cluster equipped with a separate processing unit. Each cluster performs channel estimation independently, and can also fuse or interact with data from other clusters. After all clusters' data have been fused or interacted with, the final data result, such as the channel estimation result, is output. However, the performance of this channel estimation is often low and the complexity is very high. Therefore, how to design a channel estimation method that can improve the channel estimation accuracy of the distributed architecture of a multi-antenna system and reduce the amount of data interaction has become an urgent problem to be solved.

[0054] This application provides a channel estimation method and apparatus for improving the channel estimation accuracy of a distributed architecture in a multi-antenna system and reducing the amount of data interaction in the algorithm.

[0055] Please see Figure 4 , Figure 4 A schematic flowchart of a channel estimation method 400 according to an embodiment of this application is shown. Figure 4The channel estimation method illustrated involves a first communication device and a second communication device. In the embodiments of this application, the first communication device, the second communication device, and the third communication device (hereinafter referred to as the third communication device) can be part of a distributed architecture of a multi-antenna system. For example, the first communication device can be an active antenna unit (AAU) in the distributed architecture of a multi-antenna system, or one of multiple chips included in an AAU; the second communication device can be an active antenna unit (AAU) in the distributed architecture of a multi-antenna system, or one of multiple chips included in an AAU; the third communication device can be an active antenna unit (AAU) in the distributed architecture of a multi-antenna system, or one of multiple chips included in an AAU. Figure 4 In this context, the first communication device can communicate with the second communication device. Figure 4 The channel estimation method shown includes, but is not limited to, the following steps:

[0056] S401 performs domain transformation processing on the first channel information to obtain the first transform domain information.

[0057] The first communication device performs domain transformation processing on the first channel information to obtain first transformed domain information. This first channel information may be obtained by the first communication device estimating the received pilot signal from the terminal.

[0058] In one possible implementation, the first communication device may use the least squares method to estimate the received pilot signal from the terminal to obtain the first channel information.

[0059] In one possible implementation, the first channel information is antenna domain and frequency domain information.

[0060] In one possible implementation, the first communication device transforms the first channel information from the antenna domain to the angle domain to obtain the first transform domain information.

[0061] For example, the first communication device and the second communication device are part of a distributed architecture of a multi-antenna system, and both the first communication device and the second communication device have N antennas. r The total number of antennas N in a multi-antenna system R ,but:

[0062] N R =2×N r

[0063] For example, in a multi-antenna system with a distributed architecture, there are a total of 32 antennas, divided into a first communication device and a second communication device. In this case, the number of antennas in both the first and second communication devices is 16.

[0064] This first channel information can be represented as Y1, where Y1 is a dimension N. r ×N C A matrix, where N C This represents the number of subcarriers. For example, if the pilot signal from the terminal occupies 48 subcarriers, then N... C It is 48.

[0065] For example, the first communication device can transform the first channel information from the antenna domain to the angle domain to obtain first transform domain information, which can satisfy:

[0066]

[0067] in For the first transform domain information, For angle domain information, The dimension is N R ×N C N R N represents the total number of antennas in a multi-antenna system. C For subcarriers, F1 H The conjugate transpose of F1, where F1 is a vector vector of dimension N. R ×N R The submatrix of the discrete Fourier transform (DFT) matrix, F1 has a dimension of N. r ×N R N r The number of antennas for the first communication device.

[0068] In one possible implementation, the first communication device transforms the first channel information from the frequency domain to the time delay domain to obtain the first transform domain information.

[0069] For example, the first communication device can transform the first channel information from the frequency domain to the time delay domain to obtain the first transform domain information, which can satisfy:

[0070]

[0071] in For the first transform domain information, at this time, For delay domain information, The dimension is N r ×N C , for The conjugate transpose of . For dimension N C ×N C The DFT matrix.

[0072] In one possible implementation, the first communication device transforms the first channel information from the frequency domain and antenna domain to the time delay domain and angle domain to obtain the first transform domain information.

[0073] For example, the first transform domain information can satisfy:

[0074]

[0075] in For the first transform domain information, at this time, For delay domain information, The dimension is N r ×N C , for The conjugate transpose of . For dimension N C ×N C The DFT matrix, F1 is of dimension N R ×N R The submatrix of the DFT matrix, the F1 has a dimension of N. r ×N R .

[0076] S402 performs domain transformation processing on the second channel information to obtain the second transform domain information.

[0077] The second communication device performs domain transformation processing on the second channel information to obtain second transformed domain information. This second channel information can be estimated by the second communication device from the pilot signal received from the terminal.

[0078] In one possible implementation, the second communication device may use the least squares method to estimate the received pilot signal from the terminal to obtain the second channel information.

[0079] In one possible implementation, the second channel information is antenna domain and frequency domain information.

[0080] In one possible implementation, the second communication device transforms the second channel information from the antenna domain to the angle domain to obtain the second transform domain information.

[0081] For example, the first communication device and the second communication device are part of a distributed architecture of a multi-antenna system, and both the first communication device and the second communication device have N antennas. r The total number of antennas N in a multi-antenna system R ,but:

[0082] N R =2×N r

[0083] For example, in a multi-antenna system with a distributed architecture, there are a total of 32 antennas, divided into a first communication device and a second communication device. In this case, the number of antennas in both the first and second communication devices is 16.

[0084] This second channel information can be represented as Y2, where Y2 is a dimension N. r ×N C A matrix, where N C This represents the number of subcarriers. For example, if the pilot signal from the terminal occupies 48 subcarriers, then N... C It is 48.

[0085] For example, the second communication device can transform the antenna domain of the second channel information to the angle domain to obtain the second transform domain information, which can satisfy:

[0086]

[0087] in For the second transform domain information, For angle domain information, The dimension is N R ×N C N R N represents the total number of antennas in a multi-antenna system. C For the number of subcarriers, This is the conjugate transpose of F2, where F2 is a vector vector of dimension N. R ×N R The submatrix of the DFT matrix, F2 has a dimension of N. r ×N R N r This represents the number of antennas for the second communication device.

[0088] In one possible implementation, the second communication device transforms the second channel information from the frequency domain to the time delay domain to obtain the second transform domain information.

[0089] For example, the second communication device can transform the second channel information from the frequency domain to the time delay domain to obtain second transform domain information, which can satisfy:

[0090]

[0091] in For the second transform domain information, at this time, For delay domain information, The dimension is N r ×N C , for The conjugate transpose of . For dimension N C ×N C The DFT matrix.

[0092] In one possible implementation, the second communication device transforms the second channel information from the frequency domain and antenna domain to the time delay domain and angle domain to obtain the second transform domain information.

[0093] For example, the second communication device transforms the second channel information from the frequency domain and antenna domain to the time delay domain and angle domain to obtain second transform domain information, which can satisfy:

[0094]

[0095] in For the second transform domain information, at this time, Information in the time delay domain and angle domain. The dimension is N R ×N C F2 is a dimension N R ×N R F2 is a submatrix of the DFT matrix of dimension N. r ×N R F NC For dimension N C ×N C The DFT matrix.

[0096] For example, the second communication device transforms the second channel information from the frequency domain and antenna domain to the time delay domain and angle domain to obtain second transform domain information, which may also satisfy:

[0097]

[0098] in For the second transform domain information, at this time, Information in the time delay domain and angle domain. The dimension is N r ×N C , For dimension N r ×N r The DFT matrix, For dimension N C ×N C The DFT matrix.

[0099] S403 compresses the second transform domain information to obtain the second compressed information.

[0100] The second communication device compresses the second transform domain information to obtain second compressed information. The second communication device compares this second transform domain information with a second threshold, retaining values ​​in the second transform domain information above the second threshold and setting values ​​in the second transform domain information below the second threshold to zero, thereby obtaining the compressed second compressed information. The higher the second threshold, the greater the sparsity of the second compressed information; a trade-off between channel estimation performance and data exchange volume can be achieved by adjusting the second threshold.

[0101] In one possible implementation, the compression operation described above can be performed on each value in the second transform domain information one by one.

[0102] For example, the second compression information can satisfy:

[0103]

[0104] in, This is the second compressed information. The second transform domain information is represented by D2, which is a compression matrix with elements of 0 or 1, and ⊙ represents the dot product operation.

[0105] The elements in D2 satisfy:

[0106]

[0107] Among them, [D2] mn The element in row m and column n of D2 for The element in the m-th row and n-th column.

[0108] In one possible implementation, the compression operation described above can be performed column by column on each column of the second transform domain information.

[0109] For example, the second compression information can satisfy:

[0110]

[0111] in, This is the second compressed information. D2 represents the information in the second transform domain, D2 is the compression matrix whose elements are 0 or 1, and ⊙ represents the dot product operation.

[0112] The elements in D2 satisfy:

[0113]

[0114] Among them, [D2] n This represents the nth column in D2, where 1 represents a vector of all 1s and 0 represents a vector of all 0s.

[0115] The second communication device compresses the second transform domain information according to the above method to obtain second compressed information, which includes a sparse matrix.

[0116] In one possible implementation, the second compression information also includes the position information of non-zero values ​​in the sparse matrix, such as the position information of non-zero elements in D2.

[0117] S404 sends the second compression information.

[0118] The second communication device sends second compressed information to the first communication device.

[0119] S405 merges the first transform domain information with the second compression information to obtain the first merged information.

[0120] The first communication device merges the first transform domain information with the second compressed information to obtain the first merged information.

[0121] In one possible implementation, the first communication device directly merges the first transform domain information with the second compression information to obtain the first merged information.

[0122] For example, the first merging information can satisfy:

[0123]

[0124] in, This is the first merged information. For the first transform domain information, This is the second compressed information.

[0125] In one possible implementation, the first communication device first performs domain transformation on the second compressed information, and then merges it with the first transformed domain information to obtain the first merged information.

[0126] For example, the first communication device performs a domain transformation on the second compressed information, which can satisfy:

[0127]

[0128] in, The information obtained after domain transformation of the second compressed information. For the second compressed information, F2 is a dimension N. R ×N R F2 is a submatrix of the DFT matrix of dimension N. r ×N R , For dimension N r ×N r The DFT matrix.

[0129] The first communication device merges the first transform domain information with the transformed second compressed information to obtain first merged information. For example, this first merged information satisfies:

[0130]

[0131] S406 obtains the first channel estimation information based on the first merging information.

[0132] The first communication device obtains first channel estimation information based on the first merging information.

[0133] In one possible implementation, the first merged information can be processed by adding a first soft window. The first soft window can be obtained based on a mean square error minimization algorithm.

[0134] For example, the first soft window can satisfy:

[0135]

[0136] U1 is the first soft window. For matrix The vectorization of E{} is the expected value, and h is the channel information, including the actual information of the first and second channels.

[0137] In one possible implementation, the first merging information is transformed from the angle domain to the antenna domain to obtain the first channel estimation information;

[0138] In one possible implementation, the first merging information is transformed from the time delay domain to the frequency domain to obtain the first channel estimation information;

[0139] In one possible implementation, the first merging information is transformed from the time delay domain and angle domain to the antenna domain and frequency domain to obtain the first channel estimation information;

[0140] For example, the first combined information is first processed with a soft window, and then the first channel estimation information is obtained by transforming it from the time delay domain and angle domain to the antenna domain and frequency domain. Then, the first channel estimation information can satisfy:

[0141]

[0142] Where H1 is the first channel estimation information, and F1 is a dimension N... R ×N R The submatrix of the DFT matrix, F1 is of dimension N r ×N R , For dimension N C ×N C The DFT matrix is ​​represented by mat(·), which is the inverse operation of matrix vectorization. For example, if the matrix is ​​vectorized as:

[0143]

[0144] but,

[0145]

[0146] S407 compresses the first merged information to obtain the first compressed merged information.

[0147] The first communication device compresses the first merged information to obtain first compressed merged information. The first communication device compares the first merged information with a first threshold, retaining values ​​in the first merged information above the first threshold and setting values ​​in the first merged information below the first threshold to zero, thereby obtaining the compressed first compressed merged information. The higher the first threshold, the greater the sparsity of the first compressed merged information.

[0148] In one possible implementation, the compression operation described above can be performed on each value in the first merged information one by one.

[0149] For example, the first compression and merging information can satisfy:

[0150]

[0151] in, This is the first compressed and merged information. The first merged information is D1, which is a compressed matrix with elements of 0 or 1, and ⊙ represents the dot product operation.

[0152] The elements in D1 satisfy:

[0153]

[0154] Among them, [D1] mn The element in row m and column n of D1 for The element in the m-th row and n-th column.

[0155] In one possible implementation, the compression operation described above can be performed column by column on each column of the first merged information.

[0156] For example, the first compression and merging information can satisfy:

[0157]

[0158] in, This is the first compressed and merged information. The second transform domain information is represented by D1, which is a compression matrix with elements of 0 or 1, and ⊙ represents the dot product operation.

[0159] The elements in D1 satisfy:

[0160]

[0161] Among them, [D1] n This represents the nth column in D1, where 1 represents a vector of all 1s and 0 represents a vector of all 0s.

[0162] The first communication device compresses the first merged information according to the above method to obtain first compressed merged information, which includes a sparse matrix.

[0163] In one possible implementation, the first compression merging information also includes the position information of non-zero values ​​in the sparse matrix, such as the position information of non-zero elements in D1.

[0164] S408 sends the first compression and merging information.

[0165] The first communication device sends the aforementioned first compression and merging information to the second communication device.

[0166] S409 merges the second transform domain information with the first compression merging information to obtain the second merged information.

[0167] The second communication device merges the second transform domain information with the first compression merging information to obtain the second merged information.

[0168] In one possible implementation, the second communication device deletes the second compressed information from the first compressed merged information and adds the second transform domain information to obtain the second merged information.

[0169] For example, the second merging information can satisfy:

[0170]

[0171] in, This is the second merged information. This is the first compressed and merged information. This is the second compressed information. This is the information in the second transform domain.

[0172] S410 obtains second channel estimation information based on the second merging information.

[0173] The second communication device obtains second channel estimation information based on the aforementioned second merging information.

[0174] In one possible implementation, the second merged information can be first processed by adding a second soft window. This second soft window can be obtained based on a mean squared error minimization algorithm.

[0175] For example, the second soft window can satisfy:

[0176]

[0177] U2 is the second soft window. For matrix The vectorization of E{} is the expected value, and h is the channel information, including the actual information of the first and second channels.

[0178] In one possible implementation, the second merging information is transformed from the angle domain to the antenna domain to obtain the second channel estimation information;

[0179] In one possible implementation, the second merging information is transformed from the time delay domain to the frequency domain to obtain the second channel estimation information;

[0180] In one possible implementation, the second merging information is transformed from the time delay domain and angle domain to the antenna domain and frequency domain to obtain the second channel estimation information;

[0181] For example, the second combined information is first processed with a soft window, and then the second channel estimation information is obtained by transforming it from the time delay domain and angle domain to the antenna domain and frequency domain. Then, the second channel estimation information can satisfy:

[0182]

[0183] Where H2 is the second channel estimation information, For matrix The vectorization of F2 is of dimension N. R ×N R F2 is a submatrix of the DFT matrix of dimension N. r ×N R , For dimension N C ×N C The DFT matrix is ​​denoted by mat(·), which is the inverse operation of matrix vectorization.

[0184] The channel estimation method and apparatus provided in this application can enable the first and second communication devices in a distributed architecture of a multi-antenna system to perform channel estimation based on combined information, thereby improving the accuracy of channel estimation. Furthermore, since compressed information is transmitted between the first and second communication devices, the amount of channel estimation data exchange can be reduced.

[0185] Please see Figure 5 , Figure 5 A schematic flowchart of a channel estimation method 500 according to an embodiment of this application is shown. Figure 5The channel estimation method illustrated involves a first communication device, a second communication device, and a third communication device. These three communication devices can be part of a distributed architecture of a multi-antenna system. The first communication device can communicate with the second communication device, and also with the third communication device. The channel estimation method includes, but is not limited to, the following steps:

[0186] S501 performs domain transformation processing on the first channel information to obtain the first transform domain information.

[0187] The first communication device performs domain transformation processing on the first channel information to obtain first transformed domain information. This first channel information may be obtained by the first communication device estimating the received pilot signal from the terminal.

[0188] In one possible implementation, the first communication device may use the least squares method to estimate the received pilot signal from the terminal to obtain the first channel information.

[0189] In one possible implementation, the first channel information is antenna domain and frequency domain information.

[0190] In one possible implementation, the first communication device transforms the first channel information from the antenna domain to the angle domain to obtain the first transform domain information.

[0191] For example, the first communication device, the second communication device, and the third communication device are part of a distributed architecture of a multi-antenna system, and the number of antennas in the first communication device, the second communication device, and the third communication device is N. r The total number of antennas N in a multi-antenna system R ,but:

[0192] N R =3×N r

[0193] For example, a multi-antenna system with a distributed architecture has a total of 48 antennas, divided into a first communication device, a second communication device, and a third communication device. The number of antennas in the first communication device, the second communication device, and the third communication device is 16 each.

[0194] This first channel information can be represented as Y1, where Y1 is a dimension N. r ×N C A matrix, where N C This represents the number of subcarriers. For example, if the pilot signal from the terminal occupies 48 subcarriers, then N... C It is 48.

[0195] For example, the first communication device can transform the first channel information from the antenna domain to the angle domain to obtain first transform domain information, which can satisfy:

[0196]

[0197] in For the first transform domain information, For angle domain information, The dimension is N R ×N C N R N represents the total number of antennas in a multi-antenna system. C For the number of subcarriers, The conjugate transpose of F1, where F1 is a vector vector of dimension N. R ×N R The submatrix of the DFT matrix, F1 is of dimension N r ×N R N r The number of antennas for the first communication device.

[0198] In one possible implementation, the first communication device transforms the first channel information from the frequency domain to the time delay domain to obtain the first transform domain information.

[0199] For example, the first communication device can transform the first channel information from the frequency domain to the time delay domain to obtain the first transform domain information, which can satisfy:

[0200]

[0201] in For the first transform domain information, at this time, For delay domain information, The dimension is N r ×N C , for The conjugate transpose of . For dimension N C ×N C The DFT matrix.

[0202] In one possible implementation, the first communication device transforms the first channel information from the frequency domain and antenna domain to the time delay domain and angle domain to obtain the first transform domain information.

[0203] For example, the first transform domain information can satisfy:

[0204]

[0205] in For the first transform domain information, at this time, For delay domain information, The dimension is N r ×NC , for The conjugate transpose of . For dimension N C ×N C The DFT matrix, F1 is of dimension N R ×N R The submatrix of the DFT matrix, F1 is of dimension N r ×N R .

[0206] S502 performs domain transformation processing on the second channel information to obtain the second transform domain information.

[0207] The second communication device performs domain transformation processing on the second channel information to obtain second transformed domain information. This second channel information can be estimated by the second communication device from the pilot signal received from the terminal.

[0208] In one possible implementation, the second communication device may use the least squares method to estimate the received pilot signal from the terminal to obtain the second channel information.

[0209] In one possible implementation, the second channel information is antenna domain and frequency domain information.

[0210] In one possible implementation, the second communication device transforms the second channel information from the antenna domain to the angle domain to obtain the second transform domain information.

[0211] This second channel information can be represented as Y2, where Y2 is a dimension N. r ×N C A matrix, where N C This represents the number of subcarriers. For example, if the pilot signal from the terminal occupies 48 subcarriers, then N... C It is 48.

[0212] For example, the second communication device can transform the antenna domain of the second channel information to the angle domain to obtain second transform domain information, which can satisfy:

[0213]

[0214] in For the second transform domain information, For angle domain information, The dimension is N R ×N C N R N represents the total number of antennas in a multi-antenna system. C For the number of subcarriers, This is the conjugate transpose of F2, where F2 is a vector vector of dimension N.R ×N R F2 is a submatrix of the DFT matrix of dimension N. r ×N R N r This represents the number of antennas for the second communication device.

[0215] In one possible implementation, the second communication device transforms the second channel information from the frequency domain to the time delay domain to obtain the first transform domain information.

[0216] For example, the second communication device can transform the second channel information from the frequency domain to the time delay domain to obtain second transform domain information, which can satisfy:

[0217]

[0218] in For the second transform domain information, at this time, For delay domain information, The dimension is N r ×N C , for The conjugate transpose of . For dimension N C ×N C The DFT matrix.

[0219] In one possible implementation, the second communication device transforms the second channel information from the frequency domain and antenna domain to the time delay domain and angle domain to obtain the second transform domain information.

[0220] For example, the second communication device transforms the second channel information from the frequency domain and antenna domain to the time delay domain and angle domain to obtain second transform domain information, which can satisfy:

[0221]

[0222] in For the second transform domain information, at this time, Information in the time delay domain and angle domain. The dimension is N R ×N C F2 is a dimension N R ×N R F2 is a submatrix of the DFT matrix of dimension N. r ×N R , For dimension N C ×N C The DFT matrix.

[0223] For example, the second communication device transforms the second channel information from the frequency domain and antenna domain to the time delay domain and angle domain to obtain second transform domain information, which may also satisfy:

[0224]

[0225] in For the second transform domain information, at this time, Information in the time delay domain and angle domain. The dimension is N r ×N C , For dimension N r ×N r The DFT matrix, For dimension N C ×N C The DFT matrix.

[0226] S503 compresses the second transform domain information to obtain the second compressed information.

[0227] The second communication device compresses the second transform domain information to obtain second compressed information. The second communication device compares the second transform domain information with a second threshold, retaining values ​​in the second transform domain information above the second threshold and setting values ​​in the second transform domain information below the second threshold to zero, thereby obtaining the compressed second compressed information. The higher the second threshold, the greater the sparsity of the second compressed information.

[0228] In one possible implementation, the compression operation described above can be performed on each value in the second transform domain information one by one.

[0229] For example, the second compression information can satisfy:

[0230]

[0231] in, This is the second compressed information. The second transform domain information is represented by D2, which is a compression matrix with elements of 0 or 1, and ⊙ represents the dot product operation.

[0232] The elements in D2 satisfy:

[0233]

[0234] Among them, [D2] mn The element in row m and column n of D2 for The element in the m-th row and n-th column.

[0235] In one possible implementation, the compression operation described above can be performed column by column on each column of the second transform domain information.

[0236] For example, the second compression information can satisfy:

[0237]

[0238] in, This is the second compressed information. The second transform domain information is represented by D2, which is a compression matrix with elements of 0 or 1, and ⊙ represents the dot product operation.

[0239] The elements in D2 satisfy:

[0240]

[0241] Among them, [D2] n This represents the nth column in D2, where 1 represents a vector of all 1s and 0 represents a vector of all 0s.

[0242] The second communication device compresses the second transform domain information according to the above method to obtain second compressed information, which includes a sparse matrix.

[0243] In one possible implementation, the second compression information also includes the position information of non-zero values ​​in the sparse matrix, such as the position information of non-zero elements in D2.

[0244] S504 sends the second compression information.

[0245] The second communication device sends second compressed information to the first communication device.

[0246] S505 performs domain transformation processing on the third channel information to obtain the third transform domain information.

[0247] The third communication device performs domain transformation processing on the third channel information to obtain third transformed domain information. This third channel information can be estimated by the third communication device from the pilot signal received from the terminal.

[0248] In one possible implementation, the third communication device may use the least squares method to estimate the received pilot signal from the terminal to obtain the third channel information.

[0249] In one possible implementation, the third channel information is antenna domain and frequency domain information.

[0250] In one possible implementation, the third communication device transforms the third channel information from the antenna domain to the angle domain to obtain third transform domain information.

[0251] This third channel information can be represented as Y3, where Y3 is a dimension N. r ×N C A matrix, where N C This represents the number of subcarriers.

[0252] For example, the third communication device can transform the third channel information antenna domain to the angle domain to obtain third transform domain information, which can satisfy:

[0253]

[0254] in For information in the third transform domain, For angle domain information, The dimension is N R ×N C N R N represents the total number of antennas in a multi-antenna system. C For the number of subcarriers, This is the conjugate transpose of F3, where F3 is a vector unit of dimension N. R ×N R F3 is a submatrix of the DFT matrix of dimension N. r ×N R N r This refers to the number of antennas for the third communication device.

[0255] In one possible implementation, the third communication device transforms the third channel information from the frequency domain to the time delay domain to obtain the third transform domain information.

[0256] For example, the third communication device can transform the third channel information from the frequency domain to the time delay domain to obtain third transform domain information, which can satisfy:

[0257]

[0258] in For the third transform domain information, at this time, For delay domain information, The dimension is N r ×N C , for The conjugate transpose of . For dimension N C ×N C The DFT matrix.

[0259] In one possible implementation, the third communication device transforms the third channel information from the frequency domain and antenna domain to the time delay domain and angle domain to obtain the third transform domain information.

[0260] For example, the third communication device transforms the third channel information from the frequency domain and antenna domain to the time delay domain and angle domain to obtain third transform domain information, which can satisfy:

[0261]

[0262] in For the third transform domain information, at this time, Information in the time delay domain and angle domain. The dimension is N R ×N C F3 is a dimension N R ×N R F3 is a submatrix of the DFT matrix of dimension N. r ×N R , For dimension N C ×N C The DFT matrix.

[0263] For example, the third communication device transforms the third channel information from the frequency domain and antenna domain to the time delay domain and angle domain to obtain third transform domain information, which may also satisfy:

[0264]

[0265] in For the third transform domain information, at this time, Information in the time delay domain and angle domain. The dimension is N r ×N C , For dimension N r ×N r The DFT matrix, For dimension N C ×N C The DFT matrix.

[0266] S506 compresses the third transform domain information to obtain the third compressed information.

[0267] The third communication device compresses the third transform domain information to obtain third compressed information. The third communication device compares this third transform domain information with a third threshold, retaining values ​​in the third transform domain information above the third threshold and setting values ​​in the third transform domain information below the third threshold to zero, thereby obtaining the compressed third compressed information. The higher the third threshold, the greater the sparsity of the third compressed information.

[0268] In one possible implementation, the compression operation described above can be performed on each value in the third transform domain information one by one.

[0269] In one possible implementation, the compression operation described above can be performed column by column on each column of the third transform domain information.

[0270] In one possible implementation, the third compression information also includes the location information of non-zero values ​​in the sparse matrix.

[0271] For example, the third compression information can satisfy:

[0272]

[0273] in, This is the third type of compressed information. The information is in the third transformation domain. D3 is a compression matrix with elements of 0 or 1, and ⊙ represents the dot product operation.

[0274] S507 sends the third compression information.

[0275] The third communication device sends third compressed information to the first communication device.

[0276] S508 merges the first transform domain information with the second compression information and the third compression information to obtain the first merged information.

[0277] The first communication device merges the first transform domain information with the second compressed information and the third compressed information to obtain the first merged information.

[0278] In one possible implementation, the first communication device directly merges the first transform domain information with the second compressed information and the third compressed information to obtain the first merged information.

[0279] For example, the first merging information can satisfy:

[0280]

[0281] in, This is the first merged information. For the first transform domain information, This is the second compressed information. This is the third type of compressed information.

[0282] In one possible implementation, the first communication device first performs domain transformation on the second compressed information and the third compressed information, and then merges them with the first transformed domain information to obtain the first merged information.

[0283] For example, the first communication device performs a domain transformation on the second compressed information, which can satisfy:

[0284]

[0285] in, The information obtained after domain transformation of the second compressed information. For the second compressed information, F2 is a dimension N. R ×N R F2 is a submatrix of the DFT matrix of dimension N. r ×N R , For dimension N r ×N r The DFT matrix.

[0286] The first communication device performs a domain transformation on the third compressed information, which satisfies the following:

[0287]

[0288] in, The information obtained after domain transformation of the third compressed information. For the third compressed information, F3 is a dimension N. R ×N R F3 is a submatrix of the DFT matrix of dimension N. r ×N R , For dimension N r ×N r The DFT matrix.

[0289] The first communication device merges the first transform domain information with the transformed second compressed information to obtain first merged information. For example, this first merged information satisfies:

[0290]

[0291] S509 obtains the first channel estimation information based on the first merging information.

[0292] For a detailed description of the method, please refer to step S406 of method 400, which will not be repeated here.

[0293] S510 compresses the first merged information to obtain the first compressed merged information.

[0294] The first communication device compresses the first merged information to obtain first compressed merged information. The first communication device compares the first merged information with a first threshold, retaining values ​​in the first merged information above the first threshold and setting values ​​in the first merged information below the first threshold to zero, thereby obtaining the compressed first compressed merged information. The higher the first threshold, the greater the sparsity of the first compressed merged information.

[0295] For example, the first compression and merging information can satisfy:

[0296]

[0297] in, This is the first compressed and merged information. The first merged information is D1, which is a compressed matrix with elements of 0 or 1, and ⊙ represents the dot product operation.

[0298] For a detailed description of the method, please refer to step S407 of method 400, which will not be repeated here.

[0299] S511 sends the first message.

[0300] The first communication device sends first information to the second communication device, the first information including the aforementioned first compression and merging information.

[0301] S512 merges the second transform domain information with the first compression merging information to obtain the second merged information.

[0302] The second communication device merges the second transform domain information with the first compression merging information to obtain the second merged information.

[0303] In one possible implementation, the second communication device deletes the second compressed information from the first compressed merged information and adds the second transform domain information to obtain the second merged information.

[0304] For example, the second merging information can satisfy:

[0305]

[0306] in, This is the second merged information. This is the first compressed and merged information. This is the second compressed information. This is the information in the second transform domain.

[0307] S513 obtains the second channel estimation information based on the second merging information.

[0308] For a detailed description of the method, please refer to step S410 in method 400, which will not be repeated here.

[0309] S514 sends the second message.

[0310] The first communication device sends second information to the third communication device, the second information including the aforementioned first compression and merging information.

[0311] S515 merges the third transform domain information with the first compression merging information to obtain the third merged information.

[0312] The third communication device merges the third transform domain information with the first compression merging information to obtain the third merged information.

[0313] In one possible implementation, the third communication device deletes the third compression information from the first compression merging information and adds the third transform domain information to obtain the third merged information.

[0314] For example, the third merged information can satisfy:

[0315]

[0316] in, This is the third merged information. This is the first compressed and merged information. This is the third type of compressed information. This is information from the third transform domain.

[0317] S516 obtains third channel estimation information based on third merging information.

[0318] The third communication device obtains third channel estimation information based on the aforementioned third merging information.

[0319] In one possible implementation, the third merged information can be processed by adding a third soft window. The third soft window can be obtained based on a mean square error minimization algorithm.

[0320] For example, a third soft window can satisfy:

[0321]

[0322] U3 is the third soft window. For matrix The vectorization of E{} is the expected value, and h is the channel information, including the actual information of the first channel, the second channel, and the third channel.

[0323] In one possible implementation, the third merging information is transformed from the angle domain to the antenna domain to obtain the third channel estimation information;

[0324] In one possible implementation, the third merging information is transformed from the time delay domain to the frequency domain to obtain the third channel estimation information;

[0325] In one possible implementation, the third merging information is transformed from the time delay domain and angle domain to the antenna domain and frequency domain to obtain the third channel estimation information;

[0326] For example, the third combined information is first processed with a soft window, and then the third channel estimation information is obtained by transforming it from the time delay domain and angle domain to the antenna domain and frequency domain. Then, the third channel estimation information can satisfy:

[0327]

[0328] H3 represents the third channel estimation information. For matrix The vectorization of F3, which is of dimension N R ×N R F3 is a submatrix of the DFT matrix of dimension N. r ×N R , For dimension N C ×N C The DFT matrix is ​​denoted by mat(·), which is the inverse operation of matrix vectorization.

[0329] The channel estimation method and apparatus provided in this application can enable the first, second, and third communication devices in a distributed architecture of a multi-antenna system to perform channel estimation based on combined information, thereby improving the accuracy of channel estimation. Furthermore, since compressed information is transmitted between the first, second, and third communication devices, the amount of channel estimation data exchange can be reduced.

[0330] It should be understood that Figure 5 This illustration only shows a multi-antenna distributed architecture including three communication devices. The embodiments of this application are not limited to three communication devices. For example, in addition to the first and second communication devices, there may be two or more third communication devices.

[0331] Please see Figure 6 , Figure 6 A schematic flowchart of a channel estimation method 600 according to an embodiment of this application is shown. Figure 6 The channel estimation method illustrated involves a first communication device, a second communication device, and a third communication device. These three devices can be part of a distributed architecture of a multi-antenna system. The first communication device can communicate with the second communication device, and the second communication device can communicate with the third communication device. The channel estimation method includes, but is not limited to, the following steps:

[0332] S601 performs domain transformation processing on the first channel information to obtain the first transform domain information.

[0333] The first communication device performs domain transformation processing on the first channel information to obtain first transformed domain information. This first channel information may be obtained by the first communication device estimating the received pilot signal from the terminal.

[0334] In one possible implementation, the first communication device may use the least squares method to estimate the received pilot signal from the terminal to obtain the first channel information.

[0335] In one possible implementation, the first channel information is antenna domain and frequency domain information.

[0336] In one possible implementation, the first communication device transforms the first channel information from the antenna domain to the angle domain to obtain the first transform domain information.

[0337] In one possible implementation, the first communication device transforms the first channel information from the frequency domain to the time delay domain to obtain the first transform domain information.

[0338] In one possible implementation, the first communication device transforms the first channel information from the frequency domain and antenna domain to the time delay domain and angle domain to obtain the first transform domain information.

[0339] For a detailed description, please refer to step 501 in method 500, which will not be repeated here.

[0340] S602 performs domain transformation processing on the third channel information to obtain the third transform domain information.

[0341] The third communication device performs domain transformation processing on the third channel information to obtain third transformed domain information. This third channel information can be estimated by the third communication device from the pilot signal received from the terminal.

[0342] For a detailed description, please refer to step 505 in method 500, which will not be repeated here.

[0343] S603 compresses the third transform domain information to obtain the third compressed information.

[0344] The third communication device compresses the third transform domain information to obtain third compressed information. The third communication device compares this third transform domain information with a third threshold, retaining values ​​in the third transform domain information above the third threshold and setting values ​​in the third transform domain information below the third threshold to zero, thereby obtaining the compressed third compressed information. The higher the third threshold, the greater the sparsity of the third compressed information.

[0345] For a detailed description, please refer to step 506 in method 500, which will not be repeated here.

[0346] S604 sends the third compression information.

[0347] The third communication device sends third compressed information to the second communication device.

[0348] S605 performs domain transformation processing on the second channel information to obtain the second transform domain information.

[0349] The second communication device performs domain transformation processing on the second channel information to obtain second transformed domain information. This second channel information can be estimated by the second communication device from the pilot signal received from the terminal.

[0350] For a detailed description, please refer to step 502 in method 500, which will not be repeated here.

[0351] S606 compresses the second transform domain information to obtain second compressed information.

[0352] The second communication device compresses the second transform domain information to obtain second compressed information. The second communication device compares the second transform domain information with a second threshold, retaining values ​​in the second transform domain information above the second threshold and setting values ​​in the second transform domain information below the second threshold to zero, thereby obtaining the compressed second compressed information. The higher the second threshold, the greater the sparsity of the second compressed information.

[0353] For a detailed description, please refer to step 503 in method 500, which will not be repeated here.

[0354] S607 sends total compression information.

[0355] The second communication device sends total compressed information to the first communication device, wherein the total compressed information includes the aforementioned second compressed information and third compressed information.

[0356] In one possible implementation, the second compressed information and the third compressed information are merged to obtain the total compressed information.

[0357] In one possible implementation, the second compression information and the third compression information are not merged, but are included in the total compression information.

[0358] S608 merges the first transform domain information with the total compression information to obtain the first merged information.

[0359] In one possible approach, the total compressed information is a combination of the second and third compressed information, and the first communication system directly combines the first transform domain information with the total compressed information.

[0360] In one possible approach, the total compressed information is a combination of the second and third compressed information. The first communication device first performs a domain transformation on the total compressed information, and then merges it with the first transformed domain information to obtain the first merged information.

[0361] In one possible approach, the second and third compressed information in the total compressed information are not merged, and the first communication system directly merges the first transform domain information with the second and third compressed information in the total compressed information.

[0362] In one possible approach, the second and third compressed information in the total compressed information are not merged. The first communication device first performs domain transformation on the second and third compressed information in the total compressed information, and then merges them with the first transformed domain information to obtain the first merged information.

[0363] For specific merging methods, please refer to step 508 in method 500, which will not be repeated here.

[0364] S609 obtains the first channel estimation information based on the first merging information.

[0365] For a detailed description of the method, please refer to step S406 of method 400, which will not be repeated here.

[0366] S610 compresses the first merged information to obtain the first compressed merged information.

[0367] The first communication device compresses the first merged information to obtain first compressed merged information. The first communication device compares the first merged information with a first threshold, retaining values ​​in the first merged information above the first threshold and setting values ​​in the first merged information below the first threshold to zero, thereby obtaining the compressed first compressed merged information. The higher the first threshold, the greater the sparsity of the first compressed merged information.

[0368] For example, the first compression and merging information can satisfy:

[0369]

[0370] in, This is the first compressed and merged information. The first merged information is D1, which is a compressed matrix with elements of 0 or 1, and ⊙ represents the dot product operation.

[0371] For a detailed description of the method, please refer to step S407 of method 400, which will not be repeated here.

[0372] S611 sends the first message.

[0373] The first communication device sends first information to the second communication device, the first information including the aforementioned first compression and merging information.

[0374] S612 merges the second transform domain information with the first compression merging information to obtain the second merged information.

[0375] The second communication device merges the second transform domain information with the first compressed merging information in the first information to obtain the second merged information.

[0376] For a detailed description of the method, please refer to step S512 of method 500, which will not be repeated here.

[0377] S613 obtains the second channel estimation information based on the second merging information.

[0378] For a detailed description, please refer to step S410 in method 400, which will not be repeated here.

[0379] S614 sends the second message.

[0380] The second communication device sends second information to the third communication device, the second information including the aforementioned first compression and merging information.

[0381] S615 merges the third transform domain information with the first compression merging information to obtain the third merged information.

[0382] The third communication device merges the third transform domain information with the first compression merging information to obtain the third merged information.

[0383] For a detailed description, please refer to step S515 of method 500, which will not be repeated here.

[0384] S616 obtains third channel estimation information based on third merging information.

[0385] The third communication device obtains third channel estimation information based on the aforementioned third merging information.

[0386] For a detailed description, please refer to step S516 of method 500, which will not be repeated here.

[0387] The channel estimation method and apparatus provided in this application can enable the first, second, and third communication devices in a distributed architecture of a multi-antenna system to perform channel estimation based on combined information, thereby improving the accuracy of channel estimation. Furthermore, since compressed information is transmitted between the first, second, and third communication devices, the amount of channel estimation data exchange can be reduced.

[0388] Figure 7 This is a schematic block diagram of a communication device provided in an embodiment of this application. These communication devices can be used to implement the functions of the first communication device in the above method embodiments, and therefore can also achieve the beneficial effects of the above method embodiments. In the embodiments of this application, the communication device can be the first communication device in the above method embodiments, or it can be a module (such as a chip) applied in the first communication device.

[0389] like Figure 7 As shown, the communication device 700 includes a processing module 710 and a transceiver module 720. The communication device 700 is used to implement the above-mentioned... Figure 4 , Figure 5 or Figure 6 The function of the first communication device in the corresponding embodiment.

[0390] When the communication device 700 is used to implement Figure 4 , Figure 5 or Figure 6 When the first communication device functions in the method embodiment shown, it is exemplarily described as follows:

[0391] The transceiver module 720 is used to receive second compressed information from the second communication device. The second compressed information is information obtained by domain transformation and compression of the second channel information.

[0392] In one alternative embodiment, the transceiver module 720 is also configured to send first compressed merged information to the second communication device.

[0393] The processing module 710 is used to perform domain transformation processing on the first channel information to obtain first transformed domain information, merge the first transformed domain information with the second compressed information to obtain first merged information, and compress the first merged information to obtain first compressed merged information.

[0394] In an alternative embodiment, the transceiver module 710 is further configured to compare the first merged information with a first threshold, retain values ​​in the first merged information that are higher than the first threshold, and set values ​​in the first merged information that are lower than the first threshold to zero.

[0395] In an alternative embodiment, the transceiver module 710 is further configured to perform soft-window processing on the first merged information.

[0396] In an alternative embodiment, the transceiver module 710 is further configured to transform the first merged information from the time delay domain to the frequency domain.

[0397] In an alternative embodiment, the transceiver module 710 is further configured to transform the first merged information from the angle domain to the antenna domain.

[0398] The above is only applicable when the communication device 700 is used to achieve... Figure 4 , Figure 5 or Figure 6 The examples shown in the method embodiment illustrate the functions of the processing module 710 and the transceiver module 720 in the communication device 700. Please refer to... Figure 4 , Figure 5 ,or Figure 6 The operation of the first communication device in the corresponding embodiment.

[0399] The communication device 700 can also be used to achieve the above. Figure 4 , Figure 5 or Figure 6 The function of the second communication device in the corresponding embodiment.

[0400] When the communication device 700 is used to implement Figure 4 , Figure 5 or Figure 6 When the second communication device functions in the method embodiment shown, it is exemplarily described as follows:

[0401] The transceiver module 720 is used to send the second compressed information to the first communication device.

[0402] In an alternative embodiment, the transceiver module 720 is further configured to receive first compressed and merged information from the first communication device.

[0403] The processing module 710 is used to perform domain transformation processing on the second channel information to obtain second transform domain information, compress the second transform domain information to obtain second compressed information, merge the second transform domain information with the first compressed merging information to obtain second merged information, and obtain second channel estimation information based on the second merged information.

[0404] In an alternative embodiment, the transceiver module 710 is further configured to delete the second compressed information from the first compressed merged information and then add the second transform domain information.

[0405] In one alternative embodiment, the transceiver module 710 is further configured to compare the second transform domain information with a second threshold, retain values ​​in the second transform domain information that are higher than the second threshold, and set values ​​in the second transform domain information that are lower than the second threshold to zero.

[0406] In an alternative embodiment, the transceiver module 710 is also configured to transform the second merged information from the time delay domain to the frequency domain.

[0407] In an alternative embodiment, the transceiver module 710 is also configured to transform the second combined information from the angle domain to the antenna domain.

[0408] The above is only applicable when the communication device 700 is used to achieve... Figure 4 , Figure 5 or Figure 6 The examples shown in the method embodiment illustrate the functions of the processing module 710 and the transceiver module 720 in the communication device 700. Please refer to... Figure 4 , Figure 5 ,or Figure 6 The operation of the second communication device in the corresponding embodiment.

[0409] The communication device 700 can also be used to achieve the above. Figure 5 or Figure 6 The function of the third communication device in the corresponding embodiment.

[0410] When the communication device 700 is used to implement Figure 5 or Figure 6When the third communication device functions in the method embodiment shown, it is exemplarily described as follows:

[0411] The transceiver module 720 is used to send the third compressed information to the first communication device.

[0412] In an alternative embodiment, the transceiver module 720 is further configured to receive first compressed and merged information from the first communication device.

[0413] The processing module 710 is used to perform domain transformation processing on the third channel information to obtain third transform domain information, compress the third transform domain information to obtain third compressed information, merge the third transform domain information with the first compressed merging information to obtain third merged information, and obtain third channel estimation information based on the third merged information.

[0414] In an alternative embodiment, the transceiver module 710 is further configured to delete the third compression information from the first compression merge information and then add the third transform domain information.

[0415] In an alternative embodiment, the transceiver module 710 is further configured to compare the third transform domain information with a third threshold, retain values ​​in the third transform domain information that are higher than the third threshold, and set values ​​in the third transform domain information that are lower than the third threshold to zero.

[0416] In an alternative embodiment, the transceiver module 710 is also configured to transform the third merged information from the time delay domain to the frequency domain.

[0417] In an alternative embodiment, the transceiver module 710 is also configured to transform the third combined information from the angle domain to the antenna domain.

[0418] The above is only applicable when the communication device 700 is used to achieve... Figure 5 ,or Figure 6 The examples shown in the method embodiment illustrate the functions of the processing module 710 and the transceiver module 720 in the communication device 700. Please refer to... Figure 5 or Figure 6 The operation of the third communication device in the corresponding embodiment.

[0419] Figure 8 This is another schematic block diagram of a communication device provided in an embodiment of this application. Figure 8 As shown. The communication device 800 includes a processor 810 and an interface circuit 830. The processor 810 and the interface circuit 830 are coupled to each other. It is understood that the interface circuit 830 can be a transceiver or an input / output interface.

[0420] Optionally, the communication device 800 may also include a memory 820 for storing instructions executed by the processor 820, or storing input data required for the processor 810 to run instructions, or storing data generated after the processor 810 runs instructions.

[0421] When the communication device 800 is used to implement Figure 4 , Figure 5 or Figure 6 When the first, second, or third communication device shown is used, the processor 810 is used to implement the functions of the processing module 710, and the interface circuit 830 is used to implement the functions of the transceiver module 720.

[0422] Optionally, the communication device 800 further includes a bus 840, through which the processor 810, the interface circuit 830, and the memory 820 can communicate.

[0423] This application also provides a system chip, which includes an input / output interface, at least one processor, at least one memory, and a bus. The at least one memory is used to store instructions, and the at least one processor is used to invoke the instructions in the at least one memory to perform the methods described above.

[0424] In the embodiments of this application, it should be noted that the method embodiments described above can be applied to a processor or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method embodiments can be completed by integrated logic circuits in the processor's hardware or by instructions in software form. The processor described above can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules can be located in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The storage medium is located in the memory, and the processor reads the information in the memory and, in conjunction with its hardware, completes the steps of the above method.

[0425] It is understood that the memory in the embodiments of this application can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDR SDRAM), Enhanced Synchronous DRAM (ESDRAM), Synchlink DRAM (SLDRAM), and Direct Rambus RAM (DR RAM). It should be noted that the memory used in the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0426] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented, in whole or in part, as a computer program product. The computer program product may include one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic disk), an optical medium (e.g., DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)).

[0427] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0428] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0429] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0430] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0431] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0432] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the essential contributing part of the technical solution of this application, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory, random access memory, magnetic disks, or optical disks.

[0433] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A channel estimation method, characterized in that, include: Perform domain transformation processing on the first channel information to obtain the first transform domain information; Receive second compressed information from the second communication device, wherein the second compressed information is information obtained by domain transformation and compression of the second channel information; The first transform domain information and the second compression information are merged to obtain the first merged information; First channel estimation information is obtained based on the first merging information; The first merged information is compressed to obtain the first compressed merged information; The first compression and merging information is sent to the second communication device.

2. The method according to claim 1, characterized in that, The first channel information is frequency domain information, and the first transform domain information is time delay domain information.

3. The method according to claim 1 or 2, characterized in that, The first channel information is antenna domain information, and the first transform domain information is angle domain information.

4. The method according to claim 1 or 2, characterized in that, The step of compressing the first merged information to obtain first compressed merged information includes: The first merged information is compared with a first threshold. Values ​​in the first merged information that are higher than the first threshold are retained, and values ​​in the first merged information that are lower than the first threshold are set to zero.

5. The method according to claim 1 or 2, characterized in that, The method further includes: The first merged information is then processed with a soft window.

6. The method according to claim 1 or 2, characterized in that, The step of obtaining the first channel estimation information based on the first merging information includes: The first merged information is transformed from the time delay domain to the frequency domain.

7. The method according to claim 1 or 2, characterized in that, The step of obtaining the first channel estimation information based on the first merging information includes: The first merged information is transformed from the angle domain to the antenna domain.

8. A distributed channel estimation method, characterized in that, include: The second channel information is subjected to domain transformation processing to obtain the second transform domain information; The second transform domain information is compressed to obtain the second compressed information; Send the second compressed information to the first communication device; Receive first compressed and merged information from the first communication device; The second transform domain information is merged with the first compression merging information to obtain the second merged information; Based on the second merging information, the second channel estimation information is obtained.

9. The method according to claim 8, characterized in that, The second channel information is frequency domain information, and the second transform domain information is time delay domain information.

10. The method according to claim 8 or 9, characterized in that, The second channel information is antenna domain information, and the second transform domain information is angle domain information.

11. The method according to claim 8 or 9, characterized in that, The step of merging the second transform domain information with the first compression merging information to obtain the second merged information includes: The second compression information is deleted from the first compression merging information, and then the second transform domain information is added.

12. The method according to claim 8 or 9, characterized in that, The step of compressing the second transform domain information to obtain second compressed information includes: The second transform domain information is compared with the second threshold. Values ​​in the second transform domain information that are higher than the second threshold are retained, and values ​​in the second transform domain information that are lower than the second threshold are set to zero.

13. The method according to claim 8 or 9, characterized in that, The method further includes: The second merged information is then processed with a soft window.

14. The method according to claim 8 or 9, characterized in that, The process of obtaining the second channel estimation information based on the second merging information includes: The second merged information is transformed from the time delay domain to the frequency domain.

15. The method according to claim 8 or 9, characterized in that, The process of obtaining the second channel estimation information based on the second merging information includes: The second merged information is transformed from the angle domain to the antenna domain.

16. A communication device, characterized in that, Includes a module for performing the method according to any one of claims 1-7.

17. A communication device, characterized in that, Includes a module for performing the method according to any one of claims 8-15.

18. A communication device, characterized in that, The device includes a processor coupled to a memory for storing programs or instructions that, when executed by the processor, cause the device to perform the method as described in any one of claims 1-7.

19. A communication device, characterized in that, The device includes a processor coupled to a memory for storing programs or instructions that, when executed by the processor, cause the device to perform the method as described in any one of claims 8-15.

20. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program or instructions that, when executed by a computing device, implement the method of any one of claims 1-7, or the method of any one of claims 8-15.

21. A computer program product, the computer program product comprising instructions, characterized in that, When the instructions are executed by a computer device, the method of any one of claims 1-7 or the method of any one of claims 8-15 is implemented.

22. A communication system, characterized in that, It includes one or more of the following: the communication device as described in any one of claims 16-19.

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