Precoding method and device

Abstract

The present application discloses a precoding method and apparatus, the method comprising: a network device sending N-1 reference signals to a terminal device; the network device receiving indication information of N-1 precoding matrices corresponding to the N-1 reference signals from the terminal device; the network device sending an Nth reference signal to the terminal device, where the Nth reference signal is obtained by weighting a weighting matrix, and the weighting matrix is ​​orthogonal to at least one precoding matrix of the N-1 precoding matrices; the network device receiving indication information of an Nth precoding matrix corresponding to the Nth reference signal from the terminal device; the network device determining a reconstruction matrix based on the N precoding matrices, where the N precoding matrices include N-1 precoding matrices and an Nth precoding matrix; and the network device sending a downlink signal based on the reconstruction matrix.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a precoding method and device. Background Art

[0002] In wireless communication systems, such as fourth-generation (4G) and fifth-generation (5G) wireless communication systems—new radio access technology (NR) systems—massive multiple input multiple output (MIMO) technology can significantly improve the system's spectral and energy efficiency by deploying large-scale antenna arrays (tens or even hundreds of antennas) at the base station side to simultaneously serve multiple users within a cell. For example, during downlink transmission in a massive MIMO system, the base station (BS) typically performs beamforming (also known as precoding). At this point, it is necessary to consider the weighting coefficients that map the signal to the antenna elements. These weighting coefficients are referred to as a weight matrix. The weight matrix can be used to adjust the amplitude and phase of the transmitting element on each antenna so that the signal is transmitted in a fixed direction.

[0003] In 5G systems, precoding includes codebook-based transmission modes and non-codebook-based transmission modes. The codebook-based transmission mode can be applied to frequency division duplex (FDD) and time division duplex (TDD) systems, while the non-codebook-based transmission mode is usually used in TDD systems. In the codebook-based transmission mode, the terminal selects an appropriate codebook from a predefined set of codebooks based on the channel state and indicates the index of the selected codebook to the base station via the control channel. The base station selects an appropriate precoding matrix based on the index of the codebook indicated by the terminal, uses this as a reference to reconstruct the downlink channel, and determines the weight matrix used for beamforming.

[0004] Considering the overhead of feedback codebook indexes and the complexity of precoding matrix design, the 3rd Generation Partnership Project (3GPP) protocol stipulates that only a finite number of discrete precoding matrices in the codebook can be used to quantize the infinite, continuous channel beam directions. Therefore, when the base station performs channel reconstruction and beamforming based on the codebook index fed back by the user, the quantization error generated will cause the beam direction determined by the precoding matrix to deviate from the actual channel beam direction, significantly reducing the user transmission rate. Summary of the Invention

[0005] The present application provides a precoding method and apparatus for improving the accuracy of beamforming in network equipment.

[0006] In the first aspect, the present application provides a precoding method, comprising: a network device sends N-1 reference signals to a terminal device; the network device receives indication information of N-1 precoding matrices corresponding to the N-1 reference signals from the terminal device; the network device sends an Nth reference signal to the terminal device, the Nth reference signal is obtained by weighting a weighting matrix, and the weighting matrix is ​​orthogonal to at least one precoding matrix of the N-1 precoding matrices; the network device receives indication information of an Nth precoding matrix corresponding to the Nth reference signal from the terminal device; the network device determines a reconstruction matrix based on the N precoding matrices, the N precoding matrices including the N-1 precoding matrices and the Nth precoding matrix; the network device sends a downlink signal based on the reconstruction matrix; the N-1 is a positive integer. Here, N-1 can be replaced by M, N can be replaced by M+1, and M is a positive integer.

[0007] Through the above method, the network device generates a weighted matrix for the next transmission based on the precoding matrix fed back by the terminal device. For example, the weighted matrix used for the Nth reference signal is orthogonal to at least one precoding matrix of the N-1 precoding matrices fed back by the terminal device. Therefore, the Nth precoding matrix fed back by the terminal device is orthogonal to at least one precoding matrix of the N-1 precoding matrices fed back previously, thereby reducing redundant information in the precoding matrix and better feeding back the channel characteristics. Therefore, the network device can generate a reconstruction matrix based on the N precoding matrices, effectively improving the accuracy of the reconstruction matrix in describing the channel characteristics and improving the accuracy of beamforming.

[0008] In a possible implementation, the weighting matrix F N satisfy:

[0009]

[0010] Among them, V c (N-1) represents a first matrix composed of the N-1 precoding matrices; represents the conjugate transposed matrix of the first matrix.

[0011] Through the above method, the weighting matrix used for the Nth reference signal is orthogonal to the N-1 precoding matrices fed back by the terminal device, so that the N precoding matrices fed back by the terminal device have no redundant information, and the eigenvectors of the rank required for reconstructing the channel can be achieved through a limited number of feedback times, which effectively improves the accuracy of the reconstruction matrix in describing the channel characteristics, improves the accuracy of beamforming, and effectively reduces the overhead of feedback precoding matrix and the computational complexity of network equipment in calculating the reconstruction matrix.

[0012] In a possible implementation, the first matrix satisfies:

[0013] V c (N-1)=[V1,V2,…V N-1 ]

[0014] Among them, V k represents the kth precoding matrix among the N-1 precoding matrices; k∈[1,N-1]; k is a positive integer.

[0015] Through the above method, the first matrix is ​​generated by merging N-1 precoding matrices, and the complexity of determining the first matrix is ​​low, which reduces the amount of calculation for the network device to determine the weighted matrix.

[0016] In a possible implementation, the number of layers of the i-th precoding matrix in the N precoding matrices is v i ; The i-th precoding matrix corresponds to v in the reconstruction matrix i feature vectors; i∈[1,N]; i is a positive integer; v i Is a positive integer.

[0017] Through the above method, since the weighting matrix used for the Nth reference signal is orthogonal to the N-1 precoding matrices fed back by the terminal device, the fed-back precoding matrix can correspond to the eigenvectors of the corresponding number of layers, eliminating the need for multiple feedback from the terminal device, thereby improving the efficiency of beamforming.

[0018] In a possible implementation manner, the network device determines the reconstruction matrix according to the weighted N precoding matrices.

[0019] Through the above method, the rank of the precoding matrix and the rank of the reconstruction matrix can be the same, and the reconstruction matrix can be determined based on the weighted N precoding matrices, effectively utilizing the channel characteristics in the N precoding matrices and improving the accuracy of the reconstruction matrix.

[0020] In a possible implementation, the reconstruction matrix is ​​determined according to a first covariance matrix Z1; the first covariance matrix Z1 satisfies:

[0021]

[0022] Where 0<λ i <1,λ i represents the weight coefficient of the i-th precoding matrix among the N precoding matrices corresponding to the first covariance matrix; The V i represents the i-th precoding matrix among the N precoding matrices; represents the conjugate transposed matrix of the i-th precoding matrix among the N precoding matrices; i∈[1,N]; i is a positive integer.

[0023] By using the above method, the first covariance matrix is ​​determined according to the N precoding matrices, and the first covariance matrix is ​​weighted and normalized, thereby effectively utilizing the channel characteristics in the N precoding matrices and improving the accuracy of the reconstructed matrix.

[0024] In one possible implementation, the network device determines the reconstruction matrix based on a second matrix composed of N precoding matrices; the second matrix satisfies:

[0025] V c =[V1,V2,…V N ]

[0026] Among them, V i represents the i-th precoding matrix among the N precoding matrices; i∈[1,N]; i is a positive integer.

[0027] Through the above method, the rank of the N precoding matrices can be different from the rank of the reconstruction matrix. The number of times the terminal device needs to feed back the precoding matrix can be determined based on the number of layers of different precoding matrices and the number of eigenvectors required for the reconstruction matrix. The rank of the reconstruction matrix is ​​not limited to the rank of the fed-back precoding matrix, which can improve the adaptability of the reconstruction matrix.

[0028] In one possible implementation, the number of layers of the i-th precoding matrix among the N precoding matrices is 1; the network device receives the channel quality information (CQI) value corresponding to the i-th reference signal from the terminal device; i∈[1,N]; i is a positive integer.

[0029] Through the above method, when the number of layers of the precoding matrix is ​​1, the precoding matrix fed back by the terminal device can correspond to an eigenvector in a reconstruction matrix. Thus, based on the fed-back CQI value, as the eigenvalue of the eigenvector, the characteristics of the channel are further provided, which is conducive to the network device to obtain a more accurate reconstruction matrix and improve the accuracy of beamforming.

[0030] In a possible implementation, the reconstruction matrix is ​​determined according to a second covariance matrix Z2; the second covariance matrix Z2 satisfies:

[0031]

[0032] Among them, C i represents the CQI value corresponding to the i-th reference signal; the V i represents the i-th precoding matrix among the N precoding matrices; represents the conjugate transposed matrix of the i-th precoding matrix among the N precoding matrices; i∈[1,N]; i is a positive integer.

[0033] Through the above method, the precoding matrix fed back by the terminal device can correspond to an eigenvector in a reconstruction matrix. Thus, according to the fed-back CQI value, it is used as the eigenvalue of the eigenvector and as the weight in the weighted precoding matrix, which is beneficial for the network device to obtain a more accurate reconstruction matrix and improve the accuracy of beamforming.

[0034] In a second aspect, the present application provides a communication device, for example, the communication device is a network device as described above. The communication device is configured to perform the method described in the first aspect or any possible embodiment. Specifically, the communication device may include modules for performing the method described in the first aspect or any possible embodiment, for example, a processing module and a transceiver module. Exemplarily, the transceiver module may include a transmitting module and a receiving module. The transmitting module and the receiving module may be different functional modules, or they may be the same functional module but capable of performing different functions. Exemplarily, the communication device is a communication device, or a chip or other component provided in the communication device. Exemplarily, the communication device is a network device. For example, the transceiver module may be implemented by a transceiver, and the processing module may be implemented by a processor. Alternatively, the transmitting module may be implemented by a transmitter, and the receiving module may be implemented by a receiver. The transmitter and receiver may be different functional modules, or they may be the same functional module but capable of performing different functions. If the communication device is a communication device, the transceiver may be implemented, for example, by an antenna, feeder, codec, etc. in the communication device. Alternatively, if the communication device is a chip set in a communication device, then the transceiver (or, transmitter and receiver) is, for example, a communication interface in the chip, which is connected to a radio frequency transceiver component in the communication device to realize information transmission and reception through the radio frequency transceiver component.

[0035] Regarding the technical effects brought about by the second aspect or various optional implementation methods of the second aspect, reference may be made to the introduction to the technical effects of the first aspect or each corresponding possible implementation method of the first aspect.

[0036] In a third aspect, a communication device is provided, which may be, for example, a network device as described above. The communication device includes a processor and a communication interface, which may be used to communicate with other devices or equipment. Optionally, the communication device may also include a memory for storing computer instructions. The processor and memory are coupled to each other to implement the method described in the first aspect or various possible embodiments. Alternatively, the communication device may not include a memory; the memory may be located external to the communication device. The processor, memory, and communication interface are coupled to each other to implement the method described in the first aspect or various possible embodiments. For example, when the processor executes computer instructions stored in the memory, the communication device executes the method described in the first aspect or any possible embodiment. Exemplarily, the communication device is a communication device, or a chip or other component provided in the communication device. Exemplarily, the communication device is a network device. If the communication device is a communication device, the communication interface is implemented, for example, by a transceiver (or transmitter and receiver) in the communication device. For example, the transceiver is implemented by an antenna, feeder, codec, etc. in the communication device. Alternatively, if the communication device is a chip set in a communication device, then the communication interface is, for example, the input / output interface of the chip, such as an input / output pin, etc., and the communication interface is connected to the radio frequency transceiver component in the communication device to realize information transmission and reception through the radio frequency transceiver component.

[0037] In a fourth aspect, a chip is provided, wherein the chip system includes at least one processor and a transceiver, the transceiver and the at least one processor are interconnected through lines, and the processor executes the method in the above-mentioned first aspect or any possible implementation method by running instructions.

[0038] In a fifth aspect, a computer-readable storage medium is provided, which is used to store a computer program. When the computer program runs on a computer, the computer executes the method in the above-mentioned first aspect or any possible implementation method.

[0039] In a sixth aspect, a computer program product comprising instructions is provided, wherein the computer program product is used to store a computer program, and when the computer program is run on a computer, the computer is enabled to execute a method in any possible implementation of the first aspect above. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1a A schematic diagram of a scenario applicable to an embodiment of the present application;

[0041] Figure 1b A schematic diagram of a scenario applicable to an embodiment of the present application;

[0042] Figure 2A schematic diagram of a precoding method flow chart provided in an embodiment of the present application;

[0043] Figure 3 A schematic diagram of a precoding method flow chart provided in an embodiment of the present application;

[0044] Figure 4 A schematic diagram of a precoding method provided in an embodiment of the present application;

[0045] Figure 5 A schematic diagram of a precoding method provided in an embodiment of the present application;

[0046] Figure 6 A schematic structural diagram of a communication device provided in an embodiment of the present application;

[0047] Figure 7 A schematic structural diagram of a communication device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0048] The embodiments of the present application will be described in detail below with reference to the accompanying drawings.

[0049] The precoding method provided in the present application can be applied to various communication systems. The communication system provided in the present application can be, for example, a long term evolution (LTE) system supporting 4G access technology, a new radio (NR) system of 5G access technology, any cellular system related to the third generation partnership project (3GPP), a wireless fidelity (WiFi) system, a world-wide interoperability for microwave access (WiMAX) system, a multi-radio access technology (RAT) system, or other future-oriented communication technologies. For example, it can be an Internet of Things (IoT) system, a narrowband Internet of Things (NB-IoT) system, a long term evolution (LTE) system, a fifth generation (5G) communication system, a hybrid architecture of LTE and 5G, an NR system, and new communication systems emerging in future communication developments. This application is applicable to 5G NR frequency division duplexing (FDD) MIMO system and 5G NR time division duplexing (TDD) MIMO system.

[0050] Below, some terms used in the embodiments of the present application are explained to facilitate understanding by those skilled in the art.

[0051] 1) Terminal devices, including devices that provide voice and / or data connectivity to users, may include, for example, handheld devices with wireless connectivity, or processing devices connected to wireless modems. The terminal device can communicate with the core network via the radio access network (RAN) and exchange voice and / or data with the RAN. In this application, a terminal is a device with wireless transceiver capabilities that can be deployed on land, including indoors or outdoors, handheld, wearable, or vehicle-mounted; it can also be deployed on the water (such as ships, etc.); it can also be deployed in the air (such as drones, airplanes, balloons, and satellites, etc.). The terminal can be a mobile phone, a tablet computer, a computer with wireless transceiver function, a virtual reality (VR) terminal device, an augmented reality (AR) terminal device, a wireless terminal in industrial control, a wireless terminal in self-driving, a wireless terminal in remote medical, a wireless terminal in smart grid, a wireless terminal in transportation safety, a wireless terminal in smart city, a wireless terminal in smart home, etc. The embodiments of the present application do not limit the application scenarios. The terminal may also be sometimes referred to as a terminal device, user equipment (UE), access terminal device, station, UE unit, UE station, mobile station, mobile station, remote station, remote terminal device, mobile device, UE terminal device, terminal device, wireless communication device, UE agent or UE device, or some other appropriate terminology. The terminal may also be fixed or mobile. The terminal device may include a vehicle, a vehicle module, a user equipment (UE), a wireless terminal device, a mobile terminal device, a subscriber unit, a subscriber station, a mobile station, a mobile station, a remote station, an access point (AP), a remote terminal device, an access terminal device, a user terminal, a user agent, or a user device, etc.For example, it may include mobile phones (or "cellular" phones), computers with mobile terminal devices, portable, pocket-sized, handheld, computer-built-in or vehicle-mounted mobile devices, smart wearable devices, etc. For example, personal communication service (PCS) phones, cordless phones, session initiation protocol (SIP) phones, wireless local loop (WLL) stations, personal digital assistants (PDAs), and other devices. It also includes limited devices, such as devices with low power consumption, devices with limited storage capacity, or devices with limited computing power. For example, it includes information sensing devices such as barcodes, radio frequency identification (RFID), sensors, global positioning systems (GPS), laser scanners, etc.

[0052] As an example and not a limitation, in the embodiment of the present application, the terminal device may also be a wearable device. Wearable devices may also be called wearable smart devices, which are a general term for wearable devices that are intelligently designed and developed using wearable technology for daily wear, such as glasses, gloves, watches, clothing, and shoes. A wearable device is a portable device that is worn directly on the body or integrated into the user's clothes or accessories. Wearable devices are not only hardware devices, but also achieve powerful functions through software support, data interaction, and cloud interaction. Broadly speaking, wearable smart devices include full-featured, large-sized, and independent of smartphones to achieve complete or partial functions, such as smart watches or smart glasses, as well as devices that only focus on a certain type of application function and need to be used in conjunction with other devices such as smartphones, such as various smart bracelets, smart helmets, and smart jewelry for vital sign monitoring.

[0053] The terminal device of the embodiment of the present application can also be a vehicle-mounted module, vehicle-mounted module, vehicle-mounted component, vehicle-mounted chip or vehicle-mounted unit built into the vehicle as one or more components or units. The vehicle can implement the method of the embodiment of the present application through the built-in vehicle-mounted module, vehicle-mounted module, vehicle-mounted component, vehicle-mounted chip or vehicle-mounted unit.

[0054] 2) Network equipment

[0055] A network device is a device with wireless transceiver functions or a chip that can be set in the device. The device includes but is not limited to: an evolved Node B (eNB), a radio network controller (RNC), a Node B (NB), a base station controller (BSC), a base transceiver station (BTS), a home base station (e.g., a home evolved NodeB, or a home Node B, HNB), a baseband unit (BBU), an access point (AP) in a wireless fidelity (WIFI) system, a wireless relay node, a wireless backhaul node, a transmission point (TRP or transmission point, TP), etc. It can also be a gNB in ​​a 5G, such as NR, system, or a transmission point (TRP or TP), one or a group of antenna panels (including multiple antenna panels) of a base station in a 5G system, or a network node constituting a gNB or a transmission point, such as a baseband unit (BBU) or a distributed unit (DU), etc.

[0056] In some deployments, a gNB may include a centralized unit (CU) and a DU. The gNB may also include a radio unit (RU). The CU implements some gNB functions, while the DU implements some gNB functions. For example, the CU implements radio resource control (RRC) and packet data convergence protocol (PDCP) layer functions, while the DU implements radio link control (RLC), media access control (MAC), and physical (PHY) layer functions. Because RRC layer information ultimately becomes PHY layer information, or is converted from PHY layer information, in this architecture, higher-layer signaling, such as RRC layer signaling or PDCP layer signaling, can also be considered to be sent by the DU, or by both the DU and the RU. It is understood that a network device can be a CU node, a DU node, or a device that includes both a CU node and a DU node. Furthermore, the CU can be classified as a network device in the access network (RAN) or a network device in the core network (CN), without limitation here.

[0057] (3) Beam

[0058] A beam is a communication resource. A beam can be a wide beam, a narrow beam, or other types of beams. Different beams can be considered as different resources (the resource can be a spatial domain resource). The technology for forming the beam can be beamforming technology or other technical means. The beamforming technology can specifically be digital beamforming technology, analog beamforming technology, and hybrid digital / analog beamforming technology. The same information or different information can be sent through different beams. Optionally, multiple beams with the same or similar communication characteristics can be regarded as a beam. A beam can be sent through one or more antenna ports. The beam is used to transmit data channels, control channels, and detection signals, for example, after the signal is transmitted through the beam, the distribution of signal strength can be formed in different directions in space. It can be understood that one or more antenna ports that form a beam can also be regarded as an antenna port set.

[0059] The embodiment of a beam in the NR protocol can be a spatial domain filter, or a spatial filter, or a spatial parameter (such as a spatial receive parameter and a spatial transmit parameter). The beam used to transmit signals can be called a transmission beam (Tx beam), or a spatial domain transmission filter, a spatial transmission filter, a spatial domain parameter, or a spatial transmission parameter. The beam used to receive signals can be called a reception beam (Rx beam), or a spatial domain reception filter, a spatial reception filter, a spatial domain reception parameter, or a spatial reception parameter.

[0060] 4) Beamforming (also known as precoding)

[0061] In most cases, due to the physical characteristics of radio waves, signals can be transmitted omnidirectionally or over a wide angle when using low- or medium-frequency bands. However, when using high-frequency bands, especially very high-frequency bands, because antenna size is generally based on half a wavelength, antenna size decreases as the carrier frequency increases. Compared to low-frequency bands, more antennas can be accommodated in the same space, allowing antenna arrays consisting of many antenna elements to be deployed at the transmitting and receiving ends. Furthermore, as the carrier frequency increases, path loss and penetration loss increase. Beamforming technology can be used to form narrow beams that scan and cover the entire cell, thereby improving coverage, enhancing spatial division multiplexing, reducing interference, and increasing spectral efficiency. An example is Massive MIMO.

[0062] Beamforming technology adjusts the parameters of the basic elements of the phased array to create constructive interference for signals at certain angles and destructive interference for signals at other angles, thereby enhancing signals at certain angles and directions. Beamforming generates a directional beam that is aimed at the target terminal device. Simultaneously, the transmitted signals from multiple antennas are coherently superimposed at the target terminal device, thereby improving the demodulation signal-to-noise ratio of the target terminal device and enhancing the user experience at the cell edge. Beamforming weights vary with the wireless channel environment to ensure that the beam is always aimed at the target user.

[0063] In MIMO transmission, spatial diversity and spatial multiplexing are achieved by reconstructing the channel using a precoding matrix at the transmitter. Beamforming is then performed based on the reconstructed channel to generate the transmitted signal. Spatial diversity improves signal transmission reliability, while spatial multiplexing facilitates the simultaneous transmission of multiple parallel data streams. Both spatial diversity and spatial multiplexing require a well-matched precoding matrix to the channel.

[0064] In the downlink codebook-based transmission, the determination of the precoding matrix can be determined by the terminal device side, and the precoding matrix determined by the terminal device is fed back to the network device. If the terminal device directly indicates each element in the precoding matrix to the network device through signaling, the signaling overhead will be relatively large. Therefore, in the current standard, the terminal device can send a precoding indication (Matrix Indicator, PMI) to the network device. The PMI can indicate the index of the precoding matrix, and each index corresponds to a precoding matrix in the codebook. Furthermore, the network device can calculate the downlink reconstruction channel or reconstruction matrix based on the precoding matrix fed back by the received terminal device, and finally determine the precoding matrix used to send the downlink signal.

[0065] There are many ways to obtain the reconstruction matrix through beamforming. For example, one possible way may be a codebook-based way, where the terminal device measures the channel through the downlink channel state information reference signal (CSI-RS) and feeds back the appropriate precoding matrix. Another possible way is to use a reference signal, such as a sounding reference signal (SRS), to measure the uplink channel, and perform weighted calculations through algorithms such as eigen beamforming (EBF), equal gain transmission (EGT), and maximum ratio transmission (MRT).

[0066] 5) The terms "system" and "network" in the embodiments of the present application can be used interchangeably. "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 items" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple.

[0067] Furthermore, unless otherwise indicated, ordinal numbers such as "first" and "second" in the embodiments of this application are used to distinguish multiple objects and are not used to define the order, timing, priority, or importance of multiple objects. For example, the first identifier and the second identifier are only used to distinguish different identifiers and do not indicate differences in the content, priority, or importance of the two identifiers.

[0068] To facilitate understanding of the embodiments of the present application, first Figure 1a The communication system shown in FIG. 1 is used as an example to describe in detail a communication system applicable to an embodiment of the present application. Figure 1a Schematic diagram of a communication system applicable to an embodiment of the present application is shown. Figure 1a As shown, the communication system 100 includes a network device 101 and a terminal device 102. The network device 101 may be configured with multiple antennas, and the terminal device may also be configured with multiple antennas. It should be understood that the network device 101 may also include multiple components related to signal transmission and reception (e.g., a processor, a modulator, a multiplexer, a demodulator, or a demultiplexer, etc.).

[0069] In the communication system 100, the network device 101 can communicate with multiple terminal devices (such as the terminal device 102 shown in the figure). The network device 101 can communicate with one or more terminal devices other than the terminal device 102. However, it should be understood that Figure 1a The terminal device 102 shown in the figure can communicate with the network device 102, but this only shows one possible scenario. In some scenarios, the terminal device 102 may also only communicate with the network device 101 and other network devices. This application does not limit this.

[0070] It should be understood that Figure 1a This is a simplified schematic diagram for ease of understanding only. The communication system may further include other network devices or other terminal devices. Figure 1aNot drawn in the figure. In the embodiment of the present application, different base stations may be base stations with different identifiers, or they may be base stations with the same identifier deployed in different geographical locations. Since the base station does not know whether it will be involved in the scenario applied by the embodiment of the present application before it is deployed, the base station or the baseband chip should support the method provided by the embodiment of the present application before deployment. It can be understood that the aforementioned base stations with different identifiers may be base station identifiers, cell identifiers or other identifiers.

[0071] The embodiments of the present application can be applied to frequency division duplex and time division duplex scenarios, for example, MIMO scenarios. For example, in the future IMT system, ITU proposed three major categories of communication scenarios, among which Enhanced Mobile Broadband mainly includes various consumer-oriented services, including web browsing, file downloading, text / voice / video chat, video, AR / VR, etc., and the increase in demand for high-speed services and network capacity has greatly increased. At this time, MIMO can be used to improve the coverage gain of the service channel. For example, the embodiments of the present application can be specifically applied to but not limited to the following scenarios: scenarios in which network equipment and terminal equipment establish beam pairs. For example, the eNB uses multiple beams to send synchronization signals to the UE, or the UE uses multiple beams to send synchronization signals to the eNB.

[0072] In the downlink transmission scenario, the network device sends data to the terminal device. The communication scenario is as follows: Figure 1a As shown. Figure 1a In the present invention, the network device 101 can be a gNB, ng-eNB or eNB, and an LTE downlink (LTE DL) or a new radio downlink (NR DL) can be established between the network device 101 and the terminal device 102. The data links transmitted on the Uu interface are called uplink and downlink. The Uu interface defines the communication protocol between the terminal device and the base station. The Uu interface defines a transmission protocol similar to the uplink and downlink in the NR system, and basically follows the uplink and downlink transmission protocol of the NR system in terms of frequency band allocation, bandwidth, frame structure, transmission mode or signaling definition.

[0073] Below, without loss of generality, the embodiment of the present application is described in detail by taking the interaction process between a terminal device and a network device as an example. The terminal device may be a terminal device that has a wireless connection relationship with the network device in a wireless communication system. It can be understood that the network device can implement the precoding scheme based on the same technical scheme with multiple terminal devices that have a wireless connection relationship in the wireless communication system. This application is not limited to this. In the embodiments of the present application, some scenarios are described using the scenario of the NR network in the wireless communication network as an example. It should be noted that the scheme in the embodiment of the present application can also be applied to other wireless communication networks, and the corresponding names can also be replaced by the names of corresponding functions in other wireless communication networks.

[0074] The following is a detailed description of the precoding method provided by the embodiment of the present application in conjunction with the accompanying drawings. The method can be applied to a scenario where a base station sends a downlink reference signal to a terminal device. Figure 2 As shown, the method may include:

[0075] Step 201: The network device sends reference signal configuration information to the terminal device.

[0076] In the NR system, the terminal device is supported to report channel state information (CSI) to the base station. Specifically, the base station may first determine the information of the resource carrying the reference signal, and then send the reference signal configuration information to the terminal device. The reference signal configuration information may specifically include the information of the resource carrying the reference signal. For example, the reference signal configuration information may include: the number of symbols P of the reference signal in a time slot, or the index of the symbol of the reference signal in a time slot. The reference signal configuration information may be configured through radio resource control (RRC) signaling, media access control element (MAC-CE), or downlink control information (DCI).

[0077] The reference signal configuration information may also include information such as conditions for reporting CSI. For example, the base station may send information related to the CSI reporting configuration and CSI-RS resources to the UE. The base station may configure the reference signal configuration information for the UE via higher-layer signaling. For example, the reference signal configuration information may be a CSI reporting configuration, each of which includes a CSI reporting configuration identifier (CSI report configuration ID).

[0078] Step 202: The network device sends a reference signal to the terminal device.

[0079] The reference signal may be a CSI-RS signal.

[0080] Step 203: The terminal device generates measurement information according to the received reference signal and sends the measurement information to the network device.

[0081] After receiving the measurement configuration information, the terminal device receives the reference signal on the resource carrying the reference signal indicated by the measurement configuration information, measures the reference signal, and when the reporting conditions indicated by the measurement configuration information are met, sends CSI to the network device on the resource configured for sending CSI in the measurement configuration information.

[0082] The terminal device can provide the base station with one or more of the following information by reporting measurement information (e.g., CSI): the number of layers used for data transmission, the precoding matrix, and the modulation and coding scheme (MCS). The RI indicates the number of layers used for data transmission; the PMI indicates the precoding matrix used for data transmission to support the base station's use of spatial division multiplexing; and the CQI indicates the quantized channel quality status information to support the base station's determination of the appropriate MCS.

[0083] The terminal device can carry the CSI on the physical uplink shared channel (Physical Uplink Shared Channel, PUSCH) time-frequency resources, or the physical uplink control channel (Physical Uplink Control Channel, PUCCH) time-frequency resources.

[0084] It should be noted that in this application, precoding can be understood as weighting the signal using a precoding matrix, or it can be understood as weighting the signal using a precoding vector. The same precoding used by the reference signals can be understood as the same reference signal transmission port. Generally, the channel states of the channels corresponding to signals transmitted from the same transmission port can be considered to be the same. It can be understood that the same reference signal transmission port can also be understood as the same reference signal channel state.

[0085] In a possible implementation, after receiving the reference signal sent by the first communication device, the second communication device may measure the reference signal, obtain a measurement result, and report the measurement result to the first communication device.

[0086] Step 204: The network device determines a reconstruction matrix based on the measurement information.

[0087] The network device can determine a reconstruction matrix based on the CSI report, and then use the reconstruction matrix as a precoding matrix for beamforming to generate a downlink signal sent to the terminal device. The downlink signal can be precoded data weighted according to the reconstruction matrix.

[0088] like Figure 1b As shown, the solid line represents the beam direction of the actual channel, and the dotted line represents the beam direction of the reconstruction matrix used by the base station after CSI measurement, PMI feedback and channel reconstruction.

[0089] Due to quantization error, the beam direction of the weights used by the base station to transmit data can deviate from the actual channel beam direction, resulting in a decrease in user transmission rates. With the continuous evolution of codebook types and standard protocols, from 3GPP Release 15 to Release 16, and from Type I codebooks (i.e., feeding back the precoding matrix based on implicit channel information such as the codebook's PMI) to Type II codebooks (i.e., feeding back the precoding matrix using partial explicit channel information such as the channel covariance matrix), the accuracy of the precoding matrix's characterization of the actual channel has continued to improve. For example, in wireless communication scenarios where a terminal device supports the Type II codebook under Release 15 or 16, using the Type II codebook under Release 15 or 16 can reduce the quantization error introduced by the precoding matrix. The Type II codebook under Release 15 only supports feedback of precoding matrices with a rank of 2 or less. Therefore, for channel reconstruction methods based on PMI feedback, the base station cannot perform channel reconstruction with a rank greater than 2, resulting in insufficient accuracy. In addition, although the Type II codebook under the Release 16 protocol can feedback a precoding matrix with a layer number of 3 or 4, considering the resource limitations of the terminal device's CSI feedback, the quantization error of the Type II codebook under the Release 16 protocol when feeding back a precoding matrix with a layer number of 3 or 4 is greater than that of a precoding matrix with a layer number of 1 or 2, resulting in insufficient reconstruction accuracy for channels with a rank greater than 2.

[0090] Combined with Figure 1a A schematic diagram of a scenario of an embodiment of the present application is shown. Figure 1a In the example, terminal device 102 is connected to network device 101. Network device 101 can reconstruct the downlink channel according to the precoding matrix fed back by the terminal device using the precoding method provided in the embodiment of the present application.

[0091] In order to reduce the quantization error caused by the network device reconstructing the downlink channel according to the precoding matrix fed back by the terminal device, the present application provides a method of performing multiple CSI measurements using weighted CSI-RS and reconstructing the downlink channel according to the precoding matrix fed back by the terminal device multiple times. In combination with the previous description, as Figure 3 FIGURE 1 is a flow chart of a precoding method provided in an embodiment of the present application. Figure 3 , the method comprising:

[0092] Step 301: The network device sends the i-th reference signal to the terminal device.

[0093] The i-th reference signal is used by the terminal device to perform the i-th CSI measurement. The i-th reference signal can be a weighted reference signal. In a reference signal period, the network device sends a weighted reference signal to the terminal device based on the reference signal configuration information. For example, the base station uses the weighting matrix F i The i-th CSI-RS is weighted by multiplying the weight matrix by the i-th CSI-RS, and the i-th CSI-RS is transmitted to the terminal device via a downlink channel. Accordingly, the terminal device receives the reference signal based on the reference signal configuration information.

[0094] Step 302: The terminal device determines the i-th precoding matrix according to the received i-th weighted reference signal.

[0095] Step 303: The terminal device feeds back the i-th measurement information to the network device.

[0096] For the i-th measurement, the i-th measurement information may include PMI information corresponding to the i-th precoding matrix, where the PMI information is used to indicate the index of the i-th precoding matrix. The i-th measurement information may also include the rank of the i-th precoding matrix.

[0097] In one exemplary embodiment, the precoding matrix in the terminal device may be pre-stored locally by the terminal device, or may be configured to the terminal device by the terminal device's serving base station. The precoding matrix in the network device may be pre-stored locally by the network device, which is not limited here.

[0098] Repeat steps 301-302, and the network device receives N PMI information sent by the terminal device, thereby obtaining N precoding matrices obtained by the terminal device through N measurements.

[0099] One possible implementation method is to use a random matrix to weight the reference signal (e.g., CSI-RS) during each CSI measurement. Thus, the downlink channel is reconstructed after obtaining the eigenvector of the downlink channel corresponding to the PMI fed back by the UE multiple times. Compared with the method of obtaining a single PMI, the accuracy of the reconstructed channel can be improved. However, the above method uses a randomly generated weighting matrix to weight the reference signal, resulting in the weighting matrices being uncorrelated between the multiple CSI measurements of the UE. Therefore, there may be redundant parts between the precoding matrices corresponding to the PMI fed back multiple times. In addition, considering the feedback overhead, even with a limited number of CSI measurements and feedback, it is not possible to guarantee that the complete downlink channel will be obtained.

[0100] Based on the above problem, the present application provides another possible implementation method, in which the network device can generate a weighting matrix F according to at least one precoding matrix fed back by the terminal device. N For example, based on the scenario where the network device has sent N-1 reference signals and received N-1 precoding matrices obtained by the terminal device based on the N-1 reference signals, the network device can determine the weighting matrix corresponding to the Nth reference signal based on the received N-1 precoding matrices. N There are multiple ways to represent the weighting matrix. Any of the N-1 reference signals can be represented as the i-th reference signal. Correspondingly, the precoding matrix fed back by the terminal device can be represented as the i-th precoding matrix. It should be noted that N-1 can be replaced by other characters, such as M, where M is a positive integer. The following uses methods a and b as examples to illustrate the implementation of the weighting matrix.

[0101] Method a: The weighting matrix corresponding to the Nth reference signal is orthogonal to the N-1 precoding matrices fed back for the first N-1 reference signals. Method a can be implemented in a variety of ways. Method a1 and method a2 are used as examples below.

[0102] Mode a1, precoding matrix and weighting matrix F N The relationship can satisfy:

[0103]

[0104] Among them, the kth precoding matrix among the N precoding matrices fed back by the first N-1 CSI measurements can be expressed as V k ,k∈[1,N-1]. represents the conjugate transposed matrix of the kth precoding matrix among the N precoding matrices.

[0105] In mode a2, the first matrix composed of the weighting matrix and the precoding matrix of the first N-1 feedbacks satisfies:

[0106]

[0107] Among them, the first matrix V is composed of N-1 precoding matrices fed back by the first N-1 CSI measurements c (N-1) can be implemented in many ways, such as merging, paralleling, and combining. For example, the first matrix V c (N-1) satisfies:

[0108] V c (N-1)=[V1,V2,…V N-1 ]

[0109] The following uses mode a2 as an example to illustrate the weighting matrix used for the reference signal sent for each CSI measurement in the scenario of mode a.

[0110] During the first CSI measurement, that is, when N=1, the weighting matrix can satisfy:

[0111]

[0112] in, N t dimensional unit matrix, that is, the first reference signal sent is an unweighted reference signal, N t Indicates the number of transmit antennas of a network device.

[0113] When sending the second reference signal, the weighting matrix can satisfy:

[0114]

[0115] in, The conjugate transposed matrix of the precoding matrix determined for the terminal device measuring the second reference signal.

[0116] When N>1, according to It can be determined that the weighted matrix can satisfy:

[0117]

[0118] The weighting matrix determined by the above method is an iterative matrix. The weighting matrix F used by the Nth reference signal is N is a conjugate symmetric matrix. Since the weighting matrix corresponding to the Nth reference signal is orthogonal to the N-1 precoding matrices fed back by the first N-1 reference signals, F N At V c (N-1) constitutes the null space of the space.

[0119] Mode b: At least one of the N-1 precoding matrices fed back is orthogonal to the weighting matrix. In mode b, there are multiple implementation modes, and the following uses modes b1 and b2 as examples for illustration.

[0120] In mode b1, the relationship between the precoding matrix and the weighting matrix can satisfy:

[0121]

[0122] Among them, the kth precoding matrix among the N-1 precoding matrices fed back by the first N-1 CSI measurements can be expressed as V k ,k∈[1,N-1]. The precoding matrix orthogonal to the weighting matrix is ​​represented by V j , j∈[1,M], M is less than or equal to N-1.

[0123] For example, there may be M precoding matrices orthogonal to the weighting matrix. The M precoding matrices may be arbitrarily selected from N-1 precoding matrices, or may be selected based on other information fed back by the terminal device, for example, the M precoding matrices may be determined based on the quality of a reference signal fed back by the terminal device. This application does not limit the selection method.

[0124] In mode b2, the first matrix composed of the weighting matrix and the precoding matrix of the previous N feedbacks satisfies:

[0125]

[0126] Among them, the first matrix V composed of M precoding matrices fed back by M CSI measurements is bM There are many ways to do this, such as merging, paralleling, linear combination, etc. One possible implementation is that the first matrix V bM Can satisfy:

[0127] V bM =[V'1,V'2,…V' M ]

[0128] Among them, V'1, V'2, ... V' M It may be one or more precoding matrices among M precoding matrices, where M is an integer greater than or equal to 1.

[0129] In step 302, the terminal device may perform channel estimation based on the received weighted reference signal and calculate an equivalent channel for the Nth CSI measurement. The equivalent channel may satisfy:

[0130]

[0131] Among them, H represents the downlink channel between the network device and the terminal device, and the dimension of H is Nr ×N t , N r Indicates the number of receiving antennas of the terminal device; N t Indicates the number of transmit antennas of a network device.

[0132] Thus, the terminal device determines the equivalent channel based on the equivalent channel The covariance matrix R N . Among them, the covariance matrix R N Can satisfy:

[0133]

[0134] Covariance matrix R n Perform eigendecomposition to determine the unitary matrix U after eigendecomposition N . Among them, the unitary matrix U N satisfy:

[0135]

[0136] Among them, U N is a unitary matrix composed of eigenvectors corresponding to eigenvalues; N Is a diagonal matrix, the diagonal elements are the covariance matrix R N The eigenvalue of .

[0137] According to the number of layers v of the precoding matrix fed back by the terminal device to the network device N , the terminal device pairs Λ N Center front v N The matrix U consists of the eigenvectors corresponding to the largest eigenvalues N (:,1:v N ) is quantized to determine the corresponding precoding matrix V N .

[0138] Combined with the above method a, since the weighting matrix corresponding to the Nth reference signal is orthogonal to the N-1 precoding matrices fed back corresponding to the first N-1 reference signals, the precoding matrix V fed back by the terminal device each time is l Equivalent to the equivalent channel covariance The eigenvector U l (:,1:v l ), in this case, the first matrix and the precoding matrix satisfy:

[0139]

[0140] Where l∈[2,N].

[0141] Therefore, the precoding matrix V can be approximately considered to be lThe two-to-two orthogonal elements are thus orthogonal, so that the eigenvectors corresponding to the reconstructed channels in the N-times precoding matrix reported by the terminal device can be approximately considered to be two-to-two orthogonal, thereby ensuring that the information reported by the terminal device is free of redundancy and improving resource utilization.

[0142] Combined with the above-mentioned method b, since the weighting matrix corresponding to the Nth reference signal is orthogonal to at least one precoding matrix among the N-1 precoding matrices fed back by the terminal device, taking the weighting matrix corresponding to the Nth reference signal as an example of being orthogonal to the M precoding matrices among the precoding matrices fed back N-1 times, the terminal device receives the weighting matrix F according to the received weighting matrix F. N , the determined precoding matrix V N , which is equivalent to the equivalent channel covariance The eigenvector U N (:,1:v N ), in this case, the first matrix and the precoding matrix satisfy:

[0143]

[0144] Therefore, it can be approximately considered that the precoding matrix V of the Nth feedback N It is orthogonal to the M precoding matrices, where the M precoding matrices are orthogonal to the weighting matrix corresponding to the Nth reference signal.

[0145] For example, assume that the rank of the precoding matrix fed back by the terminal device is 2, and the first reference signal corresponds to the first precoding matrix fed back. The weighting matrix of the second reference signal is determined orthogonally based on the first precoding matrix. The second reference signal corresponds to the second precoding matrix fed back. Therefore, the first precoding matrix can be approximately considered orthogonal to the second precoding matrix. The weighting matrix of the third reference signal can be determined orthogonally based on the second precoding matrix. The third reference signal corresponds to the third precoding matrix fed back. In this case, the third precoding matrix can be approximately considered orthogonal to the second precoding matrix. The weighting matrix of the fourth reference signal can be determined orthogonally based on the second and third precoding matrices. The fourth reference signal corresponds to the fourth precoding matrix fed back. In this case, the fourth precoding matrix can be approximately considered orthogonal to the second and third precoding matrices. At least six linearly independent principal eigenvectors (including two eigenvectors corresponding to the first precoding matrix, two eigenvectors corresponding to the second precoding matrix, and two eigenvectors corresponding to the fourth precoding matrix) can be determined from the four precoding matrices fed back four times by the terminal device. This method provides a more flexible way to determine the precoding matrix. Furthermore, the network device can reduce feedback overhead and improve the accuracy of reconstructed channels based on the precoding matrix fed back a limited number of times by the terminal device.

[0146] Step 304: Determine a reconstruction matrix according to the N precoding matrices.

[0147] There are multiple ways to determine the reconstruction matrix based on N precoding matrices. The following uses Way C and Way D as examples for illustration.

[0148] Method C performs a weighted average based on multiple precoding matrices to determine the reconstruction matrix. Method C can be implemented in multiple ways, with Methods C1 to C4 being used as examples below. It should be noted that Methods A and B of the weighting matrix involved in this application are applicable to Methods C1 and C2. Methods C3 and C4 can also be applied to scenarios where the weighting matrix is ​​Method A.

[0149] The network device receives N precoding matrices corresponding to N CSI measurements fed back by the terminal device. The i-th precoding matrix in the N precoding matrices can be expressed as V i , i∈[1,N].

[0150] Method C1: The network device can receive the precoding matrix V i Multiply it by the weighting matrix used in this measurement to determine the weighted precoding matrix V" i . With the weight matrix F i For example, the weighted precoding matrix V" i satisfy:

[0151] V” i =F i V i

[0152] For each weighted precoding matrix, the intermediate variable W" can be determined i , a possible implementation, intermediate variable W" i satisfy:

[0153]

[0154] Thus, the reconstructed downlink channel spatial covariance matrix Z is obtained. At this time, the covariance matrix Z satisfies:

[0155]

[0156] Among them, a i The weight coefficient of the intermediate variable calculated by the i-th CSI measurement can be set by the network device and is not limited here. A possible implementation method is to perform linear normalization to determine a i , for example, 0<a i <1, and satisfies

[0157] The network device performs eigendecomposition on the covariance matrix Z to obtain the matrix U composed of the main eigenvectors after eigendecomposition a :

[0158]

[0159] Among them, Λ a represents the eigenvalue after eigendecomposition, U a Represents the matrix composed of the main eigenvectors after eigendecomposition. represents the conjugate transposed matrix of the matrix composed of the main eigenvectors after eigendecomposition. Thus, U a It can be directly used as the reconstruction matrix for beamforming of downlink signals.

[0160] Mode C2: for the i-th precoding matrix V among the received N precoding matrices i , we can determine the intermediate variable W i A possible implementation method is to use the intermediate variable W i satisfy:

[0161]

[0162] in, represents the conjugate transposed matrix of the i-th precoding matrix among the N precoding matrices.

[0163] Thus, the N intermediate variables corresponding to the determined N precoding matrices can be weighted averaged to obtain the reconstructed downlink channel spatial covariance matrix Z. At this time, the covariance matrix Z satisfies:

[0164]

[0165] Where 0<λ i <1 indicates the weight coefficient of the intermediate variable calculated by the nth CSI measurement, and satisfies

[0166] Therefore, the network device performs eigendecomposition on the covariance matrix Z to obtain the matrix U composed of the main eigenvectors after eigendecomposition b :

[0167]

[0168] Among them, Λ b represents the eigenvalue after eigendecomposition, U b Represents the matrix composed of the main eigenvectors after eigendecomposition. represents the conjugate transposed matrix of the matrix composed of the main eigenvectors after eigendecomposition. Thus, U b It can be directly used as the reconstruction matrix for beamforming for downlink signal transmission.

[0169] Method C3, considering that when the network device performs weighted averaging on the precoding matrix obtained from multiple measurements, the average weight coefficient of each measurement result cannot accurately correspond to the characteristic information of the channel, resulting in limited accuracy of the reconstructed downlink channel. Based on this, combined with method a, considering that the number of layers of the precoding matrix fed back by the terminal device is 1, the terminal device i The eigenvector U corresponding to the maximum eigenvalue i (:,1) is quantized, that is, v i =1, obtain the precoding matrix V i The precoding matrix fed back by the i-th CSI measurement can be used as the i-th eigenvector of the downlink channel H quantification.

[0170] Before step 304, the terminal device may also feed back the channel quality information CQI value c to the network device. i The CQI value is used to represent the quantized value of the maximum eigenvalue corresponding to the covariance matrix of the CSI measurement.

[0171] In a possible implementation, the measurement information may include the CQI in step 303. Alternatively, the CQI may be reported together with the rank indication (RI), or may be reported separately, which is not limited here.

[0172] Therefore, the CQI information fed back by the i-th CSI measurement can represent the quantized eigenvalue Then the spatial covariance of the downlink channel H satisfies:

[0173]

[0174] Where r is the rank of the downlink channel, in this case, r = N. The intermediate variables satisfy:

[0175] Thus, the network device receives the i-th precoding matrix V among the N precoding matrices fed back by the terminal device. i and CQI information c i , thereby determining the intermediate variable W i and the weight coefficient c i , and perform weighted averaging to obtain the reconstructed downlink channel spatial covariance Z that satisfies:

[0176]

[0177] The network equipment performs eigendecomposition on the covariance matrix Z and determines the principal eigenvectors from the decomposition, which are then used as the principal eigenvectors in the reconstructed matrix. Using the CQI information, a more precise weighted average of the precoding matrix is ​​performed, improving the accuracy of the reconstructed downlink channel principal eigenvectors.

[0178] Method C4: Considering that the number of precoding matrix layers fed back by the terminal device is greater than 1, the measurement information fed back by the terminal device does not include the information of the eigenvalue corresponding to the estimated main eigenvector of the downlink channel. In combination with method a, a possible implementation method is that before step 304, the terminal device can also feed back the diagonal matrix Λ to the network device. N , Λ N The diagonal elements in are the covariance matrix R N The eigenvalue of , rank v N .

[0179] Therefore, the spatial covariance of the downlink channel H satisfies:

[0180]

[0181] Among them, r is the rank number of the downlink channel. At this time,

[0182] Thus, the network device receives the i-th precoding matrix V among the N precoding matrices fed back by the terminal device. i and the diagonal matrix Λ i , and then perform weighted averaging to obtain the reconstructed downlink channel spatial covariance Z that satisfies:

[0183]

[0184] The network equipment performs eigendecomposition on the covariance matrix Z and determines the principal eigenvectors from the decomposition, which serve as the principal eigenvectors in the reconstructed matrix. This diagonal matrix information allows for a more precise weighted average of the precoding matrix, improving the accuracy of the reconstructed downlink channel principal eigenvectors.

[0185] Method D determines a reconstruction matrix based on multiple precoding matrices. The number of eigenvectors in the reconstruction matrix is ​​greater than the number of layers in the precoding matrix. Methods D1 and D2 are used as examples below. It should be noted that Method A of the weighting matrix described above in this application is applicable to Method D1, and Method B of the weighting matrix described above is applicable to Method D2.

[0186] Method D1, combined with method a, in the scenario where the weighting matrix corresponding to the Nth reference signal is pairwise orthogonal to the N-1 precoding matrices fed back corresponding to the first N-1 reference signals, the number of principal eigenvectors in the reconstructed matrix determined by the network device is greater than the number of layers of the precoding matrix.

[0187] Since the N precoding matrices fed back by the terminal device are approximately orthogonal and can complement each other without redundancy, the layers of the N precoding matrices can be linearly superimposed to obtain linearly independent eigenvectors in the reconstructed matrix. For example, the number of layers of the i-th precoding matrix in the N precoding matrices is v i , i∈[1,N], then the number of linearly independent eigenvectors that the network device can determine can be That is, the rank of the reconstructed matrix can be This can effectively improve the accuracy of the reconstructed matrix.

[0188] In mode D1, in one possible implementation, the second matrix used to generate the reconstruction matrix may satisfy:

[0189] V d =[V1,V2,…V N ]

[0190] Thus, according to the second matrix base station matrix V d Schmidt orthogonalization is performed to obtain the principal eigenvectors of the reconstructed downlink channel (i.e., the eigenvectors in the reconstructed matrix). Thus, the orthogonalized matrix can be directly used as the reconstruction matrix for beamforming in downlink signal transmission.

[0191] Mode D2, combined with the above mode b, in a scenario where at least one of the N-1 precoding matrices fed back is orthogonal to the weighting matrix, the number of main eigenvectors in the reconstructed matrix determined by the network device is greater than the number of layers of the precoding matrix.

[0192] Since the N precoding matrices fed back by the terminal device are partially orthogonal and can be partially complementary, if the N precoding matrices are Schmidt orthogonalized, K orthogonalized precoding matrices can be determined, where the K orthogonalized precoding matrices are orthogonal to each other. At this time, the number of layers of the K orthogonalized precoding matrices can be linearly superimposed to obtain linearly independent eigenvectors in the reconstructed matrix. For example, the number of layers of the i-th orthogonalized precoding matrix in the K orthogonalized precoding matrices is v i , i∈[1,K], then the number of linearly independent eigenvectors that the network device can determine can be That is, the rank of the reconstructed matrix can be This can effectively improve the accuracy of the reconstructed matrix.

[0193] In one possible implementation, the second matrix used to generate the reconstruction matrix may satisfy:

[0194] V” d =[V”1,V”2,…V” K ]

[0195] Among them, V” iis the i-th orthogonalized precoding matrix among the K orthogonalized precoding matrices. Thus, according to the second matrix, the network device can calculate the matrix V according to the matrix V” d , the main eigenvector of the reconstructed downlink channel (i.e., the eigenvector in the reconstruction matrix) is obtained. Therefore, the orthogonalized matrix can be directly used as the reconstruction matrix for beamforming of downlink signal transmission.

[0196] In the following scenario, under the Release 15 protocol, where the number of layers is limited to 2, the terminal device can feed back to the network device a precoding matrix with 2 layers. The network device can determine the reconstruction matrix with an eigenvector greater than 2 based on the N precoding matrices received. Combined with the above method D1, if Figure 4 The specific process is as follows:

[0197] Step 401: The network device generates a first reference signal and sends the first reference signal to the terminal device.

[0198] Among them, the weighting matrix F1 corresponding to the first reference signal satisfies:

[0199]

[0200] Step 402: The terminal device sends indication information of the first precoding matrix to the network device.

[0201] The indication information of the first precoding matrix may be PMI information of the first precoding matrix.

[0202] Among them, the terminal device determines the equivalent channel for the first CSI measurement based on the first reference signal received Then calculate the covariance matrix The covariance matrix R1 is then eigen-decomposed to obtain a unitary matrix U1 consisting of eigenvectors. The terminal device quantizes the matrix consisting of the first v1 column vectors in U1 to determine the first precoding matrix V1. The terminal device feeds back the first precoding matrix to the network device via the PMI, where v1 = 2 or v1 = 1.

[0203] Step 403: The network device generates a second reference signal according to the first precoding matrix.

[0204] The network device generates the weighted matrix F2 for the second CSI measurement based on the V1 received from the terminal device, where The second reference signal is generated by the weighting matrix F2.

[0205] Step 404: The terminal device sends indication information of the second precoding matrix to the network device.

[0206] The indication information of the second precoding matrix may be PMI information of the second precoding matrix.

[0207] Determine the equivalent channel for the second CSI measurement based on the received second reference signal and the covariance matrix The terminal device then performs eigendecomposition on R2 to obtain a unitary matrix U2 consisting of eigenvectors. The terminal device quantizes the matrix consisting of the first v2 column vectors in U2 to determine the second precoding matrix V2. The terminal device feeds back the second precoding matrix to the network device via the PMI, where v2∈[1,2].

[0208] Step 405: The network device receives two precoding matrices fed back by the terminal device and determines a reconstruction matrix.

[0209] Here, a second matrix is ​​generated based on two precoding matrices V1 and V2. For example, the second matrix satisfies:

[0210] V d =[V1,V2];

[0211] Network device pair second matrix V d Perform Schmidt orthogonalization to obtain the v1+v2 principal eigenvectors of the reconstructed downlink channel. The orthogonalized matrix can be directly used as the reconstruction matrix for beamforming in downlink signal transmission.

[0212] Considering that the precoding matrices fed back by the terminal device are complementary and non-redundant, the number of precoding matrix layers can be linearly superimposed. The reconstruction matrix determined by at least two CSI measurements and the fed-back precoding matrix can overcome the protocol's restrictions on the number of layers, thereby effectively improving the accuracy of the reconstructed channel. For example, under the Release 15 protocol, the codebook's restrictions on the number of layers of the fed-back precoding matrix have been overcome. Assuming the number of precoding matrix layers fed back each time is no more than two, the Type II codebook can fully obtain the main eigenvectors of a downlink channel with a rank of 3 or 4 using only at least two feedbacks, thereby enabling reconstruction of a downlink channel with a rank of 3 or 4.

[0213] In the following scenario of layer number restriction, the terminal device can feed back to the network device a precoding matrix with a number of layers less than or equal to the preset limit number of layers, and the network device determines a reconstructed matrix with an eigenvector greater than the limit number of layers based on the received N precoding matrices. Figure 5 The specific process is as follows:

[0214] Step 501: The network device receives the i-th reference signal and sends the i-th reference signal to the terminal device.

[0215] Step 502: The terminal device sends indication information of the i-th precoding matrix to the network device.

[0216] The indication information of the i-th precoding matrix may be PMI information of the i-th precoding matrix.

[0217] Repeat steps 501 and 502, and the network device can generate N reference signals. The method for generating the weighting matrix corresponding to the Nth reference signal can refer to the generation method in method b and will not be repeated here. The network device can receive N precoding matrices sent by the terminal device. The number of layers of the N precoding matrices is less than or equal to the restricted number of layers. For example, when the restricted number of layers is 3, the number of layers of the N precoding matrices can be 1, 2, or 3.

[0218] Step 503: The network device determines a reconstruction matrix according to the N precoding matrices fed back by the terminal device.

[0219] The N precoding matrices are Schmidt orthogonalized to obtain K orthogonalized precoding matrices that are orthogonal to each other. A second matrix is ​​generated based on the K orthogonalized precoding matrices. For example, the second matrix satisfies:

[0220] V” d =[V1,V2,…V K ];

[0221] Network device pair second matrix V" d Perform Schmidt orthogonalization to obtain the reconstructed downlink channel The orthogonalized matrix can be directly used as the reconstruction matrix for beamforming of downlink signal transmission.

[0222] Considering that the precoding matrices fed back by the terminal device are complementary and non-redundant, the number of layers of the precoding matrix can be linearly superimposed. Through at least two CSI measurements and the feedback of the precoding matrix, the reconstruction matrix determined can break through the protocol's restrictions on the number of layers, thereby effectively improving the accuracy of the reconstructed channel.

[0223] In methods C2 to C4 and D1, combined with method a, the covariance matrix of the downlink channel is subjected to eigendecomposition, which can be expressed as:

[0224]

[0225] in, is a unitary matrix after eigendecomposition, which may be a matrix composed of the main eigenvectors of the downlink channel H. Is a diagonal matrix, the diagonal elements are the covariance matrix H H The eigenvalues ​​of H are arranged in descending order. The N precoding matrices fed back by the terminal device can correspond to Quantization of the principal eigenvector of .

[0226] The following uses the relationship between the precoding matrix obtained in each measurement and the downlink channel as an example to illustrate.

[0227] In the first measurement, the weighting matrix

[0228] The first precoding matrix V1 fed back by the terminal device is the matrix composed of v1 main eigenvectors of the downlink channel H

[0229] During the second CSI measurement, the weighting matrix F2 satisfies:

[0230]

[0231] The terminal device determines the equivalent channel based on the second reference signal received The covariance matrix R2 can satisfy:

[0232]

[0233] in, The matrix V2 represents the remaining eigenvectors of the downlink channel after removing the first v1 principal eigenvectors determined by the first precoding matrix. Therefore, the second precoding matrix V2 is a quantized representation of the v1+1th to v1+v2th eigenvectors of the downlink channel.

[0234] It can be obtained by iterating sequentially that during the i-th CSI measurement, the terminal device determines the covariance matrix R of the equivalent channel based on the received i-th reference signal i satisfy:

[0235]

[0236] in, represents the matrix of the remaining eigenvectors after removing the first γ main eigenvectors of the downlink channel H, and

[0237] At this time, V i yes Center front v i A quantitative expression of the eigenvectors, that is, the precoding matrix fed back by the terminal device during the i-th CSI measurement can correspond to the v after removing the first γ main eigenvectors in the downlink channel spatial covariance i feature vectors.

[0238] Therefore, the precoding matrix fed back by the terminal device each time is complementary to the reconstruction matrix used to reconstruct the downlink channel and has no redundancy. For a downlink channel with a rank of r, the terminal device only needs to perform no more than r CSI measurements to fully obtain the first r main eigenvectors of the downlink channel.

[0239] Therefore, it is possible to obtain the complete channel spatial covariance matrix with a limited number of measurements, thereby reducing quantization errors and improving beamforming accuracy.

[0240] In methods C2, C3, and D1, combined with method b, the covariance matrix of the downlink channel is subjected to eigendecomposition, which can be expressed as:

[0241]

[0242] in, is a unitary matrix after eigendecomposition, which may be a matrix composed of the main eigenvectors of the downlink channel H. Is a diagonal matrix, the diagonal elements are the covariance matrix H H The eigenvalues ​​of H. The N precoding matrices fed back by the terminal device can correspond to Quantization of the principal eigenvector of .

[0243] The following uses the relationship between the precoding matrix obtained in each measurement and the downlink channel as an example to illustrate.

[0244] In the first measurement, the weighting matrix

[0245] The first precoding matrix V1 fed back by the terminal device is the matrix composed of the first v1 main eigenvectors of the downlink channel H The reconstructed matrix satisfies:

[0246] [a1,a2,a3,…,ar]

[0247] Among them, ai is the main eigenvector in the reconstruction matrix, and the length of ai is N t , i∈[1,r]. Among them, N t represents the number of transmit antennas of the network device. r is the rank of the reconstruction matrix.

[0248] Take v1 as an example, satisfy:

[0249]

[0250] Among them, the first precoding matrix V1=b1, b1 corresponds to the first main eigenvector a1. The length of b1 is N t Among them, N t Indicates the number of transmit antennas of a network device.

[0251] During the second CSI measurement, the weighting matrix F2 satisfies:

[0252]

[0253] The terminal device determines the equivalent channel based on the second reference signal received The covariance matrix R2 can satisfy:

[0254]

[0255] In the above example, b1·F2=0, the second matrix V b1 =[b1]. It represents the matrix of the remaining eigenvectors after removing the first v1 main eigenvectors determined by the first precoding matrix of the downlink channel. Taking v2 as 2 as an example, satisfy:

[0256]

[0257] Among them, b2 can correspond to the main eigenvector a2 in the reconstructed matrix; b3 can correspond to the main eigenvector a3 in the reconstructed matrix. Among them, the lengths of b2 and b3 are N t Among them, N t It indicates the number of transmit antennas of the network device. It can be seen that the second precoding matrix V2 is a quantized expression of the eigenvectors from v1+1 to v1+v2 of the downlink channel.

[0258] During the third CSI measurement, the weighting matrix F3 satisfies:

[0259]

[0260] One possible implementation method is that the second matrix V b2 =[V1]. Combining the above example, b1·F3=0.

[0261] At this time, the terminal device determines the equivalent channel based on the received third reference signal The covariance matrix R3 can satisfy:

[0262]

[0263] in, It represents the matrix of the remaining eigenvectors after removing the first v1 main eigenvectors determined by the first precoding matrix of the downlink channel. Taking v3 as 3 as an example, satisfy:

[0264]

[0265] Among them, the length of each eigenvector of b4, b5, b6 is N tThe third precoding matrix V3 is orthogonal to the eigenvector a1 of the first precoding matrix. Therefore, b4, b5, and b6 can correspond to the other three main eigenvectors in the reconstructed matrix except the main eigenvector a1. However, since V3 is not orthogonal to b2 and b3, there may be redundancy between the third precoding matrix V3 and the eigenvectors b2 and b3. At this time, the third precoding matrix V3 is a quantized expression of the eigenvectors v1+1 to v1+v3 of the downlink channel.

[0266] Another possible implementation method is that the second matrix V b2 =[V2]. Combining the above example, [b2, b3]·F3=0. Thus, the third reference signal is generated. At this time, the terminal device determines the equivalent channel according to the received third reference signal. The covariance matrix R3 can satisfy:

[0267]

[0268] in, It represents the matrix of the remaining eigenvectors after removing the eigenvectors v1+1 to v1+v2 determined by the second precoding matrix of the downlink channel. Taking v3 as 3 as an example, select The three eigenvectors with the largest eigenvalues ​​in form the third precoding matrix V'3, which satisfies:

[0269] V'3=[b4',b5',b6']

[0270] Among them, the length of each eigenvector of b4', b5', b6' is N t V3 and b2, b3 are mutually orthogonal. Therefore, b4', b5', and b6' can correspond to the other three main eigenvectors in the reconstructed matrix except for the main eigenvectors a2 and a3. However, since V3 is not orthogonal to the eigenvector b1 of the first precoding matrix, there may be redundancy between the third precoding matrix V3 and the main eigenvector b1. In this case, the third precoding matrix V3 can be a quantized expression of the other v3 eigenvectors of the downlink channel except for the eigenvectors v1+1 to v1+v2.

[0271] It can be obtained by iterating sequentially that during the i-th CSI measurement, the terminal device determines the covariance matrix R of the equivalent channel based on the received i-th reference signal i satisfy:

[0272]

[0273] in, It represents the matrix of the remaining eigenvectors after removing the γ main eigenvectors of the downlink channel H, and Among them, the number of layers of the pth orthogonalized precoding matrix in the K1 orthogonalized precoding matrices is v p ,p∈[1,K1].v p Represents the number of layers in each of the M orthogonalized precoding matrices determined after orthogonalizing the i precoding matrices received by the network device. If the i precoding matrices are Schmidt orthogonalized, K1 orthogonalized precoding matrices can be determined, where each of the K1 orthogonalized precoding matrices is orthogonal. In this case, the layers of the K1 orthogonalized precoding matrices can be linearly superimposed to obtain linearly independent eigenvectors in the reconstructed matrix.

[0274] In combination with the above example, based on the first three precoding matrices V1, V2, and V3, the orthogonalized precoding matrices can be determined as: V1, V2, and V3. In this case, it can be determined that V1 corresponds to one eigenvector, V2 corresponds to two eigenvectors, and V3 is an eigenvector orthogonal to both V1 and V2. That is, the eigenvectors determined from [b4, b5, b6] that are mutually orthogonal to b1, b2, and b3 include at least one eigenvector and at most three eigenvectors. Therefore, γ is at least 4 and at most 6.

[0275] For example, the weight matrix corresponding to the i-th reference signal is the same as the M in the previous i-1 precoding matrix. i The precoding matrices are orthogonal, where the M i Among the precoding matrices, if the first precoding matrix, the third precoding matrix and the fifth precoding matrix are orthogonal to each other, then the first precoding matrix corresponds to v1 eigenvectors, the third precoding matrix corresponds to v3 eigenvectors, and the fifth precoding matrix corresponds to v5 eigenvectors, γ = v1 + v3 + v5.

[0276] At this time, V i yes Medium v i A quantitative expression of the eigenvectors, that is, the precoding matrix fed back by the terminal device during the i-th CSI measurement can correspond to the v after removing the γ main eigenvectors corresponding to the precoding matrix orthogonal to the weighting matrix in the downlink channel spatial covariance i feature vectors.

[0277] Therefore, the precoding matrix fed back by the terminal device each time is partially complementary to the reconstruction matrix used to reconstruct the downlink channel. For a downlink channel of rank r, the terminal device only needs to perform a limited number of CSI measurements to fully obtain the first r principal eigenvectors of the downlink channel. This allows the complete channel spatial covariance matrix to be obtained with a limited number of measurements, reducing quantization error and improving beamforming accuracy.

[0278] Based on the same concept as the above precoding method, the following describes the device used to implement the above method in the embodiment of the present application in conjunction with the accompanying drawings. Therefore, the above content can be used in subsequent embodiments, and repeated content will not be repeated. Figure 6 A schematic block diagram of a communication device 600 provided in an embodiment of the present application.

[0279] The communication device 600 includes a processing module 601 and a transceiver module 602. Exemplarily, the communication device 600 can be a network device, or a chip used in a network device, or other combined devices, components, etc. having the functions of the above-mentioned network device. When the communication device 600 is a network device, the transceiver module 602 can be a transceiver, which can include an antenna and a radio frequency circuit, etc., and the processing module 601 can be a processor, such as a baseband processor, which can include one or more central processing units (CPUs). When the communication device 600 is a chip system, the transceiver module 602 can be the input and output interface of the chip (such as a baseband chip), and the processing module 601 can be the processor of the chip system, which can include one or more central processing units. It should be understood that the processing module 601 in the embodiment of the present application can be implemented by a processor or a processor-related circuit component, and the transceiver module 602 can be implemented by a transceiver or a transceiver-related circuit component.

[0280] For example, the processing module 601 may be used to execute Figure 2 or Figure 3 All operations except transceiver operations performed by the network device in the embodiment shown, and / or other processes used to support the technology described herein. Figure 2 or Figure 3 The illustrated embodiments illustrate all transceiver operations performed by network devices, and / or other processes used to support the techniques described herein.

[0281] In addition, the transceiver module 602 may be a functional module that can perform both sending and receiving operations. For example, the transceiver module 602 may be used to perform Figure 2 or Figure 3 In the embodiment shown, all sending operations and receiving operations performed by the network device are as follows. For example, when performing a sending operation, the transceiver module 602 can be considered as a sending module, and when performing a receiving operation, the transceiver module 602 can be considered as a receiving module; or, the transceiver module 602 can also be two functional modules, and the transceiver module 602 can be considered as a general term for the two functional modules, which are a sending module and a receiving module respectively. The sending module is used to complete the sending operation, for example, the sending module can be used to perform Figure 2 or Figure 3In any of the embodiments shown, the receiving module is used to perform all the sending operations performed by the network device, for example, the receiving module can be used to perform Figure 2 or Figure 3 The illustrated embodiment shows all receive operations performed by the network device.

[0282] Among them, the processing module 601 is used to determine a reconstruction matrix according to N precoding matrices, where the N precoding matrices include the N-1 precoding matrices and the Nth precoding matrix; send a downlink signal according to the reconstruction matrix; and the N-1 is a positive integer.

[0283] The transceiver module 602 is configured to send N-1 reference signals to a terminal device; the network device receives indication information of N-1 precoding matrices corresponding to the N-1 reference signals from the terminal device; sends an Nth reference signal to the terminal device, where the Nth reference signal is weighted by a weighting matrix, and the weighting matrix is ​​orthogonal to at least one precoding matrix of the N-1 precoding matrices; and receives indication information of the Nth precoding matrix corresponding to the Nth reference signal from the terminal device.

[0284] In a possible implementation, the weighting matrix F of the Nth reference signal is N satisfy:

[0285]

[0286] Among them, V c (N-1) represents a first matrix composed of the N-1 precoding matrices; represents the conjugate transposed matrix of the first matrix.

[0287] In a possible implementation, the first matrix satisfies:

[0288] V c (N-1)=[V1,V2,…V N-1 ]

[0289] Among them, V k represents the kth precoding matrix among the N-1 precoding matrices; k∈[1,N-1]; k is a positive integer.

[0290] In a possible implementation, the number of layers of the i-th precoding matrix in the N precoding matrices is v i ; The i-th precoding matrix in the N precoding matrices corresponds to the v in the reconstruction matrix i feature vectors; i∈[1,N]; i is a positive integer; v i Is a positive integer.

[0291] In a possible implementation, the processing module 601 is specifically configured to determine the reconstruction matrix according to the weighted N precoding matrices.

[0292] In a possible implementation, the reconstruction matrix is ​​determined according to a first covariance matrix Z1; the first covariance matrix Z1 satisfies:

[0293]

[0294] Where 0<λ i <1,λ i represents the weight coefficient of the i-th precoding matrix among the N precoding matrices corresponding to the first covariance matrix; The V i represents the i-th precoding matrix among the N precoding matrices; represents the conjugate transposed matrix of the i-th precoding matrix among the N precoding matrices; i∈[1,N]; i is a positive integer.

[0295] In one possible implementation, the processing module 601 is specifically configured to determine the reconstruction matrix based on a second matrix composed of N precoding matrices; the second matrix satisfies:

[0296] V c =[V1,V2,…V N ]

[0297] Among them, V i represents the i-th precoding matrix among the N precoding matrices; i∈[1,N]; i is a positive integer.

[0298] In a possible implementation, the number of layers of the i-th precoding matrix in the N precoding matrices is 1;

[0299] The transceiver module 602 is further configured to receive a CQI value from the terminal device; the CQI value corresponds to the i-th precoding matrix; i∈[1,N]; and i is a positive integer.

[0300] In a possible implementation, the reconstruction matrix is ​​determined according to a second covariance matrix Z2; the second covariance matrix Z2 satisfies:

[0301]

[0302] Among them, C i represents the CQI value corresponding to the i-th reference signal; the V i represents the i-th precoding matrix among the N precoding matrices; represents the conjugate transposed matrix of the i-th precoding matrix among the N precoding matrices; i∈[1,N]; i is a positive integer.

[0303] Based on the same concept as the above precoding method, Figure 7 As shown, the embodiment of the present application further provides a communication device 700. The communication device 700 can be used to implement the method performed by the network device in the above method embodiment, and reference can be made to the description of the above method embodiment, wherein the communication device 700 can be a network device, or can be located in a network device, or can be a transmitting device.

[0304] The communication device 700 includes one or more processors 701. Processor 701 can be a general-purpose processor or a dedicated processor. For example, it can be a baseband processor or a central processing unit. The baseband processor can be used to process communication protocols and communication data, and the central processing unit can be used to control the communication device (such as a network device or chip), execute software programs, and process software program data. The communication device 700 may include a transceiver unit to implement signal input (reception) and output (transmission). For example, the transceiver unit can be a transceiver, a radio frequency chip, etc.

[0305] The communication device 700 includes one or more processors 701 , and the one or more processors 701 can implement the method executed by the network device in the above-mentioned embodiment.

[0306] Optionally, in addition to implementing the methods in the embodiments shown above, the processor 701 may also implement other functions. Optionally, in one implementation, the processor 701 may execute a computer program to cause the communication device 700 to perform the method performed by the network device in the above method embodiment. The computer program may be stored in whole or in part within the processor 701, such as computer program 703, or in whole or in part in the memory 702 coupled to the processor 701, such as computer program 704. The computer programs 703 and 704 may also be used together to cause the communication device 700 to perform the method performed by the network device in the above method embodiment.

[0307] In another possible implementation, the communication device 700 may also include a circuit, which can implement the functions performed by the network device in the aforementioned method embodiment.

[0308] In another possible implementation, the communication device 700 may include one or more memories 702 on which a computer program 704 is stored. The computer program can be executed on a processor so that the communication device 700 performs the encoding method described in the above method embodiment. Optionally, data can also be stored in the memory. Optionally, the processor can also store computer programs and / or data. For example, the one or more memories 702 can store the associations or correspondences described in the above embodiments, or the relevant parameters or tables involved in the above embodiments. The processor and memory can be provided separately, or integrated or coupled together.

[0309] In another possible implementation, the communication device 700 may further include a transceiver unit 705. The processor 701 may be referred to as a processing unit, which controls the communication device (network device). The transceiver unit 705 may be referred to as a transceiver, a transceiver circuit, or a transceiver, etc., and is configured to transmit and receive data or control signaling.

[0310] For example, if the communication device 700 is a chip used in a communication device or other combined devices, components, etc. having the functions of the above-mentioned communication device, the communication device 700 may include a transceiver unit 705.

[0311] In another possible implementation, the communication device 700 may further include a transceiver unit 705 and an antenna 706. The processor 701 may be referred to as a processing unit and controls the communication device (network device). The transceiver unit 705 may be referred to as a transceiver, a transceiver circuit, or a transceiver, and is configured to implement the transceiver function of the device via the antenna 706.

[0312] In one embodiment, the transceiver unit 705 is configured to send N-1 reference signals to a terminal device; the network device receives, from the terminal device, indication information of N-1 precoding matrices corresponding to the N-1 reference signals; send an Nth reference signal to the terminal device, the Nth reference signal being weighted by a weighting matrix, the weighting matrix being orthogonal to at least one precoding matrix of the N-1 precoding matrices; and receive, from the terminal device, indication information of the Nth precoding matrix corresponding to the Nth reference signal;

[0313] Processor 701 is configured to determine a reconstruction matrix based on N precoding matrices, where the N precoding matrices include the N-1 precoding matrices and the Nth precoding matrix; and send a downlink signal based on the reconstruction matrix, where N-1 is a positive integer.

[0314] It should be noted that the processor in the embodiments of the present application can be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method embodiment can be completed by a hardware integrated logic circuit in the processor or a computer program in software form. The above processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component. The various methods, steps, and logic block diagrams disclosed in the embodiments of the present application can be implemented or executed. The general-purpose processor can be a microprocessor or any conventional processor. The method steps disclosed in conjunction with the embodiments of the present application can be directly implemented and executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium well-known in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The storage medium is located in the memory, and the processor reads the information in the memory and, in conjunction with its hardware, completes the steps of the above method.

[0315] It is understood that the memory in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), and direct RAM bus RAM (DR RAM). It should be noted that the memory of the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0316] An embodiment of the present application further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a computer, the method of any of the above-mentioned method embodiments applied to a network device is implemented.

[0317] An embodiment of the present application also provides a computer program product, which, when executed by a computer, implements any of the above-mentioned method embodiments applied to a network device.

[0318] It should be noted that the memory described herein is intended to include, but not be limited to, these and any other suitable types of memory.

[0319] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0320] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for a specific application, but such implementation should not be considered beyond the scope of this application.

[0321] 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.

[0322] 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 units is only 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 through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0323] Units described as separate components may or may not be physically separate, and 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 to achieve the purpose of this embodiment according to actual needs.

[0324] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0325] If the function 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 technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned computer-readable storage medium can be any available medium that can be accessed by a computer. By way of example and not limitation, computer-readable media may include random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM), universal serial bus flash disk, mobile hard disk, or other optical disk storage, magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a computer.

[0326] The above are only specific embodiments of the present application, but the scope of protection of the embodiments of the present application is not limited thereto. Any person skilled in the art can easily conceive of changes or substitutions within the technical scope disclosed in the embodiments of the present application, and such changes or substitutions should be included in the scope of protection of the embodiments of the present application. Therefore, the scope of protection of the embodiments of the present application should be based on the scope of protection of the claims.

Claims

1. A precoding method, characterized in that: include: The network device sends N-1 reference signals to the terminal device; The network device receives, from the terminal device, indication information of N-1 precoding matrices corresponding to the N-1 reference signals; The network device sends an Nth reference signal to the terminal device, where the Nth reference signal is weighted by a weighting matrix, and the weighting matrix is ​​orthogonal to at least one precoding matrix among the N-1 precoding matrices; The network device receives, from the terminal device, indication information of the Nth precoding matrix corresponding to the Nth reference signal; The network device determines a reconstruction matrix according to N precoding matrices, where the N precoding matrices include the N-1 precoding matrices and the Nth precoding matrix; The network device sends a downlink signal according to the reconstruction matrix; N-1 is a positive integer.

2. The method according to claim 1, characterized in that The weighting matrix F of the Nth reference signal N satisfy: Among them, V c (N-1) represents a first matrix composed of the N-1 precoding matrices; represents the conjugate transposed matrix of the first matrix.

3. The method according to claim 2, characterized in that The first matrix satisfies: V c (N-1)=[V1,V2,…V N-1 ] Among them, V k represents the kth precoding matrix among the N-1 precoding matrices; k∈[1,N-1]; k is a positive integer.

4. The method according to claim 1, wherein The number of layers of the i-th precoding matrix in the N precoding matrices is v i ; The i-th precoding matrix corresponds to v in the reconstruction matrix i feature vectors; Said i∈[1,N]; said i is a positive integer; said v i Is a positive integer.

5. The method according to any one of claims 1 to 4, characterized in that The network device determines a reconstruction matrix according to the N precoding matrices, including: The network device determines the reconstruction matrix according to the weighted N precoding matrices.

6. The method according to claim 5, characterized in that The reconstruction matrix is ​​determined according to the first covariance matrix Z1; the first covariance matrix Z1 satisfies: Where 0<λ i <1,λ i represents the weight coefficient of the i-th precoding matrix among the N precoding matrices corresponding to the first covariance matrix; The V i represents the i-th precoding matrix among the N precoding matrices; represents the conjugate transposed matrix of the i-th precoding matrix among the N precoding matrices; i∈[1,N]; i is a positive integer.

7. The method according to any one of claims 1 to 4, characterized in that The network device determines a reconstruction matrix according to N precoding matrices, including: The network device determines the reconstruction matrix according to a second matrix composed of the N precoding matrices; the second matrix satisfies: V c =[V1,V2,…V N ] Among them, V i represents the i-th precoding matrix among the N precoding matrices; i∈[1,N]; i is a positive integer.

8. The method according to claim 1, characterized in that The number of layers of the i-th precoding matrix in the N precoding matrices is 1; and the method further includes: The network device receives a channel quality information CQI value corresponding to an i-th reference signal from the terminal device; the i∈[1,N]; the i is a positive integer.

9. The method according to claim 8, characterized in that The reconstruction matrix is ​​determined according to the second covariance matrix Z2; the second covariance matrix Z2 satisfies: Among them, C i represents the CQI value corresponding to the i-th reference signal; the V i represents the i-th precoding matrix; represents the conjugate transposed matrix of the i-th precoding matrix; i∈[1,N]; i is a positive integer.

10. A communication device, characterized in that: include: A transceiver module is used to send N-1 reference signals to the terminal device; Receiving, from the terminal device, indication information of an N-1 precoding matrix corresponding to the N-1 reference signals; sending an Nth reference signal to the terminal device, the Nth reference signal being weighted by a weighting matrix, the weighting matrix being orthogonal to at least one precoding matrix of the N-1 precoding matrices; and receiving, from the terminal device, indication information of an Nth precoding matrix corresponding to the Nth reference signal; A processing module is used to determine a reconstruction matrix according to N precoding matrices, where the N precoding matrices include the N-1 precoding matrices and the Nth precoding matrix; send a downlink signal according to the reconstruction matrix; and the N-1 is a positive integer.

11. The device according to claim 10, characterized in that The weighting matrix F of the Nth reference signal N satisfy: Among them, V c (N-1) represents a first matrix composed of the N-1 precoding matrices; represents the conjugate transposed matrix of the first matrix.

12. The device according to claim 11, characterized in that The first matrix satisfies: V c (N-1)=[V1,V2,…V N-1 ] Among them, V k represents the kth precoding matrix among the N-1 precoding matrices; k∈[1,N-1]; k is a positive integer.

13. The device according to claim 10, characterized in that The number of layers of the i-th precoding matrix in the N precoding matrices is v i ; The i-th precoding matrix corresponds to v in the reconstruction matrix i feature vectors; Said i∈[1,N]; said i is a positive integer; said v i Is a positive integer.

14. The device according to any one of claims 10 to 13, characterized in that The processing module is specifically configured to determine the reconstruction matrix according to the weighted N precoding matrices.

15. The device according to claim 14, characterized in that The reconstruction matrix is ​​determined according to the first covariance matrix Z1; the first covariance matrix Z1 satisfies: Where 0<λ i <1,λ i represents the weight coefficient of the i-th precoding matrix corresponding to the first covariance matrix; The V i represents the i-th precoding matrix; represents the conjugate transposed matrix of the i-th precoding matrix; i∈[1,N]; i is a positive integer.

16. The device according to any one of claims 10 to 13, characterized in that The processing module is specifically configured to determine the reconstruction matrix according to a second matrix composed of N precoding matrices, wherein the second matrix satisfies: V c =[V1,V2,…V N ] Among them, V i represents the i-th precoding matrix among the N precoding matrices; i∈[1,N]; i is a positive integer.

17. The device according to claim 10, characterized in that The number of layers of the i-th precoding matrix in the N precoding matrices is 1; The transceiver module is further configured to receive a channel quality information CQI value corresponding to the i-th reference signal from the terminal device; the i∈[1,N]; the i is a positive integer.

18. The device according to claim 17, characterized in that The reconstruction matrix is ​​determined according to the second covariance matrix Z2; the second covariance matrix Z2 satisfies: Among them, C i represents the CQI value corresponding to the i-th reference signal; V i represents the i-th precoding matrix; represents the conjugate transposed matrix of the i-th precoding matrix among the N precoding matrices; i∈[1,N]; i is a positive integer.

19. A communication device, characterized in that: The device includes a processor and a communication interface; The communication interface is used to receive code instructions and transmit them to the processor; the processor runs the code instructions to execute the method according to any one of claims 1 to 9.

20. A chip, characterized in that: The chip includes at least one processor and a transceiver, the transceiver and the at least one processor are interconnected via lines, and the processor executes the method according to any one of claims 1 to 9 by running instructions.

21. A readable storage medium, characterized in that The readable storage medium stores instructions, which, when executed, enable the method according to any one of claims 1 to 9 to be implemented.

22. A computer program product, characterized in that The computer program product comprises: a computer program code, and when the computer program code is run on a computer, the computer is caused to perform the method according to any one of claims 1 to 9.

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