Communication method and apparatus

Abstract

A communication method and apparatus, which relate to the technical field of communications. In the method, a first communication apparatus measures a reference signal to obtain at least two vectors, and then the first communication apparatus can process the at least two vectors on the basis of a vector scaling parameter and an association relationship between scaled vectors, wherein each vector corresponds to reference signals for N receiving antennas in the same frequency-domain unit, and N is an integer greater than or equal to 2. In the present application, when filtering is performed at a receiving end, a correlation law of vectors in a frequency domain after receiving antenna dimension normalization is taken into consideration, thereby facilitating an improvement in the filtering performance, and further helping to improve the performance of channel estimation performed by a first communication apparatus.

Description

Communication methods and devices

[0001] This application claims priority to Chinese Patent Application No. 202411845205.X, filed on December 13, 2024, entitled "Communication Method and Apparatus", the entire contents of which are incorporated herein by reference. Technical Field

[0002] This application relates to the field of communication technology, and in particular to a communication method and apparatus. Background Technology

[0003] In communication systems, estimating the uplink or downlink channel is crucial for transmitting and receiving data, obtaining system synchronization and feedback channel information. Channel estimation refers to the process of reconstructing or recovering the received signal to compensate for signal distortion caused by channel fading and noise. It utilizes pilot or reference signals (RS) known to the transmitter and receiver to detect changes in the channel's time and frequency domains. A typical implementation of current channel estimation techniques uses a Wiener filter, which is primarily based on single-input single-output (SISO) frequency domain channel modeling and filtering. However, this approach is not conducive to improving the performance of channel estimation. Summary of the Invention

[0004] This application provides a communication method and apparatus that are beneficial for improving the performance of channel estimation.

[0005] The present application is described below from different aspects. It should be understood that the different implementation methods and beneficial effects described below can be referenced from each other.

[0006] Firstly, this application provides a communication method that can be applied to a first communication device. For example, the first communication device can be a terminal, or a component within the terminal (e.g., a processor, chip, chip system, circuit, or functional module), such as a terminal or a communication / processing module within the terminal, or a circuit or chip within the terminal responsible for communication functions (e.g., a modem chip, also known as a baseband chip, or a system-on-chip (SoC) chip containing a modem core, or a system-in-package (SIP) chip), or a circuit or chip within the terminal responsible for processing functions (e.g., a graphics processing unit (GPU), an artificial intelligence (AI) processor, or an application-specific integrated circuit (ASIC), or a sensing function processor). As another example, the first communication device can also be an access network device, which can be an access network equipment, a module within the access network equipment (e.g., a circuit, chip, or chip system), or a logical node, logical module, or software capable of implementing all or part of the functions of the access network device. In this method, a first communication device measures a reference signal to obtain at least two vectors. The first communication device then processes these at least two vectors based on vector scaling parameters and the correlation between the scaled vectors. Each vector corresponds to a reference signal from N receiving antennas in the same frequency domain unit / the same time-frequency domain unit, where N is an integer greater than or equal to 2. Optionally, different vectors typically correspond to different frequency domain units; that is, one vector corresponds to the reference signal from N receiving antennas in one frequency domain unit, or there is a one-to-one correspondence between vectors and frequency domain units. In the embodiments of this application, the frequency domain unit may be, for example, a subcarrier, a resource block (RB), a precoding resource block group (PRG), or a sub-band. The time domain unit may be, for example, a symbol or a time slot. Optionally, the scaling involved in this application may also be replaced by normalization, etc., without limitation.

[0007] In this embodiment, by normalizing the vector formed by the precoded equivalent channel in the receiving antenna dimension under massive MIMO, and then filtering the correlation law in the frequency domain, the performance of channel estimation is improved. It should be understood that the vector involved in this application refers to a complex vector obtained by demodulating the reference signal received on multiple receiving antennas. More specifically, the first communication device receives a reference signal (e.g., a demodulation reference signal (DMRS)) and performs channel estimation. Each receiving antenna can measure a complex value corresponding to an equivalent channel. All the complex values ​​corresponding to the equivalent channel received on all these receiving antennas can constitute a complex vector (or simply vector) corresponding to the MIMO equivalent channel.

[0008] In one possible implementation, the method further includes:

[0009] The process involves obtaining the vector scaling parameters and the association between the scaled vectors. Optionally, the vector scaling parameters and / or the association between the scaled vectors can be configured. For example, in one possible implementation, obtaining the vector scaling parameters includes receiving information indicating the vector scaling parameters. In this implementation, the vector scaling parameters can be configured for the first communication device via a second communication device, offering greater operability and better meeting practical needs. Another possible implementation involves obtaining the association between the scaled vectors, which includes receiving information indicating the association between the scaled vectors. In this implementation, the association between the scaled vectors can be configured for the first communication device via a second communication device, making it easier to implement and better meeting practical needs.

[0010] In one possible implementation, the vector filtering parameters and / or the correlation between the scaled vectors are predefined. In this implementation, predefining the vector filtering parameters and / or the correlation between the scaled vectors can save signaling overhead.

[0011] In one possible implementation, the vector scaling parameters include one or more of the following: the dimension of the vector scaling, the processing method of the vector scaling, or the magnitude of the vector scaling. The dimension of the vector scaling can be understood as the number of elements in the vector, or the length of the vector, which is typically related to the number of receiving antennas. This implementation defines the parameters included in the vector scaling parameters, which helps to better implement vector filtering.

[0012] In one possible implementation, the dimension of the vector scaling is N, where N is the total number of receiving antennas, or the N receiving antennas belong to the same receiving antenna group (or N can be understood as the number of receiving antennas included in each receiving antenna group). In this implementation, defining the dimension of the vector scaling as the total number of receiving antennas helps reduce the computational complexity of filtering in the first communication device. Defining the dimension of the vector scaling as the number of receiving antennas included in each receiving antenna group allows the first communication device to perform vector filtering based on different antenna groups, thus further improving filtering performance.

[0013] In one possible implementation, the vector scaling process includes scaling the vector based on a measured magnitude, or scaling the vector based on a predefined magnitude or a magnitude configured in the vector scaling parameters. In this implementation, scaling the vector based on a measured magnitude helps reduce indication overhead. Scaling the vector based on a configured or predefined magnitude helps improve the performance of the vector filtering scheme.

[0014] In one possible implementation, the correlation between the scaled vectors includes one or more of the following: a method for measuring the correlation between the scaled vectors, a method for indicating the correlation between the scaled vectors, or a granularity for indicating the correlation between the scaled vectors. This implementation defines the parameters included in the correlation between the scaled vectors, which helps to better achieve vector filtering.

[0015] In one possible implementation, the measurement of the correlation between scaled vectors includes any of the following: the inner product of scaled vectors, the angle between scaled vectors, the distance between scaled vectors, or the radian between scaled vectors. This implementation defines multiple measurement methods for the correlation between scaled vectors, which helps to improve the applicability of the solution.

[0016] In one possible implementation, the indicated method for the scaled inter-vector associations includes matrices, vectors, or functions. In this implementation, using matrices to indicate the scaled inter-vector associations helps improve the accuracy of the association indication. Using matrices to indicate the scaled inter-vector associations also helps reduce signaling overhead. Furthermore, using matrices to indicate the scaled inter-vector associations further helps reduce signaling overhead.

[0017] In one possible implementation, the granularity of the scaled vector association is a flow, a flow group, or all flows; if the granularity of the scaled vector association is a flow, the at least two vectors are vectors corresponding to the same flow; or, if the granularity of the scaled vector association is a flow group, the at least two vectors belong to the same flow group; or, if the granularity of the scaled vector association is all flows, the at least two vectors belong to all flows.

[0018] In this implementation, when the granularity of the indication of the correlation between scaled vectors is a single flow, it helps improve the performance of the vector filtering scheme. When the granularity of the indication of the correlation between scaled vectors is a group of flows, it helps reduce the indication overhead. When the granularity of the indication of the correlation between scaled vectors is all flows, it helps to further reduce the indication overhead.

[0019] In one possible implementation, the method further includes receiving first information, which instructs a first communication device to employ vector filtering. In this implementation, the first communication device can be triggered / instructed to employ vector filtering by a second communication device, offering high flexibility.

[0020] In one possible implementation, the method further includes: sending capability information indicating the capability of the first communication device to support vector filtering. In this implementation, the first communication device can send the capability information indicating support for vector filtering to the second communication device, which is beneficial for the second communication device to decide whether to trigger vector filtering, and offers high operability.

[0021] In one possible implementation, processing the at least two vectors based on the vector scaling parameters and the correlation between the scaled vectors includes:

[0022] Based on the vector scaling parameters, the at least two vectors are scaled respectively to obtain at least two scaled vectors;

[0023] Based on the correlation between the scaled vectors, vector filtering is performed on the at least two scaled vectors to obtain at least two scaled reconstructed vectors;

[0024] Based on the vector scaling parameters, the vector magnitude of the at least two scaled reconstructed vectors is restored to obtain at least two reconstructed vectors.

[0025] In this implementation, the vector is scaled using vector scaling parameters, then the scaled vector is filtered based on the correlation between the scaled vectors, and finally the vector magnitude is recovered based on the vector scaling parameters for at least two scaled reconstructed vectors. This implementation scheme considers the correlation law of the vector in the frequency domain after the receiving antenna dimension is normalized when filtering at the receiving end, which is beneficial to improving the filtering performance and thus helps to improve the performance of the first communication device in channel estimation, such as improving the accuracy of channel estimation.

[0026] In one possible implementation, the method further includes:

[0027] Channel estimation information is determined based on the at least two reconstruction vectors.

[0028] Secondly, this application provides a communication method that can be applied to a second communication device. For example, the second communication device can be a terminal, or a component within the terminal (e.g., a processor, chip, chip system, circuit, or functional module), such as a communication module / processing module within the terminal, or a circuit or chip within the terminal responsible for communication functions (e.g., a modem chip, also known as a baseband chip, or a SoC chip or SIP chip containing a modem core), or a circuit or chip within the terminal responsible for processing functions (e.g., a GPU, AI processor, or ASIC). As another example, the second communication device can also be an access network device, which can be an access network equipment, a module within the access network equipment (e.g., a circuit, chip, or chip system), or a logical node, logical module, or software capable of implementing all or part of the functions of the access network device. In this method, the second communication device determines and transmits a vector scaling parameter and the association relationship between the scaled vectors. This vector scaling parameter and the association relationship between the scaled vectors are used to process the vectors.

[0029] In one possible implementation, the vector scaling parameters include one or more of the following: the dimension of the vector scaling, the processing method of the vector scaling, or the magnitude of the vector scaling.

[0030] In one possible implementation, the dimension of the vector scaling is N, where N is the total number of receiving antennas, or the N receiving antennas belong to the same receiving antenna group.

[0031] In one possible implementation, the vector scaling process includes scaling the vector based on the measured modulus, or scaling the vector based on a predefined modulus or a modulus configured in the vector scaling parameters.

[0032] In one possible implementation, the correlation between the scaled vectors includes one or more of the following: a method for measuring the correlation between the scaled vectors, a method for indicating the correlation between the scaled vectors, or a granularity for indicating the correlation between the scaled vectors.

[0033] In one possible implementation, the measurement of the correlation between the scaled vectors includes any of the following: the inner product between the scaled vectors, the angle between the scaled vectors, the distance between the scaled vectors, or the radian between the scaled vectors.

[0034] In one possible implementation, the indication of the relationship between the scaled vectors includes matrices, vectors, or functions.

[0035] In one possible implementation, the granularity of the scaled vector association is a flow, a flow group, or all flows; if the granularity of the scaled vector association is a flow, the at least two vectors are vectors corresponding to the same flow; or, if the granularity of the scaled vector association is a flow group, the at least two vectors belong to the same flow group; or, if the granularity of the scaled vector association is all flows, the at least two vectors belong to all flows.

[0036] In one possible implementation, the method further includes: sending first information, the first information instructing a first communication device to employ vector filtering.

[0037] In one possible implementation, the method further includes receiving capability information indicating the capability of the first communication device to support vector filtering.

[0038] Thirdly, this application provides a communication device comprising units, modules, or means for implementing any of the methods in the first to second aspects, or any possible implementations of any of the aspects, wherein the modules, units, or means may be implemented by software, by hardware, or by a combination of software and hardware.

[0039] Fourthly, this application provides a communication device including a processor. The processor is configured to cause the communication device to implement the methods shown in any of the first to second aspects, or any possible implementation thereof.

[0040] Optionally, the communication device further includes a transceiver for sending and receiving information.

[0041] Optionally, the communication device further includes a memory storing a computer program; the processor and transceiver are used to invoke the computer program in the memory, causing the communication device to implement the method shown in any of the first or second aspects, or any possible implementation thereof.

[0042] In one possible design, the communication device can be a chip that implements the above method or a device containing a chip.

[0043] Fifthly, this application provides a communication device comprising one or more processors, which implement, via logic circuits or execution code instructions, any of the methods described in the first or second aspects, or any possible implementation thereof.

[0044] Optionally, the communication device further includes an interface circuit for receiving signals from other communication devices outside the communication device and transmitting them to the processor, or sending signals from the processor to other communication devices outside the communication device.

[0045] Optionally, the communication device may further include a memory for storing part or all of the computer programs or instructions necessary to implement the functions involved in the first aspect above.

[0046] The aforementioned communication device may be a terminal, a communication module in a terminal, or a chip in a terminal that is responsible for communication functions, such as a modem chip (also known as a baseband chip) or a SoC or SIP chip that contains a modem module.

[0047] The aforementioned communication device may be an access network device, a module (e.g., a circuit, chip, or chip system) within the access network device, or a logic node, logic module, or software capable of implementing all or part of the functions of the access network device.

[0048] Sixthly, this application provides a computer-readable storage medium storing a computer program or instructions that, when executed by a computer, implement the method shown in any of the first to second aspects, or any possible implementation thereof.

[0049] In a seventh aspect, this application provides a computer program product, including computer program code, which, when read and executed by a computer, causes the computer to perform any of the methods in the first aspect to the second aspect, or any possible implementation thereof.

[0050] Eighthly, this application provides a chip system including at least one processor and an interface, the processor being configured to read and execute a computer program or instructions in a memory, wherein when the computer program or instructions are executed, the chip performs the method as described in any one of the first or second aspects, or the method shown in any possible implementation of either aspect.

[0051] Ninthly, this application provides a communication system that may include a first communication device and a second communication device. The first communication device is used to perform the method shown in the first aspect or any possible implementation thereof. The second communication device is used to perform the method shown in the second aspect or any possible implementation thereof. Attached Figure Description

[0052] Figure 1 is a schematic diagram of the architecture of the communication system used in the embodiments of this application;

[0053] Figure 2 is a schematic diagram of the architecture of the O-RAN system provided in this application;

[0054] Figure 3 is a schematic diagram of the network element function division and protocol layer structure of an O-RAN device provided in this application;

[0055] Figure 4 is a flowchart illustrating the communication method provided in an embodiment of this application;

[0056] Figure 5 is a schematic diagram of the measurement method of the correlation between scaled vectors provided in the embodiments of this application;

[0057] Figure 6 is a schematic diagram of vectors provided in an embodiment of this application;

[0058] Figure 7 is a schematic diagram of the structure of a possible communication device provided in an embodiment of this application;

[0059] Figure 8 is a schematic diagram of the structure of a possible communication device provided in an embodiment of this application;

[0060] Figure 9 is a schematic diagram of the structure of a possible communication device provided in an embodiment of this application. Detailed Implementation

[0061] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings.

[0062] In the description of this application, terms such as "first" and "second" are used only to distinguish different objects, not to describe a specific order. Furthermore, unless otherwise stated, " / " means "or," for example, A / B can mean A or B. "And / or" in this document is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, and B alone. Additionally, "at least one" refers to one or more, and "multiple" refers to two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or multiple items. For example, at least one of a, b, or c can represent: a, b, c; a and b; a and c; b and c; or a and b and c. Where a, b, and c can be single or multiple.

[0063] The terms “comprising” and “having”, and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the steps or units listed, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such process, method, product, or apparatus.

[0064] In this application, the words "exemplary" or "for example" are used to indicate that something is an example, illustration, or illustration. Any embodiment or design described as "exemplary," "for example," or "for example" in this application should not be construed as being more preferred or advantageous than other embodiments or designs. Rather, the use of the words "exemplary," "for example," or "for example" is intended to present the relevant concepts in a specific manner.

[0065] It is understood that in this application, "when," "if," and "if" all refer to the device making a corresponding action under certain objective circumstances, and are not time-limited, nor do they require the device to make a judgment when it is implemented, nor do they imply any other limitations.

[0066] In this application, the use of singular pronouns for elements is intended to indicate "one or more," rather than "one and only one," unless otherwise specified. The terms "system" and "network" in the embodiments of this application are used interchangeably.

[0067] It is understood that in the embodiments of this application, "B corresponding to A" means that there is a correspondence between A and B, and B can be determined based on A. Determining B based on A does not mean that B is determined solely based on A; B can also be determined based on A and / or other information.

[0068] To better understand the embodiments of this application, the system architecture involved in the embodiments of this application will be described first below:

[0069] The technical solutions of the embodiments of this application can be applied to various communication systems, such as: Long Term Evolution (LTE) systems, LTE Frequency Division Duplex (FDD) systems, and LTE Time Division Duplex (TDD) systems. The technical solutions of the embodiments of this application can also be applied to other communication systems, such as Public Land Mobile Network (PLMN) systems, LTE Advanced (LTE-A) systems, the 5th generation (5G) systems, New Radio (NR) systems, Machine-to-Machine (M2M) systems, or other future communication systems, or various other wireless communication systems employing wireless access technologies, all of which can adopt the technical solutions of the embodiments of this application.

[0070] Please refer to Figure 1, which is a schematic diagram of the architecture of the communication system applied in the embodiments of this application. It should be noted that Figure 1 is a possible, non-limiting system schematic diagram. As shown in Figure 1, the communication system 10 includes a radio access network (RAN) 100 and a core network (CN) 200. Optionally, the communication system 10 may also include an Internet 300. RAN 100 includes at least one RAN node (110a and 110b in Figure 1, collectively referred to as 110) and at least one terminal (120a-120j in Figure 1, collectively referred to as 120). RAN 100 may also include other RAN nodes, such as wireless relay devices and / or wireless backhaul devices (not shown in Figure 1). Terminal 120 is wirelessly connected to RAN node 110. RAN node 110 is connected to core network 200 wirelessly or via a wired connection. The core network elements in core network 200 and RAN nodes 110 in RAN 100 can be different physical devices, or they can be the same physical device integrating core network logical functions and radio access network logical functions, or they can be a single physical device integrating some core network element functions and some RAN node 110 functions. Terminals can be interconnected with each other, and RAN nodes 110 can be interconnected with each other via wired or wireless means. Figure 1 is only a schematic diagram. This communication system may also include other network devices, such as wireless relay devices and wireless backhaul devices. Each device may also include different functional units, which are not shown in Figure 1.

[0071] RAN 100 can be a cellular system related to the 3rd Generation Partnership Project (3GPP), such as 4G, 5G mobile communication systems, or future-oriented evolution systems. RAN 100 can also be an open RAN (O-RAN or ORAN), a cloud radio access network (CRAN), or a wireless fidelity (WiFi) system. RAN 100 can also be a communication system that integrates two or more of the above systems.

[0072] RAN node 110, sometimes also referred to as a radio access network device, access network apparatus, RAN entity, or access node, constitutes part of the communication system and is used to help terminals achieve wireless access. Multiple RAN nodes 110 in communication system 10 can be of the same type or different types. In some scenarios, the roles of RAN node 110 and terminal 120 are relative. For example, network element 120i in Figure 1 can be a helicopter or drone, which can be configured as a mobile base station. For terminals 120j accessing RAN 100 through network element 120i, network element 120i is a base station; but for base station 110a, network element 120i is a terminal. RAN node 110 and terminal 120 are sometimes both referred to as communication devices. For example, network elements 110a and 110b in Figure 1 can be understood as communication devices with base station functions, and network elements 120a-120j can be understood as communication devices with terminal functions.

[0073] In one possible scenario, RAN node 110 can be a base station, an evolved NodeB (eNodeB), an access point (AP), a transmission reception point (TRP) or transmit / receive point (TRP), a next-generation NodeB (gNB), a base station in a future mobile communication system, or an access node in a WiFi system. RAN node 110 can be a macro base station (as shown in Figure 1, 110a), a micro base station or indoor station (as shown in Figure 1, 110b), a relay node or donor node, or a radio controller in a CRAN scenario. Optionally, RAN node 110 can also be a server, a wearable device, a vehicle, or in-vehicle equipment. For example, the access network device in vehicle-to-everything (V2X) technology can be a roadside unit (RSU). All or part of the functions of RAN node 110 in this application can also be implemented through software functions running on hardware, or through virtualization functions instantiated on a platform (e.g., a cloud platform). In this application, RAN node 110 can also be a logical node, logical module, or software that can implement all or part of the functions of RAN node 110.

[0074] In another possible scenario, multiple RAN nodes 110 collaborate to assist the terminal in achieving wireless access, with each RAN node 110 implementing a portion of the base station's functions. For example, a RAN node 110 can be a centralized unit (CU), a distributed unit (DU), a CU-control plane (CP), a CU-user plane (UP), or a radio unit (RU), etc. CUs and DUs can be set up separately or included in the same network element, such as a baseband unit (BBU). RUs can be included in radio equipment or radio units, such as remote radio units (RRUs), active antenna units (AAUs), or remote radio heads (RRHs).

[0075] In different systems, CU (or CU-CP and CU-UP), DU, or RU may have different names, but those skilled in the art will understand their meaning. For example, in an ORAN system, CU can also be called O-CU (open CU), DU can also be called O-DU, CU-CP can also be called O-CU-CP, CU-UP can also be called O-CU-UP, and RU can also be called O-RU. For ease of description, this application uses CU, CU-CP, CU-UP, DU, and RU as examples. Any of the units among CU (or CU-CP, CU-UP), DU, and RU in this application can be implemented through software modules, hardware modules, or a combination of software and hardware modules.

[0076] For example, please refer to Figure 2, which is a schematic diagram of the architecture of the O-RAN system provided in this application. Figure 2 is only a schematic diagram, and the O-RAN system may also include other components besides those shown in Figure 2. As shown in Figure 2, the access network device (e.g., it may be an eNB, gNB, or next-generation access network device) communicates with the core network elements in the CN through a backhaul link and communicates with the terminal through the air interface.

[0077] Specifically, the BBU in the access network device communicates with the core network elements in the CN via a backhaul link, and the RU in the access network device communicates with at least one terminal via an air interface. The BBU communicates with at least one RU via a fronthaul link. The BBU and RU may or may not be co-located. The BBU includes at least one CU and at least one DU, which can communicate via at least one midhaul link.

[0078] Figure 3 illustrates a schematic diagram of the network element function division and protocol layer structure of an O-RAN device. In some examples, the CU is a logical node carrying the radio resource control (RRC) layer, service data adaptation protocol (SDAP) layer, packet data convergence protocol (PDCP) layer, and other control functions of the access network device. The CU connects to network nodes such as the core network through interfaces, which can be interfaces such as E2 interfaces. Optionally, the CU can have some of the functions of the core network. The CU (e.g., the PDCP layer and higher layers) connects to the DU (e.g., the RLC layer and lower layers) through interfaces, which can be interfaces such as F1 interfaces. In some examples, these interfaces (e.g., the F1 interface) can provide control plane (C-Plane) and user plane (U-Plane) functions (e.g., interface management, system information management, UE context management, RRC message transmission, etc.). F1AP is the application protocol of the F1 interface, and in some examples, it defines the signaling procedures of F1. The F1 interface supports the control plane F1-C and the user plane F1-U.

[0079] In some examples, the CU can be split into CU-CP (control unit-control plane) and CU-UP (control unit-user plane). CU-CP is a logical node carrying the RRC layer and PDCP-C (control plane part of PDCP) layer, used to implement the CU's control plane functions. CU-CP can interact with network elements in the core network used to implement control plane functions. These network elements in the core network can be access and mobility function (AMF) network elements, such as the access and mobility management function (AMF) in a 5G system. The AMF network element is responsible for mobility management in the mobile network, such as terminal location updates, terminal registration with the network, and terminal handover. CU-UP is a logical node carrying the SDAP layer and PDCP-U (user plane part of PDCP) layer, used to implement the CU's user plane functions. CU-UP can interact with network elements in the core network used to implement user plane functions. These network elements in the core network, such as the user plane function (UPF) in a 5G system, are responsible for data forwarding and receiving in the terminal. The above CU and DU configurations are merely examples; the functions of the CU and DU can be configured as needed. For instance, the CU or DU can be configured to have more protocol layer functions, or only some protocol layer processing functions. For example, some RLC layer functions and protocol layer functions above the RLC layer can be placed in the CU, while the remaining RLC layer functions and protocol layer functions below the RLC layer can be placed in the DU. Furthermore, the functions of the CU or DU can be divided according to service type or other system requirements, such as by latency. Functions that require low latency can be placed in the DU, while functions that do not require low latency can be placed in the CU.

[0080] In some examples, a DU is a logical node that carries the radio link control (RLC) layer, medium access control (or media access control, MAC) layer, higher physical layer (Higher PHY) layer, and other functions. In some examples, a DU can control at least one RU. The DU connects to the RU through interfaces, which can be fronthaul interfaces. In some examples, the Higher PHY layer includes the physical (PHY) layer processing, such as forward error correction (FEC) encoding and decoding, scrambling, modulation, and demodulation.

[0081] In some examples, the RU is a logical node that carries both lower physical layer (PHY) and radio frequency (RF) processing. In some examples, the RU can be a 3GPP transmission reception point (TRP) or remote radio head (RRH) or other similar entity. In some examples, the Low-PHY includes PHY processing functions such as Fast Fourier Transform (FFT), Inverse Fast Fourier Transform (IFFT), digital beamforming, and filtering. The RU communicates with one or more terminals via a wireless link.

[0082] The DU and RU can be co-located or not. The DU and RU exchange control plane and user plane information via a fronthaul link through the Lower-Layer Split CUS-Plane (LLS-CUS) interface. LLS-CUS may include LLS-C and LLS-U interfaces providing the control plane (C-Plane) and user plane (U-Plane), respectively. In some examples, the control plane (C-Plane) refers to real-time control between the DU and RU. The DU and RU exchange management information via an LLS-M interface on the fronthaul link; the management plane (M-Plane) refers to non-real-time management operations between the DU and RU.

[0083] DU and RU can cooperate to implement the functions of the PHY layer. A DU can be connected to one or more RUs. The functions of DU and RU can be configured in various ways depending on the design. For example, a DU can be configured to implement baseband functions, and an RU can be configured to implement mid-RF functions. Another example is that a DU can be configured to implement higher-level functions in the PHY layer, and an RU can be configured to implement lower-level functions in the PHY layer, or to implement both lower-level and RF functions. Higher-level functions in the physical layer can include a portion of the physical layer's functions that are closer to the MAC layer, while lower-level functions in the physical layer can include another portion of the physical layer's functions that are closer to the mid-RF side.

[0084] A terminal is a device or module that connects to the aforementioned communication system and possesses corresponding communication functions. Terminals can also be referred to as terminal equipment, user equipment (UE), user devices, access terminals, user units, user stations, mobile stations, mobile stations (MS), remote stations, remote terminals, mobile devices, user terminals, terminal units, terminal stations, terminal devices, wireless communication equipment, user agents, or user devices, etc. Terminals typically contain communication modules, circuits, or chips that perform the corresponding communication functions. They can also be configured with program instructions for performing these functions. Terminals can be widely used in various scenarios, such as device-to-device (D2D), vehicle-to-everything (V2X) communication, machine-type communication (MTC), the Internet of Things (IoT), virtual reality, augmented reality, industrial control, autonomous driving, telemedicine, smart grids, smart furniture, smart offices, smart wearables, smart transportation, and smart cities. The terminal can be a mobile phone, tablet computer, computer with wireless transceiver function, wearable device, vehicle, drone, helicopter, airplane, ship, robot, robotic arm, smart home device, transportation vehicle with wireless communication function, communication module, roadside unit (RSU) with terminal function, etc. The embodiments of this application do not limit the device form of the terminal.

[0085] For ease of description, the following description uses a base station as an example of RAN node 110. Base stations and terminals can be fixed or mobile. Base stations and terminals can be deployed on land, including indoors or outdoors, handheld or vehicle-mounted; they can also be deployed on water; and they can be deployed on aircraft, balloons, and satellites. The embodiments of this application do not limit the application scenarios of the base stations and terminals.

[0086] The roles of base stations and terminals can be relative. For example, the helicopter or drone 120i in Figure 1 can be configured as a mobile base station. For terminals 120j that access the wireless access network 100 through 120i, terminal 120i is a base station; however, for base station 110a, 120i is a terminal, meaning that 110a and 120i communicate via a wireless air interface protocol. Of course, 110a and 120i can also communicate via a base station-to-base station interface protocol. In this case, relative to 110a, 120i is also a base station. Therefore, both base stations and terminals can be collectively referred to as communication devices. 110a and 110b in Figure 1 can be called communication devices with base station functions, and 120a-120j in Figure 1 can be called communication devices with terminal functions.

[0087] Communication between base stations and terminals, between base stations, and between terminals can be conducted using licensed spectrum, unlicensed spectrum, or both simultaneously. Communication can be conducted using spectrum below 6 GHz, spectrum above 6 GHz, or both simultaneously. The embodiments of this application do not limit the spectrum resources used for wireless communication.

[0088] In the embodiments of this application, the functions of the base station can be executed by modules (such as chips) within the base station, or by a control subsystem that includes base station functions. This control subsystem, including base station functions, can be a control center in the aforementioned application scenarios such as smart grids, industrial control, intelligent transportation, and smart cities. Similarly, the functions of the terminal can be executed by modules (such as chips or modems) within the terminal, or by a device that includes terminal functions.

[0089] In this application, the base station sends downlink signals or downlink information to the terminal, with the downlink information carried on the downlink channel; the terminal sends uplink signals or uplink information to the base station, with the uplink information carried on the uplink channel. To communicate with the base station, the terminal needs to establish a radio connection on a cell controlled by the base station. The cell with which the terminal has established a radio connection is called the terminal's serving cell. When the terminal communicates with this serving cell, it is also susceptible to interference from signals from neighboring cells.

[0090] In this application, "sending information" can be understood as one device sending information to another device, or it can also be understood as one logical module within a device sending information to another logical module. For example, "base station sending information" can be understood as the base station sending information to another device (such as a terminal), or it can be understood as logical module 1 in the base station sending information to logical module 2 in the base station.

[0091] In this application, "receiving information" can be understood as one device receiving information from another device, or it can also be understood as a logical module within a device receiving information from another logical module. For example, "base station receiving information" can be understood as the base station receiving information from another device (such as a terminal), or it can be understood as logical module 1 in the base station receiving information from logical module 2 in the base station.

[0092] The communication between different devices involved in this application can refer to direct communication between different devices (i.e., without the need for relaying or forwarding by other devices), or communication between different devices through other devices (i.e., requiring relaying or forwarding by other devices), or communication between a functional unit within a device and other devices through another functional unit. In other words, "sending information to… (e.g., a terminal)" or the relevant illustrations in the accompanying drawings can be understood as the destination of the information being the terminal. This can include sending information directly or indirectly to the terminal. "Receiving information from… (e.g., a terminal)" or "receiving information from… (e.g., a terminal)" or "receiving information sent (e.g., by a terminal)" or the relevant illustrations in the accompanying drawings can be understood as the source of the information being the terminal. This can include receiving information directly or indirectly from the terminal. Information may undergo necessary processing between the source and destination, such as format changes, analog-to-digital conversion, amplification, filtering, etc., but the destination can understand the valid information from the source. Similar expressions in this application can be understood in a similar way, and will not be elaborated further here.

[0093] To facilitate understanding of the embodiments of this application, some knowledge / terms used in the solutions of this application are introduced below. It should be noted that these explanations are for the purpose of making the embodiments of this application easier to understand, and should not be regarded as limiting the scope of protection claimed by this application.

[0094] 1. Reference signal

[0095] Reference signals can be used for channel measurement, channel estimation, or beam quality monitoring. According to LTE or NR protocols, uplink reference signals may include, for example, a sounding reference signal (SRS), a physical uplink control channel (PUCCH)-demodulation reference signal (DMRS), a physical uplink share channel (PUSCH)-demodulation reference signal (PUSCH-DMRS), a phase noise tracking reference signal (PTRS), an uplink positioning reference signal, etc.; downlink reference signals may include, for example, a synchronization signal block (SSB), a physical downlink control channel (PDCCH)-demodulation reference signal (PDCCH-DMRS), a physical downlink share channel (PDSCH)-demodulation reference signal (PDSCH-DMRS), PTRS, a channel state information reference signal (CSI-RS), a cell reference signal (CRS), and a tracking reference signal. downlink positioning reference signal (TRS), downlink positioning reference signal (positioning RS), etc.

[0096] The reference signal in this embodiment is mainly used for channel estimation. For example, it can refer to the CSI-RS used in downlink channel estimation, the SRS used in uplink channel estimation, or other reference signals that can be used for channel estimation, such as DMRS. For ease of understanding, the following text mainly uses DMRS as an example for illustrative explanation.

[0097] 2. Receiving antenna

[0098] A receiving antenna can be understood as the antenna port of a communication device (such as a terminal or base station). Optionally, a receiving antenna is sometimes simply referred to as a receiving antenna. An antenna port is a logical concept; there is no direct correspondence between an antenna port and a physical antenna. An antenna port is usually associated with a reference signal, and its meaning can be understood as a transmit / receive interface on the channel through which the reference signal passes.

[0099] 3. Receiving antenna grouping

[0100] Antenna grouping refers to dividing the receiving antennas of a communication device into multiple groups according to different grouping methods. Each receiving antenna group includes multiple receiving antennas. For example, when the receiving antennas are single-polarized antennas, they can be grouped according to their polarization, such as grouping all horizontally polarized receiving antennas into one group and all vertically polarized receiving antennas into another. Alternatively, they can be grouped according to their arrangement. For instance, if there are 16 receiving antennas arranged in a 4×4 pattern, they can be grouped by rows, such as grouping the four receiving antennas in each row into one group, thus obtaining four receiving antenna groups. Or they can be grouped by columns, such as grouping the four receiving antennas in each column into one group, thus also obtaining four receiving antenna groups. Optionally, antenna grouping can also be simply described as antenna grouping.

[0101] 4. Vector

[0102] The vector involved in this application embodiment can be understood as a quantity that has both magnitude and direction, sometimes also called a vector. To distinguish it from the "vector" in "the indication method of the correlation between scaled vectors includes matrices, vectors, or functions" that appears later, it will be described in the following text as a vector. Specifically, in this application, a vector refers to a complex vector obtained after demodulating the reference signals received on multiple receiving antennas. More specifically, by performing channel estimation through receiving DMRS, a complex value corresponding to an equivalent channel can be measured on each receiving antenna. All the complex values ​​corresponding to the equivalent channel received on all these receiving antennas can constitute a complex vector corresponding to the MIMO equivalent channel (simply referred to as a vector in this application embodiment).

[0103] 5. Vector scaling

[0104] Vector scaling can be understood as multiplying each element of a vector by the same scaling factor. This scaling factor can be a number greater than 1, or it can be a number greater than 0 and less than 1. Generally, a scaling factor greater than 1 indicates vector magnification, while a scaling factor greater than 0 and less than 1 indicates vector shrinkage. Vector normalization can be understood as a special case of vector scaling. For vector normalization, the scaling factor is a number greater than 0 and less than 1. Alternatively, vector normalization can be understood as multiplying each element of a vector by the reciprocal of its magnitude. In the embodiments of this application, vector magnitude recovery is the inverse transformation relative to vector normalization, and its corresponding scaling factor is a number greater than 1. Specifically, vector magnitude recovery refers to multiplying each element of the scaled reconstructed vector by its magnitude.

[0105] Currently, a typical implementation of channel estimation techniques uses the Wiener filter, which is mainly based on SISO frequency domain channel modeling and filtering. However, in multiple-input multiple-output (MIMO) scenarios, modeling and filtering for each receiving antenna separately not only affects filtering efficiency but also fails to consider the frequency domain characteristics of the MIMO channel, thus hindering the improvement of channel estimation accuracy.

[0106] It should be noted that in the description of this application, "instruction" can include direct and indirect instructions, as well as explicit and implicit instructions. The information indicated by a certain piece of information (such as the vector scaling parameter instruction information described below) is called the information to be instructed. In specific implementations, there are many ways to indicate the information to be indicated. For example, the information to be indicated can be directly indicated, where the information to be indicated itself or its index is used. Alternatively, the information to be indicated can be indirectly indicated by indicating other information, where there is a correlation between the other information and the information to be indicated. Another example is that only a portion of the information to be indicated can be indicated, while the other portions are known, pre-agreed upon, or deducible. Furthermore, the instruction of specific information can be achieved by using a pre-agreed (e.g., protocol-defined) arrangement of various pieces of information, thereby reducing the instruction overhead to some extent.

[0107] The data processing method and apparatus provided in this application will be further described below with reference to the accompanying drawings. It is understood that this application uses a first communication device and a second communication device as examples of the execution entities in the interactive illustration. For instance, the first communication device can be an access network device or a terminal, and the second communication device can also be an access network device or a terminal, but this application does not limit the execution entities in the interactive illustration. For example, the method executed by the access network device in this application can be specifically implemented by the access network equipment or modules (e.g., circuits, chips, or chip systems) within the access network equipment, or by logic nodes, logic modules, or software that can implement all or part of the functions of the access network equipment; the method executed by the terminal in this application can also be implemented by the communication / processing module in the terminal or by circuits or chips (such as modem chips (also known as baseband chips), or SoC chips / SIP chips containing modem cores, or GPU / AI processors / ASICs) in the terminal responsible for communication / processing functions.

[0108] Please refer to Figure 4, which is a schematic flowchart of the communication method provided in an embodiment of this application. It should be understood that Figure 4 is a schematic flowchart of an embodiment of the method of this application, illustrating detailed communication steps or operations. However, these steps or operations are merely examples, and other operations or variations of the various operations shown in Figure 4 can also be performed in the embodiments of this application. Furthermore, the steps in Figure 4 may be performed in a different order than that presented in Figure 4, and it is not necessary to perform all the operations in Figure 4. As shown in Figure 4, the communication method may include the following steps:

[0109] S401, the first communication device sends capability information to the second communication device. Correspondingly, the second communication device receives the capability information from the first communication device.

[0110] Step S401 is optional. This capability information indicates whether the first communication device supports vector filtering, or it can be said that this capability information indicates whether the first communication device has the capability to perform vector filtering. It should be understood that when the first communication device does not support vector filtering, it will not be able to perform vector filtering based on the method proposed in this application. Therefore, the embodiments of this application will be illustrated later primarily with the first communication device possessing the capability to perform vector filtering.

[0111] Optionally, the determination of the capability of the first communication device can be as follows: if the first communication device reports capability information, it indicates that the first communication device supports the capability; if the first communication device does not report capability information, it indicates that the first communication device does not support the capability. That is, whether or not the first communication device reports capability information indicates whether the first communication device supports the corresponding capability. Alternatively, if the first communication device reports support for the capability, it indicates that the first communication device supports the capability; if the first communication device reports non-support for the capability, it indicates that the first communication device does not support the capability. That is, whether or not it supports a capability is indicated by reporting support or non-support for a particular capability. Alternatively, if the first communication device supports certain capabilities, then the first communication device must also support another capability; that is, even if the first communication device does not report capability information corresponding to a certain capability, it still indicates that the first communication device supports that capability. This application does not impose any limitations.

[0112] Optionally, the capability information sent by the first communication device can directly indicate that the first communication device has the capability of vector filtering. For example, a new bit can be added to the field used to carry the capability information supported by the first communication device. When the value of the new bit is 1, it indicates that the first communication device has the capability of vector filtering. When the value of the new bit is 0, it indicates that the first communication device does not have the capability of vector filtering.

[0113] Optionally, the capability information sent by the first communication device can also indirectly indicate that the first communication device has vector filtering capabilities. For example, the capability information sent by the first communication device may include one or more of the following: the number of receiving antennas supported by the first communication device, or the number of supported antenna ports, or the supported frequency domain bandwidth and pilot number, or the supported vector scaling dimension, or the supported vector scaling processing method, or the supported vector scaling magnitude, or the supported scaling inter-vector correlation (or metric relationship) measurement method, or the supported scaling inter-vector correlation indication method, or the supported scaling inter-vector correlation indication granularity, etc. Generally speaking, when the number of receiving antennas supported by the first communication device increases, for example, when the number of receiving antennas supported by the first communication device is greater than or equal to the receiving antenna number threshold, the vector pattern of the receiving antenna dimension is usually more obvious, and the corresponding computational load is also greater. Therefore, the first communication device can indirectly indicate its vector filtering capability by sending the number of its supported receiving antennas to the second communication device. For example, when the number of antenna ports supported by the first communication device is greater than or equal to the port number threshold, the corresponding computational load is also greater. Therefore, the first communication device can indirectly indicate its vector filtering capability by sending the number of ports it supports to the second communication device. Similarly, when the frequency domain bandwidth supported by the first communication device is too large (e.g., greater than the bandwidth threshold) and the number of pilot signals is too large (e.g., greater than the pilot number threshold), the corresponding computational load is also greater. Therefore, the first communication device can indirectly indicate its vector filtering capability by sending the frequency domain bandwidth and pilot number it supports to the second communication device. Other examples are similar and will not be elaborated upon here.

[0114] S402, the second communication device sends first information to the first communication device. Correspondingly, the first communication device receives the first information from the second communication device.

[0115] Step S402 is optional. The first information indicates whether the first communication device uses vector filtering. Generally, when the first information indicates that the first communication device uses vector filtering, the first communication device can perform vector filtering based on the method proposed in this application. When the first information indicates that the first communication device does not use vector filtering, or when the first communication device does not support vector filtering capabilities, the first communication device can perform filtering based on traditional filtering methods, such as scalar Wiener filtering. Optionally, the second communication device can indicate whether the first communication device uses a vector filtering method based on the capability information sent by the first communication device. In this embodiment, the example of the first information indicating that the first communication device uses vector filtering is used is mainly used for illustrative explanation.

[0116] Optionally, the first information may be carried in an RRC message, a medium access control element (MAC CE), or downlink control information (DCI), etc., without limitation.

[0117] Optionally, the execution order of steps S401 and S402 is not limited in the embodiments of this application. For example, step S401 can be executed before step S402, or step S401 can be executed after step S402.

[0118] S403, The first communication device acquires the vector scaling parameters and the correlation between the scaled vectors.

[0119] In one possible implementation, the second communication device can send information indicating vector scaling parameters to the first communication device. That is, the first communication device acquiring the vector scaling parameters can be understood as the first communication device receiving indication information about the vector scaling parameters from the second communication device. Optionally, besides the second communication device configuring the vector scaling parameters for the first communication device, the vector scaling parameters can also be predefined, such as those predefined by the protocol. This application does not limit this.

[0120] In one possible implementation, the second communication device can send information indicating the association relationship between scaled vectors to the first communication device. That is, the first communication device acquiring the association relationship between scaled vectors can be understood as the first communication device receiving indication information about the association relationship between scaled vectors from the second communication device. Optionally, besides the second communication device configuring the association relationship between scaled vectors for the first communication device, the association relationship between scaled vectors can also be predefined, such as that predefined by the protocol. This application does not limit this.

[0121] Optionally, when both the vector scaling parameters and the association relationships between scaled vectors are configured by the second communication device for the first communication device, the indication information of the vector scaling parameters and the indication information of the association relationships between scaled vectors can be carried in the same message, or they can be carried in different messages; this application does not limit this. Optionally, when the first communication device is a terminal, the access network device (here, the access network device is the second communication device) can configure the vector scaling parameters or the association relationships between scaled vectors for the terminal. When the first communication device is an access network device, the core network element or the terminal can configure the vector scaling parameters or the association relationships between scaled vectors for the access network device (here, the core network element or the terminal is the second communication device); this application does not limit this.

[0122] The vector scaling parameter in this embodiment can also be understood as a vector normalization parameter. Optionally, the vector scaling parameter includes one or more of the following: the dimension of vector scaling, the processing method of vector scaling, or the magnitude of vector scaling. The dimension of vector scaling can be understood as the number of elements contained in the vector, or the length of the vector, which is usually related to the number of receiving antennas. For example, if the dimension of vector scaling is N, N can be the total number of receiving antennas, or N can also be the number of receiving antennas included in each receiving antenna group (or understood as the above N receiving antennas belonging to the same receiving antenna group). In this embodiment, N is mainly used as the example of the total number of receiving antennas for understanding.

[0123] For example, vector scaling can be performed by scaling the vector based on a magnitude obtained from a measurement reference signal, or by scaling the vector based on a predefined magnitude or a magnitude configured in vector scaling parameters. Here, the magnitude obtained from the measurement reference signal can also be simply described as the measured magnitude, which can be understood as a norm of the measured vector, such as a 1-norm, 2-norm, F-norm, etc. The configured magnitude can be, for example, the magnitude included in the vector scaling parameters sent by the second communication device to the first communication device. The predefined magnitude can be, for example, a magnitude predefined by the protocol. This application embodiment mainly uses scaling the vector based on a measured magnitude as an example for illustrative purposes. Optionally, the magnitude described in this application embodiment can also be described as the magnitude used in the vector scaling process, or the vector scaling magnitude.

[0124] Optionally, the correlation between scaled vectors may include one or more of the following: the method of measuring the correlation between scaled vectors, the method of indicating the correlation between scaled vectors, or the granularity of indicating the correlation between scaled vectors.

[0125] For example, the measurement of the correlation between scaled vectors can include any of the following: the inner product of scaled vectors, the angle between scaled vectors, the distance between scaled vectors, or the radians between scaled vectors. Optionally, the inner product of scaled vectors can also be called the correlation between scaled vectors, or the dot product between scaled vectors, or the scalar product between scaled vectors. For example, taking vectors X and Y as an example, assuming vector X = [x1, x2, x3, x4] and vector Y = [y1, y2, y3, y4], then the inner product of vectors X and Y, X·Y = x1y1 + x2y2 + x3y3 + x4y4. Optionally, the angle between scaled vectors can also be called the included angle between scaled vectors. Optionally, the distance between scaled vectors can be, for example, the Euclidean distance between scaled vectors. Optionally, the radians between scaled vectors can be, for example, the spherical distance between scaled vectors.

[0126] For example, please refer to Figure 5, which is a schematic diagram of the measurement method of the relationship between scaled vectors provided in the embodiment of this application. As shown in Figure 5, taking vector 0 and vector 1 as examples, it is assumed that vector 0 is scaled to become scaled vector 0, and vector 1 is scaled to become scaled vector 1. The angle between the scaled vectors can be as shown in Figure 5(a), the distance between the scaled vectors can be as shown in Figure 5(b), or the radian between the scaled vectors can be as shown in Figure 5(c).

[0127] For example, the indication of the relationship between scaled vectors can be a matrix, a vector, or a function.

[0128] Optionally, taking the dot product as an example to measure the relationship between scaled vectors, when the indicator of the relationship between scaled vectors is a matrix, the matrix can include the relationship between the dot products of each vector and each of the other vectors. For example, taking four vectors, namely vector 0, vector 1, vector 2, and vector 3, the relationship between the dot products of these four vectors can be represented by a 4×4 matrix, as shown below:

[0129] Among them, the above R 00 The above R represents the relationship between the inner products of vectors 0 and 0. 01 The above R represents the relationship between the inner product of vector 0 and vector 1. 02 The above R represents the relationship between the inner product of vectors 0 and 2. 03 This represents the relationship between the inner product of vectors 0 and 3; the above R... 10 The above R represents the relationship between the inner product of vector 1 and vector 0. 11 The above R represents the relationship between the inner products of vectors 1 and 1. 12 The above R represents the relationship between the inner product of vector 1 and vector 2. 13 This represents the relationship between the inner product of vector 1 and vector 3; the above R 20 The above R represents the relationship between the inner product of vector 2 and vector 0. 21 The above R represents the relationship between the inner product of vector 2 and vector 1. 22 The above R represents the relationship between the inner products of vectors 2 and 2. 23 This represents the relationship between the inner product of vectors 2 and 3; the above R... 30 The above R represents the relationship between the inner product of vector 3 and vector 0. 31 The above R represents the relationship between the inner product of vector 3 and vector 1. 32 The above R represents the relationship between the inner product of vector 3 and vector 2. 33This represents the relationship between the inner products of vectors 3 and 3. Generally speaking, R... 00 =R 11 =R 22 =R 33 =1,R 01 =R 10 R 02 =R 20 R 03 =R 30 R 12 =R 21 R 13 =R 31 R 23 =R 32 .

[0130] Optionally, taking the inner product as the metric for the correlation between scaled vectors, when the indicator of the correlation between scaled vectors is a vector, each value in the vector can represent the relationship of the inner product between vectors at different frequency domain intervals. For example, taking four vectors as an example, these four vectors are vector 0, vector 1, vector 2, and vector 3, where the frequency domain interval between any two adjacent vectors in vectors 0, 1, 2, and 3 is the same. Then the correlation of the inner product between these four vectors can be represented by a vector, for example, this vector is [R]. 01 R 02 R 03 ], where R 01 R represents the inner product of vector 0 and vector 1 (that is, the inner product of two vectors with a frequency domain spacing of "1 unit interval"). 02 R represents the inner product of vectors 0 and 2 (i.e., the inner product of two vectors with a frequency domain spacing of "2 units"). 03 This represents the inner product of vectors 0 and 3 (i.e., the inner product of two vectors with a frequency domain spacing of "3 units"). For example, this vector can also be [R]. 12 R 13 R 03 ], where R 12 R represents the inner product of vector 1 and vector 2 (that is, the inner product of two vectors with a frequency domain spacing of "1 unit interval"). 13 R represents the inner product of vector 1 and vector 3 (that is, the inner product of two vectors with a frequency domain spacing of "2 units"). 03 This represents the inner product of vectors 0 and 3 (i.e., the inner product of two vectors with a frequency domain spacing of "3 units"). The reason this vector representation can be used is that when vectors 0, 1, 2, and 3 are uniformly distributed in the frequency domain, R can be considered... 01 R 12 , and R 23 R is roughly the same02 and R 13 Since they are roughly the same, in order to save transmission overhead, the correlation between the inner product of two vectors with the same frequency domain spacing can be represented by a single value.

[0131] Optionally, taking the inner product as an example to measure the correlation between scaled vectors, when the indicator of the correlation between scaled vectors is a function, this function can be a function with the frequency domain interval as the independent variable, which can be used to represent the relationship of the inner product between vectors under different frequency domain intervals. For example, again taking four vectors as an example, and these four vectors are vector 0, vector 1, vector 2, and vector 3, then the correlation between these four vectors can be represented by a function, as shown below: Let this function be f(x), then the inner product relationship between vector 0 and vector 1 can be understood as f(x) 01 ), here x 01 The interval between the frequency domain cells containing vectors 0 and 1 is represented by f(x). The inner product relationship between vectors 0 and 2 can be understood as f(x) 02 ), here x 02 The interval between the frequency domain units containing vectors 0 and 2 is not listed here.

[0132] For ease of understanding, the embodiments of this application are mainly illustrated using a matrix as a representation of the relationship between scaled vectors.

[0133] For example, the granularity of the indication of the scaling vector association can be a single flow, a group of flows, or all flows. Specifically, when the granularity of the indication of the scaling vector association is a single flow (or a single stream), the at least two vectors acquired by the first communication device can be vectors corresponding to the same flow. When the granularity of the indication of the scaling vector association is a group of flows (or a partial flow), the at least two vectors acquired by the first communication device belong to the same group of flows. When the granularity of the indication of the scaling vector association is all flows (or a common flow), the at least two vectors acquired by the first communication device belong to all flows. This application embodiment is primarily understood with the indication granularity of the scaling vector association being all flows.

[0134] Optionally, the streams involved in this application refer to independent data streams transmitted simultaneously through multiple antennas. Each stream can be viewed as an independent channel, and each channel can carry different data. The process of obtaining a stream can be illustrated by the following example:

[0135] (1) Channel estimation: The base station sends CSI-RS, and the UE measures CSI-RS accordingly and calculates the channel matrix H.

[0136] (2) Rank selection: The UE analyzes the channel matrix H. Assuming that the rank of the channel matrix is ​​3, the UE reports the rank indicator (RI) = 3 to the base station through the CSI feedback mechanism.

[0137] (3) Precoding matrix selection: The UE reports a precoding matrix indicator (PMI) to the base station through the CSI feedback mechanism, indicating the optimal precoding matrix. Accordingly, the base station receives the PMI and then selects a suitable precoding matrix based on the PMI.

[0138] (4) Data transmission: The base station generates three independent data streams and precodes these three data streams using a selected precoding matrix. The data streams are then mapped onto four antennas. The base station simultaneously transmits the three precoded data streams through these four antennas. Correspondingly, the UE receives the three data streams through the four antennas and decodes them using the corresponding decoding matrix to recover the original data.

[0139] S404. The first communication device measures the reference signal and obtains at least two vectors.

[0140] In one possible implementation, the first communication device measuring the reference signal and obtaining at least two vectors can be understood as follows: the first communication device receives / measures the reference signal (e.g., DMRS) and performs channel estimation (e.g., channel estimation for pilot positions) on at least two different frequency domain units. Each receiving antenna can measure a complex value corresponding to an equivalent channel. All the complex values ​​corresponding to the equivalent channel received on these receiving antennas can constitute a complex vector (or simply vector) corresponding to a MIMO equivalent channel. As can be seen from the method of vector acquisition, the elements contained in the vector in this embodiment are complex values ​​(or simply complex numbers). Generally speaking, a number of the form a + bi (where a and b are both real numbers) is called a complex number, where a is the real part, b is the imaginary part, and i is the imaginary unit. Complex numbers are usually represented by z, i.e., z = a + bi. When the imaginary part b = 0, z is a real number; when the imaginary part b ≠ 0 and the real part a = 0, z is often called a purely imaginary number. For ease of description, when giving specific examples of the size of the elements contained in a vector in the following text, we will use z as a real number for illustrative purposes.

[0141] In this context, each vector corresponds to a reference signal from N receiving antennas in the same frequency domain unit, or it can be understood as a vector corresponding to a reference signal transmitted through multiple antennas in one frequency domain unit, where N is an integer greater than or equal to 2. Optionally, the statement that each vector corresponds to a reference signal from N receiving antennas in the same frequency domain unit can also be understood as: each vector corresponds to a reference signal from N receiving antennas in the same time-frequency domain unit. Exemplarily, the frequency domain unit involved in this application embodiment can be a subcarrier, or an RB, or a PRG, or a sub-band, etc., without limitation. Exemplarily, the time domain unit involved in this application embodiment can be a symbol, such as an orthogonal frequency division multiplexing (OFDM) symbol, or a time domain unit can also be a slot, etc., without limitation. For ease of understanding, the following text will mainly use subcarriers as the frequency domain unit and OFDM symbols as the time domain unit for illustrative purposes.

[0142] Optionally, a vector corresponding to the reference signal of N receiving antennas in the same frequency domain unit / time-frequency domain unit can be understood as follows: the N elements included in a vector are the information of the reference signal received by the N receiving antennas in the same frequency domain unit / time-frequency domain unit. Or, more specifically, the vector is the MIMO equivalent channel (i.e., a complex vector) formed by a certain flow on all receiving antennas by the first communication device through receiving reference signals (e.g., DMRS). Optionally, the frequency domain units / time-frequency domain units corresponding to different vectors are usually different, or in other words, a vector corresponds to the reference signal of N receiving antennas in one frequency domain unit / time-frequency domain unit, or in other words, there is a one-to-one correspondence between the vector and the frequency domain unit / time-frequency domain unit.

[0143] Generally, different vectors correspond to different frequency domain units / time-frequency domain units. For example, please refer to Figure 6, which is a schematic diagram of vectors provided in an embodiment of this application. As shown in Figure 6, taking N=4, and receiving antennas 0, 1, 2, and 3 respectively, as an example, vector 0 corresponds to the reference signal received by these four receiving antennas on symbol 0 and subcarrier 0, vector 1 corresponds to the reference signal received by these four receiving antennas on symbol 0 and subcarrier 2, vector 2 corresponds to the reference signal received by these four receiving antennas on symbol 0 and subcarrier 4, vector 3 corresponds to the reference signal received by these four receiving antennas on symbol 0 and subcarrier 6, vector 4 corresponds to the reference signal received by these four receiving antennas on symbol 0 and subcarrier 8, and vector 5 corresponds to the reference signal received by these four receiving antennas on symbol 0 and subcarrier 10.

[0144] S405, The first communication device processes at least two vectors based on vector scaling parameters and the correlation between the scaled vectors.

[0145] Specifically, the first communication device can scale at least two vectors based on vector scaling parameters to obtain at least two scaled vectors. Then, based on the correlation between the scaled vectors, it performs vector filtering on the at least two scaled vectors to obtain at least two scaled reconstructed vectors. Finally, it performs vector magnitude recovery on the at least two scaled reconstructed vectors based on the vector scaling parameters to obtain at least two reconstructed vectors. Specifically, these at least two reconstructed vectors represent the filtered MIMO equivalent channels in the two frequency domain units. Optionally, the first communication device can further determine channel estimation information based on these at least two reconstructed vectors. For example, the first communication device can perform channel estimation at non-pilot positions based on these at least two reconstructed vectors to obtain complete channel estimation information, or in other words, the complete channel estimation information includes channel estimation information at pilot positions (e.g., the aforementioned at least two reconstructed vectors) and channel estimation information at non-pilot positions. Optionally, even further, the first communication device can process communication data from the second communication device based on the channel estimation information.

[0146] Alternatively, the scaled vector can also be called a normalized vector or a unit vector, etc., without limitation.

[0147] The following sections elaborate on ① how to scale at least two vectors based on vector scaling parameters to obtain at least two scaled vectors, ② how to perform vector filtering on at least two scaled vectors based on the correlation between the scaled vectors to obtain at least two scaled reconstructed vectors (or filtered scaled vectors), and ③ how to recover the vector magnitude of at least two scaled reconstructed vectors based on vector scaling parameters to obtain at least two reconstructed vectors.

[0148] Regarding ①, in one possible implementation 1.1, assuming the vector scaling dimension in the vector scaling parameters is 4 (e.g., the total number of receiving antennas is 4), and the number of vectors is 3, for example, these 3 vectors are vector 0, vector 1, and vector 2, and the vector scaling process is based on scaling the vectors according to the measured magnitude, assuming the original (here, original means without noise interference) vector 0 = [1, 2, 0, -2], vector 1 = [2, 2, -2, -2], and vector 2 = [2, 1, -2, 0], after transmission through the channel, due to noise interference and other factors, the vectors obtained by the terminal's DMRS measurement have changed. For example, the measured noisy vector 0 = [1, 2, -1, -2], therefore, the measured magnitude of vector 0 is... The measured noisy vector 1 = [2, 2, -2, -1], therefore the magnitude of the measured vector 1 is The measured noisy vector 2 = [2, 1, -2, -1], therefore the magnitude of the measured vector 2 is Normalizing the vector based on the measured modulus yields a scaled vector. Scaled vector Scaled vector In this example, the scaling factor of the measured vector 0 is... The scaling factor for vector 1 is The scaling factor for vector 2 is It should be understood that implementing the method of scaling vectors based on the measured modulus in 1.1 helps to reduce indication overhead.

[0149] Regarding ①, in another possible implementation 1.2, the vector scaling dimension included in the vector scaling parameters is 4 (e.g., the total number of receiving antennas is 4), and the number of vectors is 3. For example, these 3 vectors are vector 0, vector 1, and vector 2, and the vector scaling method is to scale the vectors based on the configured magnitude. Assuming the original vector 0 = [1, 2, 0, -2], vector 1 = [2, 2, -2, -2], and vector 2 = [2, 1, -2, 0], then the magnitude of vector 0 is... The magnitude of vector 1 is The magnitude of vector 2 is The modulus 3, 4, 3 can be the modulus configured by the second communication device for the first communication device. For example, the vector scaling parameters sent by the second communication device to the first communication device carry the modulus 3, 4, 3 corresponding to vector 0, vector 1, and vector 2, respectively. It is also assumed that after transmission through the channel, due to factors such as noise interference, the noisy vector 0 obtained by the terminal measurement DMRS is [1, 2, -1, -2], the noisy vector 1 is [2, 2, -2, -1], and the noisy vector 2 is [2, 1, -2, -1]. Normalizing the vectors using the indicated vector magnitude yields scaled vectors 0 = [1 / 3, 2 / 3, -1 / 3, -2 / 3], 1 = [2 / 4, 2 / 4, -2 / 4, -1 / 4], and 2 = [2 / 3, 1 / 3, -2 / 3, -1 / 3]. In this example, the scaling factor for vector 0 is configured as 1 / 3, for vector 1 as 1 / 4, and for vector 2 as 1 / 3. It should be understood that implementing this method of scaling vectors based on a configured or predefined magnitude, as described in section 1.2, helps improve the performance of vector filtering schemes.

[0150] For ease of description, the following text will mainly use implementation 1.1 as an example for illustrative purposes.

[0151] Regarding ②, in one possible implementation, assuming the correlation between scaled vectors is measured by their inner product, taking the original vectors 0 = [1,2,0,﹣2], 1 = [2,2,﹣2,﹣2], and 2 = [2,1,﹣2,0] as an example, the inner product of scaled vectors 0 and 1 is: (1 / 3)*(1 / 2)+(2 / 3)*(1 / 2)+0*(﹣1 / 2). +(﹣2 / 3)*(﹣1 / 2)=5 / 6, the dot product of vector 0 and vector 2 after scaling is: (1 / 3)*(2 / 3)+(2 / 3)*(1 / 3)+0*(﹣2 / 3)+(﹣2 / 3)*0=4 / 9, the dot product of vector 1 and vector 2 after scaling is: (1 / 2)*(2 / 3)+(1 / 2)*(1 / 3)+(﹣1 / 2)*(﹣2 / 3)+(﹣1 / 2)*0=5 / 6. Assuming the second communication device sends an indication of the correlation between the scaled vectors in the form of a matrix, then this matrix is: The matrix R can be understood as a noise-free, scaled correlation matrix of inner products between vectors, or an ideal, scaled correlation matrix of inner products between vectors, which can be configured / indicated by the second communication device to the first communication device. Further assume that the first communication device measures the DMRS and performs scaling to obtain a scaled noisy vector. Scaling with noisy vector Scaling with noisy vector The inner product matrix between these noisy scaled vectors is obviously not equal to the inner product matrix indicated by the second communication device. Therefore, after performing vector filtering on the scaled noisy vector 0, scaled noisy vector 1 and scaled noisy vector 2 according to the (ideal, noise-free) correlation matrix R between the scaled vectors indicated by the second communication device, we can obtain the scaled reconstructed vector 0 = [1 / 3, 2 / 3, 0, -2 / 3], scaled reconstructed vector 1 = [1 / 2, 1 / 2, -1 / 2, -1 / 2], and scaled reconstructed vector 2 = [2 / 3, 1 / 3, -2 / 3, 0].

[0152] Regarding ③, in one possible implementation, assume that the scaled reconstructed vectors obtained after filtering in ② are: 0 = [1 / 3, 2 / 3, 0, -2 / 3], 1 = [1 / 2, 1 / 2, -1 / 2, -1 / 2], and 2 = [2 / 3, 1 / 3, -2 / 3, 0]. Then, the scaled reconstructed vectors are restored to their original magnitudes based on the configured / indicated magnitudes. For example, if the magnitude of vector 0 is 3, the magnitude of vector 1 is 4, and the magnitude of vector 2 is 3, then the restored reconstructed vectors are: 0 = [1, 2, 0, -2], 1 = [2, 2, -2, -2], and 2 = [2, 1, -2, 0].

[0153] In this embodiment, filtering is performed by normalizing the vector formed by the precoded equivalent channel in the receiving antenna dimension under large-scale MIMO and then filtering it in the frequency domain, which is beneficial to improve the performance of channel estimation.

[0154] Optionally, the embodiments shown in Figure 4 above can also be applied to O-RAN scenarios. It should be understood that in O-RAN scenarios, the communication devices belonging to the access network devices in Figure 4 can be replaced by CU (e.g., CU-CP or CU-UP) or DU or RU, etc.

[0155] The communication device provided in this application will now be described in detail with reference to Figures 7 to 9.

[0156] It is understood that, in order to achieve the functions in the above embodiments, the communication device includes hardware structures and / or software modules corresponding to each function. Those skilled in the art should readily recognize that, based on the units and method steps described in conjunction with the embodiments disclosed in this application, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed by hardware or by computer software driving hardware depends on the specific application scenario and design constraints of the technical solution.

[0157] Figures 7 and 9 are schematic diagrams of possible communication devices provided in embodiments of this application. These communication devices can be used to implement the functions of the first or second communication device in the above method embodiments, and thus can also achieve the beneficial effects of the above method embodiments. Here, the first and second communication devices are collectively referred to as communication devices. In the embodiments of this application, the communication device can be one of the terminals 120a-120j shown in Figure 1, or it can be RAN node 110a or 110b shown in Figure 1. Optionally, the communication device can also be a module (such as a chip) applied to a terminal or access network device. For ease of description, the following description uses the first communication device as a terminal and the second communication device as an access network device as an example for illustrative purposes.

[0158] As shown in Figure 7, the communication device 700 includes a processing unit 710 and a transceiver unit 720. The communication device 700 is used to implement the functions of the terminal or access network device in the method embodiment shown in Figure 4 above.

[0159] In one implementation, when the communication device 700 is used to implement the function of the first communication device (e.g., a terminal) in the method embodiment shown in FIG4: the processing unit 710 is used to measure the reference signal to obtain at least two vectors, each of the vectors corresponding to the reference signals of N receiving antennas in the same frequency domain unit, wherein N is an integer greater than or equal to 2; the processing unit 710 is used to process the at least two vectors based on the vector scaling parameters and the correlation between the scaled vectors.

[0160] Optionally, the processing unit 710 is used to obtain vector scaling parameters and the correlation between scaled vectors.

[0161] Optionally, when acquiring the vector scaling parameters, the transceiver unit 720 is configured to: receive information indicating the vector scaling parameters.

[0162] Optionally, when obtaining the correlation between the scaled vectors, the transceiver unit 720 is used to: receive information indicating the correlation between the scaled vectors.

[0163] Optionally, the vector filtering parameters and / or the correlation between the scaled vectors are predefined.

[0164] Optionally, the vector scaling parameters include one or more of the following: the dimension of vector scaling, the processing method of vector scaling, or the magnitude of vector scaling.

[0165] Optionally, the dimension of the vector scaling is N, where N is the total number of receiving antennas, or the N receiving antennas belong to the same receiving antenna group.

[0166] Optionally, the vector scaling process includes scaling the vector based on the measured modulus, or scaling the vector based on a predefined modulus or a modulus configured in the vector scaling parameters.

[0167] Optionally, the correlation between the scaled vectors includes one or more of the following: the measurement method of the correlation between the scaled vectors, the indication method of the correlation between the scaled vectors, or the indication granularity of the correlation between the scaled vectors.

[0168] Optionally, the measurement method for the correlation between the scaled vectors includes any of the following: the inner product between the scaled vectors, the angle between the scaled vectors, the distance between the scaled vectors, or the radian between the scaled vectors.

[0169] Optionally, the indication of the relationship between the scaled vectors may include a matrix, a vector, or a function.

[0170] Optionally, the granularity of the scaling vector association is a flow, a flow group, or all flows; when the granularity of the scaling vector association is a flow, the at least two vectors are vectors corresponding to the same flow; or, when the granularity of the scaling vector association is a flow group, the at least two vectors belong to the same flow group; or, when the granularity of the scaling vector association is all flows, the at least two vectors belong to all flows.

[0171] Optionally, the transceiver unit 720 is further configured to: receive first information, wherein the first information indicates that the first communication device uses vector filtering.

[0172] Optionally, the transceiver unit 720 is further configured to: transmit capability information, the capability information indicating the capability of the first communication device to support vector filtering.

[0173] Optionally, when processing the at least two vectors based on the vector scaling parameters and the correlation between the scaled vectors, the processing unit 710 is specifically used to: scale the at least two vectors respectively based on the vector scaling parameters to obtain at least two scaled vectors; perform vector filtering on the at least two scaled vectors according to the correlation between the scaled vectors to obtain at least two scaled reconstructed vectors; and perform vector magnitude recovery on the at least two scaled reconstructed vectors based on the vector scaling parameters to obtain at least two reconstructed vectors.

[0174] Optionally, the processing unit 710 is further configured to: determine channel estimation information based on the at least two reconstruction vectors.

[0175] In one implementation, when the communication device 700 is used to implement the function of the second communication device (e.g., an access network device) in the method embodiment shown in FIG4:

[0176] Processing unit 710 is used to determine the correlation between vector scaling parameters and the scaled vector, wherein the correlation between the vector scaling parameters and the scaled vector is used to process the vector;

[0177] The transceiver unit 720 is used to send the vector scaling parameters and the correlation between the scaled vectors.

[0178] Optionally, the vector scaling parameters include one or more of the following: the dimension of vector scaling, the processing method of vector scaling, or the magnitude of vector scaling.

[0179] Optionally, the dimension of the vector scaling is N, where N is the total number of receiving antennas, or the N receiving antennas belong to the same receiving antenna group.

[0180] Optionally, the vector scaling process includes scaling the vector based on the measured modulus, or scaling the vector based on a predefined modulus or a modulus configured in the vector scaling parameters.

[0181] Optionally, the correlation between the scaled vectors includes one or more of the following: the measurement method of the correlation between the scaled vectors, the indication method of the correlation between the scaled vectors, or the indication granularity of the correlation between the scaled vectors.

[0182] Optionally, the measurement method for the correlation between the scaled vectors includes any of the following: the inner product between the scaled vectors, the angle between the scaled vectors, the distance between the scaled vectors, or the radian between the scaled vectors.

[0183] Optionally, the indication of the relationship between the scaled vectors may include a matrix, a vector, or a function.

[0184] Optionally, the granularity of the scaling vector association is a flow, a flow group, or all flows; when the granularity of the scaling vector association is a flow, the at least two vectors are vectors corresponding to the same flow; or, when the granularity of the scaling vector association is a flow group, the at least two vectors belong to the same flow group; or, when the granularity of the scaling vector association is all flows, the at least two vectors belong to all flows.

[0185] Optionally, the transceiver unit 720 is further configured to: send first information, wherein the first information instructs the first communication device to use vector filtering.

[0186] Optionally, the transceiver unit 720 is further configured to: receive capability information, the capability information indicating the capability of the first communication device to support vector filtering.

[0187] For a more detailed description of the processing unit 710 and the transceiver unit 720, please refer to the relevant description in the method embodiment shown in Figure 4.

[0188] As shown in Figure 8, the communication device 800 includes a processor 810, and optionally an interface circuit 820. The processor 810 and the interface circuit 820 are coupled to each other. It is understood that the interface circuit 820 can be a transceiver or an input / output interface. Optionally, the communication device 800 may also include a memory 830 for storing instructions executed by the processor 810, or storing input data required by the processor 810 to execute instructions, or storing data generated after the processor 810 executes instructions.

[0189] When the communication device 800 is used to implement the method shown in FIG4, the processor 810 is used to implement the function of the processing unit 710, and the interface circuit 820 is used to implement the function of the transceiver unit 720.

[0190] When the aforementioned communication device is a chip applied to a terminal, the terminal chip implements the functions of the terminal in the above method embodiments. The terminal chip receives information sent to the terminal by the access network device through other modules (such as an RF module or antenna) in the terminal; or, the terminal chip sends information to other modules (such as an RF module or antenna) in the terminal, which is information sent by the terminal to the access network device.

[0191] When the aforementioned communication device is a module applied to an access network device, the access network device module implements the functions of the access network device in the above method embodiments. The access network device module receives information from other modules (such as radio frequency modules or antennas) in the access network device, which is information sent by the terminal to the access network device; or, the access network device module sends information to other modules (such as radio frequency modules or antennas) in the access network device, which is information sent by the access network device to the terminal. Here, the access network device module can be the baseband chip of the access network device, or a CU, DU, or other module, or a device under an open radio access network (O-RAN) architecture, such as an open CU, open DU, etc.

[0192] It is understood that the processor in the embodiments of this application can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), microprocessors (MPUs), microcontroller units (MCUs), graphics processing units (GPUs), field-programmable gate arrays (FPGAs), artificial intelligence processors (AI processors), neural network processors (NPUs), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. A general-purpose processor can be a microprocessor or any conventional processor.

[0193] As shown in Figure 9, the communication device 900 includes a processor 910, a memory 920, and a transceiver 930. The processor 910 is mainly used for processing communication protocols and communication data; controlling the first / second communication device; executing software programs; and processing data from the software programs. The memory 920 can store computer program code, software programs, and data. The transceiver 930 includes a transmitter 931, a receiver 932, radio frequency circuitry (not shown in Figure 9), and an antenna 933.

[0194] The processor 910 can also be called a processing unit, processing board, processing module, or processing device. The transceiver 930 can also be called a transceiver unit, transceiver, or transceiver device.

[0195] Optionally, the devices in transceiver 930 used to implement the receiving function can be considered as receiving modules, and the devices in transceiver 930 used to implement the transmitting function can be considered as transmitting modules. That is, transceiver 930 includes a receiver and / or a transmitter. A transceiver may also be called a transceiver unit, transceiver module, or transceiver circuit, etc. A receiver may also be called a receiver unit, receiving module, or receiving circuit, etc. A transmitter may also be called a transmitter, transmitting module, or transmitting circuit, etc.

[0196] Processor 910 is used to execute the processing operations of the first communication device in the embodiment shown in FIG. 4. Transceiver 930 is used to execute the transmission and reception operations of the first communication device in the embodiment shown in FIG. 4. Alternatively, processor 910 is used to execute the processing operations of the second communication device in the embodiment shown in FIG. 4. Transceiver 930 is used to execute the transmission and reception operations of the second communication device in the embodiment shown in FIG. 4.

[0197] When the communication device 900 is a chip, the chip includes a processor and a transceiver. The transceiver can be an input / output circuit or a communication interface. The processor can be a processing module integrated on the chip, a microprocessor, or an integrated circuit. In the above method embodiments, the transmitting operation of the first communication device can be understood as the chip's output, and the receiving operation of the first communication device in the above method embodiments can be understood as the chip's input. Similarly, in the above method embodiments, the transmitting operation of the second communication device can be understood as the chip's output, and the receiving operation of the second communication device in the above method embodiments can be understood as the chip's input.

[0198] This application also provides a computer-readable storage medium storing a computer program or instructions for implementing the method executed by the first communication device or the second communication device in the above-described method embodiments.

[0199] For example, when the computer program is executed by a computer, it enables the computer to implement the method executed by the first communication device or the second communication device in the above method embodiments.

[0200] This application also provides a computer program product containing a program or instructions, which, when executed by a computer, causes the computer to implement the method executed by the first communication device or the second communication device in the above method embodiments.

[0201] This application also provides a communication system, which includes a first communication device and a second communication device as described in the above embodiments. The first communication device is used to perform some or all of the operations performed by the first communication device in the above method embodiments, and the second communication device is used to perform some or all of the operations performed by the second communication device in the above method embodiments.

[0202] This application also provides a chip device, including a processor, for calling a computer program or computer instructions stored in the memory, so that the processor executes the method provided in the embodiment shown in FIG4 above.

[0203] In one possible implementation, the input of the chip device corresponds to the receiving operation in any one of the embodiments shown in FIG4, and the output of the chip device corresponds to the sending operation in any one of the embodiments shown in FIG4.

[0204] Optionally, the processor is coupled to the memory via an interface.

[0205] Optionally, the chip device further includes a memory storing computer programs or computer instructions.

[0206] It is understood that the processor in the embodiments of this application can be a CPU, or other general-purpose processors, DSPs, ASICs, FPGAs, or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. A general-purpose processor can be a microprocessor or any conventional processor.

[0207] The method steps in the embodiments of this application can be implemented in hardware or in software instructions executable by a processor. The software instructions can consist of corresponding software modules, which can be stored in random access memory, flash memory, read-only memory, programmable read-only memory, erasable programmable read-only memory, electrically erasable programmable read-only memory, registers, hard disks, portable hard disks, CD-ROMs, or any other form of storage medium known in the art. An exemplary storage medium is coupled to a processor, enabling the processor to read information from and write information to the storage medium. The storage medium can also be a component of the processor. The processor and storage medium can reside in an ASIC. Additionally, the ASIC can reside in a second communication device or a first communication device. The processor and storage medium can also exist as discrete components in the second or first communication device.

[0208] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer programs or instructions. When the computer program or instructions are loaded and executed on a computer, the processes or functions described in the embodiments of this application are performed entirely or partially. The computer can be a general-purpose computer, a special-purpose computer, a computer network, a network device, a user equipment, or other programmable device. The computer program or instructions can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another. For example, the computer program or instructions can be transferred from one website, computer, server, or data center to another website, computer, server, or data center via wired or wireless means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium, such as a floppy disk, hard disk, or magnetic tape; it can also be an optical medium, such as a digital video optical disc; or it can be a semiconductor medium, such as a solid-state drive. The computer-readable storage medium may be a volatile or non-volatile storage medium, or may include both types of storage media.

[0209] In the various embodiments of this application, unless otherwise specified or in case of logical conflict, the terminology and / or descriptions of different embodiments are consistent and can be referenced by each other. The technical features of different embodiments can be combined to form new embodiments according to their inherent logical relationship.

[0210] It is understood that the various numerical designations used in the embodiments of this application are merely for descriptive convenience and are not intended to limit the scope of the embodiments of this application. The order of the process numbers described above does not imply the order of execution; the execution order of each process should be determined by its function and internal logic.

Claims

1. A communication method characterized by comprising: include: Measure the reference signal to obtain at least two vectors, each of which corresponds to the reference signal of N receiving antennas in the same frequency domain unit, where N is an integer greater than or equal to 2; The at least two vectors are processed based on the vector scaling parameters and the correlation between the scaled vectors.

2. The method according to claim 1, characterized in that, The method further includes: Obtain the correlation between the vector scaling parameters and the scaled vector.

3. The method according to claim 1 or 2, characterized in that, The vector filtering parameters and / or the correlation between the scaled vectors are configured or predefined.

4. The method according to any one of claims 1-3, characterized in that, The vector scaling parameters include one or more of the following: The dimensions of vector scaling, the processing method of vector scaling, or the magnitude of vector scaling.

5. The method according to claim 4, characterized in that, The dimension of the vector scaling is N, where N is the total number of receiving antennas, or the N receiving antennas belong to the same receiving antenna group.

6. The method according to claim 4 or 5, characterized in that, The vector scaling processing method includes scaling the vector based on the magnitude obtained from the measurement reference signal, or scaling the vector based on a predefined magnitude or a magnitude configured in the vector scaling parameters.

7. The method according to any one of claims 1-6, characterized in that, The relationships between the scaled vectors include one or more of the following: The method of measuring the relationship between scaled vectors, the method of indicating the relationship between scaled vectors, or the granularity of indicating the relationship between scaled vectors.

8. The method according to claim 7, characterized in that, The method for measuring the correlation between the scaled vectors includes any of the following: The inner product of scaled vectors, the angle between scaled vectors, the distance between scaled vectors, or the radian between scaled vectors.

9. The method according to claim 7 or 8, characterized in that, The indication of the relationship between the scaled vectors can be a matrix, a vector, or a function.

10. The method according to any one of claims 7-9, characterized in that, The granularity of the indication of the correlation between the scaled vectors is a single flow, a group of flows, or all flows; When the granularity of the indication of the correlation between the scaled vectors is a flow, the at least two vectors are vectors corresponding to the same flow; or, When the granularity of the correlation indication between the scaled vectors is a flow group, the at least two vectors belong to the same flow group; or... When the granularity of the correlation between the scaled vectors is the entire flow, the at least two vectors belong to the vectors corresponding to the entire flow.

11. The method according to any one of claims 1-10, characterized in that, The method further includes: Receive first information, which instructs the first communication device to use vector filtering.

12. The method according to any one of claims 1-11, characterized in that, The method further includes: Send capability information, which indicates that the first communication device supports vector filtering capabilities.

13. The method according to any one of claims 1-12, characterized in that, The processing of the at least two vectors based on the vector scaling parameters and the correlation between the scaled vectors includes: Based on the vector scaling parameters, the at least two vectors are scaled respectively to obtain at least two scaled vectors; Based on the correlation between the scaled vectors, vector filtering is performed on the at least two scaled vectors to obtain at least two scaled reconstructed vectors; Based on the vector scaling parameters, the vector magnitude of the at least two scaled reconstructed vectors is restored to obtain at least two reconstructed vectors.

14. The method according to claim 13, characterized in that, The method further includes: Channel estimation information is determined based on the at least two reconstruction vectors.

15. A communication device, characterized in that, Includes units or modules for implementing the method as described in any one of claims 1-14.

16. A communication device, characterized in that, Includes a processor for executing computer programs or instructions to cause the communication device to implement the method as described in any one of claims 1-14.

17. A communication device, characterized in that, The device includes a processor and a transceiver, the transceiver being used to send and receive information, and the processor being used to execute computer programs or instructions to cause the communication device to implement the method as described in any one of claims 1-14.

18. A communication device, characterized in that, The device includes a processor and an interface circuit, wherein the interface circuit is used to receive signals from other communication devices besides the communication device and transmit them to the processor or to send signals from the processor to other communication devices besides the communication device, and the processor is used to execute computer programs or instructions to cause the communication device to implement the method as described in any one of claims 1-14.

19. A computer-readable storage medium, characterized in that, The storage medium stores a computer program or instructions, which, when executed by a communication device, implement the method as described in any one of claims 1-14.

20. A computer program product, characterized in that, Includes computer program code, which, when run on a computer, implements the method of any one of claims 1-14.

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