WO2021012159A1 - 信道信息处理方法、设备及存储介质 - Google Patents

信道信息处理方法、设备及存储介质 Download PDF

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Publication number
WO2021012159A1
WO2021012159A1 PCT/CN2019/097138 CN2019097138W WO2021012159A1 WO 2021012159 A1 WO2021012159 A1 WO 2021012159A1 CN 2019097138 W CN2019097138 W CN 2019097138W WO 2021012159 A1 WO2021012159 A1 WO 2021012159A1
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Prior art keywords
information
channel
quantized
downlink channel
downlink
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PCT/CN2019/097138
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English (en)
French (fr)
Inventor
陈文洪
黄莹沛
吴朝武
Original Assignee
Oppo广东移动通信有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
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Application filed by Oppo广东移动通信有限公司 filed Critical Oppo广东移动通信有限公司
Priority to CN201980057711.3A priority Critical patent/CN112673664B/zh
Priority to PCT/CN2019/097138 priority patent/WO2021012159A1/zh
Publication of WO2021012159A1 publication Critical patent/WO2021012159A1/zh

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements

Definitions

  • the embodiments of the present application relate to communication technologies, and in particular, to a channel information processing method, device, and storage medium.
  • a network device (such as a base station) sends a downlink reference signal to a terminal device, and the terminal device can perform channel estimation based on the downlink reference signal to obtain downlink channel information. Further, the terminal device can feed back the downlink channel information to the network device, so that the network device can determine the precoding matrix according to the downlink channel information, and precode the downlink data according to the precoding matrix.
  • the terminal device needs to quantify the downlink channel information before feeding back the downlink channel information to the network device. Further, when the quantized downlink channel information is sent to the network device, since the accuracy of the quantized downlink channel information is low, the precoding matrix determined by the network device is inaccurate, thereby reducing the downlink transmission performance of the network device.
  • the embodiments of the present application provide a channel information processing method, device, and storage medium to improve the downlink transmission performance of the network device.
  • embodiments of the present application may provide a channel information processing method, which is applied to a terminal device, and the method includes:
  • the embodiments of the present application may provide a channel information processing method, which is applied to a network device, and the method includes:
  • the precoding matrix corresponding to the terminal device is determined.
  • the embodiments of the present application may provide a terminal device, including:
  • the receiving module is used to receive the downlink reference signal sent by the network device;
  • a channel estimation module configured to perform channel estimation according to the downlink reference signal to obtain channel estimation downlink channel information
  • the sending module is configured to send error information between the quantized downlink channel information and the channel estimated downlink channel information, and the quantized information of the channel estimated downlink channel information to the network device.
  • the embodiments of the present application may provide a network device, including:
  • the sending module is used to send a downlink reference signal to the terminal device
  • a receiving module configured to receive error information between the quantized downlink channel information and the channel estimated downlink channel information sent by the terminal equipment, and the quantized information of the channel estimated downlink channel information;
  • the processing module is configured to reconstruct to obtain reconstructed downlink channel information according to the error information and the quantization information of the channel estimated downlink channel information; and determine the preset corresponding to the terminal device according to the reconstructed downlink channel information Encoding matrix.
  • embodiments of the present application may provide a terminal device, including:
  • Processor memory, and interface for communication with network equipment
  • the memory stores computer execution instructions
  • the processor executes the computer-executable instructions stored in the memory, so that the processor executes the channel information processing method as described in the first aspect.
  • the embodiments of the present application may provide a network device, including:
  • Processor memory, and interface for communication with network equipment
  • the memory stores computer execution instructions
  • the processor executes the computer-executable instructions stored in the memory, so that the processor executes the channel information processing method described in the second aspect.
  • an embodiment of the present application provides a computer-readable storage medium having computer-executable instructions stored in the computer-readable storage medium.
  • the computer-executable instructions are executed by a processor, the The described channel information processing method.
  • an embodiment of the present application provides a computer-readable storage medium, which stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, it is used to implement the The described channel information processing method.
  • an embodiment of the present application provides a chip, including: a processor, configured to call and run a computer program from a memory, so that a device installed with the chip executes the channel described in the first or second aspect Information processing methods.
  • an embodiment of the present application provides a computer program product, including computer program instructions, which cause a computer to execute the channel information processing method described in the first aspect or the second aspect.
  • an embodiment of the present application also provides a computer program that enables a computer to execute the channel information processing method described in the first or second aspect above.
  • the terminal device receives the downlink reference signal sent by the network device, and performs channel estimation according to the downlink reference signal to obtain the channel estimated downlink channel information, and further sends the downlink channel information to the network device
  • the quantized information is reconstructed to obtain the reconstructed downlink channel information.
  • the network device Since the error information reflects the error of the quantized downlink channel information relative to the downlink channel information obtained by the terminal equipment through channel estimation, it is compared with the existing In the technology, the network device only receives the quantized downlink channel information sent by the terminal device, and the accuracy of the downlink channel information reconstructed by the network device is higher than the accuracy of the quantized downlink channel information of the terminal device. That is to say, compared with the quantized downlink channel information of the terminal equipment, the downlink channel information reconstructed by the network equipment is closer to the downlink channel information obtained by the terminal equipment through channel estimation. When the network equipment is based on the reconstructed downlink channel information When determining the precoding matrix corresponding to the terminal device, the accuracy of the precoding matrix can be improved. The network device further precodes the downlink data according to the precoding matrix, thereby improving the downlink transmission performance of the network device.
  • Figure 1 is a schematic diagram of a communication system provided by this application.
  • Figure 2 is a signaling diagram of a channel information processing method provided by this application.
  • FIG. 3 is a signaling diagram of another channel information processing method provided by this application.
  • FIG. 4 is a signaling diagram of yet another channel information processing method provided by this application.
  • FIG. 5 is a schematic structural diagram of the terminal device provided by this application.
  • FIG. 6 is a schematic diagram of a structure of a network device provided by this application.
  • FIG. 7 is a schematic diagram of another structure of the terminal device provided by this application.
  • FIG. 8 is a schematic diagram of another structure of the network device provided by this application.
  • GSM Global System of Mobile Communication
  • CDMA Code Division Multiple Access
  • WCDMA Wideband Code Division Multiple Access
  • GSM Global System of Mobile Communication
  • GPRS General Packet Radio Service
  • LTE Long Term Evolution
  • FDD Frequency Division Duplex
  • TDD Time Division Duplex
  • LTE-A Advanced long term evolution
  • NR New Radio
  • NR NR system evolution system
  • LTE on unlicensed frequency bands LTE-based access to unlicensed spectrum, LTE-U
  • NR NR-based access to unlicensed spectrum, NR-U
  • UMTS Universal Mobile Telecommunication System
  • UMTS Universal Mobile Telecommunication System
  • WiMAX Worldwide Interoperability for Microwave Access
  • WiMAX Wireless Local Area Networks
  • WLAN Wireless Fidelity
  • WiFi next-generation communication systems or other communication systems, etc.
  • the communication system 100 applied in the embodiment of this application is shown in FIG. 1.
  • the communication system 100 may include a network device 110, and the network device 110 may be a device that communicates with a terminal device 120 (or called a communication terminal or a terminal).
  • the network device 110 may provide communication coverage for a specific geographic area, and may communicate with terminal devices located in the coverage area.
  • the network device 110 may be a base station (Base Transceiver Station, BTS) in a GSM system or a CDMA system, a base station (NodeB, NB) in a WCDMA system, or an evolved base station in an LTE system (Evolutional Node B, eNB or eNodeB), or the wireless controller in the Cloud Radio Access Network (CRAN), or the network equipment can be a mobile switching center, a relay station, an access point, a vehicle-mounted device, Wearable devices, hubs, switches, bridges, routers, network-side devices in 5G networks, or network devices in the future evolution of the Public Land Mobile Network (PLMN), etc.
  • BTS Base Transceiver Station
  • NodeB, NB base station
  • LTE Long Term Evolutional Node B
  • eNB evolved base station
  • CRAN Cloud Radio Access Network
  • the network equipment can be a mobile switching center, a relay station, an access point, a vehicle-mounted device, Wearable devices, hubs, switches
  • the communication system 100 also includes at least one terminal device 120 located within the coverage area of the network device 110.
  • the "terminal equipment” used here includes but is not limited to connection via wired lines, such as via public switched telephone networks (PSTN), digital subscriber lines (Digital Subscriber Line, DSL), digital cables, and direct cable connections ; And/or another data connection/network; and/or via a wireless interface, such as for cellular networks, wireless local area networks (WLAN), digital TV networks such as DVB-H networks, satellite networks, AM- FM broadcast transmitter; and/or another terminal device that is set to receive/send communication signals; and/or Internet of Things (IoT) equipment.
  • PSTN public switched telephone networks
  • DSL Digital Subscriber Line
  • DSL Digital Subscriber Line
  • DSL Digital Subscriber Line
  • DSL Digital Subscriber Line
  • DSL Digital Subscriber Line
  • DSL Digital Subscriber Line
  • DSL Digital Subscriber Line
  • DSL Digital Subscriber Line
  • DSL Digital Subscriber Line
  • DSL Digital Subscriber Line
  • DSL
  • a terminal device set to communicate through a wireless interface may be referred to as a "wireless communication terminal", a “wireless terminal” or a “mobile terminal”.
  • mobile terminals include, but are not limited to, satellites or cellular phones; Personal Communications System (PCS) terminals that can combine cellular radio phones with data processing, fax, and data communication capabilities; can include radio phones, pagers, Internet/intranet PDA with internet access, web browser, memo pad, calendar, and/or Global Positioning System (GPS) receiver; and conventional laptop and/or palmtop receivers or others including radio phone transceivers Electronic device.
  • PCS Personal Communications System
  • GPS Global Positioning System
  • Terminal equipment can refer to access terminals, user equipment (UE), user units, user stations, mobile stations, mobile stations, remote stations, remote terminals, mobile equipment, user terminals, terminals, wireless communication equipment, user agents, or User device.
  • the access terminal can be a cellular phone, a cordless phone, a Session Initiation Protocol (SIP) phone, a wireless local loop (Wireless Local Loop, WLL) station, a personal digital processing (Personal Digital Assistant, PDA), with wireless communication Functional handheld devices, computing devices or other processing devices connected to wireless modems, in-vehicle devices, wearable devices, terminal devices in 5G networks, or terminal devices in the future evolution of PLMN, etc.
  • SIP Session Initiation Protocol
  • WLL Wireless Local Loop
  • PDA Personal Digital Assistant
  • direct terminal connection (Device to Device, D2D) communication may be performed between the terminal devices 120.
  • the 5G system or 5G network may also be referred to as a New Radio (NR) system or NR network.
  • NR New Radio
  • Figure 1 exemplarily shows one network device and two terminal devices.
  • the communication system 100 may include multiple network devices and the coverage of each network device may include other numbers of terminal devices. The embodiment does not limit this.
  • the network device may be an access device, for example, it may be an access device in an NR-U system, such as a 5G New Radio (NR) base station (next generation Node B, gNB) or small station,
  • NR 5G New Radio
  • the micro station can also be a relay station, a transmission and reception point (Transmission and Reception Point, TRP), a road side unit (Road Side Unit, RSU), etc.
  • TRP Transmission and Reception Point
  • RSU road side unit
  • the terminal equipment may also be called a mobile terminal, user equipment (UE), access terminal, user unit, user station, mobile station, mobile station, user terminal, terminal, wireless communication equipment, user agent, or user device.
  • UE user equipment
  • access terminal user unit
  • user station mobile station
  • mobile station mobile station
  • user terminal terminal
  • wireless communication equipment user agent
  • user device Specifically, it can be smart phones, cellular phones, cordless phones, personal digital assistant (PDA) devices, handheld devices with wireless communication functions, or other processing devices connected to wireless modems, in-vehicle devices, wearable devices, etc.
  • PDA personal digital assistant
  • the terminal device has an interface for communicating with a network device (for example, a cellular network).
  • a network device for example, a cellular network
  • the communication system 100 may also include other network entities such as a network controller and a mobility management entity, which are not limited in the embodiment of the present application.
  • network entities such as a network controller and a mobility management entity, which are not limited in the embodiment of the present application.
  • the communication device may include a network device 110 with a communication function and a terminal device 120.
  • the network device 110 and the terminal device 120 may be the specific devices described above, which will not be repeated here.
  • the communication device may also include other devices in the communication system 100, such as other network entities such as a network controller and a mobility management entity, which are not limited in this embodiment of the application.
  • the terminal device in the communication system 100 is not limited to one, and may also be two or more.
  • the terminal device 130 may also be included.
  • the method of the embodiment of the present application can be applied to the communication system shown in FIG. 1.
  • the network device 110 sends a downlink reference signal to the terminal device 120
  • the terminal device 120 performs channel estimation according to the downlink reference signal to obtain downlink channel information. Further, the terminal device 120 may feed back the downlink channel information to the network device 110, so that the network device 110 can determine the precoding matrix of the terminal device 120 according to the downlink channel information.
  • the network device 110 precodes the downlink data according to the precoding matrix, and sends the precoded downlink data to the terminal device 120.
  • the terminal device needs to quantify the downlink channel information before the terminal device feeds back the downlink channel information to the network device. Further, the terminal device sends the quantized downlink channel information to the network device. Since the accuracy of the quantized downlink channel information is low, the precoding matrix corresponding to the terminal device determined by the network device is inaccurate. The downlink transmission performance of the network equipment is reduced.
  • this application provides a channel information processing method, which will be introduced below in conjunction with specific embodiments.
  • FIG. 2 is a signaling diagram of a channel information processing method provided by this application. As shown in Figure 2, the channel information processing method includes the following steps:
  • the network device sends a downlink reference signal to the terminal device.
  • the downlink reference signal sent by the network device to the terminal device is not limited.
  • the downlink reference signal may be a cell-specific reference signal, a user-specific reference signal, a location reference signal, a channel state information (CSI) reference signal, and the like.
  • the terminal device receives the downlink reference signal issued by the network device.
  • the network device may be the network device 110 shown in FIG. 1, and the terminal device may specifically be the terminal device 120 or the terminal device 130 shown in FIG. 1.
  • S202 The terminal device performs channel estimation according to the downlink reference signal to obtain downlink channel information of the channel estimation.
  • the terminal device After the terminal device receives the downlink reference signal sent by the terminal device, it performs channel estimation according to the downlink reference signal to obtain channel estimated downlink channel information, and the channel estimated downlink channel information may specifically be CSI. Further, the terminal device quantizes the downlink channel information of the channel estimation to obtain quantized information of the downlink channel information of the channel estimation. Specifically, the terminal device may quantize each element in the downlink channel information of the channel estimation to obtain quantized information of each element. Correspondingly, the quantization information of the downlink channel information of the channel estimation may be the quantization information of each element in the downlink channel information of the channel estimation. The terminal device determines the quantized downlink channel information according to the quantization information of each element in the downlink channel information of the channel estimation, and calculates the error information between the quantized downlink channel information and the downlink channel information of the channel estimation.
  • the terminal device sends the error information between the quantized downlink channel information and the downlink channel information of the channel estimation, and the quantization information of the downlink channel information of the channel estimation to the network device.
  • the terminal device sends the aforementioned error information and the quantized information of the downlink channel information of the channel estimation to the network device.
  • the network device receives the error information and the quantized information of the downlink channel information of the channel estimation sent by the terminal device.
  • the network device reconstructs to obtain reconstructed downlink channel information according to the error information and the quantization information of the channel estimated downlink channel information.
  • the network device After the network device receives the error information and the quantized information of the downlink channel information of the channel estimation, it first uses the quantized information of the downlink channel information of the channel estimation, for example, the quantized information of each element in the downlink channel information of the channel estimation, To determine the quantized downlink channel information as described above, specifically, the method for the network device and the terminal device to determine the quantized downlink channel information according to the quantization information of each element in the downlink channel information of the channel estimation may be Consistent.
  • the network device reconstructs to obtain reconstructed downlink channel information according to the error information and the quantized downlink channel information. It can be understood that the downlink channel information reconstructed by the network device and the downlink channel information obtained by the terminal device through channel estimation according to the aforementioned downlink reference signal may be the same or different.
  • the network device determines a precoding matrix corresponding to the terminal device according to the reconstructed downlink channel information.
  • the network device determines the precoding matrix corresponding to the terminal device according to its reconstructed downlink channel information. That is, for the error information reported by different terminal devices and the quantized information of the downlink channel information of the channel estimation, the downlink channel information reconstructed by the network device may be different, and thus the precoding matrix obtained for different terminal devices may also be different.
  • this embodiment does not limit the method of determining the precoding matrix based on the reconstructed downlink channel information.
  • the network device may use a linear precoding algorithm to calculate the precoding matrix, or use a nonlinear precoding algorithm to calculate the precoding matrix.
  • linear precoding algorithms can include zero-forcing (ZF) precoding algorithms, minimum mean square error (MMSE) precoding algorithms, and block diagonalization (BD) precoding algorithms. Encoding algorithm, etc.
  • Non-linear precoding algorithms may include Dirty Paper Code (DPC) algorithms, Tomlinson-Harashima Precoding (THP) algorithms, Vector Perturbation (VP) precoding algorithms, and the like.
  • DPC Dirty Paper Code
  • THP Tomlinson-Harashima Precoding
  • VP Vector Perturbation
  • a terminal device receives a downlink reference signal sent by a network device, and performs channel estimation according to the downlink reference signal to obtain channel estimated downlink channel information, and further, sends the quantized downlink channel information to the network device And the error information between the downlink channel information of the channel estimation and the quantization information of the downlink channel information of the channel estimation, so that the network device can reconstruct the obtained information according to the error information and the quantization information of the downlink channel information of the channel estimation.
  • the reconstructed downlink channel information because the error information reflects the error of the quantized downlink channel information relative to the downlink channel information obtained by the terminal device through channel estimation, therefore, compared with the prior art, the network device only receives To the quantized downlink channel information sent by the terminal device, the accuracy of the downlink channel information reconstructed by the network device is higher than the accuracy of the quantized downlink channel information of the terminal device.
  • the downlink channel information reconstructed by the network equipment is closer to the downlink channel information obtained by the terminal equipment through channel estimation.
  • the network equipment is based on the reconstructed downlink channel information
  • the accuracy of the precoding matrix can be improved.
  • the network device further precodes the downlink data according to the precoding matrix, thereby improving the downlink transmission performance of the network device.
  • the quantized downlink channel information is reconstructed based on the quantized information of the downlink channel information of the channel estimation.
  • the quantization information of the downlink channel information of the channel estimation may be the quantization information of each element in the downlink channel information of the channel estimation, and the network device or the terminal equipment is When the quantization information determines the quantized downlink channel information, the quantized downlink channel information may be reconstructed according to the quantization information of each element in the downlink channel information of the channel estimation.
  • the downlink channel information of the channel estimation is a channel covariance matrix.
  • the channel covariance matrix is a square matrix, and this embodiment does not limit the size of the channel covariance matrix.
  • the channel covariance matrix is a 4*4 square matrix, and correspondingly, the channel covariance matrix includes 16 elements.
  • the quantization information of the downlink channel information of the channel estimation is the quantization information of each element in the channel covariance matrix.
  • the terminal device may quantize each of the 16 elements in the channel covariance matrix to obtain the quantization information of each element, and use the quantization information of each element in the channel covariance matrix as the channel estimate
  • the quantization information of the downlink channel information is the quantization information of the channel covariance matrix.
  • each element in the channel covariance matrix may include both the real part and the imaginary part, or may include only the real part or only the imaginary part.
  • each element in the channel covariance matrix including real and imaginary parts
  • the specific value of each element in the channel covariance matrix is The real part and the imaginary part are quantized to obtain the quantization information of the real part of each element in the channel covariance matrix and the quantization information of the imaginary part of each element in the channel covariance matrix.
  • the quantization information of each element in the channel covariance matrix includes: quantization information of the real part of each element in the channel covariance matrix and quantization information of the imaginary part of each element in the channel covariance matrix. Quantitative information.
  • some elements in the channel covariance matrix may include both real and imaginary parts, some elements may only include real parts, and some elements may only include imaginary parts.
  • the real and imaginary parts of the element are quantized separately; if the element only includes the real part, then the element Quantize the real part of; if the element only includes the imaginary part, then quantize the imaginary part of the element.
  • the terminal equipment reconstructs the quantized downlink channel information according to the quantization information of each element in the channel covariance matrix to obtain the quantized downlink channel information, that is, the quantized channel covariance matrix.
  • the quantized information of the real part and the quantized information of the imaginary part of each element are reconstructed to obtain the quantized channel covariance matrix.
  • the downlink channel information of the channel estimation is an eigenvector.
  • the feature vector can be decomposed into multiple beams.
  • the N may be a positive integer greater than or equal to 1.
  • the feature vector can be regarded as a linear superposition of N beams.
  • the quantization information of the downlink channel information of the channel estimation is the quantization information of each beam in the multiple beams after the feature vector is decomposed.
  • the terminal device quantizes each of the N beams after the feature vector is decomposed to obtain the quantization information of each beam, and uses the quantization information of each beam as the quantization information of the downlink channel information.
  • the quantization information of the feature vector includes: beam vector information of each beam in the multiple beams, amplitude information of each beam in the multiple beams, and the multiple beams The phase information of each beam in.
  • the amplitude information may be broadband amplitude information or subband amplitude information.
  • the terminal device performs reconstruction according to the quantization information of each of the N beams to obtain the quantized downlink channel information, that is, the quantized feature vector.
  • the terminal device When the terminal equipment reconstructs according to the quantization information of each element in the channel covariance matrix to obtain the quantized downlink channel information, that is, the quantized channel covariance matrix, or according to the quantization information of each of the N beams After reconstructing the quantized downlink channel information, that is, the quantized feature vector, the terminal device further calculates the error information between the quantized downlink channel information and the channel estimated downlink channel information.
  • the error information is quantized information of the mean square error between the quantized downlink channel information and the channel estimated downlink channel information.
  • the terminal device may first calculate the channel covariance matrix R and the quantized channel covariance matrix Mean Square Error (MSE), where R and The mean square error between is recorded as MSE R , specifically, Among them, diag represents the operation of taking diagonal elements. Further, the terminal device may be the mean square error MSE R quantized, the quantization information to obtain the mean square error MSE R, specifically, the quantization information MSE R may be the mean square error of the mean square error MSE R each Quantitative information of each element.
  • MSE Mean Square Error
  • the quantized information of the mean square error MSE R is taken as R and The error information between R and The error information between is understood as Error information relative to R.
  • R and The error information between can not be limited to R and The quantization information of the mean square error between may also be other error information in some embodiments.
  • the error information is the mean square error MSE R , which is only a schematic illustration here.
  • the terminal device sends the quantization information of each element in the mean square error MSE R and the quantization information of the channel covariance matrix R to the network device, where the quantization information of the channel covariance matrix R is the channel covariance matrix
  • the quantization information of each element in R for example, the quantization information of the real part and the imaginary part of each element.
  • the network device When the network device receives the quantization information of each element in the mean square error MSE R and the quantization information of each element in the channel covariance matrix R sent by the terminal device, the network device first performs the quantization information according to the channel covariance matrix R The quantized information of each element in the quantized information is reconstructed to obtain the quantized channel covariance matrix, which is And reconstruct the quantized mean square error according to the quantization information of each element in the mean square error MSE R.
  • the quantized mean square error is recorded as Further, the network device according to the quantized mean square error And the quantized channel covariance matrix Reconstruct the channel covariance matrix.
  • the channel covariance matrix reconstructed by the network device may be different from the channel covariance matrix R obtained by the terminal device according to the downlink reference signal issued by the network device for channel estimation, the channel covariance matrix reconstructed by the network device Marked as R', specifically, Among them, DiagMatrix said that The elements of as diagonal elements form a diagonal matrix operation.
  • the terminal device may first calculate the feature vector V and the quantized feature vector The mean square error between V and The mean square error between is recorded as MSE V , specifically, Further, the terminal device may be the mean square error MSE V quantized, the quantization information to obtain the mean square error MSE V, and particularly, the mean square error MSE V quantization information may be the mean square error MSE V per Quantitative information of each element.
  • the quantized information of the mean square error MSE V is taken as V and The error information between V and The error information between is understood as Error information relative to V.
  • V and The error information between is not limited to V and The quantization information of the mean square error between may also be other error information in some embodiments.
  • the error information is the mean square error MSE V , which is just a schematic illustration here.
  • the terminal device sends the quantization information of each element in the mean square error MSE V and the quantization information of the feature vector V to the network device, where the quantization information of the feature vector V is the multiplicity of the feature vector V decomposed. The quantized information of each beam in each beam.
  • the network device When the network device receives the quantization information of each element in the mean square error MSE V sent by the terminal device and the quantization information of each beam in the multiple beams after the feature vector V is decomposed, the network device first The quantized information of each beam in the multiple beams is reconstructed to obtain the quantized feature vector, which is And reconstruct the quantized mean square error according to the quantization information of each element in the mean square error MSE V.
  • the quantized mean square error is recorded as Further, the network device according to the quantized mean square error And the quantized feature vector Reconstruct the feature vector.
  • the eigenvector reconstructed by the network device may be different from the eigenvector V obtained by the terminal device through channel estimation based on the downlink reference signal issued by the network device, the eigenvector reconstructed by the network device is recorded as V', specific, among them, Means The conjugate transposed matrix.
  • the terminal device reconstructs the quantized downlink channel information according to the quantized information of each element in the downlink channel information of the channel estimation, and calculates the quantized downlink channel information and the channel
  • the quantization information of the mean square error between the estimated downlink channel information, and the quantization information of the mean square error and the quantization information of each element in the downlink channel information of the channel estimation are sent to the network device, so that the network device first
  • the quantized information of each element in the downlink channel information of the channel estimation is reconstructed to obtain the quantized downlink channel information, and further, the reconstructed downlink channel is reconstructed according to the quantized information of the mean square error and the quantized downlink channel information
  • the quantized information of the mean square error reflects the error of the quantized downlink channel information relative to the downlink channel information obtained by the terminal device through channel estimation
  • the accuracy of the downlink channel information reconstructed by the network device is high The accuracy of the downlink channel information directly quantized by the terminal equipment.
  • since the error reflects the error of
  • the channel information in the lower row is the channel covariance matrix as an example to introduce the information interaction process between the network device and the terminal device. Specifically, it includes the following steps as shown in Figure 3:
  • the network device sends a downlink reference signal to the terminal device.
  • the network device communicates with multiple terminal devices, take one terminal device as an example for schematic description.
  • the terminal device is a terminal device of user k, and the terminal device receives the downlink reference signal issued by the network device.
  • the terminal device performs channel estimation according to the downlink reference signal to obtain a channel covariance matrix.
  • the channel covariance matrix obtained by the terminal equipment of user k through channel estimation based on the downlink reference signal is denoted as R(k), that is, the channel covariance matrix obtained by the terminal equipment of different users may be different.
  • R(k) the channel covariance matrix obtained by the terminal equipment of different users
  • the terminal device respectively quantizes and reconstructs the real part and the imaginary part of each element in the channel covariance matrix to obtain a quantized channel covariance matrix.
  • the channel covariance matrix R(k) is a 4*4 square matrix
  • each element of R(k) is a complex number, that is, each element includes real and imaginary parts, for example, a 11 + b 11 i is the first element of the first row of R(k), a 11 Is the real part of the element, b 11 is the imaginary part of the element, the other elements are the same, so I won’t repeat them.
  • the terminal device quantizes the real and imaginary parts of each element of the channel covariance matrix R(k), for example, the first element a 11 + b 11 i of the first row of R(k)
  • the real part a 11 and the imaginary part b 11 are respectively quantized to obtain the quantization information of the real part a 11
  • the quantitative information of the imaginary part b 11 In the same way, the real and imaginary parts of the other elements in the R(k) are quantized separately to obtain the quantized information of the real part and the imaginary part of the other elements.
  • the quantization information of the real part and the imaginary part of each element in R(k) can be used as the quantization information of the R(k).
  • the terminal device can reconstruct the quantized channel covariance matrix according to the quantization information of R(k) That is, the terminal device can reconstruct the quantized channel covariance matrix according to the quantized information of the real part and the quantized information of the imaginary part of each element in the R(k) Specifically, R(k) and After quantizing the element at a certain position in R(k) to obtain the quantized information of the real and imaginary parts of the element, the quantization information of the real and imaginary parts of the element can be reconstructed to obtain the Elements in the same position in the. For example, the quantization information of the real part a 11 of the first element in the first row of R(k) And the quantitative information of the imaginary part b 11 Can be reconstructed into the The first element in the first row in the final result For example
  • the terminal device calculates the quantized channel covariance matrix and the mean square error between the channel covariance matrix.
  • the terminal equipment calculation The mean square error MSE R between and R(k), specifically, Among them, diag represents the operation of taking diagonal elements. Understandable, Is a 4*4 square matrix, It is also a 4*4 square matrix, It's still a 4*4 square matrix, right When taking diagonal elements, 4 diagonal elements can be obtained.
  • the mean square error MSE R between and R(k) includes 4 elements, and each element of MSE R is also a complex number.
  • the terminal device quantizes the mean square error.
  • the terminal device may further quantizing each element of the MSE R included in the MSE R quantization information obtained in each element. Because of the The mean square error MSE R between R and R(k) includes 4 elements. Therefore, the quantization of the mean square error MSE R is the quantization of each element in the MSE R.
  • the 4 elements included in the MSE R are sequentially denoted as A 1 + B 1 i, A 2 + B 2 i, A 3 + B 3 i, A 4 + B 4 i, and the terminal device responds to each of the 4 elements.
  • the real and imaginary parts of each element are quantized, for example, the real part of A 1 +B 1 i is quantized as Quantify the imaginary part of A 1 + B 1 i as Similarly, the real part of A 2 +B 2 i is quantified as Quantify the imaginary part of A 2 + B 2 i as Quantify the real part of A 3 + B 3 i as Quantify the imaginary part of A 3 +B 3 i as Quantify the real part of A 4 + B 4 i as Quantify the imaginary part of A 4 + B 4 i as
  • the following takes the real part A 1 of A 1 + B 1 i as an example to introduce a quantization method. It is understandable that the quantization method can also be applied to quantize the imaginary part of each element in MSE R. The quantization The method can also be applied to quantize the real and imaginary parts of each element in R(k).
  • 1.34 belongs to the range of 1.25-1.49, that is, for the sixth stage, the quantized information of 1.34 is 101. It can be understood that this is only a schematic description, and does not specifically limit the quantification method and the quantification process.
  • the terminal device sends the quantization information of each element in the channel covariance matrix and the quantization information of the mean square error to the network device.
  • the terminal device may quantize the quantization information of each element in the channel covariance matrix R(k), for example, And the quantitative information of each element in the mean square error MSE R , for example, Send to network equipment.
  • Step S307 The network device reconstructs the quantized channel covariance matrix according to the quantization information of each element in the channel covariance matrix.
  • the network device When the network device receives the quantization information of each element in the channel covariance matrix R(k), for example, And the quantitative information of each element in the mean square error MSE R , for example, At this time, the network device can use the quantization information of each element in the channel covariance matrix R(k), for example, Reconstruct the quantized channel covariance matrix
  • the network device reconstructs to obtain a reconstructed channel covariance matrix according to the quantization information of the mean square error and the quantized channel covariance matrix.
  • the network device may also use the quantitative information of each element in the mean square error MSE R , for example, Reconstruction to get the quantized mean square error Also includes 4 elements, The 4 elements included are recorded as
  • the network device according to the quantized mean square error And the quantized channel covariance matrix
  • the reconstructed channel covariance matrix is obtained by reconstruction, and the channel covariance matrix reconstructed by the network device is denoted as R'(k), specifically, Among them, DiagMatrix said that The elements of as diagonal elements form a diagonal matrix operation.
  • the network device determines a precoding matrix corresponding to the terminal device according to the reconstructed channel covariance matrix.
  • the network device can calculate the precoding matrix corresponding to the terminal device by using a linear ZF precoding algorithm or a nonlinear VP precoding algorithm according to the reconstructed channel covariance matrix R'(k).
  • the network device precodes the downlink data according to the precoding matrix.
  • a terminal device receives a downlink reference signal sent by a network device, and performs channel estimation according to the downlink reference signal to obtain a channel covariance matrix, and further, sends the quantized channel covariance matrix and The error information between the channel covariance matrices and the quantization information of the channel covariance matrix, so that the network device can reconstruct the reconstructed channel covariance matrix according to the error information and the quantization information of the channel covariance matrix, Since the error information reflects the error of the quantized channel covariance matrix with respect to the channel covariance matrix obtained by the terminal device through channel estimation, compared with the prior art, the network device only receives the data sent by the terminal device.
  • the accuracy of the channel covariance matrix reconstructed by the network equipment is higher than the accuracy of the quantized channel covariance matrix of the terminal equipment, that is, compared to the quantized channel covariance matrix of the terminal equipment Variance matrix, the channel covariance matrix reconstructed by the network device is closer to the channel covariance matrix obtained by the terminal device through channel estimation, when the network device determines the precoding matrix corresponding to the terminal device according to the reconstructed channel covariance matrix , The accuracy of the precoding matrix can be improved, and the network device further precodes the downlink data according to the precoding matrix, thereby improving the downlink transmission performance of the network device.
  • the network device sends a downlink reference signal to the terminal device.
  • the network device communicates with multiple terminal devices, take one terminal device as an example for schematic description.
  • the terminal device is a terminal device of user k, and the terminal device receives the downlink reference signal issued by the network device.
  • the terminal device performs channel estimation according to the downlink reference signal to obtain a feature vector.
  • the terminal equipment of user k performs channel estimation according to the downlink reference signal to obtain a channel covariance matrix R(k), and further performs eigenvalue decomposition on the channel covariance matrix R(k) to obtain an eigenvector V.
  • the terminal device quantizes and reconstructs each of the multiple beams after the feature vector is decomposed to obtain a quantized feature vector.
  • the terminal device may decompose the feature vector V into N beams, and quantize each beam separately to obtain the quantization information of each beam.
  • the quantization information of each beam includes the beam of the beam.
  • the quantization information of each of the N beams can be used as the quantization information of the feature vector V. Further, the terminal device reconstructs according to the quantization information of each of the N beams to obtain the quantized feature vector
  • S404 The terminal device calculates the mean square error between the quantized feature vector and the feature vector.
  • the terminal device calculates the feature vector V and the quantized feature vector The mean square error between V and The mean square error between is recorded as MSE V , specifically,
  • the terminal device performs quantization processing on the mean square error.
  • the terminal device may perform quantization processing on the mean square error MSE V to obtain quantization information of the mean square error MSE V.
  • the mean square error (MSE) of the quantization information quantization information V may be the mean square error (MSE) of each V element.
  • the terminal device sends to the network device the quantization information of each of the multiple beams in which the feature vector is decomposed and the quantization information of the mean square error.
  • the terminal device sends the quantization information of each element in the mean square error MSE V and the quantization information of the feature vector V to the network device, where the quantization information of the feature vector V is the multiple beams after the feature vector V is decomposed Quantitative information for each beam.
  • the network device reconstructs the quantized feature vector according to the quantization information of each of the multiple beams after the feature vector is decomposed.
  • the network device When the network device receives the quantization information of each element in the mean square error MSE V sent by the terminal device and the quantization information of each beam in the multiple beams after the feature vector V is decomposed, the network device first The quantized information of each beam in the multiple beams is reconstructed to obtain the quantized feature vector, which is
  • the network device reconstructs to obtain a reconstructed feature vector according to the quantized information of the mean square error and the quantized feature vector.
  • the network device can also reconstruct the quantized mean square error according to the quantization information of each element in the mean square error MSE V.
  • the quantized mean square error is recorded as Further, the network device according to the quantized mean square error And the quantized feature vector Reconstruct the feature vector, the reconstructed feature vector V'is among them, Means The conjugate transposed matrix.
  • the network device determines a precoding matrix corresponding to the terminal device according to the reconstructed feature vector.
  • the network device may calculate the precoding matrix corresponding to the terminal device by using a linear ZF or BD precoding algorithm or a nonlinear VP precoding algorithm according to the reconstructed eigenvector V'.
  • the network device may also directly use the reconstructed feature vector V'as the precoding matrix corresponding to the terminal device.
  • the precoding matrix W of the terminal device calculated by the network device using the linear ZF precoding algorithm according to the reconstructed eigenvector V' may be:
  • the network device precodes the downlink data according to the precoding matrix.
  • a terminal device receives a downlink reference signal sent by a network device, and performs channel estimation according to the downlink reference signal to obtain a feature vector, and further, sends the quantized feature vector and the feature vector to the network device
  • the error information and the quantization information of the feature vector so that the network device can reconstruct the reconstructed feature vector according to the error information and the quantization information of the feature vector, because the error information reflects the quantized feature
  • the accuracy of the feature vector reconstructed by the network device is The performance is higher than the accuracy of the quantized feature vector of the terminal device. That is to say, the feature vector reconstructed by the network device is closer to the feature vector obtained by the terminal device through channel estimation than the quantized feature vector of the terminal device.
  • Vector When the network device determines the precoding matrix corresponding to the terminal device according to the reconstructed feature vector, the accuracy of the precoding matrix can be improved.
  • the network device further precodes the downlink data according to the precoding matrix, thereby improving the network device Downlink transmission performance.
  • FIG. 5 is a schematic structural diagram of the terminal device provided by this application. As shown in FIG. 5, the terminal device 50 includes:
  • the receiving module 51 is configured to receive a downlink reference signal sent by a network device
  • the channel estimation module 52 is configured to perform channel estimation according to the downlink reference signal to obtain channel estimation downlink channel information
  • the sending module 53 is configured to send error information between the quantized downlink channel information and the channel estimated downlink channel information, and the quantized information of the channel estimated downlink channel information to the network device.
  • the terminal device provided in this embodiment is used to implement the technical solution on the terminal device side in any of the foregoing method embodiments, and its implementation principles and technical effects are similar, and will not be repeated here.
  • the quantized downlink channel information is reconstructed based on the quantized information of the downlink channel information of the channel estimation.
  • the downlink channel information of the channel estimation is a channel covariance matrix or an eigenvector.
  • the downlink channel information of the channel estimation is a channel covariance matrix
  • the quantization information of the downlink channel information of the channel estimation is quantization information of each element in the channel covariance matrix.
  • the quantization information of each element in the channel covariance matrix includes: quantization information of the real part of each element in the channel covariance matrix and quantization information of the imaginary part of each element in the channel covariance matrix. Quantitative information.
  • the downlink channel information of the channel estimation is an eigenvector
  • the quantization information of the downlink channel information of the channel estimation is the quantization information of each beam in a plurality of beams after the eigenvector is decomposed.
  • the quantized information of each beam in the multiple beams includes: beam vector information of each beam in the multiple beams, amplitude information of each beam in the multiple beams, and the multiple beams The phase information of each beam in.
  • the error information is quantized information of a mean square error between the quantized downlink channel information and the channel estimated downlink channel information.
  • the mean square error is:
  • MSE R represents the mean square error
  • diag represents the operation of taking diagonal elements
  • R represents the channel covariance matrix
  • the mean square error is:
  • MSE V represents the mean square error
  • V represents the feature vector
  • FIG. 6 is a schematic structural diagram of the network device provided by this application. As shown in FIG. 6, the network device 60 includes:
  • the sending module 61 is configured to send a downlink reference signal to a terminal device
  • the receiving module 62 is configured to receive error information between the quantized downlink channel information and the channel estimated downlink channel information sent by the terminal equipment, and the quantized information of the channel estimated downlink channel information;
  • the processing module 63 is configured to reconstruct to obtain reconstructed downlink channel information according to the error information and the quantization information of the channel estimated downlink channel information; and determine the corresponding terminal device according to the reconstructed downlink channel information Precoding matrix.
  • the network device provided in this embodiment is used to implement the technical solution on the network device side in any of the foregoing method embodiments, and its implementation principles and technical effects are similar, and will not be repeated here.
  • the quantized downlink channel information is reconstructed based on the quantized information of the downlink channel information of the channel estimation.
  • the downlink channel information of the channel estimation is a channel covariance matrix or an eigenvector.
  • the downlink channel information of the channel estimation is a channel covariance matrix
  • the quantization information of the downlink channel information of the channel estimation is quantization information of each element in the channel covariance matrix.
  • the quantization information of each element in the channel covariance matrix includes: quantization information of the real part of each element in the channel covariance matrix and quantization information of the imaginary part of each element in the channel covariance matrix. Quantitative information.
  • the downlink channel information of the channel estimation is an eigenvector
  • the quantization information of the downlink channel information of the channel estimation is the quantization information of each beam in a plurality of beams after the eigenvector is decomposed.
  • the quantized information of each beam in the multiple beams includes: beam vector information of each beam in the multiple beams, amplitude information of each beam in the multiple beams, and the multiple beams The phase information of each beam in.
  • the error information is quantized information of a mean square error between the quantized downlink channel information and the channel estimated downlink channel information.
  • the reconstructed channel covariance matrix is: Where R'represents the reconstructed channel covariance matrix, Represents the quantized channel covariance matrix, Represents the quantized mean square error, the quantized mean square error is reconstructed based on the quantization information of the mean square error, and DiagMatrix represents The elements of as diagonal elements form a diagonal matrix operation.
  • the reconstructed feature vector is: Where V'represents the reconstructed feature vector, Represents the quantized feature vector, Means The conjugate transpose matrix of Represents the quantized mean square error, and the quantized mean square error is reconstructed based on the quantization information of the mean square error.
  • FIG. 7 is a schematic diagram of another structure of the terminal device provided by this application. As shown in FIG. 7, the terminal device 70 includes:
  • a processor 71 for communicating with network equipment;
  • the memory 72 stores computer execution instructions
  • the processor 71 executes the computer-executable instructions stored in the memory 72, so that the processor 71 executes the technical solution on the terminal device side in any of the foregoing method embodiments.
  • FIG. 7 is a simple design of a terminal device.
  • the embodiment of the present application does not limit the number of processors and memories in the terminal device.
  • FIG. 7 only uses 1 as an example for illustration.
  • FIG. 8 is a schematic diagram of another structure of the network device provided by this application. As shown in FIG. 8, the network device 80 includes:
  • a processor 81 for communicating with terminal equipment;
  • the memory 82 stores computer execution instructions
  • the processor 81 executes the computer-executable instructions stored in the memory 82, so that the processor 81 executes the technical solution on the network device side in any of the foregoing method embodiments.
  • Fig. 8 is a simple design of a network device.
  • the embodiment of the present application does not limit the number of processors and memories in the network device.
  • Fig. 8 only uses 1 as an example for illustration.
  • the memory, the processor, and the interface may be connected by a bus.
  • the memory may be integrated inside the processor.
  • the embodiment of the present application also provides a computer-readable storage medium.
  • the computer-readable storage medium stores computer-executable instructions. When the computer-executable instructions are executed by a processor, they are used to implement the terminal device in any of the foregoing method embodiments. Side technical solutions.
  • An embodiment of the present application also provides a computer-readable storage medium that stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, it is used to implement the network in any of the foregoing method embodiments.
  • Technical solutions on the equipment side are provided.
  • An embodiment of the present application also provides a chip, including a processor, configured to call and run a computer program from a memory, so that a device installed with the chip executes the channel information processing method described in any of the foregoing method embodiments.
  • the embodiments of the present application also provide a computer program product, including computer program instructions, which cause a computer to execute the channel information processing method described in any of the foregoing method embodiments.
  • the embodiment of the present application also provides a computer program that enables a computer to execute the channel information processing method described in any of the foregoing method embodiments.
  • the disclosed device and method may be implemented in other ways.
  • the device embodiments described above are only illustrative.
  • the division of the modules is only a logical function division, and there may be other divisions in actual implementation, for example, multiple modules can be combined or integrated. To another system, or some features can be ignored, or not implemented.
  • the displayed or discussed mutual coupling or direct coupling or communication connection may be through some interfaces.
  • the indirect coupling or communication connection of the modules may be in electrical, mechanical or other forms.
  • the processor may be a central processing unit (English: Central Processing Unit, abbreviated as: CPU), or other general-purpose processors, digital signal processors (English: Digital Signal Processor, referred to as DSP), application specific integrated circuit (English: Application Specific Integrated Circuit, referred to as ASIC), etc.
  • the general-purpose processor may be a microprocessor or the processor may also be any conventional processor or the like. The steps of the method disclosed in this application may be directly embodied as being executed by a hardware processor, or executed by a combination of hardware and software modules in the processor.
  • All or part of the steps in the foregoing method embodiments can be implemented by a program instructing relevant hardware.
  • the aforementioned program can be stored in a readable memory.
  • the program executes the steps including the foregoing method embodiments; and the foregoing memory (storage medium) includes: read-only memory (English: read-only memory, abbreviated as: ROM), RAM, flash memory, hard disk, Solid state drives, magnetic tapes (English: magnetic tape), floppy disks (English: floppy disk), optical discs (English: optical disc) and any combination thereof.

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Abstract

本申请实施例提供一种信道信息处理方法、设备及存储介质，终端设备接收网络设备发送的下行参考信号，并根据该下行参考信号进行信道估计得到信道估计的下行信道信息，进一步，向网络设备发送量化后的下行信道信息和信道估计的下行信道信息之间的误差信息、以及信道估计的下行信道信息的量化信息，使得网络设备可根据该误差信息和该信道估计的下行信道信息的量化信息重构得到重构的下行信道信息，由于重构的下行信道信息的准确性高于量化后的下行信道信息的准确性，当网络设备根据该重构出的下行信道信息确定终端设备对应的预编码矩阵时，可提高预编码矩阵的准确性，网络设备根据预编码矩阵对下行数据进行预编码，从而提高网络设备的下行传输性能。

Description

信道信息处理方法、设备及存储介质 技术领域
本申请实施例涉及通信技术，尤其涉及一种信道信息处理方法、设备及存储介质。
背景技术
现有技术中，网络设备(例如基站)会向终端设备发送下行参考信号，终端设备可根据该下行参考信号进行信道估计从而得到下行信道信息。进一步，终端设备可以将下行信道信息反馈给网络设备，使得网络设备可以根据下行信道信息确定预编码矩阵，并根据预编码矩阵对下行数据进行预编码。
通常终端设备向网络设备反馈下行信道信息之前，需要对下行信道信息进行量化。进一步，将量化后的下行信道信息发送给网络设备，由于量化后的下行信道信息的准确性较低，导致网络设备确定出的预编码矩阵也不准确，从而降低了网络设备的下行传输性能。
发明内容
本申请实施例提供一种信道信息处理方法、设备及存储介质，以提高网络设备的下行传输性能。
第一方面，本申请实施例可提供一种信道信息处理方法，应用于终端设备，该方法包括：
接收网络设备发送的下行参考信号；
根据所述下行参考信号进行信道估计得到信道估计的下行信道信息；
向所述网络设备发送量化后的下行信道信息和所述信道估计的下行信道信息之间的误差信息、以及所述信道估计的下行信道信息的量化信息。
第二方面，本申请实施例可提供一种信道信息处理方法，应用于网络设备，该方法包括：
向终端设备发送下行参考信号；
接收所述终端设备发送的量化后的下行信道信息和信道估计的下行信道信息之间的误差信息、以及所述信道估计的下行信道信息的量化信息；
根据所述误差信息和所述信道估计的下行信道信息的量化信息重构得到重构的下行信道信息；
根据所述重构的下行信道信息，确定所述终端设备对应的预编码矩阵。
第三方面，本申请实施例可提供一种终端设备，包括：
接收模块，用于接收网络设备发送的下行参考信号；
信道估计模块，用于根据所述下行参考信号进行信道估计得到信道估计的下行信道信息；
发送模块，用于向所述网络设备发送量化后的下行信道信息和所述信道估计的下行信道信息之间的误差信息、以及所述信道估计的下行信道信息的量化信息。
第四方面，本申请实施例可提供一种网络设备，包括：
发送模块，用于向终端设备发送下行参考信号；
接收模块，用于接收所述终端设备发送的量化后的下行信道信息和信道估计的下行信道信息之间的误差信息、以及所述信道估计的下行信道信息的量化信息；
处理模块，用于根据所述误差信息和所述信道估计的下行信道信息的量化信息重构得 到重构的下行信道信息；根据所述重构的下行信道信息，确定所述终端设备对应的预编码矩阵。
第五方面，本申请实施例可提供一种终端设备，包括：
处理器、存储器、与网络设备进行通信的接口；
所述存储器存储计算机执行指令；
所述处理器执行所述存储器存储的计算机执行指令，使得所述处理器执行如第一方面所述的信道信息处理方法。
第六方面，本申请实施例可提供一种网络设备，包括：
处理器、存储器、与网络设备进行通信的接口；
所述存储器存储计算机执行指令；
所述处理器执行所述存储器存储的计算机执行指令，使得所述处理器执行如第二方面所述的信道信息处理方法。
第七方面，本申请实施例提供一种计算机可读存储介质，所述计算机可读存储介质中存储有计算机执行指令，当所述计算机执行指令被处理器执行时用于实现如第一方面所述的信道信息处理方法。
第八方面，本申请实施例提供一种计算机可读存储介质，所述计算机可读存储介质中存储有计算机执行指令，当所述计算机执行指令被处理器执行时用于实现如第二方面所述的信道信息处理方法。
第九方面，本申请实施例提供一种芯片，包括：处理器，用于从存储器中调用并运行计算机程序，使得安装有所述芯片的设备执行如第一方面或第二方面所述的信道信息处理方法。
第十方面，本申请实施例提供一种计算机程序产品，包括计算机程序指令，该计算机程序指令使得计算机执行如第一方面或第二方面所述的信道信息处理方法。
第十一方面，本申请实施例还提供一种计算机程序，该计算机程序使得计算机执行如上第一方面或第二方面所述的信道信息处理方法。
本申请实施例提供的信道信息处理方法、设备及存储介质，终端设备接收网络设备发送的下行参考信号，并根据该下行参考信号进行信道估计得到信道估计的下行信道信息，进一步，向网络设备发送量化后的下行信道信息和所述信道估计的下行信道信息之间的误差信息、以及所述信道估计的下行信道信息的量化信息，使得网络设备可根据该误差信息和该信道估计的下行信道信息的量化信息重构得到重构的下行信道信息，由于该误差信息反映出了该量化后的下行信道信息相对于该终端设备通过信道估计得到的下行信道信息的误差，因此，相比于现有技术中网络设备只接收到终端设备发送的量化后的下行信道信息，网络设备重构出的下行信道信息的准确性高于终端设备量化后的下行信道信息的准确性。也就是说，相比于终端设备量化后的下行信道信息，网络设备重构出的下行信道信息更接近于终端设备通过信道估计得到的下行信道信息，当网络设备根据重构出的下行信道信息确定终端设备对应的预编码矩阵时，可提高预编码矩阵的准确性，网络设备进一步根据预编码矩阵对下行数据进行预编码，从而提高网络设备的下行传输性能。
附图说明
为了更清楚地说明本申请实施例或现有技术中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图做一简单地介绍，显而易见地，下面描述中的附图是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动性的前提下，还可以根据这些附图获得其他的附图。
图1为本申请提供的一种通信系统的示意图；
图2为本申请提供的一种信道信息处理方法的信令图；
图3为本申请提供的另一种信道信息处理方法的信令图；
图4为本申请提供的再一种信道信息处理方法的信令图；
图5为本申请提供的终端设备的一种结构示意图；
图6为本申请提供的网络设备的一种结构示意图；
图7为本申请提供的终端设备的另一种结构示意图；
图8为本申请提供的网络设备的另一种结构示意图。
具体实施方式
为使本申请实施例的目的、技术方案和优点更加清楚，下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例是本申请一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。
本申请实施例的说明书、权利要求书及上述附图中的术语“第一”、“第二”等是用于区别类似的对象，而不必用于描述特定的顺序或先后次序。应该理解这样使用的数据在适当情况下可以互换，以便这里描述的本申请的实施例例如能够以除了在这里图示或描述的那些以外的顺序实施。此外，术语“包括”和“具有”以及他们的任何变形，意图在于覆盖不排他的包含，例如，包含了一系列步骤或单元的过程、方法、系统、产品或设备不必限于清楚地列出的那些步骤或单元，而是可包括没有清楚地列出的或对于这些过程、方法、产品或设备固有的其它步骤或单元。
下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行描述，显然，所描述的实施例是本申请一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。
本申请实施例的技术方案可以应用于各种通信系统，例如：全球移动通讯(Global System of Mobile communication，GSM)系统、码分多址(Code Division Multiple Access，CDMA)系统、宽带码分多址(Wideband Code Division Multiple Access，WCDMA)系统、通用分组无线业务(General Packet Radio Service，GPRS)、长期演进(Long Term Evolution，LTE)系统、LTE频分双工(Frequency Division Duplex，FDD)系统、LTE时分双工(Time Division Duplex，TDD)系统、先进的长期演进(Advanced long term evolution，LTE-A)系统、新无线(New Radio，NR)系统、NR系统的演进系统、非授权频段上的LTE(LTE-based access to unlicensed spectrum，LTE-U)系统、非授权频段上的NR(NR-based access to unlicensed spectrum，NR-U)系统、通用移动通信系统(Universal Mobile Telecommunication System，UMTS)、全球互联微波接入(Worldwide Interoperability for Microwave Access，WiMAX)通信系统、无线局域网(Wireless Local Area Networks，WLAN)、无线保真(Wireless Fidelity，WiFi)、下一代通信系统或其他通信系统等。
通常来说，传统的通信系统支持的连接数有限，也易于实现。然而，随着通信技术的发展，移动通信系统将不仅支持传统的通信，还将支持例如，设备到设备(Device to Device，D2D)通信，机器到机器(Machine to Machine，M2M)通信，机器类型通信(Machine Type Communication，MTC)，以及车辆间(Vehicle to Vehicle，V2V)通信等，本申请实施例也可以应用于这些通信系统。
示例性的，本申请实施例应用的通信系统100如图1所示。该通信系统100可以包括网络设备110，网络设备110可以是与终端设备120(或称为通信终端、终端)通信的设 备。网络设备110可以为特定的地理区域提供通信覆盖，并且可以与位于该覆盖区域内的终端设备进行通信。可选地，该网络设备110可以是GSM系统或CDMA系统中的基站(Base Transceiver Station，BTS)，也可以是WCDMA系统中的基站(NodeB，NB)，还可以是LTE系统中的演进型基站(Evolutional Node B，eNB或eNodeB)，或者是云无线接入网络(Cloud Radio Access Network，CRAN)中的无线控制器，或者该网络设备可以为移动交换中心、中继站、接入点、车载设备、可穿戴设备、集线器、交换机、网桥、路由器、5G网络中的网络侧设备或者未来演进的公共陆地移动网络(Public Land Mobile Network，PLMN)中的网络设备等。
该通信系统100还包括位于网络设备110覆盖范围内的至少一个终端设备120。作为在此使用的“终端设备”包括但不限于经由有线线路连接，如经由公共交换电话网络(Public Switched Telephone Networks，PSTN)、数字用户线路(Digital Subscriber Line，DSL)、数字电缆、直接电缆连接；和/或另一数据连接/网络；和/或经由无线接口，如，针对蜂窝网络、无线局域网(Wireless Local Area Network，WLAN)、诸如DVB-H网络的数字电视网络、卫星网络、AM-FM广播发送器；和/或另一终端设备的被设置成接收/发送通信信号的装置；和/或物联网(Internet of Things，IoT)设备。被设置成通过无线接口通信的终端设备可以被称为“无线通信终端”、“无线终端”或“移动终端”。移动终端的示例包括但不限于卫星或蜂窝电话；可以组合蜂窝无线电电话与数据处理、传真以及数据通信能力的个人通信系统(Personal Communications System，PCS)终端；可以包括无线电电话、寻呼机、因特网/内联网接入、Web浏览器、记事簿、日历以及/或全球定位系统(Global Positioning System，GPS)接收器的PDA；以及常规膝上型和/或掌上型接收器或包括无线电电话收发器的其它电子装置。终端设备可以指接入终端、用户设备(User Equipment，UE)、用户单元、用户站、移动站、移动台、远方站、远程终端、移动设备、用户终端、终端、无线通信设备、用户代理或用户装置。接入终端可以是蜂窝电话、无绳电话、会话启动协议(Session Initiation Protocol，SIP)电话、无线本地环路(Wireless Local Loop，WLL)站、个人数字处理(Personal Digital Assistant，PDA)、具有无线通信功能的手持设备、计算设备或连接到无线调制解调器的其它处理设备、车载设备、可穿戴设备、5G网络中的终端设备或者未来演进的PLMN中的终端设备等。
可选地，终端设备120之间可以进行终端直连(Device to Device，D2D)通信。
可选地，5G系统或5G网络还可以称为新无线(New Radio，NR)系统或NR网络。
图1示例性地示出了一个网络设备和两个终端设备，可选地，该通信系统100可以包括多个网络设备并且每个网络设备的覆盖范围内可以包括其它数量的终端设备，本申请实施例对此不做限定。
在图1中，网络设备可以是接入设备，例如可以是NR-U系统中的接入设备，例如5G的新无线(New Radio，NR)基站(next generation Node B，gNB)或小站、微站，还可以是中继站、发送和接收点(Transmission and Reception Point，TRP)、路边单元(Road Side Unit,RSU)等。
终端设备也可以称为移动终端、用户设备(User Equipment，UE)、接入终端、用户单元、用户站、移动站、移动台、用户终端、终端、无线通信设备、用户代理或用户装置。具体可以是智能手机、蜂窝电话、无绳电话、个人数字处理(Personal Digital Assistant，简称：PDA)设备、具有无线通信功能的手持设备或连接到无线调制解调器的其它处理设备、车载设备、可穿戴设备等。在本申请实施例中，该终端设备具有与网络设备(例如：蜂窝网络)进行通信的接口。
可选地，该通信系统100还可以包括网络控制器、移动管理实体等其他网络实体，本申请实施例对此不作限定。
应理解，本申请实施例中网络/系统中具有通信功能的设备可称为通信设备。以图1 示出的通信系统100为例，通信设备可包括具有通信功能的网络设备110和终端设备120，网络设备110和终端设备120可以为上文所述的具体设备，此处不再赘述；通信设备还可包括通信系统100中的其他设备，例如网络控制器、移动管理实体等其他网络实体，本申请实施例中对此不做限定。此外，该通信系统100中的终端设备不限于一个，还可以是两个及以上，例如，还可以包括终端设备130。
应理解，本文中术语“系统”和“网络”在本文中常被可互换使用。本文中术语“和/或”，仅仅是一种描述关联对象的关联关系，表示可以存在三种关系，例如，A和/或B，可以表示：单独存在A，同时存在A和B，单独存在B这三种情况。另外，本文中字符“/”，一般表示前后关联对象是一种“或”的关系。
本申请实施例的方法可以应用于如图1所示的通信系统，以终端设备120为例，网络设备110给终端设备120发送下行数据之前，网络设备110向该终端设备120发送下行参考信号，终端设备120根据该下行参考信号进行信道估计从而得到下行信道信息。进一步，终端设备120可以将该下行信道信息反馈给网络设备110，使得该网络设备110可以根据该下行信道信息确定该终端设备120的预编码矩阵。当网络设备110向该终端设备120发送下行数据时，该网络设备110根据该预编码矩阵对下行数据进行预编码，并将预编码之后的下行数据发送给该终端设备120。
但是，通常终端设备向网络设备反馈下行信道信息之前，该终端设备需要对该下行信道信息进行量化。进一步，该终端设备将量化后的下行信道信息发送给网络设备，由于量化后的下行信道信息的准确性较低，导致该网络设备确定出的该终端设备对应的预编码矩阵也不准确，从而降低了该网络设备的下行传输性能。针对该问题，本申请提供了一种信道信息处理方法，下面结合具体的实施例对该信道信息处理方法进行介绍。
图2为本申请提供的一种信道信息处理方法的信令图。如图2所示，该信道信息处理方法包括如下步骤：
S201、网络设备向终端设备发送下行参考信号。
在本实施例中不限定该网络设备向终端设备发送的下行参考信号。具体的，该下行参考信号可以是小区专用参考信号、用户专用参考信号、位置参考信号、信道状态信息(Channel State Information，CSI)参考信号等。相应的，该终端设备接收该网络设备下发的该下行参考信号。该网络设备可以是如图1所示的网络设备110，该终端设备具体可以是如图1所示的终端设备120或终端设备130。
S202、终端设备根据所述下行参考信号进行信道估计得到信道估计的下行信道信息。
当该终端设备接收到该终端设备发送的下行参考信号后，根据该下行参考信号进行信道估计得到信道估计的下行信道信息，该信道估计的下行信道信息具体可以是CSI。进一步，该终端设备对该信道估计的下行信道信息进行量化，得到该信道估计的下行信道信息的量化信息。具体的，该终端设备可以对该信道估计的下行信道信息中的每个元素进行量化，得到每个元素的量化信息。相应的，该信道估计的下行信道信息的量化信息可以是该信道估计的下行信道信息中每个元素的量化信息。该终端设备根据该信道估计的下行信道信息中每个元素的量化信息，确定量化后的下行信道信息，并计算量化后的下行信道信息和该信道估计的下行信道信息之间的误差信息。
S203、终端设备向所述网络设备发送量化后的下行信道信息和所述信道估计的下行信道信息之间的误差信息、以及所述信道估计的下行信道信息的量化信息。
具体的，该终端设备向网络设备发送如上所述的误差信息和该信道估计的下行信道信息的量化信息。相应的，该网络设备接收该终端设备发送的该误差信息和该信道估计的下行信道信息的量化信息。
S204、网络设备根据所述误差信息和所述信道估计的下行信道信息的量化信息重构得到重构的下行信道信息。
该网络设备接收到该误差信息和该信道估计的下行信道信息的量化信息后，首先根据该信道估计的下行信道信息的量化信息，例如该信道估计的下行信道信息中每个元素的量化信息，确定如上所述的量化后的下行信道信息，具体的，该网络设备和该终端设备分别根据该信道估计的下行信道信息中每个元素的量化信息确定该量化后的下行信道信息的方法可以是一致的。
进一步，该网络设备根据该误差信息和该量化后的下行信道信息重构得到重构的下行信道信息。可以理解的是，该网络设备重构的下行信道信息和该终端设备根据如上所述的下行参考信号进行信道估计得到的下行信道信息可能相同，也可能不同。
S205、网络设备根据所述重构的下行信道信息，确定所述终端设备对应的预编码矩阵。
该网络设备根据其重构的下行信道信息，确定该终端设备对应的预编码矩阵。也就是说，针对不同终端设备上报的误差信息和信道估计的下行信道信息的量化信息，该网络设备重构的下行信道信息可能不同，从而针对不同终端设备得到的预编码矩阵也可能不同。
另外，本实施例并不限定根据重构的下行信道信息，确定预编码矩阵的方法。例如，该网络设备可以采用线性的预编码算法计算该预编码矩阵，或者采用非线性的预编码算法计算该预编码矩阵。
其中，线性的预编码算法可以包括迫零(Zero-Forcing,ZF)预编码算法、最小均方误差(Minimum Mean-Squared Error,MMSE)预编码算法、块对角化(Block Diagonalization,BD)预编码算法等。
非线性的预编码算法可以包括脏纸编码(Dirty Paper Code，DPC)算法、Tomlinson-Harashima预编码(Tomlinson-Harashima Precoding,THP)算法、矢量扰动(Vector Perturbation，VP)预编码算法等。对于DPC算法而言，如果发射端能够知道所有的加性干扰，则可以完美的消除信道间干扰(Inter-Channel Interference，ICI)，从而获得最理想的性能增益。但是DPC的复杂度极高，而且在实际系统中，发射端无法知道所有的加性干扰，因此在实际中很难实现。为了降低DPC的复杂度同时获得较好的性能，THP算法和VP预编码算法相继被提出，相对于THP算法而言，在VP预编码算法中，发射端在发送信号上叠加扰动矢量，从而可以进一步限制发送功率，提高接收端的信噪比，从而获得更好的性能增益。
本实施例提供的信道信息处理方法，终端设备接收网络设备发送的下行参考信号，并根据该下行参考信号进行信道估计得到信道估计的下行信道信息，进一步，向网络设备发送量化后的下行信道信息和所述信道估计的下行信道信息之间的误差信息、以及所述信道估计的下行信道信息的量化信息，使得网络设备可根据该误差信息和该信道估计的下行信道信息的量化信息重构得到重构的下行信道信息，由于该误差信息反映出了该量化后的下行信道信息相对于该终端设备通过信道估计得到的下行信道信息的误差，因此，相比于现有技术中网络设备只接收到终端设备发送的量化后的下行信道信息，网络设备重构出的下行信道信息的准确性高于该终端设备量化后的下行信道信息的准确性。也就是说，相比于终端设备量化后的下行信道信息，网络设备重构出的下行信道信息更接近于终端设备通过信道估计得到的下行信道信息，当网络设备根据重构出的下行信道信息确定终端设备对应的的预编码矩阵时，可提高预编码矩阵的准确性，网络设备进一步根据预编码矩阵对下行数据进行预编码，从而提高网络设备的下行传输性能。
在上述实施例的基础上，所述量化后的下行信道信息基于所述信道估计的下行信道信息的量化信息重构得到。例如，该信道估计的下行信道信息的量化信息可以是该信道估计的下行信道信息中每个元素的量化信息，该网络设备或该终端设备在根据该信道估计的下 行信道信息中每个元素的量化信息确定该量化后的下行信道信息时，具体可根据该信道估计的下行信道信息中每个元素的量化信息重构得到该量化后的下行信道信息。
作为一种可能的方式，所述信道估计的下行信道信息为信道协方差矩阵。具体的，该信道协方差矩阵是一个方阵，本实施例并不限定该信道协方差矩阵的大小。例如，该信道协方差矩阵为一个4*4的方阵，相应的，该信道协方差矩阵包括16个元素。
具体的，所述信道估计的下行信道信息的量化信息为所述信道协方差矩阵中每个元素的量化信息。例如，该终端设备可以对该信道协方差矩阵中16个元素中的每个元素进行量化，得到每个元素的量化信息，并将该信道协方差矩阵中每个元素的量化信息作为该信道估计的下行信道信息的量化信息即该信道协方差矩阵的量化信息。可选的，该信道协方差矩阵中的每个元素可能既包括实部也包括虚部，也可能只包括实部或者只包括虚部。以信道协方差矩阵中的每个元素包括实部和虚部为例，该终端设备对该信道协方差矩阵中的每个元素进行量化时，具体对该信道协方差矩阵中的每个元素的实部和虚部进行量化，从而得到该信道协方差矩阵中每个元素的实部的量化信息和该信道协方差矩阵中每个元素的虚部的量化信息。可选的，所述信道协方差矩阵中每个元素的量化信息包括：所述信道协方差矩阵中每个元素的实部的量化信息和所述信道协方差矩阵中每个元素的虚部的量化信息。
在其他实施例中，信道协方差矩阵中的部分元素可能既包括实部也包括虚部，部分元素可能只包括实部，部分元素可能只包括虚部，在这种情况下，在对该信道协方差矩阵中的每个元素进行量化时，如果该元素既包括实部也包括虚部，则对该元素的实部和虚部分别进行量化；如果该元素只包括实部，则对该元素的实部进行量化；如果该元素只包括虚部，则对该元素的虚部进行量化。
进一步,该终端设备根据该信道协方差矩阵中每个元素的量化信息进行重构得到量化后的下行信道信息即量化后的信道协方差矩阵，例如，该终端设备根据该信道协方差矩阵中每个元素的实部的量化信息和虚部的量化信息进行重构得到量化后的信道协方差矩阵。
作为另一种可能的方式，所述信道估计的下行信道信息为特征向量。在这种情况下，可以将该特征向量分解为多个波束。例如，N个波束，该N可以是大于或等于1的正整数。也就是说，该特征向量可以看作是N个波束的线性叠加。
具体的，所述信道估计的下行信道信息的量化信息为所述特征向量被分解后的多个波束中每个波束的量化信息。例如，该终端设备对该特征向量被分解后的N个波束中的每个波束进行量化，得到每个波束的量化信息，并将每个波束的量化信息作为该下行信道信息的量化信息即该特征向量的量化信息。可选的，所述多个波束中每个波束的量化信息包括：所述多个波束中每个波束的波束向量信息、所述多个波束中每个波束的幅度信息和所述多个波束中每个波束的相位信息。其中，该幅度信息可以是宽带的幅度信息或子带的幅度信息。
进一步，该终端设备根据该N个波束中的每个波束的量化信息进行重构得到量化后的下行信道信息即量化后的特征向量。
当终端设备根据信道协方差矩阵中每个元素的量化信息进行重构得到量化后的下行信道信息即量化后的信道协方差矩阵，或者，根据该N个波束中的每个波束的量化信息进行重构得到量化后的下行信道信息即量化后的特征向量之后，该终端设备进一步计算该量化后的下行信道信息和该信道估计的下行信道信息之间的误差信息。可选的，所述误差信息为所述量化后的下行信道信息和所述信道估计的下行信道信息之间的均方误差的量化信息。
具体的，当所述信道估计的下行信道信息为信道协方差矩阵时，将该信道协方差矩阵记为R，将量化后的信道协方差矩阵记为
Figure PCTCN2019097138-appb-000001
该终端设备可以首先计算该信道协方差矩阵 R和该量化后的信道协方差矩阵
Figure PCTCN2019097138-appb-000002
之间的均方误差(Mean Square Error，MSE)，此处，将R和
Figure PCTCN2019097138-appb-000003
之间的均方误差记为MSE R，具体的，
Figure PCTCN2019097138-appb-000004
其中，diag表示取对角元素的操作。进一步，该终端设备可以对该均方误差MSE R进行量化处理，得到该均方误差MSE R的量化信息，具体的，该均方误差MSE R的量化信息可以是该均方误差MSE R中每个元素的量化信息。此处，将该均方误差MSE R的量化信息作为R和
Figure PCTCN2019097138-appb-000005
之间的误差信息，此处可以将R和
Figure PCTCN2019097138-appb-000006
之间的误差信息理解为
Figure PCTCN2019097138-appb-000007
相对于R的误差信息。此外，R和
Figure PCTCN2019097138-appb-000008
之间的误差信息可以不限于R和
Figure PCTCN2019097138-appb-000009
之间均方误差的量化信息，在一些实施例中还可以是其他的误差信息，例如，该误差信息为该均方误差MSE R，此处只是一种示意性说明。进一步，该终端设备将该均方误差MSE R中每个元素量化信息以及该信道协方差矩阵R的量化信息发送给网络设备，其中，该信道协方差矩阵R的量化信息为该信道协方差矩阵R中每个元素的量化信息，例如，每个元素的实部的量化信息和虚部的量化信息。
当该网络设备接收到该终端设备发送的均方误差MSE R中每个元素的量化信息以及该信道协方差矩阵R中每个元素的量化信息时，该网络设备首先根据该信道协方差矩阵R中每个元素的量化信息进行重构得到量化后的信道协方差矩阵即
Figure PCTCN2019097138-appb-000010
以及根据该均方误差MSE R中每个元素的量化信息进行重构得到量化后的均方误差，此处，将量化后的均方误差记为
Figure PCTCN2019097138-appb-000011
进一步，该网络设备根据该量化后的均方误差
Figure PCTCN2019097138-appb-000012
以及量化后的信道协方差矩阵
Figure PCTCN2019097138-appb-000013
重构信道协方差矩阵。由于网络设备重构的信道协方差矩阵可能和该终端设备根据该网络设备下发的下行参考信号进行信道估计得到的信道协方差矩阵R不同，因此，将该网络设备重构的信道协方差矩阵记为R’，具体的，
Figure PCTCN2019097138-appb-000014
其中，DiagMatrix表示将
Figure PCTCN2019097138-appb-000015
的元素作为对角元素构成对角矩阵的操作。
当所述信道估计的下行信道信息为特征向量时，将该特征向量记为V，将该量化后的特征向量记为
Figure PCTCN2019097138-appb-000016
该终端设备可以首先计算该特征向量V和该量化后的特征向量
Figure PCTCN2019097138-appb-000017
之间的均方误差，此处，将V和
Figure PCTCN2019097138-appb-000018
之间的均方误差记为MSE V，具体的，
Figure PCTCN2019097138-appb-000019
进一步，该终端设备可以对该均方误差MSE V进行量化处理，得到该均方误差MSE V的量化信息，具体的，该均方误差MSE V的量化信息可以是该均方误差MSE V中每个元素的量化信息。此处，将该均方误差MSE V的量化信息作为V和
Figure PCTCN2019097138-appb-000020
之间的误差信息，此处可以将V和
Figure PCTCN2019097138-appb-000021
之间的误差信息理解为
Figure PCTCN2019097138-appb-000022
相对于V的误差信息。可以理解的是，V和
Figure PCTCN2019097138-appb-000023
之间的误差信息不限于V和
Figure PCTCN2019097138-appb-000024
之间均方误差的量化信息，在一些实施例中还可以是其他的误差信息，例如，该误差信息为该均方误差MSE V，此处只是一种示意性说明。进一步，该终端设备将该均方误差MSE V中每个元素的量化信息以及特征向量V的量化信息发送给网络设备，其中，该特征向量V的量化信息为该特征向量V被分解后的多个波束中每个波束的量化信息。
当该网络设备接收到该终端设备发送的均方误差MSE V中每个元素的量化信息以及该特征向量V被分解后的多个波束中每个波束的量化信息时，该网络设备首先根据该多个波 束中每个波束的量化信息进行重构得到量化后的特征向量即
Figure PCTCN2019097138-appb-000025
以及根据该均方误差MSE V中每个元素的量化信息进行重构得到量化后的均方误差，此处，将量化后的均方误差记为
Figure PCTCN2019097138-appb-000026
进一步，该网络设备根据该量化后的均方误差
Figure PCTCN2019097138-appb-000027
以及量化后的特征向量
Figure PCTCN2019097138-appb-000028
重构特征向量。由于该网络设备重构的特征向量可能和该终端设备根据该网络设备下发的下行参考信号进行信道估计得到的特征向量V不同，因此，将该网络设备重构的特征向量记为V’，具体的，
Figure PCTCN2019097138-appb-000029
其中，
Figure PCTCN2019097138-appb-000030
表示
Figure PCTCN2019097138-appb-000031
的共轭转置矩阵。
本实施例提供的信道信息处理方法，终端设备根据该信道估计的下行信道信息中每个元素的量化信息重构得到该量化后的下行信道信息，并计算该量化后的下行信道信息和该信道估计的下行信道信息之间的均方误差的量化信息，并将该均方误差的量化信息和该信道估计的下行信道信息中每个元素的量化信息发送给网络设备，使得网络设备首先根据该信道估计的下行信道信息中每个元素的量化信息进行重构得到量化后的下行信道信息，进一步，根据该均方误差的量化信息和该量化后的下行信道信息重构得到重构的下行信道信息，由于该均方误差的量化信息反映出了该量化后的下行信道信息相对于终端设备通过信道估计得到的下行信道信息的误差，因此，网络设备重构出的下行信道信息的准确性高于终端设备直接量化后的下行信道信息的准确性，此外，由于终端设备向网络设备发送的误差信息是均方误差的量化信息，从而提高了终端设备的信息发送速率，以及提高了网络设备重构出下行信道信息的速率。
下面以下行信道信息为信道协方差矩阵为例，介绍该网络设备和该终端设备的信息交互过程。具体包括如图3所示的如下几个步骤：
S301、网络设备向终端设备发送下行参考信号。
假设该网络设备与多个终端设备进行通信，以其中的一个终端设备为例进行示意性说明。例如，该终端设备是用户k的终端设备，该终端设备接收到了该网络设备下发的下行参考信号。
S302、终端设备根据所述下行参考信号进行信道估计得到信道协方差矩阵。
此处，将用户k的终端设备根据下行参考信号进行信道估计得到的信道协方差矩阵记为R(k)，也就是说，不同用户的终端设备进行信道估计得到的信道协方差矩阵可能是不同的，此处，通过k进行分区。
S303、终端设备对该信道协方差矩阵中每个元素的实部和虚部分别进行量化并重构，得到量化后的信道协方差矩阵。
例如，该信道协方差矩阵R(k)是一个4*4的方阵，
Figure PCTCN2019097138-appb-000032
其中，R(k)的每个元素均为复数，即每个元素均包括实部和虚部，例如，a 11+b 11i是R(k)的第一行第一个元素，a 11是该元素的实部，b 11是该元素的虚部，其他元素同理，不再赘述。
该终端设备对该信道协方差矩阵R(k)中的每个元素的实部和虚部分别进行量化，例如，对R(k)的第一行第一个元素a 11+b 11i的实部a 11和虚部b 11分别进行量化，得到实部a 11的量化信息
Figure PCTCN2019097138-appb-000033
以及虚部b 11的量化信息
Figure PCTCN2019097138-appb-000034
同理，对该R(k)中其他元素的实部和虚部分别进行量化，得到其他元素实部的量化信息和虚部的量化信息。具体的，R(k)中每个元素 的实部的量化信息和虚部的量化信息可作为该R(k)的量化信息。
该终端设备可根据该R(k)的量化信息重构得到量化后的信道协方差矩阵
Figure PCTCN2019097138-appb-000035
即该终端设备可根据该R(k)中每个元素的实部的量化信息和虚部的量化信息进行重构得到量化后的信道协方差矩阵
Figure PCTCN2019097138-appb-000036
具体的，R(k)和
Figure PCTCN2019097138-appb-000037
的大小相同，对该R(k)中某一位置上的元素进行量化得到该元素的实部和虚部的量化信息后，可根据该元素的实部和虚部的量化信息重构得到该
Figure PCTCN2019097138-appb-000038
中相同位置上的元素。例如，该R(k)的第一行第一个元素的实部a 11的量化信息
Figure PCTCN2019097138-appb-000039
以及虚部b 11的量化信息
Figure PCTCN2019097138-appb-000040
可重构成该
Figure PCTCN2019097138-appb-000041
中的第一行第一个元素，最终得到的
Figure PCTCN2019097138-appb-000042
例如为
Figure PCTCN2019097138-appb-000043
S304、终端设备计算量化后的信道协方差矩阵和该信道协方差矩阵之间的均方误差。
该终端设备计算
Figure PCTCN2019097138-appb-000044
和R(k)之间的均方误差MSE R，具体的，
Figure PCTCN2019097138-appb-000045
其中，diag表示取对角元素的操作。可以理解，
Figure PCTCN2019097138-appb-000046
是一个4*4的方阵，
Figure PCTCN2019097138-appb-000047
也是一个4*4的方阵，
Figure PCTCN2019097138-appb-000048
还是一个4*4的方阵，对
Figure PCTCN2019097138-appb-000049
取对角元素时，可获取到4个对角元素。也就是说，
Figure PCTCN2019097138-appb-000050
和R(k)之间的均方误差MSE R包括4个元素，且MSE R的每个元素也是复数。
S305、终端设备对该均方误差进行量化处理。
该终端设备还可以对该MSE R中包括的每个元素进行量化处理，得到该MSE R中每个元素的量化信息。由于该
Figure PCTCN2019097138-appb-000051
和R(k)之间的均方误差MSE R包括4个元素，因此，对均方误差MSE R的量化处理即是对该MSE R中每个元素的量化处理。
例如，MSE R包括的4个元素依次记为A 1+B 1i、A 2+B 2i、A 3+B 3i、A 4+B 4i，该终端设备对该4个元素中每个元素的实部和虚部进行量化处理，例如，将A 1+B 1i的实部量化为
Figure PCTCN2019097138-appb-000052
将A 1+B 1i的虚部量化为
Figure PCTCN2019097138-appb-000053
同理，将A 2+B 2i的实部量化为
Figure PCTCN2019097138-appb-000054
将A 2+B 2i的虚部量化为
Figure PCTCN2019097138-appb-000055
将A 3+B 3i的实部量化为
Figure PCTCN2019097138-appb-000056
将A 3+B 3i的虚部量化为
Figure PCTCN2019097138-appb-000057
将A 4+B 4i的实部量化为
Figure PCTCN2019097138-appb-000058
将A 4+B 4i的虚部量化为
Figure PCTCN2019097138-appb-000059
下面以A 1+B 1i的实部A 1为例，介绍一种量化的方法，可以理解的是，该量化方法也可以应用于对MSE R中每个元素的虚部进行量化，该量化方法还可以适用于对R(k)中每个元素的实部和虚部进行量化。
具体的，假设该A 1+B 1i的实部A 1是一个小数，例如，1.34。并且MSE R中每个元素的实部都大于或等于0.00，且小于或等于2.00。例如，可以采用3个比特来表示1.34的量化信息。具体的，由于3个比特可以表示8个不同的二进制值，因此，可以将0.00到2.00划分为8个阶段，具体划分结果以及与二进制值的对应关系如下表1所示：
表1
小数 阶段 二进制值
0.00-0.24 第一阶段 000
0.25-0.49 第二阶段 001
0.50-0.74 第三阶段 010
0.75-0.99 第四阶段 011
1.00-1.24 第五阶段 100
1.25-1.49 第六阶段 101
1.50-1.74 第七阶段 110
1.75-2.00 第八阶段 111
由于1.34属于1.25-1.49这个范围，即对于第六阶段，所以1.34的量化信息为101。可以理解，此处只是一种示意性说明，并不对量化方法和量化过程做具体限定。
S306、终端设备向网络设备发送该信道协方差矩阵中每个元素的量化信息和该均方误差的量化信息。
具体的，该终端设备可以将该信道协方差矩阵R(k)中每个元素的量化信息，例如，
Figure PCTCN2019097138-appb-000060
Figure PCTCN2019097138-appb-000061
以及该均方误差MSE R中每个元素的量化信息，例如，
Figure PCTCN2019097138-appb-000062
发送给网络设备。
步骤S307、网络设备根据该信道协方差矩阵中每个元素的量化信息进行重构得到量化后的信道协方差矩阵。
当该网络设备接收到该信道协方差矩阵R(k)中每个元素的量化信息，例如，
Figure PCTCN2019097138-appb-000063
Figure PCTCN2019097138-appb-000064
以及该均方误差MSE R中每个元素的量化信息，例如，
Figure PCTCN2019097138-appb-000065
Figure PCTCN2019097138-appb-000066
时，该网络设备可根据该信道协方差矩阵R(k)中每个元素的量化信息，例如，
Figure PCTCN2019097138-appb-000067
重构得到量化后的信道协方差矩阵
Figure PCTCN2019097138-appb-000068
S308、网络设备根据该均方误差的量化信息和该量化后的信道协方差矩阵重构得到重构的信道协方差矩阵。
该网络设备还可以根据该均方误差MSE R中每个元素的量化信息，例如，
Figure PCTCN2019097138-appb-000069
Figure PCTCN2019097138-appb-000070
重构得到量化后的均方误差
Figure PCTCN2019097138-appb-000071
也包括4个元素，
Figure PCTCN2019097138-appb-000072
包括的4个元素依次记为
Figure PCTCN2019097138-appb-000073
进一步，该网络设备根据该量化后的均方误差
Figure PCTCN2019097138-appb-000074
和该量化后的信道协方差矩阵
Figure PCTCN2019097138-appb-000075
重构得到重构的信道协方差矩阵，将该网络设备重构的信道协方差矩阵记为R’(k)，具体的，
Figure PCTCN2019097138-appb-000076
其中，DiagMatrix表示将
Figure PCTCN2019097138-appb-000077
的元素作为对角元素构成对角矩阵的操作。
S309、网络设备根据重构的信道协方差矩阵，确定终端设备对应的预编码矩阵。
例如，该网络设备可根据重构的信道协方差矩阵R’(k)，并采用线性的ZF预编码算法或非线性的VP预编码算法，计算该终端设备对应的预编码矩阵。
S310、网络设备根据预编码矩阵对下行数据进行预编码。
本实施例提供的信道信息处理方法，终端设备接收网络设备发送的下行参考信号，并根据该下行参考信号进行信道估计得到信道协方差矩阵，进一步，向网络设备发送量化后 的信道协方差矩阵和所述信道协方差矩阵之间的误差信息、以及所述信道协方差矩阵的量化信息，使得网络设备可根据该误差信息和信道协方差矩阵的量化信息重构得到重构的信道协方差矩阵，由于该误差信息反映出了该量化后的信道协方差矩阵相对于该终端设备通过信道估计得到的信道协方差矩阵的误差，因此，相比于现有技术中网络设备只接收到终端设备发送的量化后的信道协方差矩阵，网络设备重构出的信道协方差矩阵的准确性高于终端设备量化后的信道协方差矩阵的准确性，也就是说，相比于终端设备量化后的信道协方差矩阵，网络设备重构出的信道协方差矩阵更接近于终端设备通过信道估计得到的信道协方差矩阵，当网络设备根据该重构出的信道协方差矩阵确定终端设备对应的预编码矩阵时，可提高该预编码矩阵的准确性，网络设备进一步根据预编码矩阵对下行数据进行预编码，从而提高了网络设备的下行传输性能。
下面再以下行信道信息为特征向量为例，介绍该网络设备和该终端设备的信息交互过程。具体包括如图4所示的如下几个步骤：
S401、网络设备向终端设备发送下行参考信号。
假设该网络设备与多个终端设备进行通信，以其中的一个终端设备为例进行示意性说明。例如，该终端设备是用户k的终端设备，该终端设备接收到了该网络设备下发的下行参考信号。
S402、终端设备根据所述下行参考信号进行信道估计得到特征向量。
此处，将用户k的终端设备根据下行参考信号进行信道估计得到信道协方差矩阵R(k)，进一步对该信道协方差矩阵R(k)进行特征值分解得到特征向量V。
S403、终端设备对该特征向量被分解后的多个波束中的每个波束进行量化并重构，得到量化后的特征向量。
具体的，该终端设备可以将该特征向量V分解为N个波束，并对每个波束分别进行量化，得到每个波束的量化信息，具体的，每个波束的量化信息包括所述波束的波束向量信息、幅度信息和相位信息。该N个波束中每个波束的量化信息可作为该特征向量V的量化信息。进一步，该终端设备根据该N个波束中的每个波束的量化信息进行重构得到量化后的特征向量
Figure PCTCN2019097138-appb-000078
S404、终端设备计算量化后的特征向量和该特征向量之间的均方误差。
该终端设备计算该特征向量V和该量化后的特征向量
Figure PCTCN2019097138-appb-000079
之间的均方误差，此处，将V和
Figure PCTCN2019097138-appb-000080
之间的均方误差记为MSE V，具体的，
Figure PCTCN2019097138-appb-000081
S405、终端设备对该均方误差进行量化处理。
进一步，该终端设备可以对该均方误差MSE V进行量化处理，得到该均方误差MSE V的量化信息。具体的，该均方误差MSE V的量化信息可以是该均方误差MSE V中每个元素的量化信息。
S406、终端设备向网络设备发送该特征向量被分解后的多个波束中的每个波束的量化信息和该均方误差的量化信息。
终端设备将该均方误差MSE V中每个元素的量化信息以及特征向量V的量化信息发送给网络设备，其中，该特征向量V的量化信息为该特征向量V被分解后的多个波束中每个波束的量化信息。
S407、网络设备根据该特征向量被分解后的多个波束中的每个波束的量化信息进行重构得到量化后的特征向量。
当该网络设备接收到该终端设备发送的均方误差MSE V中每个元素的量化信息以及该 特征向量V被分解后的多个波束中每个波束的量化信息时，该网络设备首先根据该多个波束中每个波束的量化信息进行重构得到量化后的特征向量即
Figure PCTCN2019097138-appb-000082
S408、网络设备根据该均方误差的量化信息和该量化后的特征向量重构得到重构的特征向量。
该网络设备还可以根据该均方误差MSE V中每个元素的量化信息进行重构得到量化后的均方误差，此处，将量化后的均方误差记为
Figure PCTCN2019097138-appb-000083
进一步，该网络设备根据该量化后的均方误差
Figure PCTCN2019097138-appb-000084
以及量化后的特征向量
Figure PCTCN2019097138-appb-000085
重构特征向量，重构的特征向量V’为
Figure PCTCN2019097138-appb-000086
其中，
Figure PCTCN2019097138-appb-000087
表示
Figure PCTCN2019097138-appb-000088
的共轭转置矩阵。
S409、网络设备根据重构的特征向量，确定终端设备对应的预编码矩阵。
具体的，该网络设备可根据重构的特征向量V’，并采用线性的ZF或BD预编码算法或非线性的VP预编码算法计算该终端设备对应的预编码矩阵。或者，该网络设备还可以将该重构的特征向量V’直接作为该终端设备对应的预编码矩阵。
例如，该网络设备根据重构的特征向量V’采用线性的ZF预编码算法计算得到的该终端设备的预编码矩阵W可以为：
Figure PCTCN2019097138-appb-000089
S410、网络设备根据预编码矩阵对下行数据进行预编码。
本实施例提供的信道信息处理方法，终端设备接收网络设备发送的下行参考信号，并根据该下行参考信号进行信道估计得到特征向量，进一步，向网络设备发送量化后的特征向量和所述特征向量之间的误差信息、以及所述特征向量的量化信息，使得网络设备可根据该误差信息和特征向量的量化信息重构得到重构的特征向量，由于该误差信息反映出了该量化后的特征向量相对于该终端设备通过信道估计得到的特征向量的误差，因此，相比于现有技术中网络设备只接收到终端设备发送的量化后的特征向量，网络设备重构出的特征向量的准确性高于终端设备量化后的特征向量的准确性，也就是说，相比于该终端设备量化后的特征向量，网络设备重构出的特征向量更接近于该终端设备通过信道估计得到的特征向量，当网络设备根据重构出的特征向量确定终端设备对应的预编码矩阵时，可提高预编码矩阵的准确性，网络设备进一步根据预编码矩阵对下行数据进行预编码，从而提高了网络设备的下行传输性能。
图5为本申请提供的终端设备的一种结构示意图，如图5所示，该终端设备50包括：
接收模块51，用于接收网络设备发送的下行参考信号；
信道估计模块52，用于根据所述下行参考信号进行信道估计得到信道估计的下行信道信息；
发送模块53，用于向所述网络设备发送量化后的下行信道信息和所述信道估计的下行信道信息之间的误差信息、以及所述信道估计的下行信道信息的量化信息。
本实施例提供的终端设备，用于执行前述任一方法实施例中终端设备侧的技术方案，其实现原理和技术效果类似，此处不再赘述。
在上述图5所示的实施例的基础上，所述量化后的下行信道信息基于所述信道估计的下行信道信息的量化信息重构得到。
可选地，所述信道估计的下行信道信息为信道协方差矩阵或特征向量。
可选地，所述信道估计的下行信道信息为信道协方差矩阵，所述信道估计的下行信道信息的量化信息为所述信道协方差矩阵中每个元素的量化信息。
可选地，所述信道协方差矩阵中每个元素的量化信息包括：所述信道协方差矩阵中每 个元素的实部的量化信息和所述信道协方差矩阵中每个元素的虚部的量化信息。
可选地，所述信道估计的下行信道信息为特征向量，所述信道估计的下行信道信息的量化信息为所述特征向量被分解后的多个波束中每个波束的量化信息。
可选地，所述多个波束中每个波束的量化信息包括：所述多个波束中每个波束的波束向量信息、所述多个波束中每个波束的幅度信息和所述多个波束中每个波束的相位信息。
可选地，所述误差信息为所述量化后的下行信道信息和所述信道估计的下行信道信息之间的均方误差的量化信息。
可选地，当所述信道估计的下行信道信息为信道协方差矩阵时，所述均方误差为：
Figure PCTCN2019097138-appb-000090
其中,MSE R表示所述均方误差,diag表示取对角元素的操作，R表示所述信道协方差矩阵,
Figure PCTCN2019097138-appb-000091
表示量化后的信道协方差矩阵。
可选地，当所述信道估计的下行信道信息为特征向量时，所述均方误差为：
Figure PCTCN2019097138-appb-000092
其中,MSE V表示所述均方误差,V表示所述特征向量,
Figure PCTCN2019097138-appb-000093
表示量化后的特征向量。
图6为本申请提供的网络设备的一种结构示意图，如图6所示，该网络设备60包括：
发送模块61，用于向终端设备发送下行参考信号；
接收模块62，用于接收所述终端设备发送的量化后的下行信道信息和信道估计的下行信道信息之间的误差信息、以及所述信道估计的下行信道信息的量化信息；
处理模块63，用于根据所述误差信息和所述信道估计的下行信道信息的量化信息重构得到重构的下行信道信息；根据所述重构的下行信道信息，确定所述终端设备对应的预编码矩阵。
本实施例提供的网络设备，用于执行前述任一方法实施例中网络设备侧的技术方案，其实现原理和技术效果类似，此处不再赘述。
进一步的，所述量化后的下行信道信息基于所述信道估计的下行信道信息的量化信息重构得到。
可选地，所述信道估计的下行信道信息为信道协方差矩阵或特征向量。
可选地，所述信道估计的下行信道信息为信道协方差矩阵，所述信道估计的下行信道信息的量化信息为所述信道协方差矩阵中每个元素的量化信息。
可选地，所述信道协方差矩阵中每个元素的量化信息包括：所述信道协方差矩阵中每个元素的实部的量化信息和所述信道协方差矩阵中每个元素的虚部的量化信息。
可选地，所述信道估计的下行信道信息为特征向量，所述信道估计的下行信道信息的量化信息为所述特征向量被分解后的多个波束中每个波束的量化信息。
可选地，所述多个波束中每个波束的量化信息包括：所述多个波束中每个波束的波束向量信息、所述多个波束中每个波束的幅度信息和所述多个波束中每个波束的相位信息。
可选地，所述误差信息为所述量化后的下行信道信息和所述信道估计的下行信道信息之间的均方误差的量化信息。
可选地，当所述信道估计的下行信道信息为信道协方差矩阵时，重构的信道协方差矩阵为：
Figure PCTCN2019097138-appb-000094
其中，R’表示所述重构的信道协方差矩阵，
Figure PCTCN2019097138-appb-000095
表示量化后的信道协方差矩阵，
Figure PCTCN2019097138-appb-000096
表示量化后的均方误差，所述量化后的均方误差基于所述均方误差的量化信息重构得到，DiagMatrix表示将
Figure PCTCN2019097138-appb-000097
的元素作为对角元素构成对角矩阵的操作。
可选地，当所述信道估计的下行信道信息为特征向量时，重构的特征向量为：
Figure PCTCN2019097138-appb-000098
其中，V’表示所述重构的特征向量，
Figure PCTCN2019097138-appb-000099
表示量化后的特征向量，
Figure PCTCN2019097138-appb-000100
表示
Figure PCTCN2019097138-appb-000101
的共轭转置矩阵，
Figure PCTCN2019097138-appb-000102
表示量化后的均方误差，所述量化后的均方误差基于所述均方误差的量化信息重构得到。
图7为本申请提供的终端设备的另一种结构示意图，如图7所示，该终端设备70包括：
处理器71、存储器72、与网络设备进行通信的接口73；
所述存储器72存储计算机执行指令；
所述处理器71执行所述存储器72存储的计算机执行指令，使得所述处理器71执行前述任一方法实施例中终端设备侧的技术方案。
图7为终端设备的一种简单设计，本申请实施例不限制终端设备中处理器和存储器的个数，图7仅以个数为1作为示例说明。
图8为本申请提供的网络设备的另一种结构示意图，如图8所示，该网络设备80包括：
处理器81、存储器82、与终端设备进行通信的接口83；
所述存储器82存储计算机执行指令；
所述处理器81执行所述存储器82存储的计算机执行指令，使得所述处理器81执行前述任一方法实施例中网络设备侧的技术方案。
图8为网络设备的一种简单设计，本申请实施例不限制网络设备中处理器和存储器的个数，图8仅以个数为1作为示例说明。
在上述图7所示的终端设备和图8所述的网络设备的一种具体实现中，存储器、处理器以及接口之间可以通过总线连接，可选的，存储器可以集成在处理器内部。
本申请实施例还提供一种计算机可读存储介质所述计算机可读存储介质中存储有计算机执行指令，当所述计算机执行指令被处理器执行时用于实现前述任一方法实施例中终端设备侧的技术方案。
本申请实施例还提供一种计算机可读存储介质，所述计算机可读存储介质中存储有计算机执行指令，当所述计算机执行指令被处理器执行时用于实现前述任一方法实施例中网络设备侧的技术方案。
本申请实施例还提供一种芯片，包括：处理器，用于从存储器中调用并运行计算机程序，使得安装有所述芯片的设备执行前述任一方法实施例中所述的信道信息处理方法。
本申请实施例还提供一种计算机程序产品，包括计算机程序指令，该计算机程序指令使得计算机执行前述任一方法实施例中所述的信道信息处理方法。
本申请实施例还提供一种计算机程序，该计算机程序使得计算机执行前述任一方法实施例中所述的信道信息处理方法。
在本申请所提供的几个实施例中，应该理解到，所揭露的设备和方法，可以通过其它的方式实现。例如，以上所描述的设备实施例仅仅是示意性的，例如，所述模块的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个模块可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，模块的间接耦合或通信连接，可以是电性，机械或其它的形式。
在上述终端设备和网络设备的具体实现中，应理解，处理器可以是中央处理单元(英文：Central Processing Unit，简称：CPU)，还可以是其他通用处理器、数字信号处理器(英文：Digital Signal Processor，简称：DSP)、专用集成电路(英文：Application Specific Integrated Circuit，简称：ASIC)等。通用处理器可以是微处理器或者该处理器也可以是任何常规的处理器等。结合本申请所公开的方法的步骤可以直接体现为硬件处理器执行完成，或者用处理器中的硬件及软件模块组合执行完成。
实现上述各方法实施例的全部或部分步骤可以通过程序指令相关的硬件来完成。前述的程序可以存储于一可读取存储器中。该程序在执行时，执行包括上述各方法实施例的步骤；而前述的存储器(存储介质)包括：只读存储器(英文：read-only memory，简称：ROM)、RAM、快闪存储器、硬盘、固态硬盘、磁带(英文：magnetic tape)、软盘(英文：floppy disk)、光盘(英文：optical disc)及其任意组合。

Claims (47)

  1. 一种信道信息处理方法，其特征在于，应用于终端设备，所述方法包括：
    接收网络设备发送的下行参考信号；
    根据所述下行参考信号进行信道估计得到信道估计的下行信道信息；
    向所述网络设备发送量化后的下行信道信息和所述信道估计的下行信道信息之间的误差信息、以及所述信道估计的下行信道信息的量化信息。
  2. 根据权利要求1所述的方法，其特征在于，所述量化后的下行信道信息基于所述信道估计的下行信道信息的量化信息重构得到。
  3. 根据权利要求1或2所述的方法，其特征在于，所述信道估计的下行信道信息为信道协方差矩阵或特征向量。
  4. 根据权利要求3所述的方法，其特征在于，所述信道估计的下行信道信息为信道协方差矩阵，所述信道估计的下行信道信息的量化信息为所述信道协方差矩阵中每个元素的量化信息。
  5. 根据权利要求4所述的方法，其特征在于，
    所述信道协方差矩阵中每个元素的量化信息包括：所述信道协方差矩阵中每个元素的实部的量化信息和所述信道协方差矩阵中每个元素的虚部的量化信息。
  6. 根据权利要求3所述的方法，其特征在于，所述信道估计的下行信道信息为特征向量，所述信道估计的下行信道信息的量化信息为所述特征向量被分解后的多个波束中每个波束的量化信息。
  7. 根据权利要求6所述的方法，其特征在于，所述多个波束中每个波束的量化信息包括：
    所述多个波束中每个波束的波束向量信息、所述多个波束中每个波束的幅度信息和所述多个波束中每个波束的相位信息。
  8. 根据权利要求1-7任一项所述的方法，其特征在于，所述误差信息为所述量化后的下行信道信息和所述信道估计的下行信道信息之间的均方误差的量化信息。
  9. 根据权利要求8所述的方法，其特征在于，当所述信道估计的下行信道信息为信道协方差矩阵时，所述均方误差为：
    Figure PCTCN2019097138-appb-100001
    其中,MSE R表示所述均方误差,diag表示取对角元素的操作，R表示所述信道协方差矩阵,
    Figure PCTCN2019097138-appb-100002
    表示量化后的信道协方差矩阵。
  10. 根据权利要求8所述的方法，其特征在于，当所述信道估计的下行信道信息为特征向量时，所述均方误差为：
    Figure PCTCN2019097138-appb-100003
    其中,MSE V表示所述均方误差,V表示所述特征向量,
    Figure PCTCN2019097138-appb-100004
    表示量化后的特征向量。
  11. 一种信道信息处理方法，其特征在于，应用于网络设备，所述方法包括：
    向终端设备发送下行参考信号；
    接收所述终端设备发送的量化后的下行信道信息和信道估计的下行信道信息之间的误差信息、以及所述信道估计的下行信道信息的量化信息；
    根据所述误差信息和所述信道估计的下行信道信息的量化信息重构得到重构的下行信道信息；
    根据所述重构的下行信道信息，确定所述终端设备对应的预编码矩阵。
  12. 根据权利要求11所述的方法，其特征在于，所述量化后的下行信道信息基于所述信道估计的下行信道信息的量化信息重构得到。
  13. 根据权利要求11或12所述的方法，其特征在于，所述信道估计的下行信道信息为信道协方差矩阵或特征向量。
  14. 根据权利要求13所述的方法，其特征在于，所述信道估计的下行信道信息为信道协方差矩阵，所述信道估计的下行信道信息的量化信息为所述信道协方差矩阵中每个元素的量化信息。
  15. 根据权利要求14所述的方法，其特征在于，
    所述信道协方差矩阵中每个元素的量化信息包括：所述信道协方差矩阵中每个元素的实部的量化信息和所述信道协方差矩阵中每个元素的虚部的量化信息。
  16. 根据权利要求13所述的方法，其特征在于，所述信道估计的下行信道信息为特征向量，所述信道估计的下行信道信息的量化信息为所述特征向量被分解后的多个波束中每个波束的量化信息。
  17. 根据权利要求16所述的方法，其特征在于，所述多个波束中每个波束的量化信息包括：
    所述多个波束中每个波束的波束向量信息、所述多个波束中每个波束的幅度信息和所述多个波束中每个波束的相位信息。
  18. 根据权利要求11-17任一项所述的方法，其特征在于，所述误差信息为所述量化后的下行信道信息和所述信道估计的下行信道信息之间的均方误差的量化信息。
  19. 根据权利要求18所述的方法，其特征在于，当所述信道估计的下行信道信息为信道协方差矩阵时，重构的信道协方差矩阵为：
    Figure PCTCN2019097138-appb-100005
    其中，R’表示所述重构的信道协方差矩阵，
    Figure PCTCN2019097138-appb-100006
    表示量化后的信道协方差矩阵，
    Figure PCTCN2019097138-appb-100007
    表示量化后的均方误差，所述量化后的均方误差基于所述均方误差的量化信息重构得到，DiagMatrix表示将
    Figure PCTCN2019097138-appb-100008
    的元素作为对角元素构成对角矩阵的操作。
  20. 根据权利要求18所述的方法，其特征在于，当所述信道估计的下行信道信息为特征向量时，重构的特征向量为：
    Figure PCTCN2019097138-appb-100009
    其中，V’表示所述重构的特征向量，
    Figure PCTCN2019097138-appb-100010
    表示量化后的特征向量，
    Figure PCTCN2019097138-appb-100011
    表示
    Figure PCTCN2019097138-appb-100012
    的共轭转置矩阵，
    Figure PCTCN2019097138-appb-100013
    表示量化后的均方误差，所述量化后的均方误差基于所述均方误差的量化信息重构得到。
  21. 一种终端设备，其特征在于，包括：
    接收模块，用于接收网络设备发送的下行参考信号；
    信道估计模块，用于根据所述下行参考信号进行信道估计得到信道估计的下行信道信息；
    发送模块，用于向所述网络设备发送量化后的下行信道信息和所述信道估计的下行信道信息之间的误差信息、以及所述信道估计的下行信道信息的量化信息。
  22. 根据权利要求21所述的终端设备，其特征在于，所述量化后的下行信道信息基于所述信道估计的下行信道信息的量化信息重构得到。
  23. 根据权利要求21或22所述的终端设备，其特征在于，所述信道估计的下行信道信息为信道协方差矩阵或特征向量。
  24. 根据权利要求23所述的终端设备，其特征在于，所述信道估计的下行信道信息为信道协方差矩阵，所述信道估计的下行信道信息的量化信息为所述信道协方差矩阵中每个元素的量化信息。
  25. 根据权利要求24所述的终端设备，其特征在于，
    所述信道协方差矩阵中每个元素的量化信息包括：所述信道协方差矩阵中每个元素的 实部的量化信息和所述信道协方差矩阵中每个元素的虚部的量化信息。
  26. 根据权利要求23所述的终端设备，其特征在于，所述信道估计的下行信道信息为特征向量，所述信道估计的下行信道信息的量化信息为所述特征向量被分解后的多个波束中每个波束的量化信息。
  27. 根据权利要求26所述的终端设备，其特征在于，所述多个波束中每个波束的量化信息包括：
    所述多个波束中每个波束的波束向量信息、所述多个波束中每个波束的幅度信息和所述多个波束中每个波束的相位信息。
  28. 根据权利要求21-27任一项所述的终端设备，其特征在于，所述误差信息为所述量化后的下行信道信息和所述信道估计的下行信道信息之间的均方误差的量化信息。
  29. 根据权利要求28所述的终端设备，其特征在于，当所述信道估计的下行信道信息为信道协方差矩阵时，所述均方误差为：
    Figure PCTCN2019097138-appb-100014
    其中,MSE R表示所述均方误差,diag表示取对角元素的操作，R表示所述信道协方差矩阵,
    Figure PCTCN2019097138-appb-100015
    表示量化后的信道协方差矩阵。
  30. 根据权利要求28所述的终端设备，其特征在于，当所述信道估计的下行信道信息为特征向量时，所述均方误差为：
    Figure PCTCN2019097138-appb-100016
    其中,MSE V表示所述均方误差,V表示所述特征向量,
    Figure PCTCN2019097138-appb-100017
    表示量化后的特征向量。
  31. 一种网络设备，其特征在于，包括：
    发送模块，用于向终端设备发送下行参考信号；
    接收模块，用于接收所述终端设备发送的量化后的下行信道信息和信道估计的下行信道信息之间的误差信息、以及所述信道估计的下行信道信息的量化信息；
    处理模块，用于根据所述误差信息和所述信道估计的下行信道信息的量化信息重构得到重构的下行信道信息；根据所述重构的下行信道信息，确定所述终端设备对应的预编码矩阵。
  32. 根据权利要求31所述的网络设备，其特征在于，所述量化后的下行信道信息基于所述信道估计的下行信道信息的量化信息重构得到。
  33. 根据权利要求31或32所述的网络设备，其特征在于，所述信道估计的下行信道信息为信道协方差矩阵或特征向量。
  34. 根据权利要求33所述的网络设备，其特征在于，所述信道估计的下行信道信息为信道协方差矩阵，所述信道估计的下行信道信息的量化信息为所述信道协方差矩阵中每个元素的量化信息。
  35. 根据权利要求34所述的网络设备，其特征在于，
    所述信道协方差矩阵中每个元素的量化信息包括：所述信道协方差矩阵中每个元素的实部的量化信息和所述信道协方差矩阵中每个元素的虚部的量化信息。
  36. 根据权利要求33所述的网络设备，其特征在于，所述信道估计的下行信道信息为特征向量，所述信道估计的下行信道信息的量化信息为所述特征向量被分解后的多个波束中每个波束的量化信息。
  37. 根据权利要求36所述的网络设备，其特征在于，所述多个波束中每个波束的量化信息包括：
    所述多个波束中每个波束的波束向量信息、所述多个波束中每个波束的幅度信息和所述多个波束中每个波束的相位信息。
  38. 根据权利要求31-37任一项所述的网络设备，其特征在于，所述误差信息为所述 量化后的下行信道信息和所述信道估计的下行信道信息之间的均方误差的量化信息。
  39. 根据权利要求38所述的网络设备，其特征在于，当所述信道估计的下行信道信息为信道协方差矩阵时，重构的信道协方差矩阵为：
    Figure PCTCN2019097138-appb-100018
    其中，R’表示所述重构的信道协方差矩阵，
    Figure PCTCN2019097138-appb-100019
    表示量化后的信道协方差矩阵，
    Figure PCTCN2019097138-appb-100020
    表示量化后的均方误差，所述量化后的均方误差基于所述均方误差的量化信息重构得到，DiagMatrix表示将
    Figure PCTCN2019097138-appb-100021
    的元素作为对角元素构成对角矩阵的操作。
  40. 根据权利要求38所述的网络设备，其特征在于，当所述信道估计的下行信道信息为特征向量时，重构的特征向量为：
    Figure PCTCN2019097138-appb-100022
    其中，V’表示所述重构的特征向量，
    Figure PCTCN2019097138-appb-100023
    表示量化后的特征向量，
    Figure PCTCN2019097138-appb-100024
    表示
    Figure PCTCN2019097138-appb-100025
    的共轭转置矩阵，
    Figure PCTCN2019097138-appb-100026
    表示量化后的均方误差，所述量化后的均方误差基于所述均方误差的量化信息重构得到。
  41. 一种终端设备，其特征在于，包括：
    处理器、存储器、与网络设备进行通信的接口；
    所述存储器存储计算机执行指令；
    所述处理器执行所述存储器存储的计算机执行指令，使得所述处理器执行如权利要求1至10任一项所述的信道信息处理方法。
  42. 一种网络设备，其特征在于，包括：
    处理器、存储器、与网络设备进行通信的接口；
    所述存储器存储计算机执行指令；
    所述处理器执行所述存储器存储的计算机执行指令，使得所述处理器执行如权利要求11至20任一项所述的信道信息处理方法。
  43. 一种计算机可读存储介质，其特征在于，所述计算机可读存储介质中存储有计算机执行指令，当所述计算机执行指令被处理器执行时用于实现如权利要求1至10任一项所述的信道信息处理方法。
  44. 一种计算机可读存储介质，其特征在于，所述计算机可读存储介质中存储有计算机执行指令，当所述计算机执行指令被处理器执行时用于实现如权利要求11至20任一项所述的信道信息处理方法。
  45. 一种芯片，其特征在于，包括：处理器，用于从存储器中调用并运行计算机程序，使得安装有所述芯片的设备执行如权利要求1至20中任一项所述的方法。
  46. 一种计算机程序产品，其特征在于，包括计算机程序指令，该计算机程序指令使得计算机执行如权利要求1至20中任一项所述的方法。
  47. 一种计算机程序，其特征在于，所述计算机程序使得计算机执行如权利要求1至20中任一项所述的方法。
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