Data transmission method and device

Abstract

The embodiments of the present application disclose a data transmission method and apparatus for improving beam gain of downlink channel transmission with minimal phase mismatch performance loss. The method of the embodiment of the present application includes: a network device can determine a first downlink statistical autocorrelation matrix of a downlink channel based on a first uplink statistical autocorrelation matrix of the uplink channel, and instruct a terminal to receive a second weight of data based on a first weight indicated by the terminal, and then determine a third weight different from the second weight based on the first downlink statistical autocorrelation matrix and the second weight, and send data to the terminal based on the third weight.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of wireless communication technologies, and in particular, to a data transmission method and apparatus. Background Art

[0002] Beamforming is a key technology in multiple-input, multiple-output (MIMO) systems. It's a signal preprocessing method based on antenna arrays. It achieves array gain by adjusting the weighting coefficients of the array elements to create a directional beam. Therefore, independent control of the elements is key to achieving this gain.

[0003] In wireless communication systems, such as long-term evolution (LTE) systems, a terminal uses a cell-specific reference signal (CRS) for channel estimation and feeds back a precoding matrix indicator (PMI) to the base station to instruct it to precode and send data. The terminal then receives data from the base station based on the precoding weights corresponding to the PMI.

[0004] However, for terminals that use CRS to demodulate data, high-performance beam gain cannot be obtained due to limitations on the accuracy of PMI codebook quantization and the requirement for wide CRS coverage. Summary of the Invention

[0005] The embodiments of the present application provide a data transmission method and apparatus for solving the problem that a terminal is unable to obtain high-performance beam gain due to the constraints of a wide beam and the accuracy of quantization of a precoding indicator codebook, thereby improving the beam gain of downlink channel transmission with little phase mismatch performance loss.

[0006] In a first aspect, an embodiment of the present application provides a communication method, which can be executed by a network device, or by a component of the network device (such as a processor, a chip, or a chip system, etc.), or by a logic module or software that can implement all or part of the network device functions. The method includes: obtaining a first uplink statistical autocorrelation matrix of an uplink channel between the terminal, determining a first downlink statistical autocorrelation matrix of a downlink channel between the terminal based on the first uplink statistical autocorrelation matrix, obtaining a first precoding matrix indicator (PMI) from the terminal, the first PMI indicating a first weight, determining a second weight based on the first weight, determining a third weight based on the first downlink statistical autocorrelation matrix and the second weight, and the third weight is different from the second weight, sending a second PMI to the terminal, the second PMI indicating the second weight, and sending data to the terminal based on the third weight.

[0007] In the first aspect above, the execution subject of the above method is, for example, a network device, which exchanges data with the terminal. The network device cannot obtain relevant information of the downlink channel by means of channel estimation. The network device can determine the first downlink statistical autocorrelation matrix of the downlink channel based on the first uplink statistical autocorrelation matrix of the uplink channel, and determine the second weight to indicate to the terminal to receive data from the network device based on the first weight indicated by the terminal and the preset weight. The network device also determines a third weight different from the second weight based on the first downlink statistical autocorrelation matrix and the second weight, and sends data based on the third weight. The terminal can receive the data based on the second weight. Although there is a phase difference between the third weight and the second weight, the phase adaptation performance loss is small, and the beam gain can be improved. Therefore, the above method provided by the present application can improve the downlink beam gain when the quantization accuracy of the precoding indication codebook is constrained.

[0008] In one possible implementation, the above-mentioned determination of the first downlink statistical autocorrelation matrix of the downlink channel between the terminal based on the first uplink statistical autocorrelation matrix includes: determining the first downlink statistical autocorrelation matrix based on one or more of the first uplink and downlink frequency points, the first antenna shape or the first array spacing, and the first uplink statistical autocorrelation matrix.

[0009] In the above possible implementation manner, the reciprocity between the uplink and downlink channel information can be utilized based on one or more of the first uplink and downlink frequency points, the first antenna shape, or the first array spacing between the terminal, and combined with the first uplink statistical autocorrelation matrix to determine the first downlink statistical autocorrelation matrix to obtain weights with more precise directionality, thereby effectively improving the power of the target signal.

[0010] In one possible implementation, the above-mentioned determination of the first downlink statistical autocorrelation matrix based on one or more of the first uplink and downlink frequency points, the first antenna shape or the first array spacing, and the first uplink statistical autocorrelation matrix includes: processing the first uplink statistical autocorrelation matrix based on the first transformation matrix to obtain the first downlink statistical autocorrelation matrix, and the first transformation matrix is ​​related to one or more of the first uplink and downlink frequency points, the first antenna shape or the first array spacing.

[0011] In the above possible implementation manner, information about the downlink channel and the uplink channel is determined based on one or more of the first uplink and downlink frequency points, the first antenna shape, or the first array spacing, and then a first transformation matrix is ​​generated based on the information about the downlink channel and the uplink channel. The first transformation matrix can also be understood as an uplink and downlink statistical covariance correction matrix, including parameters determined by one or more of the first uplink and downlink frequency points, the first antenna shape, or the first array spacing. Using this first transformation matrix, the first uplink statistical autocorrelation matrix can be corrected to a first downlink statistical autocorrelation matrix to obtain weights with more precise directivity, thereby effectively improving the power of the target signal.

[0012] In a possible implementation, the third weight satisfies:

[0013] w d =(R DL +δ 2 I) -1 R DL w p

[0014] w d represents the third weight, w p Represents the second weight, R DL represents the first downlink statistical autocorrelation matrix, δ 2 represents the first channel estimation error and the first quantization error, I represents the identity matrix, (·) -1 Indicates inversion.

[0015] In the above possible implementation, the third weight actually used for data transmission is different from the second weight notified to the terminal. Although there is a phase difference between the third weight and the second weight, the above approach can minimize the loss of phase adaptation performance and improve beam gain. Therefore, the above method provided by this application can improve beam gain even when the quantization accuracy of the precoding indicator codebook is constrained.

[0016] A second aspect of an embodiment of the present application provides a communication method, which can be executed by a terminal, or by a component of the terminal (such as a processor, a chip, or a chip system, etc.), or by a logic module or software that can implement all or part of the terminal functions. The method includes: obtaining a second downlink statistical autocorrelation matrix of a downlink channel between a network device, determining a second uplink statistical autocorrelation matrix of an uplink channel between the network device based on the second downlink statistical autocorrelation matrix, obtaining a third PMI from the network device, the third PMI indicating a fourth weight, determining a fifth weight based on the second uplink statistical autocorrelation matrix and the fourth weight, the fifth weight being different from the fourth weight, and sending data to the network device based on the fifth weight.

[0017] In the above-mentioned second aspect, the execution subject of the above-mentioned method is a terminal, which interacts with the network device for data. The terminal cannot obtain relevant information of the uplink channel by means of channel estimation. The terminal can determine the second uplink statistical autocorrelation matrix of the uplink channel based on the second downlink statistical autocorrelation matrix of the downlink channel, and determine a fifth weight different from the fourth weight based on the fourth weight indicated by the network device and the second uplink statistical autocorrelation matrix. The terminal sends data to the network device based on the fifth weight, and the network device receives the data based on the fourth weight. Although there is a phase difference between the fifth weight and the fourth weight, the phase adaptation performance loss is small, and the beam gain can be improved. Therefore, the above-mentioned method provided by the present application can improve the uplink beam gain when the quantization accuracy of the precoding indication codebook is constrained.

[0018] In one possible implementation, the above-mentioned step of determining the second uplink statistical autocorrelation matrix of the uplink channel between the network device based on the second downlink statistical autocorrelation matrix includes: determining the second uplink statistical autocorrelation matrix based on one or more of the second uplink and downlink frequencies, the second antenna shape or the second array spacing, and the second downlink statistical autocorrelation matrix.

[0019] In one possible implementation, the above steps are based on one or more of the second uplink and downlink frequencies, the second antenna shape, or the second array spacing, and the second downlink statistical autocorrelation matrix, and determining the second uplink statistical autocorrelation matrix includes: processing the second downlink statistical autocorrelation matrix based on the second transformation matrix to obtain the second uplink statistical autocorrelation matrix, and the second transformation matrix is ​​related to one or more of the second uplink and downlink frequencies, the second antenna shape, or the second array spacing.

[0020] In a possible implementation, the fifth weight satisfies:

[0021] w d ′=(R UL ′+(δ′) 2 I) -1 RUL ′w p '

[0022] w d ′ represents the fifth weight, w p ' represents the fourth weight, R UL ′ represents the second uplink statistical autocorrelation matrix, (δ′) 2 represents the second channel estimation error and the second quantization error, I represents the identity matrix, (·) -1 Indicates inversion.

[0023] A third aspect of the embodiments of the present application provides a communication device that can implement the method in the first aspect or any possible implementation of the first aspect. The device includes corresponding units or modules for executing the above method. The units or modules included in the device can be implemented in software and / or hardware. The device can be, for example, a network device, or a chip, chip system, or processor that supports the network device to implement the above method. It can also be a logic module or software that can implement all or part of the network device functions.

[0024] A fourth aspect of the embodiments of the present application provides a communication device that can implement the method in the second aspect or any possible implementation of the second aspect. The device includes corresponding units or modules for executing the above method. The units or modules included in the device can be implemented in software and / or hardware. The device can be, for example, a terminal, or a chip, chip system, or processor that supports the terminal to implement the above method, or a logic module or software that can implement all or part of the terminal functions.

[0025] A fifth aspect of the present application provides a communication device, including: a processor coupled to a memory, the memory configured to store instructions, wherein when the instructions are executed by the processor, the device implements the method of the first aspect or any possible implementation of the first aspect. The device may be, for example, a network device, or a chip or chip system that supports the network device in implementing the method.

[0026] A sixth aspect of the present application provides a communication device, including: a processor coupled to a memory, the memory configured to store instructions, wherein when the instructions are executed by the processor, the device implements the method of the second aspect or any possible implementation of the second aspect. The device may be, for example, a terminal, or a chip or chip system that supports a terminal in implementing the method.

[0027] The seventh aspect of the embodiments of the present application provides a computer-readable storage medium, which stores instructions. When the instructions are executed, the computer executes the method provided by the first aspect or any possible implementation method of the first aspect.

[0028] An eighth aspect of an embodiment of the present application provides a computer-readable storage medium, which stores instructions. When the instructions are executed, the computer executes the method provided by the aforementioned second aspect or any possible implementation method of the second aspect.

[0029] A ninth aspect of the embodiments of the present application provides a computer program product, which includes computer program code. When the computer program code is executed, it enables the computer to execute the method provided by the first aspect or any possible implementation method of the first aspect.

[0030] The tenth aspect of the embodiments of the present application provides a computer program product, which includes computer program code. When the computer program code is executed, it enables the computer to execute the method provided by the second aspect or any possible implementation method of the second aspect.

[0031] The technical effects of the above-mentioned second to tenth aspects can refer to the description in the first aspect, and the repeated parts will not be repeated. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 A schematic diagram of a communication system provided in this application;

[0033] Figure 2 A schematic diagram of a communication method provided by this application;

[0034] Figure 3 A schematic diagram of a process for obtaining a downlink statistical autocorrelation matrix provided in this application;

[0035] Figure 4 A schematic diagram of the structure of a network device provided in this application;

[0036] Figure 5 A schematic diagram of another communication method provided by this application;

[0037] Figure 6 A schematic diagram of the structure of a terminal provided in this application;

[0038] Figure 7 A schematic diagram of a communication device provided in this application;

[0039] Figure 8 A schematic diagram of another communication device provided in this application. DETAILED DESCRIPTION

[0040] The embodiments of the present application provide a data transmission method and apparatus for improving the beam gain of downlink channel transmission with minimal phase mismatch performance loss.

[0041] The embodiments of the present application are described below with reference to the accompanying drawings.

[0042] The terms "first", "second" and the like in this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this manner can be interchangeable where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or that are inherent to these processes, methods, products or devices.

[0043] In this application, "exemplary" means "serving as an example or illustration." Something described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other things.

[0044] In this application, "at least one" means one or more, and "plurality" means two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, "one or more of A, B or C" includes A, B, C, AB, AC, BC or ABC. And, unless otherwise specified, the ordinal numbers such as "first" and "second" mentioned in the embodiments of this application are used to distinguish multiple objects, and are not used to limit the order, timing, priority or importance of multiple objects.

[0045] In addition, to better illustrate the present application, specific details are provided in the following detailed description. Those skilled in the art will understand that the present application can be practiced without certain specific details. In some instances, methods, means, components, and circuits well known to those skilled in the art are not described in detail in order to highlight the main purpose of the present application.

[0046] Some terms in this application are explained below.

[0047] Transmission weights: Network devices and terminals transmit data via multiple-input, multiple-output (MIMO) technology. Due to the correlation between multiple antennas, network devices or terminals can weight the transmitted data. This is done by assigning different transmission complex values ​​to different antennas to control the beam width and direction, thereby pointing the beam in the desired direction. This allows beam tracking and suppresses the sidelobe level in the interference direction. The weights used by the network device to weight the data sent to the terminal are the downlink transmission weights, and the weights used by the terminal to weight the data sent to the network device are the uplink transmission weights. Weighting can sometimes also be referred to as precoding.

[0048] In this application, (·) H represents the conjugate transpose operation of the matrix, E{·} represents the mean operation, (·) * To take the conjugate operation, |·| 2 is the modulo square operation, (·) -1 Indicates the inverse, Indicates the pseudo-inverse,<a,b> Represents the inner product of vector a and vector b.

[0049] vec(·) represents a matrix straightening operation, which involves constructing a vector by arranging the columns (or rows) of a matrix one by one (or one by one). Matrix straightening is also known as matrix vectorization (e.g., column vectorization or row vectorization).

[0050] For a matrix containing complex numbers (referred to as a complex matrix), you can extract the real part of the elements in the complex matrix and form a real column vector in the order of the columns. You can also extract the imaginary part of the elements in the complex matrix and form an imaginary column vector in the order of the columns. Then, you can connect the imaginary column vector to the real column vector to complete the matrix straightening operation of the complex matrix. For example, if the complex matrix is ​​[2+1j,3-5j], then the straightened vector is (2,3,1,-5). H For complex matrices, represents the real part of the elements in the complex matrix, Represents the imaginary part of a complex matrix element. It can represent matrix straightening operations on complex matrices.

[0051] The matrix straightening operation may also be performed in other ways, such as using the Hermitian characteristic and the Toeplitz characteristic. This application does not limit the matrix straightening method.

[0052] For the matrix recovery of the vector obtained by the matrix straightening operation of the complex matrix, taking the column vector as an example, the column vector can be divided into a real column vector and an imaginary column vector with equal number of elements, and then the real column vector and the imaginary column vector are restored to the positions of the respective elements in the matrix according to the number of columns of the matrix before the matrix straightening operation, thus completing the matrix recovery. For example, for the vector (2,3,1,-5) obtained above H , the real column vector is (2,3) H , the imaginary column vector is (1, -5) H , the number of columns of the matrix before the matrix straightening operation is 2, then the complex matrix that can be restored is [2+1j,3-5j].

[0053] Matrix recovery can also be performed in other ways. For example, for a column vector obtained by performing a matrix straightening operation using Hermitian and Toeplitz characteristics, matrix recovery can be performed based on the Hermitian and Toeplitz characteristics. This application does not limit the method of matrix recovery.

[0054] Figure 1 FIG. 1 is a schematic diagram of the architecture of the communication system 1000 used in the embodiment of the present application. Figure 1 As shown, the communication system includes a wireless access network 100 and a core network 200. Optionally, the communication system 1000 may also include the Internet 300. The wireless access network 100 may include at least one wireless access network device (such as Figure 1 110a and 110b), and may further include at least one terminal (such as Figure 1 (See 120a-120j in the figure). The terminal is wirelessly connected to the radio access network equipment, which is then connected to the core network via wireless or wired connections. The core network equipment and the radio access network equipment can be independent, distinct physical devices, or the core network equipment and the radio access network equipment's logical functions can be integrated into the same physical device. Alternatively, a single physical device can integrate some of the core network equipment's functions and some of the radio access network equipment's functions. Terminals and radio access network equipment can be connected to each other via wired or wireless connections. Figure 1 This is just a schematic diagram. The communication system may also include other network devices, such as wireless relay devices and wireless backhaul devices. Figure 1 Not drawn in the middle.

[0055] The wireless access network device (sometimes also referred to as the network device in this application) can be a base station, an evolved NodeB (eNodeB), a transmission reception point (TRP), a next generation base station (next generation NodeB, gNB) in the fifth generation (5G) mobile communication system, a next generation base station in the sixth generation (6G) mobile communication system, a base station in a future mobile communication system or an access node in a WiFi system, etc.; it can also be a module or unit that completes part of the functions of a base station, for example, it can be a centralized unit (CU) or a distributed unit (DU). The wireless access network device can be a macro base station (such as Figure 1 110a), or a micro base station or an indoor station (such as Figure 1 110b), it can also be a relay node or a donor node, etc. It is understood that all or part of the functions of the wireless access network device in this application can also be implemented by software functions running on hardware, or by virtualization functions instantiated on a platform (such as a cloud platform). The embodiments of this application do not limit the specific technology and specific device form used by the wireless access network device. For ease of description, the following description uses a base station as an example of a wireless access network device.

[0056] A terminal may also be referred to as a terminal device, user equipment (UE), mobile station, mobile terminal, etc. The terminal can be widely used in various scenarios, such as device-to-device (D2D), vehicle-to-everything (V2X) communication, machine-type communication (MTC), Internet of Things (IOT), virtual reality, augmented reality, industrial control, autonomous driving, telemedicine, smart grid, smart furniture, smart office, smart wearable, smart transportation, smart city, etc. The terminal can be a mobile phone, tablet computer, computer with wireless transceiver function, wearable device, vehicle, drone, helicopter, airplane, ship, robot, robotic arm, smart home device, etc. The embodiments of the present application do not limit the specific technology and specific device form adopted by the terminal.

[0057] Base stations and terminals can be fixed or mobile. They can be deployed on land, indoors or outdoors, handheld or vehicle-mounted; on water; or in the air on aircraft, balloons, and satellites. The embodiments of this application do not limit the application scenarios of base stations and terminals.

[0058] The roles of base stations and terminals can be relative, for example, Figure 1 The helicopter or drone 120i in the figure can be configured as a mobile base station. For the terminals 120j that access the wireless access network 100 through 120i, the terminal 120i is a base station; but for the base station 110a, 120i is a terminal, that is, the communication between 110a and 120i is carried out through the wireless air interface protocol. Of course, the communication between 110a and 120i can also be carried out through the interface protocol between base stations. In this case, relative to 110a, 120i is also a base station. Therefore, base stations and terminals can be collectively referred to as communication devices. Figure 1 110a and 110b in the figure can be called communication devices with base station functions. Figure 1 120a-120j in the figure can be called communication devices with terminal functions.

[0059] Communication between base stations and terminals, between base stations, and between terminals can be carried out through authorized spectrum, unauthorized spectrum, or both; communication can be carried out through spectrum below 6 gigahertz (GHz), spectrum above 6 GHz, or spectrum below 6 GHz and spectrum above 6 GHz. The embodiments of the present application do not limit the spectrum resources used for wireless communication.

[0060] In the embodiments of the present application, the functions of the base station may also be performed by a module (such as a chip) in the base station, or by a control subsystem that includes the base station function. The control subsystem that includes the base station function here can be a control center in the application scenarios of the above-mentioned terminals such as smart grid, industrial control, intelligent transportation, and smart city. The functions of the terminal may also be performed by a module (such as a chip or a modem) in the terminal, or by a device that includes the terminal function.

[0061] In this application, the base station sends a downlink signal (such as a synchronization signal, a downlink reference signal, etc.) or downlink information to the terminal, and the downlink information is carried on a downlink channel; the terminal sends an uplink signal (such as an uplink reference signal) or uplink information to the base station, and the uplink information is carried on an uplink channel.

[0062] The terminal can use the cell-specific reference signal (CRS) to perform channel estimation and feed back a precoding matrix indicator (PMI) to the base station to instruct the base station to precode and send data, and then receive data from the base station according to the precoding weight corresponding to the PMI.

[0063] However, for terminals that use CRS to demodulate data, high-performance beam gain cannot be obtained due to limitations on the accuracy of PMI codebook quantization and the requirement for wide CRS coverage.

[0064] For example, when a base station transmits data to a terminal operating in the fourth transmission mode (TM4) of the Long Term Evolution (LTE) system, namely, a closed-loop spatial multiplexing mode, the base station uses the PMI fed back by the TM4 terminal based on the CRS as a reference for determining downlink transmission weights. Because the CRS is transmitted using a wide beam, the TM4 terminal is constrained by the wide beam and the accuracy of the PMI codebook quantization, and cannot achieve optimal beam gain.

[0065] TM4 terminals precode and transmit data based on the PMI fed back by the terminal. The base station notifies the terminal via the PDCCH to use the PMI index. The terminal uses the CRS to perform channel estimation to determine the channel value, then uses the PMI to determine the corresponding precoding weight, and then performs equalization to obtain the data value. As shown in Equation (1), y is the received signal, H is the channel estimated using the CRS, P is the precoding weight, s is the transmitted data, and n is the interference and noise added after the signal passes through the channel.

[0066] y=HPs+n (1)

[0067] To solve the above problems, an embodiment of the present application provides a downlink transmission method, which is described as follows.

[0068] See also Figure 2 ,like Figure 2 The figure shows a schematic diagram of a communication method provided by an embodiment of the present application. The method can be applied to Figure 1 The communication system shown in FIG. 1 is not limited to this embodiment of the present application. Figure 2 The method is illustrated by taking the network device and the terminal as the execution subject of the interaction, but the present application does not limit the execution subject of the interaction. Figure 2 The network device in the method may also be a chip, a chip system, or a processor that supports the network device to implement the method, or may be a logic module or software that can implement all or part of the network device functions. Figure 2The terminal in the method may also be a chip, a chip system, or a processor that supports the terminal to implement the method, or may be a logic module or software that can implement all or part of the terminal functions.

[0069] 201. The network device obtains a first uplink statistical autocorrelation matrix of an uplink channel between the network device and the terminal.

[0070] In an embodiment of the present application, a network device transmits downlink data and a downlink reference signal. The terminal receives the downlink data transmitted by the network device and can provide feedback to the network device on whether the downlink data is successfully received. The terminal can also use the downlink reference signal transmitted by the network device to measure downlink channel quality and provide relevant measurement information back to the network device. The terminal can send uplink data and an uplink reference signal to the network device. The network device receives the uplink data transmitted by the terminal and can indicate to the terminal whether the uplink data is successfully received. The network device can also use the uplink reference signal transmitted by the terminal to perform channel estimation and channel measurement.

[0071] A network device may send configuration information to a terminal on a downlink channel. This configuration information may configure the terminal to send a sounding reference signal (SRS) to the network device. The terminal may then send the SRS to the network device based on the configuration information. The network device receives the SRS and performs uplink channel estimation, using the channel estimation result to obtain a first uplink statistical autocorrelation matrix corresponding to the uplink channel. The first uplink statistical autocorrelation matrix reflects the statistical characteristics of the uplink channel, such as the channel state information (CSI) of the uplink channel.

[0072] In a possible implementation, the first uplink statistical autocorrelation matrix R UL Satisfies the following formula.

[0073]

[0074] Among them, H t，i It represents the channel information obtained by performing uplink channel estimation for the tth time in the time domain and the i-th subcarrier in the frequency domain. T represents the number of statistical time domain samples, and N represents the number of statistical subcarriers in the frequency domain.

[0075] Alternatively, time-frequency domain filtering can be performed, and the first uplink statistical autocorrelation matrix R UL Current filtered value R t,UL Satisfies the following formula.

[0076]

[0077] Among them, α is the filter coefficient, R t,ULrepresents the value of the first uplink statistical autocorrelation matrix after the tth filtering in the time domain, R t-1,UL represents the value of the first uplink statistical autocorrelation matrix after the t-1th filtering in the time domain,

[0078] 202. The network device determines a first downlink statistical autocorrelation matrix of a downlink channel between the network device and the terminal based on the first uplink statistical autocorrelation matrix.

[0079] In an embodiment of the present application, in order to perform downlink data transmission, the network device needs to obtain downlink channel information, including PMI and channel quality indicator (CQI). To this end, the terminal can obtain the downlink channel information based on the downlink reference signal (such as CRS) measurement, and then feedback the above information to the network device through the uplink channel. However, information such as PMI and CQI is information that has been compressed to a certain extent on the downlink channel information, and cannot fully and accurately reflect the actual situation of the downlink channel. The channel characteristics of the uplink and downlink in the communication system sometimes have channel reciprocity. For example, in a time division duplex (TDD) system, the uplink and downlink use the same frequency, and the uplink and downlink generally have relatively ideal channel reciprocity. When the antenna is ideally calibrated, the network device can use the channel reciprocity to perform a conversion operation based on the first uplink statistical autocorrelation matrix obtained by the uplink SRS measurement to obtain a first downlink statistical autocorrelation matrix for downlink data transmission. The first downlink statistical autocorrelation matrix reflects the statistical characteristics of the downlink channel, for example, reflects the CSI of the downlink channel.

[0080] In a possible implementation of step 202, the network device determines the first downlink statistical autocorrelation matrix based on one or more of the first uplink and downlink frequencies, the first antenna configuration, or the first array spacing, and the first uplink statistical autocorrelation matrix. For example, the network device may determine the first downlink statistical autocorrelation matrix based on the first uplink and downlink frequencies and the first uplink statistical autocorrelation matrix, or may determine the first downlink statistical autocorrelation matrix based on the first antenna configuration and the first uplink statistical autocorrelation matrix, or may determine the first downlink statistical autocorrelation matrix based on the first uplink and downlink frequencies, the first antenna configuration, and the first uplink statistical autocorrelation matrix, or may determine the first downlink statistical autocorrelation matrix based on the first uplink and downlink frequencies, the first array spacing, and the first uplink statistical autocorrelation matrix, or may determine the first downlink statistical autocorrelation matrix based on the first uplink and downlink frequencies, the first array spacing, and the first uplink statistical autocorrelation matrix, or may determine the first downlink statistical autocorrelation matrix based on the first array spacing, the first antenna configuration, and the first uplink statistical autocorrelation matrix, or may determine the first downlink statistical autocorrelation matrix based on the first uplink and downlink frequencies, the first antenna configuration, the first array spacing, and the first uplink statistical autocorrelation matrix simultaneously.

[0081] The network device may obtain one or more of the following: a first uplink and downlink frequency, a first antenna configuration, or a first array spacing, which is pre-configured or detected and used for communication between the network device and the terminal. The first antenna configuration may include various types, such as a linear array, a planar array, a uniform array, or a non-uniform array. The first uplink and downlink frequency refers to the frequency of the uplink carrier and / or the downlink carrier. The first array spacing refers to the distance between the physical units of the antenna that transmit and receive signals.

[0082] In a possible implementation of determining the first downlink statistical autocorrelation matrix based on one or more of the first uplink and downlink frequencies, the first antenna shape, or the first array spacing, and the first uplink statistical autocorrelation matrix, the network device processes the first uplink statistical autocorrelation matrix based on a first transformation matrix to obtain the first downlink statistical autocorrelation matrix, and the first transformation matrix is ​​related to one or more of the first uplink and downlink frequencies, the first antenna shape, or the first array spacing.

[0083] The first transformation matrix, which can also be understood as an uplink and downlink statistical covariance correction matrix, is determined by the network device based on one or more of the first uplink and downlink frequencies, the first antenna configuration, or the first array spacing. The first transformation matrix can reflect the difference in uplink and downlink channel information and the channel reciprocity between the uplink and downlink channels.

[0084] Specifically, the first downlink statistical autocorrelation matrix of the network device satisfies the following formula:

[0085] r d =Tr u (4)

[0086] in, R DL represents the first downlink statistical autocorrelation matrix, T is the first transformation matrix, where T satisfies the following formula:

[0087]

[0088]

[0089]

[0090]

[0091]

[0092] in, for a u (θ i )a u (θ i ) H One of the M elements in the column vector after column vectorization, for a d (θ i )a d (θ i ) H One of the M elements in the column vector after column vectorization, m = 1…M, M = 2N 2 , i=1…N,a u (θ i ) is the steering vector of the upward subpath, a d (θ i ) is the steering vector of the downlink subpath, θ i is the angle of arrival of the i-th subpath, and N is the number of antenna channels or arrays. In MIMO technology, N antennas are used to transmit and receive data. Each channel between a pair of transmitting and receiving antennas between two devices is called a subpath. When N antennas are used for data transmission and reception, there are N subpaths. The subpath where the network device sends data to the terminal is called the downlink subpath, and the subpath where the terminal sends data to the network device is called the uplink subpath. The steering vector of a subpath reflects the direction and strength of the signal on the subpath.

[0093] In the above implementation, the network device may determine the steering vector of the uplink sub-path and the steering vector of the downlink sub-path according to one or more of the first uplink and downlink frequencies, the first antenna shape, or the first array spacing.

[0094] Among them, α u (θ i ) is related to one or more of the first uplink frequency, the first antenna shape and the first array spacing, that is, the network device can determine a according to the first uplink frequency u (θ i ), or determine a according to the first antenna form u (θ i ), or determine a based on the first array spacing u (θ i ), in the embodiment of the present application, a may be determined based on two or three of the first uplink frequency, the first antenna shape, and the first array spacing. u (θ i ), which is not limited in the present embodiment. d (θ i ) is related to one or more of the first downlink frequency, the first antenna form, and the first array spacing, that is, the network device can determine a according to the first downlink frequency d (θ i ), or determine a according to the first antenna form d (θ i ), or determine a based on the first array spacing d (θ i), in the embodiment of the present application, a may be determined based on two or three of the first downlink frequency, the first antenna shape, and the first array spacing. d (θ i ), which is not limited in the embodiments of the present application.

[0095] Exemplarily, after the network device obtains the first uplink statistical autocorrelation matrix, the specific implementation process of using the first transformation matrix to determine the first downlink statistical autocorrelation matrix is ​​as follows: Figure 3 shown.

[0096] First, we can UL Column vectorization can be performed, for example, using the Hermitian and Toeplitz characteristics to vectorize R UL Perform column vectorization to generate r u , based on the first transformation matrix T, obtain r d =Tr u . Network equipment can be based on r d The first downlink statistical autocorrelation matrix R is obtained by matrix recovery DL .

[0097] 203. The terminal sends a first PMI to the network device, and accordingly, the network device obtains the first PMI from the terminal. The first PMI indicates a first weight.

[0098] In an embodiment of the present application, a network device may send a CRS to a terminal, and the CRS may be used for coherent detection and data demodulation by the terminal. The network device may weight the CRS based on a preset weight. By using the preset weight, the bit error rate of the CRS received by the terminal may be reduced to improve the wide beam gain.

[0099] After receiving the CRS, the terminal may determine a first weight based on the CRS, and feed back a first PMI indicating the first weight to the network device.

[0100] It is understood that the present application does not limit the relative order of step 203 to steps 201 and 202. For example, 203 can be performed before 201, between 201 and 202, after 202, or simultaneously with 201 or 202, and the present application does not limit this.

[0101] 204. The network device determines a second weight based on the first weight.

[0102] In the embodiment of the present application, after receiving the first PMI, the network device may obtain a first weight according to the first PMI, and determine a second weight used to instruct the terminal to receive data based on the first weight. p Represents the second weight, V CRSis the preset weight of CRS in step 203, W PMI is the first weight, then w p Satisfies the following formula:

[0103] w p =V CRS *W PMI (10)

[0104] 205. The network device determines a third weight based on the first downlink statistical autocorrelation matrix and the second weight.

[0105] In the embodiments of the present application, the network device may determine the third weight used for transmitting data based on the first downlink statistical autocorrelation matrix and the second weight under different design principles. For example, the minimum phase deviation principle may be adopted, whereby the network device indicates to the terminal that the phase difference between the second weight and the third weight is minimized, thereby reducing phase mismatch performance loss.

[0106] Optional, third weight w d Satisfies the following formula:

[0107] w d =(R DL +δ 2 I) -1 R DL w p (11)

[0108] Among them, R DL represents the first downstream statistical autocorrelation matrix, w p represents the second weight, δ 2 represents the first channel estimation error and the first quantization error, and I represents the identity matrix. The first channel estimation error is caused by a channel estimation mismatch that occurs when the network device performs uplink channel estimation, and the first quantization error is caused by codebook quantization of the first PMI.

[0109] In the low signal-to-noise ratio scenario, δ in the above formula (11) 2 approaches infinity, i.e. δ 2 →+∞, then Equation (11) can be transformed into w d =R DL w p .

[0110] The network device determines the third weight based on the first downlink statistical autocorrelation matrix, the first channel estimation error caused by the channel estimation mismatch, the first quantization error caused by the first PMI, and the second weight, so that when the terminal uses the second weight to receive data weighted by the third weight, it can reduce the loss caused by weight mismatch as much as possible on the basis of obtaining signal power gain.

[0111] 206. The network device sends a second PMI to the terminal, where the second PMI indicates a second weight. Correspondingly, the terminal receives the second PMI from the network device and obtains a second weight according to the second PMI.

[0112] In an embodiment of the present application, after determining the second weight, the network device sends a second PMI indicating the second weight to the terminal, so that after receiving the second PMI, the terminal can determine the second weight according to the second PMI and receive data from the network device according to the second weight.

[0113] The embodiment of the present application does not limit the order of step 205 and step 206.

[0114] 207. The network device sends data to the terminal based on the third weight, and correspondingly, the terminal receives data from the network device based on the second weight.

[0115] In the embodiment of the present application, after the network device determines the third weight, it can use the determined third weight to weight the service data to be sent to the terminal, and then send the weighted service data to the terminal. The signal received by the terminal satisfies the following formula:

[0116] y=Hw d s+n (12)

[0117] Among them, y represents the signal received by the terminal, H represents the channel through which the data passes, and w d Represents the third weight, s represents the data sent, and n represents the interference and noise experienced by the signal when passing through the channel.

[0118] The terminal is based on the second weight w p The received signal y is processed to obtain received data.

[0119] The technical solution of the embodiment of the present application is that the network device determines the first downlink statistical autocorrelation matrix based on the first uplink statistical autocorrelation matrix, and determines the third weight for data transmission based on the second weight indicated by the network device to the terminal. The terminal can then receive data based on the second weight. Although there is a difference between the third weight and the second weight, the above method can minimize the loss of phase adaptation performance and improve beam gain. Therefore, the above method provided by the present application can improve downlink beam gain even when the quantization accuracy of the precoding indicator codebook is constrained.

[0120] The network device of the embodiment of the present application can be referred to Figure 4As shown in the schematic diagram of the network device structure, the network device includes a first uplink statistical autocorrelation matrix acquisition module, a first downlink statistical autocorrelation matrix determination module, a first PMI acquisition module, a second weight determination module, a third weight determination module, a second PMI sending module and a first data sending module.

[0121] Among them, the first uplink statistical autocorrelation matrix acquisition module is used to execute step 201, the first downlink statistical autocorrelation matrix determination module is used to execute step 202, the first PMI acquisition module is used to execute step 203, the second weight determination module is used to execute step 204, the third weight determination module is used to execute step 205, the second PMI sending module is used to execute step 206, and the first data sending module is used to execute step 207.

[0122] The above describes how the weight of the data sent by the network device and the weight of the data received by the terminal meet the principle of minimum phase deviation. In an embodiment of the present application, an adaptive weight can also be determined on the terminal side, and data can be sent to the network device based on the adaptive weight.

[0123] See also Figure 5 ,like Figure 5 Another communication method provided by the embodiment of the present application is shown. This method can be applied to Figure 1 The communication system shown in FIG. 1 is not limited to this embodiment of the present application. Figure 5 The method is illustrated by taking the network device and the terminal as the execution subject of the interaction, but the present application does not limit the execution subject of the interaction. Figure 5 The network device in the method may also be a chip, a chip system, or a processor that supports the network device to implement the method, or may be a logic module or software that can implement all or part of the network device functions. Figure 5 The terminal in the method may also be a chip, chip system, or processor that supports the terminal to implement the method, or a logic module or software that can implement all or part of the terminal functions. Including:

[0124] 501. The terminal obtains a second downlink statistical autocorrelation matrix of a downlink channel between the terminal and the network device.

[0125] In an embodiment of the present application, the terminal can obtain a second downlink statistical autocorrelation matrix through a downlink reference signal. The terminal performs downlink channel estimation based on the downlink reference signal to obtain the second downlink statistical autocorrelation matrix. The downlink reference signal can be a CRS or other downlink reference signal, and the present application does not limit this.

[0126] 502. The terminal determines a second uplink statistical autocorrelation matrix of an uplink channel between the terminal and the network device based on the second downlink statistical autocorrelation matrix.

[0127] Optionally, the terminal determines the second uplink statistical autocorrelation matrix based on one or more of the second uplink and downlink frequencies, the second antenna shape, or the second array spacing, and the second downlink statistical autocorrelation matrix.

[0128] Optionally, the above-mentioned terminal determines the second uplink statistical autocorrelation matrix based on one or more of the second uplink and downlink frequencies, the second antenna shape or the second array spacing, and the second downlink statistical autocorrelation matrix, including: processing the second downlink statistical autocorrelation matrix based on the second transformation matrix to obtain the second uplink statistical autocorrelation matrix, and the second transformation matrix is ​​correlated with one or more of the second uplink and downlink frequencies, the second antenna shape or the second array spacing.

[0129] In the embodiment of the present application, in step 502, the terminal determines the second uplink statistical autocorrelation matrix according to the second downlink statistical autocorrelation matrix. Figure 2 The description of how the network device determines the first downlink statistical autocorrelation matrix by using the first uplink statistical autocorrelation matrix in step 202 is omitted here.

[0130] 503. The network device sends the third PMI to the terminal. Correspondingly, the terminal receives the third PMI from the network device.

[0131] In the embodiment of the present application, the terminal receives a third PMI from the network device, and obtains a fourth weight based on the third PMI. The fourth weight is a weight used by the network device when receiving the terminal data.

[0132] It is understood that the present application does not limit the relative order of step 503 to steps 501 and 502. For example, 503 can be performed before 501, between 501 and 502, after 502, or simultaneously with 501 or 502, and the present application does not limit this.

[0133] 504. The terminal determines a fifth weight based on the second uplink statistical autocorrelation matrix and the fourth weight.

[0134] Optionally, the fifth weight satisfies:

[0135] w d ′=(R UL ′+(δ′) 2 I) -1 R UL ′w p ′ (13)

[0136] w d ′ represents the fifth weight, w p ' represents the fourth weight, R UL ' represents the second uplink statistical autocorrelation matrix, (δ′) 2represents the second channel estimation error and the second quantization error, I represents the identity matrix, (·) -1 Indicates inversion.

[0137] In the embodiment of the present application, the method for determining the fifth weight value based on the second uplink statistical autocorrelation matrix and the fourth weight value in step 504 can refer to Figure 2 The relevant description of the network device determining the third weight based on the first downlink statistical autocorrelation matrix and the second weight is not repeated here.

[0138] 505. The terminal sends data to the network device based on the fifth weight, and correspondingly, the network device receives the data based on the fourth weight.

[0139] After the terminal determines the fifth weight, it can use the determined fifth weight to weight the service data to be sent to the network device, and then send the weighted service data to the network device. The signal received by the network device terminal satisfies the following formula:

[0140] y′=H′w d ′s′+n′ (14)

[0141] Among them, y′ represents the signal received by the network device, H′ represents the channel through which the data passes, and w d ' represents the fifth weight, s' represents the data sent by the terminal, and n' represents the interference and noise experienced by the data when passing through the channel.

[0142] The network device is based on the fourth weight w p ' processes the received signal y' to obtain received data.

[0143] In the above method, the terminal interacts with the network device for data, and the terminal cannot obtain relevant information of the uplink channel by means of channel estimation. The terminal can determine the second uplink statistical autocorrelation matrix of the uplink channel based on the second downlink statistical autocorrelation matrix of the downlink channel, and determine a fifth weight different from the fourth weight based on the fourth weight indicated by the network device and the second uplink statistical autocorrelation matrix. The terminal sends data based on the fifth weight, and the network device receives data based on the fourth weight. Although there is a phase difference between the fifth weight and the fourth weight, the phase adaptation performance loss is small, and the beam gain can be improved. Therefore, the above method provided by the present application can improve the uplink beam gain when the quantization accuracy of the precoding indication codebook is constrained.

[0144] The terminal of the embodiment of the present application can refer to Figure 6 The terminal shown in the structural diagram includes a second downlink statistical autocorrelation matrix acquisition module, a second uplink statistical autocorrelation matrix determination module, a third PMI acquisition module, a fifth weight determination module and a second data sending module.

[0145] Among them, the second downlink statistical autocorrelation matrix acquisition module is used to execute step 501, the second uplink statistical autocorrelation matrix determination module is used to execute step 502, the third PMI acquisition module is used to execute step 503, the fifth weight determination module is used to execute step 504, and the second data sending module is used to execute step 505.

[0146] refer to Figure 7 , is a schematic diagram of a communication device provided in an embodiment of the present application. The communication device is used to implement each step corresponding to the network device or terminal in each of the above embodiments, such as Figure 7 As shown, the communication device 700 includes a transceiver unit 710 and a processing unit 720 .

[0147] In the first embodiment, the communication device is used to implement the steps corresponding to the network devices in the above embodiments:

[0148] Processing unit 720 is configured to obtain a first uplink statistical autocorrelation matrix of an uplink channel with the terminal, determine a first downlink statistical autocorrelation matrix of a downlink channel with the terminal based on the first uplink statistical autocorrelation matrix, obtain a first precoding matrix indicator PMI from the terminal, the first PMI indicating a first weight, determine a second weight based on the first weight, and determine a third weight based on the first downlink statistical autocorrelation matrix and the second weight, where the third weight is different from the second weight.

[0149] The transceiver unit 710 is configured to send a second PMI to the terminal, where the second PMI indicates a second weight;

[0150] The processing unit 720 is configured to control the transceiver unit 710 to send data to the terminal based on the third weight.

[0151] Optionally, the processing unit 720 is configured to determine a first downlink statistical autocorrelation matrix of a downlink channel with the terminal based on the first uplink statistical autocorrelation matrix, including:

[0152] The processing unit 720 is configured to determine a first downlink statistical autocorrelation matrix based on one or more of the first uplink and downlink frequency points, the first antenna shape, or the first array spacing, and the first uplink statistical autocorrelation matrix.

[0153] Optionally, the processing unit 720 is configured to determine a first downlink statistical autocorrelation matrix based on one or more of the first uplink and downlink frequency points, the first antenna shape, or the first array spacing, and the first uplink statistical autocorrelation matrix, including:

[0154] The processing unit 720 is used to process the first uplink statistical autocorrelation matrix based on the first transformation matrix to obtain a first downlink statistical autocorrelation matrix, where the first transformation matrix is ​​related to one or more of the first uplink and downlink frequencies, the first antenna shape, or the first array spacing.

[0155] Optionally, the third weight satisfies:

[0156] w d =(R DL +δ 2 I) -1 R DL w p

[0157] w d represents the third weight, w p Represents the second weight, R DL represents the first downlink statistical autocorrelation matrix, δ 2 represents the first channel estimation error and the first quantization error, I represents the identity matrix, (·) -1 Indicates inversion.

[0158] In a second embodiment, the communication device is used to implement the steps corresponding to the terminal in the above embodiments:

[0159] Processing unit 720 is configured to: obtain a second downlink statistical autocorrelation matrix of a downlink channel with the network device, determine a second uplink statistical autocorrelation matrix of an uplink channel with the network device based on the second downlink statistical autocorrelation matrix, obtain a third precoding matrix indicator PMI from the network device, the third PMI indicating a fourth weight, and determine a fifth weight based on the second uplink statistical autocorrelation matrix and the fourth weight, where the fifth weight is different from the fourth weight.

[0160] The processing unit 720 is further configured to control the transceiver unit 710 to send data to the network device based on the fifth weight.

[0161] Optionally, the processing unit 720 is configured to determine a second uplink statistical autocorrelation matrix of an uplink channel with the network device based on the second downlink statistical autocorrelation matrix, including:

[0162] The processing unit 720 is configured to determine a second uplink statistical autocorrelation matrix based on one or more of the second uplink and downlink frequencies, the second antenna shape, or the second array spacing, and the second downlink statistical autocorrelation matrix.

[0163] Optionally, the processing unit 720 is configured to determine a second uplink statistical autocorrelation matrix based on one or more of the second uplink and downlink frequency points, the second antenna shape, or the second array spacing, and the second downlink statistical autocorrelation matrix, including:

[0164] The processing unit 720 is configured to process the second downlink statistical autocorrelation matrix based on the second transformation matrix to obtain a second uplink statistical autocorrelation matrix, where the second transformation matrix is ​​related to one or more of the second uplink and downlink frequencies, the second antenna shape, or the second array spacing.

[0165] Optionally, the fifth weight satisfies:

[0166] w d ′=(R UL ′+(δ′) 2 I) -1 R UL ′w p '

[0167] w d ′ represents the fifth weight, w p ' represents the fourth weight, R UL ′ represents the second uplink statistical autocorrelation matrix, (δ′) 2 represents the second channel estimation error and the second quantization error, I represents the identity matrix, (·) -1 Indicates inversion.

[0168] Optionally, the communication device may further include a storage unit for storing data or instructions (also referred to as code or program). Each of the above units may interact or couple with the storage unit to implement the corresponding method or function. For example, the processing unit 720 may read the data or instructions in the storage unit so that the communication device implements the method in the above embodiment.

[0169] It should be understood that the division of units in the above communication device is merely a division of logical functions. In actual implementation, they can be fully or partially integrated into a physical entity, or they can be physically separated. Moreover, the units in the communication device can all be implemented in the form of software called through a processing element; or all be implemented in the form of hardware; or some units can be implemented in the form of software called through a processing element, and some units can be implemented in the form of hardware. For example, each unit can be a separately established processing element, or it can be integrated into a chip of the communication device. In addition, it can also be stored in the form of a program in a memory, called by a processing element of the communication device to perform the function of the unit. In addition, these units can be fully or partially integrated together, or they can be implemented independently. The processing element described here can also be a processor, which can be an integrated circuit with signal processing capabilities. In the implementation process, each step of the above method or each unit above can be implemented by an integrated logic circuit of hardware in the processor element or by software called through a processing element.

[0170] In one example, the unit in any of the above communication devices may be one or more integrated circuits configured to implement the above method, such as one or more application specific integrated circuits (ASICs), or one or more digital singnal processors (DSPs), or one or more field programmable gate arrays (FPGAs), or a combination of at least two of these integrated circuit forms. For another example, when the unit in the communication device can be implemented in the form of a processing element scheduler, the processing element may be a general-purpose processor, such as a central processing unit (CPU) or other processor that can call a program. For another example, these units can be integrated together and implemented in the form of a system-on-a-chip (SOC).

[0171] refer to Figure 8 , is a schematic diagram of a communication device provided in an embodiment of the present application, which is used to implement the operation of the network device or terminal in the above embodiment. Figure 8 As shown, the communication device includes: a processor 810 and an interface 830, wherein the processor 810 is coupled to the interface 830. The interface 830 is used to implement communication with other devices. The interface 830 can be a transceiver or an input / output interface. The interface 830 can be, for example, an interface circuit. Optionally, the communication device also includes a memory 820 for storing instructions executed by the processor 810, input data required by the processor 810 to execute instructions, or data generated after the processor 810 executes instructions.

[0172] The method executed by the network device or terminal in the above embodiment can be implemented by the processor 810 calling a program stored in a memory (which can be the memory 820 in the network device or terminal, or an external memory). That is, the network device or terminal may include a processor 810, and the processor 810 executes the method executed by the network device or terminal in the above method embodiment by calling the program in the memory. The processor here can be an integrated circuit with signal processing capabilities, such as a CPU. The network device or terminal can be implemented by one or more integrated circuits configured to implement the above method. For example: one or more ASICs, or one or more microprocessors DSPs, or one or more FPGAs, etc., or a combination of at least two of these integrated circuit forms. Alternatively, the above implementation methods can be combined.

[0173] Specifically, Figure 7 The functions / implementation processes of the transceiver unit 710 and the processing unit 720 can be realized by Figure 8 The processor 810 in the communication device 800 shown calls the computer executable instructions stored in the memory 820 to implement. Alternatively, Figure 7 The function / implementation process of the processing unit 720 can be achieved by Figure 8 The processor 810 in the communication device 800 shown calls the computer execution instructions stored in the memory 820 to implement, Figure 7 The function / implementation process of the transceiver unit 710 can be achieved by Figure 8 800 is implemented by the interface 830 in the communication device 800 shown in FIG. 8 . Exemplarily, the function / implementation process of the transceiver unit 710 can be implemented by the processor calling program instructions in the memory to drive the interface 830 .

[0174] When the communication device is a chip used in a terminal device, the terminal device chip implements the functions of the terminal device in the above method embodiment. The terminal device chip receives information from other modules in the terminal device (such as a radio frequency module or antenna), and the information comes from other terminal devices or network devices; or the terminal device chip sends information to other modules in the terminal device (such as a radio frequency module or antenna), and the information comes from the terminal device to other terminal devices or network devices.

[0175] When the communication device is a chip used in a network device, the network device chip implements the functions of the network device in the above method embodiment. The network device chip receives information from other modules in the network device (such as a radio frequency module or antenna), and the information comes from other network devices or terminal devices; or the network device chip sends information to other modules in the network device (such as a radio frequency module or antenna), and the information comes from the network device to other network devices or terminal devices.

[0176] In another embodiment of the present application, a computer-readable storage medium is further provided. The computer-readable storage medium stores computer-executable instructions. When the processor of the device executes the computer-executable instructions, the device executes the above-mentioned Figure 2 The steps of the communication method executed by the network device in the method embodiment.

[0177] In another embodiment of the present application, a computer-readable storage medium is further provided. The computer-readable storage medium stores computer-executable instructions. When the processor of the device executes the computer-executable instructions, the device executes the above-mentioned Figure 5 The steps of the communication method executed by the terminal in the method embodiment.

[0178] In another embodiment of the present application, a computer program product is further provided. The computer program product includes computer-executable instructions stored in a computer-readable storage medium. When the processor of the device executes the computer-executable instructions, the device executes the above-mentioned Figure 2 The steps of the communication method executed by the network device in the method embodiment.

[0179] In another embodiment of the present application, a computer program product is further provided. The computer program product includes computer-executable instructions stored in a computer-readable storage medium. When the processor of the device executes the computer-executable instructions, the device executes the above-mentioned Figure 5 The steps of the communication method executed by the terminal in the method embodiment.

[0180] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0181] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0182] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected based on actual needs to achieve the purpose of this embodiment.

[0183] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0184] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the part that essentially contributes to the technical solution of the present application or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

Claims

1. A communication method, characterized in that: include: Obtaining a first uplink statistical autocorrelation matrix of an uplink channel between the terminal and the uplink channel; Determine a first downlink statistical autocorrelation matrix of a downlink channel between the terminal and the first uplink statistical autocorrelation matrix; Obtaining a first precoding matrix indicator PMI from the terminal, where the first PMI indicates a first weight; determining a second weight based on the first weight; determining a third weight based on the first downlink statistical autocorrelation matrix and the second weight, where the third weight is different from the second weight; Sending a second PMI to the terminal, where the second PMI indicates the second weight, and the second weight is a weight used by the terminal when receiving data; Data is sent to the terminal based on the third weight.

2. The communication method according to claim 1, wherein: The determining, based on the first uplink statistical autocorrelation matrix, a first downlink statistical autocorrelation matrix of a downlink channel between the terminal and the terminal comprises: The first downlink statistical autocorrelation matrix is ​​determined based on one or more of the first uplink and downlink frequency points, the first antenna shape, or the first array spacing, and the first uplink statistical autocorrelation matrix.

3. The communication method according to claim 2, wherein: The determining the first downlink statistical autocorrelation matrix based on one or more of the first uplink and downlink frequency points, the first antenna shape, or the first array spacing, and the first uplink statistical autocorrelation matrix includes: The first uplink statistical autocorrelation matrix is ​​processed based on a first transformation matrix to obtain the first downlink statistical autocorrelation matrix, where the first transformation matrix is ​​related to one or more of the first uplink and downlink frequency points, the first antenna shape, or the first array spacing.

4. The communication method according to any one of claims 1 to 3, characterized in that: The third weight satisfies: w d =(R DL +δ 2 I) -1 R DL w p w d represents the third weight, w p represents the second weight, R DL represents the first downlink statistical autocorrelation matrix, δ 2 represents the first channel estimation error and the first quantization error, I represents the identity matrix, (·) -1 Indicates inversion.

5. A communication method, characterized in that: include: Acquire a second downlink statistical autocorrelation matrix of a downlink channel between the network device and the network device; Determine a second uplink statistical autocorrelation matrix of an uplink channel with the network device based on the second downlink statistical autocorrelation matrix; Obtaining a third precoding matrix indication PMI from the network device, where the third PMI indicates a fourth weight, and the fourth weight is a weight used by the network device when receiving data; determining a fifth weight based on the second uplink statistical autocorrelation matrix and the fourth weight, where the fifth weight is different from the fourth weight; Data is sent to the network device based on the fifth weight. The communication method according to claim 5 , wherein: Determining the second uplink statistical autocorrelation matrix of the uplink channel between the network device and the network device based on the second downlink statistical autocorrelation matrix includes: The second uplink statistical autocorrelation matrix is ​​determined based on one or more of the second uplink and downlink frequency points, the second antenna shape, or the second array spacing, and the second downlink statistical autocorrelation matrix.

7. The communication method according to claim 6, wherein: The determining the second uplink statistical autocorrelation matrix based on one or more of the second uplink and downlink frequency points, the second antenna shape, or the second array spacing, and the second downlink statistical autocorrelation matrix includes: The second downlink statistical autocorrelation matrix is ​​processed based on a second transformation matrix to obtain the second uplink statistical autocorrelation matrix, where the second transformation matrix is ​​related to one or more of the second uplink and downlink frequency points, the second antenna shape, or the second array spacing.

8. The communication method according to any one of claims 5 to 7, characterized in that: The fifth weight satisfies: w d ′=(R UL ′+(δ′) 2 I) -1 R UL ′w p ′ w d ' represents the fifth weight, w p ' represents the fourth weight, R UL ′ represents the second uplink statistical autocorrelation matrix, (δ′) 2 represents the second channel estimation error and the second quantization error, I represents the identity matrix, (·) -1 Indicates inversion.

9. A communication device, characterized in that: include: a processing unit, configured to obtain a first uplink statistical autocorrelation matrix of an uplink channel with a terminal, determine a first downlink statistical autocorrelation matrix of a downlink channel with the terminal based on the first uplink statistical autocorrelation matrix, obtain a first precoding matrix indicator (PMI) from the terminal, the first PMI indicating a first weight, determine a second weight based on the first weight, and determine a third weight based on the first downlink statistical autocorrelation matrix and the second weight, where the third weight is different from the second weight; A transceiver unit, configured to send a second PMI to the terminal, where the second PMI indicates the second weight, and the second weight is a weight used by the terminal when receiving data; The processing unit is configured to control the transceiver unit to send data to the terminal based on the third weight.

10. The communication device according to claim 9, wherein: The processing unit is configured to determine a first downlink statistical autocorrelation matrix of a downlink channel between the terminal and the processing unit based on the first uplink statistical autocorrelation matrix, including: The processing unit is configured to determine the first downlink statistical autocorrelation matrix based on one or more of the first uplink and downlink frequency points, the first antenna shape, or the first array spacing, and the first uplink statistical autocorrelation matrix. The communication device according to claim 10 , wherein: The processing unit is configured to determine the first downlink statistical autocorrelation matrix based on one or more of the first uplink and downlink frequency points, the first antenna shape, or the first array spacing, and the first uplink statistical autocorrelation matrix, including: The processing unit is used to process the first uplink statistical autocorrelation matrix based on a first transformation matrix to obtain the first downlink statistical autocorrelation matrix, where the first transformation matrix is ​​related to one or more of the first uplink and downlink frequency points, the first antenna shape, or the first array spacing.

12. The communication device according to any one of claims 9 to 11, characterized in that: The third weight satisfies: w d =(R DL +δ 2 I) -1 R DL w p w d represents the third weight, w p represents the second weight, R DL represents the first downlink statistical autocorrelation matrix, δ 2 represents the first channel estimation error and the first quantization error, I represents the identity matrix, (·) -1 Indicates inversion.

13. A communication device, characterized in that: include: processing unit and transceiver unit; The processing unit is configured to: obtain a second downlink statistical autocorrelation matrix of a downlink channel between the network device and the network device, determine a second uplink statistical autocorrelation matrix of an uplink channel between the network device and the network device based on the second downlink statistical autocorrelation matrix, obtain a third precoding matrix indicator PMI from the network device, the third PMI indicating a fourth weight, and determine a fifth weight based on the second uplink statistical autocorrelation matrix and the fourth weight, the fifth weight being different from the fourth weight, the fourth weight being a weight used by the network device when receiving data; The processing unit is further configured to control the transceiver unit to send data to the network device based on the fifth weight.

14. The communication device according to claim 13, wherein: The processing unit is configured to determine a second uplink statistical autocorrelation matrix of an uplink channel with the network device based on the second downlink statistical autocorrelation matrix, including: The processing unit is configured to determine the second uplink statistical autocorrelation matrix based on one or more of the second uplink and downlink frequency points, the second antenna shape, or the second array spacing, and the second downlink statistical autocorrelation matrix.

15. The communication device according to claim 14, wherein: The processing unit is configured to determine the second uplink statistical autocorrelation matrix based on one or more of the second uplink and downlink frequency points, the second antenna shape, or the second array spacing, and the second downlink statistical autocorrelation matrix, including: The processing unit is used to process the second downlink statistical autocorrelation matrix based on the second transformation matrix to obtain the second uplink statistical autocorrelation matrix, where the second transformation matrix is ​​related to one or more of the second uplink and downlink frequency points, the second antenna shape, or the second array spacing.

16. The communication device according to any one of claims 13 to 15, characterized in that: The fifth weight satisfies: w d ′=(R UL ′+(δ′) 2 I) -1 R UL ′w p ′ w d ' represents the fifth weight, w p ' represents the fourth weight, R UL ′ represents the second uplink statistical autocorrelation matrix, (δ′) 2 represents the second channel estimation error and the second quantization error, I represents the identity matrix, (·) -1 Indicates inversion.

17. A communication device, characterized in that: include: a processor coupled to the memory, The processor is configured to execute instructions stored in the memory, so that the apparatus performs the method according to any one of claims 1 to 4.

18. A communication device, characterized in that: include: a processor coupled to the memory, The processor is configured to execute instructions stored in the memory, so that the apparatus performs the method according to any one of claims 5 to 8.

19. A computer-readable storage medium, characterized in that The computer-readable storage medium stores instructions, which, when executed, enable a computer to execute the method according to any one of claims 1 to 4, or enable a computer to execute the method according to any one of claims 5 to 8.

20. A computer program product, characterized in that The computer program product includes computer program code, and is characterized in that when the computer program code is run on a computer, the computer is enabled to implement the method according to any one of claims 1 to 4, or the method according to any one of claims 5 to 8.

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