Communication method and related apparatus

Abstract

The present application provides a communication method and a related apparatus. The method comprises: acquiring first information, the first information being used for indicating a first channel reconstruction method, and the first channel reconstruction method corresponding to a first model; sending second information, the second information being used for indicating a first reference signal pattern corresponding to the first model; and on the basis of the first reference signal pattern, sending a first reference signal. In the described method, a reference signal pattern that helps reconstruct complete channel information can be acquired.

Description

Communication methods and related devices

[0001] This application claims priority to Chinese Patent Application No. 202411794412.7, filed on December 6, 2024, entitled "Communication Method and Related 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 communication methods and related devices. Background Technology

[0003] Machine learning is an important branch of artificial intelligence and a technological means to achieve artificial intelligence. Among the many research directions in machine learning, neural networks have become a highly promising technique due to their ability to infinitely approximate any continuous function, granted by the universal approximation theorem. They can accurately abstract and model complex high-dimensional problems.

[0004] How to design pilot patterns using neural networks is a topic worthy of discussion in the industry. Summary of the Invention

[0005] This application provides a communication method and related apparatus for acquiring a reference signal pattern (or pilot pattern) that helps reconstruct channel information.

[0006] 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.

[0007] In a first aspect, this application provides a communication method that can be executed by a first device, which may be a terminal or a chip, chip system, module, or control unit in the terminal; or, the first device may be a network device or a chip, chip system, module, or control unit in the network device, such as a server on the network side or a component (e.g., circuit, chip, or chip system) in the server, and this application does not limit the specific device.

[0008] It should be noted that, in this application, the term "terminal" can refer to either the terminal itself or the chip, functional module, or integrated circuit within the terminal that performs the methods provided in this application; no specific limitation is made in this application. For example, the chips in this application include, but are not limited to, modem chips, baseband chips, or system-on-chip (SoC) chips or system-in-package (SIP) chips containing modem cores, which will not be elaborated further below.

[0009] It should be noted that, in this application, when referring to network equipment, it may refer to the network equipment itself, or to the chip, functional module, or integrated circuit in the network equipment that performs the method provided in this application, and this application does not make any specific limitation.

[0010] In a first aspect and its possible implementations, the method is described as being performed by a first device. The method includes: the first device acquiring first information, the first information indicating a first channel reconstruction method, the first channel reconstruction method corresponding to a first model; the first device sending second information, the second information indicating a first reference signal pattern corresponding to the first model; and the first device sending a first reference signal based on the first reference signal pattern.

[0011] In this embodiment of the application, the first device uses a neural network (i.e., the first model) and a first channel reconstruction method to design a reference signal pattern, which can obtain a first reference signal pattern that helps to reconstruct complete channel information.

[0012] Optionally, the first model can be deployed only on the first device; that is, the first model is a single-ended neural network model. This method has low implementation complexity and high feasibility. Optionally, the first device acquiring the first information can mean that the first device acquires the first information from other devices (such as the second device), or that the first device determines the first channel reconstruction method.

[0013] Optionally, if the first device determines the first channel reconstruction method, it can also send first information to the second device. Then, the second device can determine the first channel reconstruction method based on the first information, and further, can determine the first channel information based on the first reference signal and the first channel reconstruction method.

[0014] In conjunction with the first aspect, in one possible implementation, the method further includes: a first device receiving third information from a second device, the third information being used to instruct the second device to support channel reconstruction using a reference signal pattern corresponding to a neural network; the first device acquiring the first information includes: the first device receiving the first information from the second device; the first device sending the second information includes: the first device sending the second information to the second device.

[0015] In this embodiment, the first device obtains first information and third information from the second device, which helps the first device to obtain the channel reconstruction capability of the second device and helps the first device to determine whether to send the reference signal pattern corresponding to the neural network to the second device.

[0016] In this application, the reference signal pattern corresponding to the neural network can refer to a reference signal pattern designed (or generated) based on the neural network. For example, the first reference signal pattern corresponding to the first model can refer to a first reference signal pattern designed (or generated) based on a neural network (such as the first model); or, the output of the neural network (such as the first model) includes the first reference signal pattern; or, the output of the neural network (such as the first model) is used to obtain the first reference signal pattern, such as the output of the first model being channel information of the first reference signal position.

[0017] In this application, a first device is used to transmit a first reference signal, and a second device is used to receive the first reference signal. For example, if the first device is a network device, the second device can be a terminal; or, if the first device is a terminal, the second device can be a network device.

[0018] For example, the first device is a network device (i.e., the device sending the first reference signal is a network device, and the first reference signal is a downlink reference signal), and the second device is a terminal. The terminal can send the aforementioned third information and the aforementioned first information to the network device. The terminal can send the third information first and then the first information, or it can send the third information and the first information simultaneously; this application does not limit this. In this method, the first reference signal is a downlink reference signal. This method provides a procedural specification for designing downlink reference signal patterns based on neural networks and channel reconstruction methods for downlink reference signal scenarios. The obtained downlink reference signal pattern helps to reconstruct complete channel information.

[0019] In conjunction with the first aspect, in one possible implementation, the method further includes, prior to: the first device sending fourth information to the second device, the fourth information being used to instruct the first device to support channel reconstruction using a reference signal pattern corresponding to the neural network; the first device acquiring the first information includes: the first device receiving the first information from the second device; the first device sending the second information includes: the first device sending the second information to the second device.

[0020] In this embodiment, the first device can first send fourth information to the second device. This helps the first device acquire its channel reconstruction capability and determines whether to subsequently send the aforementioned first information. For example, the second device can send the first information after receiving the fourth information. This method avoids wasting communication resources when the second device still sends the first information even though the first device does not support channel reconstruction using the reference signal pattern corresponding to the neural network.

[0021] Optionally, the meaning of the fourth information can also be: to indicate the channel reconstruction method selected by the transmitting second device, that is, the fourth information can be a trigger instruction, which is used to trigger the second device to send the aforementioned first information.

[0022] For example, the first device is a terminal (i.e., the device sending the first reference signal is the terminal, and the first reference signal is an uplink reference signal), and the second device is a network device. The terminal can send fourth information to the network device, and correspondingly, the network device receives the fourth information from the terminal; then, the terminal sends the aforementioned first information back to the network device. In this method, the first reference signal is an uplink reference signal. This method provides a process specification for designing uplink reference signal patterns based on neural networks and channel reconstruction methods for uplink reference signal scenarios. The obtained uplink reference signal pattern helps to reconstruct complete channel information.

[0023] In conjunction with the first aspect, in one possible implementation, the method further includes: a first device determining a first correspondence based on first information, the first correspondence being used to indicate the neural network corresponding to the first channel reconstruction method; and determining the neural network corresponding to the first channel reconstruction method as a first model. Determining the first model based on the first correspondence in this method can improve the efficiency of the first device in determining the first model.

[0024] Optionally, the first device can acquire the correspondence between multiple neural networks and multiple channel reconstruction methods, including the aforementioned first correspondence. Optionally, the first device can also pre-store the aforementioned correspondence between multiple neural networks and multiple channel reconstruction methods, where each neural network and channel reconstruction method can correspond one-to-one. Optionally, the aforementioned correspondence can also be sent to the first device by a second device or other devices.

[0025] In another possible implementation, the method further includes: the first device can determine the neural network corresponding to the first channel reconstruction method as the first model based on first information and the correspondence between multiple neural networks and multiple channel reconstruction methods. The correspondence between the multiple neural networks and multiple channel reconstruction methods includes the aforementioned first correspondence.

[0026] In this application, the correspondence can be represented by tables, two-dimensional arrays, or text.

[0027] In conjunction with the first aspect, in one possible implementation, the method further includes: a first device receiving fifth information, the fifth information being used to indicate first channel information, the first channel information being obtained based on a first reference signal and a first channel reconstruction method.

[0028] In this embodiment of the application, the first device can obtain the first channel information based on the first reference signal and the first channel reconstruction method, so that the first device can perform data transmission based on the first channel information, which can improve the efficiency of data transmission between the first device and the second device.

[0029] In conjunction with the first aspect, in one possible implementation, the first model is obtained by training a neural network based on the first channel reconstruction method. For example, the first model is obtained by training a neural network multiple times based on the first channel reconstruction method, and the first reference signal pattern is generated by the first model.

[0030] In conjunction with the first aspect, in one possible implementation, the method further includes: a first device training an initial neural network multiple times based on a first channel reconstruction method; wherein the multiple trainings include an i-th training, the i-th training comprising: the first device inputting the i-th channel information into the neural network obtained from the (i-1)-th training to obtain the i-th reference signal pattern; the first device obtaining the i-th reconstructed channel information based on the i-th reference signal pattern and the first channel reconstruction method; if the i-th training does not meet the training requirements, then adjusting the neural network obtained from the (i-1)-th training based on the i-th reconstructed channel information and the i-th channel information to obtain the neural network obtained from the i-th training; if the i-th reconstructed channel information meets the training requirements, then determining the neural network obtained from the (i-1)-th training as the first model, the first reference signal pattern as the i-th reference signal pattern, and i being a positive integer.

[0031] In this embodiment of the application, the neural network is trained according to the first channel reconstruction method to obtain a first reference signal pattern corresponding to the reconstructed channel information that meets the training requirements, so that the first reference signal pattern helps to reconstruct the complete channel information.

[0032] In conjunction with the first aspect, in one possible implementation, the first reference signal is a demodulation reference signal (DMRS), a channel state information reference signal (CSI-RS), or a sounding reference signal (SRS).

[0033] Secondly, this application provides a communication method that can be executed by a second device, which may be a terminal or a chip, chip system, module, or control unit in the terminal; or, the second device may be a network device or a chip, chip system, module, or control unit in the network device, such as a server on the network side or a component (e.g., circuit, chip, or chip system) in the server, and this application does not limit the specific device.

[0034] In the second aspect and its possible implementations, the method is described as being performed by a second device. The method includes: the second device sending first information, the first information indicating a first channel reconstruction method, the first channel reconstruction method corresponding to a first model; the second device receiving second information, the second information indicating a first reference signal pattern corresponding to the first model; the second device receiving a first reference signal based on the first reference signal pattern; and the second device obtaining first channel information based on the first reference signal and the first channel reconstruction method.

[0035] In this embodiment, the first reference signal pattern is related to the neural network (i.e., the first model) and the first channel reconstruction method. The first reference signal pattern helps to reconstruct complete channel information, and the method can improve the accuracy of the first channel information.

[0036] In conjunction with the second aspect, in one possible implementation, the method further includes, prior to implementation, a second device determining a first channel reconstruction method from a plurality of channel reconstruction methods. Optionally, the plurality of channel reconstruction methods can be channel reconstruction methods known to both the first and second devices, or channel reconstruction methods supported by both devices. "Supported" can mean capable of executing the channel reconstruction method or possessing a neural network (such as a reference signal pattern design network) corresponding to the channel reconstruction method. In this method, the second device can select a channel reconstruction method based on its hardware, accuracy requirements, and channel conditions. The first channel reconstruction method selected by the second device better matches its capabilities, exhibiting good adaptability and high flexibility.

[0037] Optionally, the first device determines the first reference signal pattern through a neural network based on the channel reconstruction method selected by the second device. The pilot pattern determined by this method has good compatibility with the second device, which is beneficial for the second device to perform channel reconstruction.

[0038] In conjunction with the second aspect, in one possible implementation, the method further includes, prior to: the second device sending third information to the first device, the third information being used to instruct the second device to support channel reconstruction using a reference signal pattern corresponding to the neural network; the second device sending first information, including: the second device sending the first information to the first device; and the second device receiving second information, including: the second device receiving the second information from the first device.

[0039] In conjunction with the second aspect, in one possible implementation, the method further includes, prior to: the second device receiving fourth information from the first device, the fourth information being used to instruct the first device to support channel reconstruction using a reference signal pattern corresponding to the neural network; the second device sending the first information includes: the second device sending the first information to the first device; the second device receiving the second information includes: the second device receiving the second information from the first device.

[0040] In conjunction with the second aspect, in one possible implementation, the method further includes: the second device sending fifth information, the fifth information being used to indicate the first channel information.

[0041] In conjunction with the second aspect, in one possible implementation, the method further includes: the second device sending sixth information, the sixth information being used to instruct a second channel reconstruction method.

[0042] Optionally, the second device may change the channel reconstruction method when the channel reconstruction accuracy changes, etc., and this application does not limit this.

[0043] In conjunction with the second aspect, in one possible implementation, the first model is trained based on the first channel reconstruction method.

[0044] In conjunction with the second aspect, in one possible implementation, the first reference signal is DMRS, CSI-RS, or SRS.

[0045] Thirdly, this application provides a communication method that can be executed by a second device, which may be a terminal or a chip, chip system, module, or control unit in the terminal; or, the second device may be a network device or a chip, chip system, module, or control unit in the network device, such as a server on the network side or a component (e.g., circuit, chip, or chip system) in the server, and this application does not limit the specific device.

[0046] In the third aspect and its possible implementations, the method is described as being performed by a second device. The method includes: sending second information, the second information indicating a first reference signal pattern corresponding to a first model; receiving a first reference signal based on the first reference signal pattern; and obtaining first channel information based on the first reference signal and a first channel reconstruction method corresponding to the first model.

[0047] In conjunction with the third aspect, in one possible implementation, the method further includes, prior to implementation,: determining a first channel reconstruction method; and determining a first reference signal pattern based on the first channel reconstruction method.

[0048] In conjunction with the third aspect, in one possible implementation, the method further includes, prior to: receiving fourth information from the first device, the fourth information being used to instruct the first device to support channel reconstruction using a reference signal pattern corresponding to the neural network.

[0049] In conjunction with the third aspect, in one possible implementation, the method further includes: sending fifth information, the fifth information being used to indicate the first channel information.

[0050] In conjunction with the third aspect, in one possible implementation, the first model is trained based on the first channel reconstruction method.

[0051] In conjunction with the third aspect, in one possible implementation, the first reference signal is DMRS, CSI-RS, or SRS.

[0052] In conjunction with the third aspect, in one possible implementation, the method further includes: training the initial neural network multiple times based on the first channel reconstruction method; wherein the multiple training times include the i-th training, the i-th training including: inputting the i-th channel information into the neural network obtained from the (i-1)-th training to obtain the i-th reference signal pattern; obtaining the i-th reconstructed channel information based on the i-th reference signal pattern and the first channel reconstruction method; if the i-th training does not meet the training requirements, adjusting the neural network obtained from the (i-1)-th training based on the i-th reconstructed channel information and the i-th channel information to obtain the neural network obtained from the i-th training; if the i-th reconstructed channel information meets the training requirements, determining the neural network obtained from the (i-1)-th training as the first model, the first reference signal pattern as the i-th reference signal pattern, and i being a positive integer.

[0053] Fourthly, this application provides a communication device, which may be a first device or a chip / circuit therein. The communication device is used to perform the methods of the first aspect or any possible implementation thereof. The communication device includes units having the ability to perform the methods of the first aspect or any possible implementation thereof.

[0054] Fifthly, this application provides a communication device, which may be a second device or a chip / circuit therein. The communication device is used to perform the methods in any possible implementation of the second aspect, the third aspect, or any of the aspects. The communication device includes units having the ability to perform the methods in any possible implementation of the second aspect, the third aspect, or any of the aspects.

[0055] In the fourth or fifth aspect, the aforementioned communication device may include a transceiver module and a processing module. Further details regarding the transceiver module and processing module can be found in the device embodiments shown below. The beneficial effects of the fourth to fifth aspects can be referenced in the relevant descriptions of the first to third aspects, and will not be repeated here.

[0056] In a sixth aspect, this application provides a communication device, which includes a processor for executing the method described in any possible implementation of the first aspect, the second aspect, the third aspect, or any of the above aspects.

[0057] In a seventh aspect, this application provides a communication device including a processor coupled to a memory storing instructions that, when executed by the processor, cause the communication device to perform the method described in any possible implementation of the first aspect, the second aspect, the third aspect, or any of the above aspects.

[0058] In one possible implementation, the communication device further includes a memory. Optionally, the processor and memory are integrated (i.e., the memory is built-in memory). Optionally, the memory and processor are independently configured (i.e., the memory is external memory).

[0059] Eighthly, this application provides a communication device that may include a processor and an interface circuit connected together. The interface circuit is used for exchanging (or sending / receiving or inputting / outputting) information or data, and the processor is used for running programs or instructions to cause the communication device to perform the methods described in any possible implementation of the first aspect, the second aspect, the third aspect, or any of these aspects. The interface circuit may be a communication interface or a transceiver. The transceiver may be a radio frequency module in the communication device, or a combination of a radio frequency module and an antenna, or an input / output interface of a chip or circuit.

[0060] Ninthly, this application provides a readable storage medium storing a program or instructions that, when run on a computer, cause the computer to perform the method described in any possible implementation of the first aspect, the second aspect, the third aspect, or any of the aspects described above.

[0061] In a tenth aspect, this application provides a computer program product containing programs or instructions that, when run, causes the method described in any possible implementation of the first aspect, the second aspect, the third aspect, or any of the aspects to be executed.

[0062] Eleventhly, this application provides an apparatus, which can be implemented in the form of a chip or a device, including a processor. The processor is used to read and execute programs or instructions stored in a memory to execute one or more of the first, second, or third aspects described above, or one or more of any possible implementations of any aspect thereof, providing an information interaction method. Optionally, the apparatus further includes a memory connected to the processor via a circuit. Further optionally, the apparatus includes a communication interface connected to the processor. The communication interface is used to receive information to be processed, the processor obtains the information from the communication interface, processes the information, and outputs the processing result through the communication interface. The communication interface can be an input / output interface.

[0063] In one possible implementation, the processor and memory can be physically independent units, or the memory can be integrated with the processor.

[0064] In a twelfth aspect, this application provides a communication system comprising a first device and a second device; wherein the first device is configured to perform the method described in the first aspect or any possible implementation thereof, and the second device is configured to perform the method described in the second aspect or the third aspect or any possible implementation thereof.

[0065] The technical effects achieved in the above aspects can be referred to each other or to the beneficial effects in the method embodiments shown below, which will not be repeated here. Attached Figure Description

[0066] Figure 1A is a schematic diagram of a communication system provided in an embodiment of this application;

[0067] Figure 1B is a schematic diagram of an open RAN (O-RAN or ORAN) system provided in an embodiment of this application;

[0068] Figure 1C is a schematic diagram of the structure of an access network device provided in an embodiment of this application;

[0069] Figure 2 is a schematic diagram of a neural network provided in an embodiment of this application;

[0070] Figure 3A is a flowchart illustrating a communication method provided in an embodiment of this application;

[0071] Figure 3B illustrates an exemplary flowchart of the process for obtaining the first model;

[0072] Figure 3C illustrates an exemplary flowchart of the process for obtaining first channel information;

[0073] Figure 4 is a flowchart illustrating another communication method provided in an embodiment of this application;

[0074] Figure 5 is a flowchart illustrating another communication method provided in an embodiment of this application;

[0075] Figure 6 is a flowchart illustrating another communication method provided in an embodiment of this application;

[0076] Figure 7 is a flowchart illustrating another communication method provided in an embodiment of this application;

[0077] Figure 8A is a schematic diagram of the structure of a communication device provided in an embodiment of this application;

[0078] Figure 8B is a schematic diagram of another communication device provided in an embodiment of this application;

[0079] Figure 9 is a schematic diagram of another communication device provided in an embodiment of this application;

[0080] Figure 10 is a schematic diagram of the structure of a terminal provided in an embodiment of this application;

[0081] Figure 11 is a schematic diagram of the structure of a network device provided in an embodiment of this application. Detailed Implementation

[0082] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0083] References to "one embodiment" or "some embodiments" as described in this application mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0084] In the description of this application, 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. Furthermore, "at least one" means one or more, and "multiple" means 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.

[0085] It is understood that in this application, "instruction" can include direct instruction, indirect instruction, explicit instruction, and implicit instruction. When describing a certain instruction information to indicate A, it can be understood that the instruction information carries A, directly indicates A, or indirectly indicates A.

[0086] Furthermore, in this application, words such as "exemplarily" and "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as an "example" in this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "example" is intended to present concepts in a concrete manner. In this application, "of," "corresponding, relevant," and "corresponding" are sometimes used interchangeably, and it should be noted that their intended meanings are consistent unless their distinction is emphasized.

[0087] The technical solutions of this application can be applied to various communication systems. For example, 5th generation (5G) systems, new radio (NR) systems, long term evolution (LTE) systems, LTE frequency division duplex (FDD) systems, LTE time division duplex (TDD) systems, universal mobile telecommunication system (UMTS), mobile communication systems after 5G networks (e.g., future mobile communication systems), vehicle-to-everything (V2X) communication systems, device-to-device (D2D) communication systems, Internet of Things (IoT) communication systems, industrial internet communication systems, or satellite communication systems, etc. The wireless communication systems involved in this application also include, but are not limited to, narrowband Internet of Things (NB-IoT) systems.

[0088] Please refer to Figure 1A. The communication system to which this application applies includes a first device 101 and a second device 102, wherein the first device 101 is the transmitting end of the first reference signal and the second device 102 is the receiving end of the first reference signal.

[0089] For example, the first device 101 is a network device, the second device 102 is a terminal, and the first reference signal is a downlink reference signal.

[0090] In another example, the first device 101 is a terminal, the second device 102 is a network device, and the first reference signal is an uplink reference signal.

[0091] The following section introduces network devices and terminals.

[0092] The terminal can be a wireless terminal capable of receiving network device scheduling information and instruction information. The terminal can be a device that provides voice and / or data connectivity to the user, a handheld device with wireless connectivity, or other processing device connected to a wireless modem.

[0093] A terminal, also known as user equipment (UE), mobile station (MS), mobile terminal (MT), customer premises equipment (CPE), etc., is a device that includes wireless communication capabilities (providing voice / data connectivity to users). A terminal can be a transportation vehicle or communication module with wireless communication capabilities. For example, it can be a handheld device with wireless connectivity or an in-vehicle device. Currently, examples of such terminals include: mobile phones, smart devices, tablets, laptops, PDAs, mobile internet devices (MIDs), wearable devices, robots, virtual reality (VR) devices, augmented reality (AR) devices, wireless terminals in industrial control, wireless terminals in vehicle-to-everything (V2X) communication, wireless terminals in self-driving cars, wireless terminals in remote medical surgery, wireless terminals in smart grids, wireless terminals in transportation safety, wireless terminals in smart cities, and wireless terminals in smart homes. For example, wireless terminals in self-driving cars can be drones, helicopters, or airplanes. For example, wireless terminals in V2X communication can be in-vehicle equipment, vehicle equipment, in-vehicle modules, vehicles, or ships. Wireless terminals in industrial control can be cameras, robots, or robotic arms. Wireless terminals in smart homes can be televisions, air conditioners, robot vacuums, speakers, or set-top boxes.

[0094] It should be noted that the terminal can be a device or apparatus with a chip, or a device or apparatus with integrated circuitry, or a chip, chip system, module, or control unit in the device or apparatus shown above; the specific application is not limited to any particular type. It should also be noted that in this application, the term "terminal" can refer to the terminal itself, or to the chip, functional module, or integrated circuit within the terminal that performs the method provided in this application; the specific application is not limited to any particular type.

[0095] A network device is a device deployed in a radio access network to provide wireless communication functions for terminals. Network devices may also be referred to as radio access network (RAN) entities, access nodes, network nodes, access network equipment, or communication devices, etc.

[0096] Specifically, the network equipment can be access network equipment for cellular systems related to the 3rd Generation Partnership Project (3GPP). For example, fourth-generation (4G) mobile communication systems, 5G mobile communication systems, or future mobile communication systems. The network equipment can also be access network equipment in open RAN (O-RAN or ORAN) or cloud radio access network (CRAN). Alternatively, the network equipment can also be access network equipment in a communication system resulting from the integration of two or more of the above communication systems.

[0097] Network equipment includes, but is not limited to: evolved Node B (eNB), radio network controller (RNC), Node B (NB), base station controller (BSC), base transceiver station (BTS), home base station (e.g., home evolved Node B, or home Node B, HNB), baseband unit (BBU), access point (AP) in wireless fidelity (WIFI) systems, macro base station, micro base station, wireless relay node, donor node, radio controller in CRAN scenarios, wireless backhaul node, transmission point (TP) or transmission and reception point (TRP). Network equipment can also be access network equipment in 5G mobile communication systems. For example, a next-generation NodeB (gNB), TRP, TP in a new radio (NR) system, or one or a group of antenna panels (including multiple antenna panels) in a base station in a 5G mobile communication system. Alternatively, network equipment can also be network nodes that constitute a gNB or transmission point. For example, a centralized unit (CU), a distributed unit (DU), a CU-control plane (CP), a CU-user plane (UP), or a radio unit (RU), etc. CU and DU can be set up separately or included in the same network element. For example, a BBU. RU can be included in radio equipment or radio units. For example, in a remote radio unit (RRU), an active antenna unit (AAU), or a remote radio head (RRH). Alternatively, network equipment can also be a server, wearable device, vehicle, or in-vehicle equipment, etc. For example, in V2X technology, network equipment can be a roadside unit (RSU).

[0098] It should be noted that CU (or CU-CP and CU-UP), DU, or RU may have different names in different systems, but those skilled in the art will understand their meaning. For example, in an ORAN system, CU can also be called an open centralized unit (O-CU) or an open CU, DU can also be called an open distributed unit (O-DU), centralized unit control plane (CU-CP) can also be called an open centralized unit control plane (O-CU-CP) or an open CU-CP, centralized unit user plane (CU-UP) can also be called an open centralized unit user plane (O-CU-UP) or an open CU-UP, and RU can also be called an open radio unit (O-RU). This application does not impose any specific limitations. Any of the units CU, 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.

[0099] Figure 1B is a schematic diagram of an open RAN (O-RAN or ORAN) system provided in an embodiment of this application. The ORAN system includes a core network, access network equipment, and UE. Optionally, the ORAN system may also include other components besides those shown in Figure 1B, which is not limited in this application.

[0100] This application can be applied to the system shown in Figure 1B. Therefore, the network device in this application can be the access network device in Figure 1B, such as the CU (CU-CP or CU-UP) or DU or RU mentioned above, and the terminal in this application can be the UE in Figure 1B.

[0101] Access network devices can communicate with the core network (CN) via a backhaul link. Access network devices can also communicate with the UE via an air interface. Specifically, the BBU in the access network device communicates with the core network via a backhaul link. The RU in the access network device communicates with at least one UE 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.

[0102] A BBU consists of at least one CU and at least one DU, and the CU and DU can communicate with each other via at least one midhaul link.

[0103] In one possible implementation, as shown in Figure 1C, the CU is a logical node carrying the radio resource control (RRC), service data adaptation protocol (SDAP) layer, packet data convergence protocol (PDCP) layer, and other control functions of the access network equipment. The CU can connect to network nodes such as the core network through interfaces, such as the E2 interface. Optionally, the CU can have some core network functions. The CU (e.g., the PDCP layer and / or higher) connects to the DU (e.g., the radio link control (RLC) layer and lower layers of the DU) through interfaces, such as the F1 interface. Optionally, 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, defining the signaling procedures of F1 in some examples. The F1 interface supports control plane F1-C and user plane F1-U.

[0104] Optionally, as shown in Figure 1C, the CU can be split into CU-CP and CU-UP. CU-CP is a logical node carrying the control plane (PDCP-C) layer, which carries the RRC layer and the Packet Data Convergence Protocol layer, and is 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 (AMF) function 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 user plane (PDCP-U) layer, which carries the SDAP layer and the Packet Data Convergence Protocol layer, and is 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. In the core network, network elements used to implement user plane functions, such as the user plane function (UPF) in a 5G system, are responsible for forwarding and receiving data in terminals. The above configuration of CU and DU is merely an example; in practical applications, the functions of CU and DU can be configured as needed. For example, CU or DU can be configured to have more protocol layer functions, or to have only some protocol layer processing functions. For instance, some functions of the RLC layer and protocol layer functions above the RLC layer can be placed in the CU, while the remaining functions of the RLC layer and protocol layer functions below the RLC layer can be placed in the DU. Furthermore, the functions of CU or DU can be divided according to service type or other system requirements, such as by latency, placing functions that need to meet low latency requirements in the DU and functions that do not need to meet such latency requirements in the CU.

[0105] In one possible implementation, as shown in Figure 1C, the DU is a logical node carrying the RLC layer, medium access control (MAC) layer, higher physical layer (Higher PHY) layer, and other functions. In some examples, the 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 PHY layer processing, such as forward error correction (FEC) encoding and decoding, scrambling, modulation, and demodulation.

[0106] In one possible implementation, as shown in Figure 1C, the RU is a logical node carrying both lower physical layer (PHY) and radio frequency (RF) processing. In some examples, the RU may be a 3GPP TRP, a 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 UEs via a radio link.

[0107] 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 a lower-layer split CUS-Plane (LLS-CUS) interface. LLS-CUS may include a lower-layer split control (LLS-C) interface and a lower-layer split user (LLS-U) interface, 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.

[0108] 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.

[0109] 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.

[0110] For example, network devices and terminals include an RRC signaling interaction module, a MAC signaling interaction module, and a PHY interaction module. The RRC signaling interaction module is used to send and receive RRC signaling, the MAC signaling interaction module is used to send and receive MAC-CE signaling, and the PHY interaction module is used to send and receive uplink / downlink control signaling and uplink / downlink data, such as transmitting physical downlink control channel (PDCCH), physical downlink shared channel (PDSCH), physical uplink control channel (PUCCH), and physical uplink shared channel (PUSCH).

[0111] It should be noted that network devices can be devices or apparatuses with chips, or devices or apparatuses with integrated circuits, or chips, chip systems, modules, or control units in the devices or apparatuses shown above; this application does not impose any specific limitations. It should also be noted that in this application, the term "network device" can refer to the network device itself, or to chips, functional modules, or integrated circuits within the network device that implement the methods provided in this application; this application does not impose any specific limitations.

[0112] First, let me introduce some of the technical terms used in this application.

[0113] 1. Artificial intelligence (AI)

[0114] (1) AI can enable machines to possess human-like intelligence, for example, allowing machines to use computer hardware and software to simulate certain intelligent human behaviors. To achieve artificial intelligence, machine learning methods can be used. In machine learning, machines learn (or train) a model using training data. This model represents the mapping between input and output. The learned model can be used for reasoning (or prediction), that is, it can be used to predict the output corresponding to a given input. This output can also be called the reasoning result (or prediction result).

[0115] (2) A neural network (NN) is a specific model in machine learning. According to the general approximation theorem, a neural network can theoretically approximate any continuous function, thus enabling it to learn arbitrary mappings. Traditional communication systems require extensive expert knowledge to design communication modules, while deep learning communication systems based on neural networks can automatically discover hidden pattern structures from large datasets, establish mapping relationships between data, and achieve performance superior to traditional modeling methods.

[0116] Neural networks are, for example, deep neural networks (DNNs). For instance, DNNs can include feedforward neural networks (FNNs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), and fully connected neural networks.

[0117] DNNs are typically multi-layered structures. Increasing the depth and width of a neural network can improve its expressive power, providing more powerful information extraction and abstract modeling capabilities for complex systems. DNNs can include feedforward neural networks and feedback neural networks, among others.

[0118] Figure 2 illustrates a schematic diagram of a feedforward neural network. Figure 2 shows three neural network layers: an input layer, hidden layers, and an output layer. The input layer is used to input the information to be processed; a DNN typically contains more than one hidden layer, which extracts information features to varying degrees; the output layer maps the extracted feature information to the desired output information. Circular symbols represent neurons in each layer. The connection method and activation function used for each neuron determine the neural network's expression function.

[0119] In this application, the first model is based on a neural network, which can be a DNN, specifically an RNN, a CNN, or something else; this application does not limit this.

[0120] In this application, the model (such as the first model) may also be referred to as an AI model, rule, or other names. An AI model can be considered a specific method for implementing AI functions. An AI model represents the mapping relationship or function between the model's input and output. AI functions may include one or more of the following: data collection, model training (or model learning), model information dissemination, model inference (or model reasoning, inference, or prediction, etc.), model monitoring or model validation, or inference result dissemination, etc. AI functions may also be referred to as AI (related) operations or AI-related functions.

[0121] The communication system provided in this application (such as the system in Figure 1A above) can incorporate AI network elements to implement some or all AI-related operations (such as training a first model). AI network elements can also be called AI nodes, AI devices, AI entities, AI modules, AI models, or AI units, etc. These AI network elements can be built into the network elements of the communication system. For example, an AI network element can be an AI module built into: access network equipment, core network equipment, cloud server, or operation, administration and maintenance (OAM) management system, used to implement AI-related functions. The aforementioned OAM can be the management system of the core network equipment and / or the management system of the access network equipment. Alternatively, the aforementioned AI network element can also be a network element independently set up in the communication system. Optionally, the terminal or the chip built into the terminal can also include an AI entity to implement AI-related functions.

[0122] 2. Reference signal (RS)

[0123] RS can also be referred to as a pilot, reference sequence, etc. In the embodiments of this application, the reference signal can be a reference signal used for channel measurement. For example, the reference signal can be a CSI-RS used for downlink channel measurement or an SRS used for uplink channel measurement.

[0124] It should be understood that the reference signals listed above are merely examples and should not be construed as limiting this application in any way. This application does not preclude the possibility of defining other reference signals in future agreements to achieve the same or similar functions, nor does it preclude the possibility of defining other reference signals in future agreements to achieve different functions.

[0125] Currently, pilot pattern design using neural networks is not yet mature, and there is no complete design scheme.

[0126] In view of this, this application provides a communication method and related apparatus. In this method, a first device designs a reference signal pattern using a neural network (i.e., a first model) and a first channel reconstruction method, which can obtain a first reference signal pattern that helps to reconstruct complete channel information. A second device reconstructs complete channel information based on the first reference signal pattern and the first channel reconstruction method, which can obtain channel information with higher accuracy.

[0127] The technical solution of this application is described below with reference to specific embodiments. Figure 3A is a schematic flowchart of a communication method provided by an embodiment of this application.

[0128] Referring to Figure 3A, the method may include the following steps:

[0129] Step S301: The first device obtains first information, which is used to indicate the first channel reconstruction method and the first channel reconstruction method corresponds to the first model.

[0130] For example, the first device obtaining the first information may mean that the first device determines a first channel reconstruction method. For instance, the first device can determine the first channel reconstruction method from channel reconstruction methods supported by both the first device and the second device. Optionally, after determining the first channel reconstruction method, the first device may also send the aforementioned first information to the second device.

[0131] Another example is that the first device obtaining the first information can mean that the second device sends the first information to the first device, and correspondingly, the first device receives the first information from the second device.

[0132] For example, the first channel reconstruction method may be linear interpolation, linear minimum mean square error (LMMSE) interpolation, or other channel reconstruction methods, and this application does not limit this method.

[0133] In one implementation, the second device can send third information to the first device, and correspondingly, the first device receives the third information from the second device. The third information is used to instruct the second device to support channel reconstruction using a reference signal pattern corresponding to the neural network. For example, the first device is a network device, and the second device is a terminal. The terminal can send the aforementioned third information and the aforementioned first information to the network device. The third information is used to instruct the terminal to support channel reconstruction using a reference signal pattern corresponding to the neural network. The terminal can send the aforementioned third information first and then send the first information, or it can send the third information and the first information simultaneously. This application does not limit this.

[0134] In another implementation, the first device can send fourth information to the second device. This fourth information instructs the first device to support channel reconstruction using a reference signal pattern corresponding to the neural network. The second device then receives the fourth information from the first device and subsequently sends the first information back to the first device. For example, the first device can be a terminal, and the second device can be a network device. The terminal can send the fourth information to the network device, and the network device receives the fourth information from the terminal. The network device then sends the first information back to the terminal. This method avoids wasting communication resources due to the first device not supporting channel reconstruction using a reference signal pattern corresponding to the neural network.

[0135] Step S302: The first device sends second information to the second device, the second information being used to indicate the first reference signal pattern corresponding to the first model.

[0136] Correspondingly, the second device receives the second information from the first device.

[0137] In some embodiments, after receiving the first information, the first device may indicate to the second device a reference signal pattern (i.e., a first reference signal pattern) corresponding to the first channel reconstruction method. It should be understood that the first channel reconstruction method corresponds to a first model, and the first model corresponds to a first reference signal pattern; therefore, the reference signal pattern corresponding to the first channel reconstruction method is the first reference signal pattern.

[0138] In one possible implementation, after receiving the first information, the first device can obtain the neural network (i.e., the first model) corresponding to the first channel reconstruction method from the correspondence between multiple neural networks and multiple channel reconstruction methods based on the first information; and then determine the reference signal pattern corresponding to the neural network as the first reference signal pattern.

[0139] Optionally, the first device can determine the correspondence between multiple sets of neural networks and channel reconstruction methods (as shown in Table 1), wherein the neural network in each set is obtained based on the channel reconstruction method in that set. Optionally, the first device can generate the above correspondence, or obtain the above correspondence from the second device or other devices; the second device can also store the correspondence (as shown in Table 1).

[0140] Table 1

[0141] Table 1 illustrates, for example, the correspondence between the neural network, the channel reconstruction method, and the reference signal. For instance, the first device may store Table 1, and if the first information acquired by the first device is used to indicate Type 1, then the first device may determine that the first model is Model 1 and the first reference signal pattern is Pattern 1.

[0142] Optionally, Table 1 may include only the first and second columns, or only the first and third columns, or only the second or third column. It should be noted that the above correspondence can also be expressed in words or other forms, and this application does not limit this.

[0143] For example, if Table 1 only includes the first and second columns, the neural networks in Table 1 (such as Model 1 and Model 2) can be untrained initial neural networks. Assuming the first information is used to indicate Type 1, the first device can determine Model 1 based on Table 1 and Type 1; then, Model 1 is trained to obtain the neural network and Pattern 1 corresponding to Type 1; and Pattern 1 is used to determine the first reference signal pattern. As another example, if Table 1 only includes the first and second columns, the neural networks in Table 1 (such as Model 1 and Model 2) can be trained initial neural networks. Assuming the first information is used to indicate Type 1, the first device can input sample data (such as channel information) into Model 1 to obtain Pattern 1 or local channel information, which is used to acquire Pattern 1; and Pattern 1 is used to determine the first reference signal pattern.

[0144] For example, if Table 1 only includes the first and third columns, the reference signal pattern can be obtained by a neural network based on the channel reconstruction method located in the same row. Assuming that the first information is used to indicate Type 1, the first device can determine that pattern 1 is the first reference signal pattern based on Table 1 and Type 1.

[0145] For example, the process of determining the neural network and reference signal pattern based on the channel reconstruction method can be found in the training process described below. This application does not limit the specific structure, type, or training method (e.g., the type of loss function used, individual training, or joint training) of the neural network.

[0146] For example, the second information can be sent via downlink control information (DCI), or it can be sent via other methods, which are not limited in this application.

[0147] Optionally, after receiving the first information, the first device may acquire (or pre-store) the correspondence between the channel reconstruction method and the reference signal pattern, which may include the first channel reconstruction method corresponding to the first reference signal pattern; or, after receiving the first information, the first device may acquire (or pre-store) the correspondence between the channel reconstruction method and the model, and the correspondence between the model and the reference signal pattern, which may include the first channel reconstruction method corresponding to the first model, and the first model corresponding to the first reference signal pattern.

[0148] The first reference signal pattern corresponding to the first model can mean that the first reference signal pattern is designed (or generated) based on the first model, or that the output of the first model includes the first reference signal pattern.

[0149] Optionally, the first model corresponding to the first channel reconstruction method can mean that the first model can be trained based on the first channel reconstruction method. It should be noted that the first model can be trained before the first device receives the aforementioned second information, or it can be trained after the first device receives the aforementioned second information; this application does not limit this.

[0150] For example, the first device can train the initial neural network (or pilot pattern design network) multiple times based on the first channel reconstruction method; wherein, the multiple trainings include the i-th training, and the i-th training includes: the first device transferring the i-th channel information The neural network obtained from the (i-1)th training iteration is input to obtain the i-th reference signal pattern (or pilot pattern i); the first device, based on the i-th reference signal pattern and the first channel reconstruction method (or Type 1), obtains the i-th reconstructed channel information. If the i-th training iteration does not meet the training requirements, the first device can reconstruct the channel information based on the i-th iteration. and the i-th channel information The neural network obtained from the (i-1)th training is adjusted to obtain the neural network obtained from the i-th training. If the i-th training meets the training requirements, the first device determines the neural network obtained from the (i-1)th training as the first model, and the first reference signal pattern is the i-th reference signal pattern, where i is a positive integer.

[0151] As shown in Figure 3B, assuming the i-th training does not meet the training requirements, then after obtaining the neural network from the i-th training, the first device performs the (i+1)-th training until the j-th reconstructed channel information. To meet the training requirements, the first device determines the neural network obtained from the (j-1)th training as the first model, and the first reference signal pattern is the j-th reference signal pattern, where j is a positive integer. In this application, the neural network obtained from the i-th training can refer to any neural network obtained from multiple training sessions.

[0152] The training requirements can refer to the criteria for determining whether training is complete. For example, the criteria for determining whether training is complete could be: the total number of iterations (i.e., the number of training iterations, or the number of epochs) reaching a first threshold; or, based on the input (such as... ) and output (such as The loss function value obtained reaches a first threshold; or other conditions, which are not limited in this application. The i-th channel information may refer to the channel information used in the i-th training. The channel information used in the i-th training may be one or more channel information, such as the i-th channel information being a sample set including one or more channel information. The channel information used in each training process may be the same, such as the i-th channel information being the same as the (i+1)-th channel information, both being the aforementioned sample set. For example, Used to represent a sample set that includes information from multiple channels. Used to represent the output corresponding to these multiple channel information.

[0153] For example, the first training can be as follows: the first device inputs the first channel information H1 into the neural network obtained from the 0th training (i.e., the initial neural network) to obtain the first reference signal pattern (or pilot pattern 1); the first device obtains the first reconstructed channel information based on the first reference signal pattern and the first channel reconstruction method (or Type 1). like If the training requirements are not met, the first device can be based on H1 and The initial neural network is adjusted to obtain the neural network obtained from the first training; if If the training requirements are met, the first device determines the initial neural network as the first model, and the first reference signal pattern as the 1st reference signal pattern, where i is a positive integer. Assume... If the training requirements are not met, then after obtaining the neural network from the first training, the first device performs a second training, and so on, until the j-th reconstructed channel information is obtained. To meet the training requirements, the first device determines the neural network obtained from the (j-1)th training as the first model, and the first reference signal pattern as the j-th reference signal pattern, where j is a positive integer. Optionally, the output of the neural network obtained from the i-th training (such as the initial neural network or the first model) can be information about the reference signal (such as channel information corresponding to the position of the reference signal), or a reference signal pattern, wherein the information about the reference signal is used to generate the reference signal pattern. For example, the output of the first model can be channel information corresponding to the position of the first reference signal, or the first reference signal pattern, wherein the channel information corresponding to the position of the first reference signal is used to generate the first reference signal pattern.

[0154] Optionally, the first device obtains the i-th reconstructed channel information based on the i-th reference signal pattern and the first channel reconstruction method (or Type 1). The process may include channel estimation and other processes, which are not limited in this application.

[0155] Optionally, the training of the first model can be performed by the first device or by other devices (such as a server), and this application does not limit this.

[0156] For example, the input of the above neural network (or pilot pattern design network, such as the first model) can be complete channel information, and its output can be local channel information (or the time-frequency spatial domain resources corresponding to the local channel information, i.e., reference signal pattern).

[0157] In this application, channel information refers to information that reflects channel characteristics and / or channel quality. As an example, channel information includes at least one of the following: channel state information (such as CSI), time-varying channel information, or channel frequency offset information, or information obtained based on channel state information (such as information obtained by multiplying CSI by a precoding matrix). That is to say, the input and output of the aforementioned neural network (such as the first model) can be the aforementioned channel information.

[0158] For example, CSI may include at least one of the following: precoding matrix indicator (PMI), channel quality indicator (CQI), rank indicator (RI), layer indicator (LI), reference signal received power (RSRP), CSI-RS resource indicator (CRI), synchronization signal / physical broadcast channel block resource indicator (SSBRI), etc.

[0159] Step S303: The first device sends a first reference signal based on the first reference signal pattern.

[0160] Correspondingly, the second device receives the first reference signal from the first device based on the first reference signal pattern.

[0161] For example, the first reference signal is DMRS, CSI-RS, or SRS, and this application does not limit the first reference information.

[0162] Optionally, if the first reference signal is downlink DMRS, the first device can be a network device and the second device can be a terminal. Examples of embodiments in this scenario can be found in Figure 4. If the first reference signal is uplink DMRS, the first device can be a terminal and the second device can be a network device. Examples of embodiments in this scenario can be found in Figure 6. If the first reference signal is CSI-RS, the first device can be a network device and the second device can be a terminal. Examples of embodiments in this scenario can be found in Figure 5. If the first reference signal is SRS, the first device can be a terminal and the second device can be a network device. Examples of embodiments in this scenario can be found in Figure 6.

[0163] Step S304: The second device obtains the first channel information based on the first reference signal and the first channel reconstruction method.

[0164] It should be noted that step S304 is an optional step.

[0165] In one implementation, the second device can perform channel estimation based on the received first reference signal to obtain second channel information; and reconstruct the complete channel using the second channel information through a first channel reconstruction method to obtain the first channel information.

[0166] Optionally, the second device may send fifth information to the first device, and correspondingly, the first device receives the fifth information. The fifth information is used to indicate the first channel information, which is obtained based on the first reference signal and the first channel reconstruction method. For example, the first reference signal is CSI-RS, and the first channel information can be channel state information (CSI); the first reference signal can also be other reference signals, and the first channel information can also be the channel information corresponding to other reference signals. This application does not limit this.

[0167] Figure 3C illustrates an exemplary flowchart of the process for obtaining the first channel information. As shown in Figure 3C, S1: The second device can determine type1 from multiple channel reconstruction methods; S2: The second device indicates type1 to the first device; S3: The first device determines the first reference signal pattern based on type1, such as determining the output of the first model trained based on type1 as the first reference signal pattern. For the specific determination process, please refer to step S302; S4: The first device indicates the first reference signal pattern to the second device; S5: The first reference signal is received based on the first reference signal pattern; Channel estimation is performed based on the first reference signal to obtain the second channel information; S6: The first channel information is obtained based on type1 and the second channel information.

[0168] Optionally, the second device sends a sixth message, which is used to instruct the second channel reconstruction method.

[0169] The method embodiment shown in Figure 3A above includes many possible implementation schemes. Some of these implementation schemes will be illustrated below with reference to Figures 4 to 8A. It should be noted that related concepts, operations or logical relationships not explained in Figures 4 to 8A can be referred to the corresponding descriptions in the embodiment shown in Figure 3A.

[0170] In this application, the embodiments shown in Figures 4 to 8A can be used as a single embodiment, and the embodiments shown in Figures 4 to 8A can all be independent of the technical solution in Figure 3A; some steps in the embodiments shown in Figures 4 to 8A can also be used as a single embodiment.

[0171] Figure 4 is a flowchart of another communication method provided in an embodiment of this application.

[0172] This application embodiment uses the example of a first device as a network device, a second device as a terminal, a first reference signal as a downlink pilot (as in downlink DMRS), a first channel reconstruction method as a first interpolation method, and a second information as a pilot pattern indication.

[0173] The functions performed by the network device in this application can also be performed by modules (e.g., chips) in the network device; the functions performed by the terminal in this application can also be performed by modules (e.g., chips) in the terminal.

[0174] S401 and S402 can be optional steps. For example, the information involved in S401 can be pre-configured, and the network device is configured with the terminal's channel reconfiguration capability, so the terminal does not need to report the channel reconfiguration capability. If the first interpolation method in S402 can be determined, predefined, or preset by the network device, then the terminal does not need to report the first interpolation method.

[0175] As shown in Figure 4, the method may include the following steps:

[0176] S401: Terminal reporting channel reconfiguration capability.

[0177] Among them, the terminal's channel reconstruction capability is used to indicate whether the terminal supports channel reconstruction based on pilot patterns determined by neural networks.

[0178] Optionally, the terminal's channel reconstruction capability can also be used to indicate whether the terminal supports channel reconstruction based on interpolation methods.

[0179] In this application, the channel reconstruction capability of the terminal may also refer to whether the terminal supports the communication method provided in this application, such as whether the terminal supports selecting the interpolation method, and whether the terminal can perform channel reconstruction based on the pilot pattern determined by the first model corresponding to the interpolation method.

[0180] S402: The terminal sends first information, which is used to indicate the first interpolation method.

[0181] In one implementation, the terminal selects a first interpolation method (e.g., type 1) from the interpolation methods (type1, type2, ...) known to the transceiver; then, the terminal reports the first interpolation method. For example, the first interpolation method may be determined based on factors such as the accuracy of the reconstructed channel and the complexity of the interpolation method.

[0182] For example, the first interpolation method may include linear interpolation, LMMSE interpolation, etc., and this application does not limit it.

[0183] Optionally, the first interpolation method may also be determined by the network device or other devices, and this application does not limit it.

[0184] S403: The network device determines a first model based on a first interpolation method.

[0185] In one implementation, the network device can select the pilot pattern design network (i.e., the first model) to be used based on the first interpolation method selected by the terminal. The first model can be generated and trained after the terminal reports its capabilities / selects the first interpolation method, or it can be generated and trained in advance before the terminal reports its capabilities / selects the first interpolation method. There is no temporal order between model generation and training and terminal capability reporting / selection of the first interpolation method.

[0186] Optionally, the network device may also pre-store the correspondence between the aforementioned multiple neural networks and multiple interpolation methods. The multiple neural networks and multiple interpolation methods may be in a one-to-one correspondence, or the terminal or other device may indicate this correspondence to the network device. Examples can be found in the relevant description in step S302, and will not be repeated here.

[0187] S404: The network device sends the pilot pattern indication corresponding to the first model to the terminal.

[0188] The pilot pattern indicator can be used to indicate any combination of antenna ports, time domain, and frequency domain. For example, the pilot pattern indicator corresponding to the first model described above can be represented by an index set I, where the index set I = {I...} 1 ,I 2 ,…,I k}, where k is the number of pilot signals, k is a positive integer, and the index of the i-th pilot is...

[0189] S405: The network device sends a pilot signal to the terminal.

[0190] Optionally, the process may also include data transfer.

[0191] S406: The terminal performs channel reconstruction based on the pilot signal and pilot pattern indication to obtain the first channel information.

[0192] For example, step S406 may include the following steps S4061 to S4063:

[0193] S4061: Pilot pattern-based indication (I i (Position) to obtain pilot signal p′.

[0194] S4062: Channel Estimation: Based on the pilot signal p′ and the channel estimation method f(·), obtain the channel information of the pilot position. Channel estimation methods f(·) include, but are not limited to, the minimum mean square error (MMSE) method.

[0195] S4063: Channel reconstruction based on the first interpolation method: based on I i Channel information corresponding to the location Using the selected first interpolation method, the complete channel is reconstructed to obtain complete channel information. (i.e., first channel information).

[0196] S407: The terminal transmits data with the network device based on the first channel information.

[0197] S408: The terminal sends the sixth information, which is used to indicate the second interpolation method.

[0198] Optionally, if the terminal changes the channel reconstruction method, such as changing it from the first interpolation method to the second interpolation method, the terminal can report the second interpolation method. Correspondingly, the network device can determine a second model based on the second interpolation method, send a pilot pattern indication corresponding to the second model to the terminal, and send a pilot signal to the terminal. Accordingly, the terminal performs channel reconstruction based on the pilot signal and the pilot pattern indication to obtain second channel information; the terminal then transmits data with the network device based on the second channel information. This process can be exemplarily described in steps S402 to S407 above.

[0199] Figure 5 is a flowchart of another communication method provided in an embodiment of this application.

[0200] This application embodiment uses the example of a first device as a network device, a second device as a terminal, a first reference signal as a downlink pilot (as in downlink CSI-RS), a first channel reconstruction method as a first interpolation method, and a second information as a pilot pattern indication.

[0201] The functions performed by the network device in this application can also be performed by modules (e.g., chips) in the network device; the functions performed by the terminal in this application can also be performed by modules (e.g., chips) in the terminal.

[0202] S501 and S502 can be optional steps. For example, the information involved in S501 can be pre-configured, and the network device is configured with the terminal's channel reconfiguration capability, so the terminal does not need to report the channel reconfiguration capability. If the first interpolation method in S502 can be determined, predefined, or preset by the network device, then the terminal does not need to report the first interpolation method.

[0203] As shown in Figure 5, the method may include the following steps:

[0204] S501: Terminal reporting channel reconfiguration capability.

[0205] S502: The terminal sends first information to the network device, the first information being used to indicate the first interpolation method.

[0206] S503: The network device determines a first model based on the first interpolation method.

[0207] Optionally, the network device may also pre-store the correspondence between the aforementioned multiple neural networks and multiple interpolation methods. The multiple neural networks and multiple interpolation methods may be in a one-to-one correspondence, or the terminal or other device may indicate this correspondence to the network device. Examples can be found in the relevant description in step S302, and will not be repeated here.

[0208] S504: The network device sends the pilot pattern indication corresponding to the first model to the terminal.

[0209] S505: Network devices send CSI-RS to terminals.

[0210] S506: The terminal performs channel reconstruction based on CSI-RS and pilot pattern indication to obtain CSI.

[0211] For example, step S506 may include the following steps S5061 to S5063:

[0212] S5061: Terminal obtains CSI-RS(p′).

[0213] S5062: The terminal performs channel estimation, for example, by obtaining channel information of the pilot position based on CSI-RSp′ and the channel estimation method f(·). Channel estimation methods f(·) include, but are not limited to, the MMSE method.

[0214] S5063: Channel reconstruction by the terminal based on the first interpolation method, such as based on pilot pattern indication (e.g., I...). i Using the channel information corresponding to the location and the first interpolation method, the complete channel is reconstructed to obtain the complete channel information. (i.e., first channel information).

[0215] Steps S501 to S506 can be found in the relevant parts of Figure 4, and will not be repeated here.

[0216] S507: Terminal reports CSI.

[0217] In other words, the terminal sends CSI to the network device.

[0218] S508: Terminals and network devices transmit data based on CSI.

[0219] Optionally, in the embodiment shown in Figure 5, if the terminal changes the channel reconstruction method, such as changing the channel reconstruction method from the first interpolation method to the second interpolation method, the terminal can report the second interpolation method. Furthermore, the process by which the network device and the terminal can perform channel reconstruction based on the second interpolation method can be found in the relevant content above (such as step S408), and will not be repeated here.

[0220] Figure 6 is a flowchart of another communication method provided in an embodiment of this application.

[0221] This application embodiment uses a first device as the terminal, a second device as the network device, a first reference signal as an uplink pilot (such as uplink DMRS), a first channel reconstruction method as a first interpolation method, and a second information as a pilot pattern indication as an example for description.

[0222] The functions performed by the network device in this application can also be performed by modules (e.g., chips) in the network device; the functions performed by the terminal in this application can also be performed by modules (e.g., chips) in the terminal.

[0223] S601 and S602 can be optional steps. For example, the information involved in S601 can be pre-configured, and the network device is configured with the terminal's channel reconfiguration capability, so the terminal does not need to report the channel reconfiguration capability. If the first interpolation method in S602 can be determined, predefined, or preset by the network device, then the terminal does not need to report the first interpolation method.

[0224] As shown in Figure 6, the method may include the following steps:

[0225] S601: Terminal reporting channel reconfiguration capability.

[0226] S602: The network device sends first information to the terminal, the first information being used to indicate the first interpolation method.

[0227] S603: The terminal determines the first model based on the first interpolation method.

[0228] Optionally, the terminal may also pre-store the correspondence between the aforementioned multiple neural networks and multiple interpolation methods. The multiple neural networks and multiple interpolation methods may be in a one-to-one correspondence, or the correspondence may be indicated to the terminal by a network device or other device. For examples, please refer to the relevant description in step S302, which will not be repeated here.

[0229] S604: The terminal sends the pilot pattern indication corresponding to the first model to the network device.

[0230] S605: The terminal sends pilot signals to the network device.

[0231] S606: The network device performs channel reconstruction based on the pilot signal and pilot pattern indication to obtain the first channel information.

[0232] For example, step S606 may include the following steps S6061 to S6063:

[0233] S6061: The terminal acquires the pilot signal (p′).

[0234] S6062: The terminal performs channel estimation, for example, by obtaining channel information of the pilot position based on the pilot signal p′ and the channel estimation method f(·). Channel estimation methods f(·) include, but are not limited to, the MMSE method.

[0235] S6063: Channel reconstruction by the terminal based on the first interpolation method, such as based on pilot pattern indication (e.g., I...). i Using the channel information corresponding to the location and the first interpolation method, the complete channel is reconstructed to obtain the complete channel information. (i.e., first channel information).

[0236] Steps S601 to S606 can be found in the relevant parts of Figure 4, and will not be repeated here.

[0237] S607: The terminal transmits data with the network device based on the first channel information.

[0238] Optionally, in the embodiment shown in Figure 6, if the network device changes the channel reconstruction method, such as changing the channel reconstruction method from the first interpolation method to the second interpolation method, the network device can send sixth information to the terminal, which is used to indicate the second interpolation method. Furthermore, the process by which the network device and the terminal can perform channel reconstruction based on the second interpolation method can be found in the relevant content above (such as step S408), and will not be repeated here.

[0239] The technical solution of this application is described below with reference to specific embodiments. Figure 7 is a flowchart illustrating another communication method provided in an embodiment of this application.

[0240] Please refer to Figure 7. The method may include the following steps:

[0241] Step S701: The second device determines the first channel reconstruction method, which corresponds to the first model.

[0242] For example, the second device can determine the first information, that is, the second device determines the first channel reconstruction method. For instance, the second device can determine the first channel reconstruction method from channel reconstruction methods supported by the first device and the second device.

[0243] For example, the first channel reconstruction method may be linear interpolation, LMMSE interpolation, or other channel reconstruction methods, and this application does not limit this method.

[0244] In one implementation, the first device can send fourth information to the second device, indicating that the first device supports channel reconstruction using a reference signal pattern corresponding to the neural network; correspondingly, the second device receives the fourth information from the first device; and then, the second device can determine a first channel reconstruction method. For example, the first device is a terminal, and the second device is a network device. The terminal can send the fourth information to the network device, and correspondingly, the network device receives the fourth information from the terminal; then, the network device determines the first channel reconstruction method. This method can avoid the waste of communication resources caused by the first device not supporting channel reconstruction using a reference signal pattern corresponding to the neural network.

[0245] Optionally, the second device may also pre-store the correspondence between the aforementioned multiple neural networks and multiple channel reconstruction methods. The multiple neural networks and multiple channel reconstruction methods may be in a one-to-one correspondence, or the correspondence may be indicated to the second device by the second device or other devices. Examples can be found in the relevant description in step S302, and will not be repeated here.

[0246] Step S702: The second device sends second information to the first device, the second information being used to indicate the first reference signal pattern corresponding to the first model.

[0247] Correspondingly, the first device receives the second information from the second device.

[0248] In some embodiments, after determining the first channel reconstruction method, the first device may indicate to the second device a reference signal pattern (i.e., the first reference signal pattern) corresponding to the first channel reconstruction method. It should be understood that the first channel reconstruction method corresponds to a first model, and the first model corresponds to the first reference signal pattern; therefore, the reference signal pattern corresponding to the first channel reconstruction method is the first reference signal pattern.

[0249] For example, the second information can be sent via DCI, or by other methods, which are not limited in this application.

[0250] Optionally, the second device may acquire (or pre-store) the correspondence between the channel reconstruction method and the reference signal pattern, which may include the first channel reconstruction method corresponding to the first reference signal pattern; or, after receiving the first information, the first device may acquire (or pre-store) the correspondence between the channel reconstruction method and the model, and the correspondence between the model and the reference signal pattern, which may include the first channel reconstruction method corresponding to the first model, and the first model corresponding to the first reference signal pattern.

[0251] The first reference signal pattern corresponding to the first model can mean that the first reference signal pattern is designed (or generated) based on the first model, or that the output of the first model includes the first reference signal pattern.

[0252] Optionally, the first model corresponding to the first channel reconstruction method can mean that the first model can be trained based on the first channel reconstruction method. It should be noted that the first model can be trained before the first device receives the aforementioned second information, or it can be trained after the first device receives the aforementioned second information; this application does not limit this.

[0253] For example, the process of training the first model using the second device can be seen in Figure 3A and related descriptions, which will not be repeated here.

[0254] Optionally, the training of the first model can also be performed by other devices (such as servers), and this application does not limit this.

[0255] Step S703: The first device sends a first reference signal based on the first reference signal pattern.

[0256] Correspondingly, the second device receives the first reference signal from the first device based on the first reference signal pattern.

[0257] For example, the first reference signal is DMRS, CSI-RS, or SRS, and this application does not limit the first reference information.

[0258] Step S704: The second device obtains the first channel information based on the first reference signal and the first channel reconstruction method.

[0259] It should be noted that step S704 is an optional step.

[0260] In one implementation, the second device can perform channel estimation based on the received first reference signal to obtain second channel information; and reconstruct the complete channel using the second channel information through a first channel reconstruction method to obtain the first channel information.

[0261] Optionally, the second device may send fifth information to the first device, and the first device receives the fifth information. The fifth information is used to indicate the first channel information, which is obtained based on the first reference signal and the first channel reconstruction method.

[0262] Figure 3C illustrates an exemplary flowchart of the process for obtaining the first channel information. As shown in Figure 3C, S1: The second device can determine type1 from multiple channel reconstruction methods; S2: The first device indicates type1 to the second device; S3: The first device determines the first reference signal pattern based on type1, such as determining the output of the first model trained based on type1 as the first reference signal pattern. For the specific determination process, please refer to step S702; S4: The second device indicates the first reference signal pattern to the first device; S5: The first reference signal is received based on the first reference signal pattern; Channel estimation is performed based on the first reference signal to obtain the second channel information; S6: The first channel information is obtained based on type1 and the second channel information.

[0263] Optionally, the second device sends a sixth message, which is used to instruct the second channel reconstruction method.

[0264] The following is a schematic diagram of a communication device according to an embodiment of this application. Referring to FIG8A, the communication device can be used to execute the process performed by the first device in the embodiment shown in FIG3A, and for details, please refer to the relevant description in the foregoing method embodiments.

[0265] The communication device 900 includes a transceiver module 901 and a processing module 902.

[0266] The processing module 902 is used for data processing. The transceiver module 901 can implement the corresponding communication functions. The transceiver module 901 can also be called a communication interface or a communication module.

[0267] Optionally, the communication device 900 may further include a storage module, which can be used to store program code and / or program instructions and / or data. The processing module 902 can read the instructions and / or data in the storage module so that the communication device 900 can implement the aforementioned method embodiments.

[0268] The communication device 900 can be used to perform the actions performed by the first device in the above method embodiments. For example, it can be the first device, a communication module within the first device, or a circuit or chip in the first device responsible for communication functions. The communication device 900 can be the first device or a component configurable on the first device. The processing module 902 is used to perform processing-related operations on the first device side in the above method embodiments. The transceiver module 901 is used to perform receiving-related operations on the first device side in the above method embodiments.

[0269] Optionally, the transceiver module 901 may include a sending module and / or a receiving module. The sending module is used to perform the sending operation in the above method embodiments. The receiving module is used to perform the receiving operation in the above method embodiments.

[0270] It should be noted that the communication device 900 may include a transmitting module but not a receiving module. Alternatively, the communication device 900 may include a receiving module but not a transmitting module. Specifically, it depends on whether the above-described scheme performed by the communication device 900 includes both transmitting and receiving actions. For example, the communication device 900 is used to perform the actions performed by the first device in the embodiments shown in Figures 3A to 6. For details, please refer to the relevant descriptions in the embodiments shown in Figures 3A to 6, which will not be elaborated here. For example, the communication device 900 is used to perform the following scheme:

[0271] The transceiver module 901 is used to acquire first information, which is used to indicate a first channel reconstruction method, and the first channel reconstruction method corresponds to a first model; to send second information, which is used to indicate a first reference signal pattern corresponding to the first model; and to send a first reference signal based on the first reference signal pattern.

[0272] For other implementation methods, please refer to the relevant descriptions in the embodiments shown in Figures 3A to 6 above.

[0273] It should be understood that the specific procedures for each module to perform the above-mentioned corresponding processes have been described in detail in the above method embodiments, and will not be repeated here for the sake of brevity.

[0274] Optionally, when the communication device 900 is a first device or a communication module within a first device, the processing module 902 in the above embodiments can be implemented by at least one processor or processor-related circuitry. Specifically, the processor may include a modem chip, or a SoC chip or SIP chip containing a modem core. The transceiver module 901 can be implemented by a transceiver or transceiver-related circuitry. The transceiver module 901 may also be referred to as a communication module or communication interface. The storage module can be implemented by at least one memory.

[0275] Optionally, when the communication device 900 is a circuit or chip in the first device responsible for communication functions, such as a modem chip or a SoC chip or SIP chip containing a modem core, the function of the processing module 902 can be implemented by a circuit system in the aforementioned chip that includes one or more processors or processing cores. The function of the transceiver module 901 can be implemented by the interface circuit or data transceiver circuit on the aforementioned chip.

[0276] The following is a schematic diagram of another communication device according to an embodiment of this application. Referring to FIG8B, the communication device can be used to execute the process performed by the second device in the embodiments shown in FIG3A to FIG6, and the details can be found in the relevant descriptions in the foregoing method embodiments.

[0277] The communication device 1000 includes a transceiver module 1001. Optionally, the communication device 1000 may also include a processing module 1002.

[0278] The processing module 1002 is used for data processing. The transceiver module 1001 can implement the corresponding communication functions. The transceiver module 1001 can also be called a communication interface or a communication module.

[0279] Optionally, the communication device 1000 may further include a storage module, which can be used to store program code, program instructions and / or data. The processing module 1002 can read the instructions and / or data in the storage module so that the communication device 1000 can implement the aforementioned method embodiments.

[0280] The communication device 1000 can be used to perform the actions performed by the second device in the above method embodiments. For example, it can be the second device, a communication module within the second device, or a circuit or chip in the second device responsible for communication functions. The communication device 1000 can be the second device or a component configurable on the second device. The processing module 1002 is used to perform processing-related operations on the second device side in the above method embodiments. The transceiver module 1001 is used to perform receiving-related operations on the second device side in the above method embodiments.

[0281] Optionally, the transceiver module 1001 may include a sending module and a receiving module. The sending module is used to perform the sending operation in the above method embodiments. The receiving module is used to perform the receiving operation in the above method embodiments.

[0282] It should be noted that the communication device 1000 may include a transmitting module but not a receiving module. Alternatively, the communication device 1000 may include a receiving module but not a transmitting module. Specifically, it depends on whether the above-described scheme executed by the communication device 1000 includes both transmitting and receiving actions. For example, the communication device 1000 is used to execute the actions performed by the second device in the embodiments shown in Figures 3A to 6. For details, please refer to the relevant descriptions in the embodiments shown in Figures 3A to 6, which will not be elaborated here. For example, the communication device 1000 is used to execute the following scheme:

[0283] Transceiver module 1001 is configured to: transmit first information, the first information indicating a first channel reconstruction method, the first channel reconstruction method corresponding to a first model; receive second information, the second information indicating a first reference signal pattern corresponding to the first model; and receive a first reference signal based on the first reference signal pattern.

[0284] The processing module 1002 is used to obtain the first channel information based on the first reference signal and the first channel reconstruction method.

[0285] For other implementation methods, please refer to the relevant descriptions in the embodiments shown in Figures 3A to 6 above.

[0286] It should be understood that the specific procedures for each module to perform the above-mentioned corresponding processes have been described in detail in the above method embodiments, and will not be repeated here for the sake of brevity.

[0287] The processing module 1002 in the above embodiments can be implemented by at least one processor or processor-related circuitry. The transceiver module 1001 can be implemented by a transceiver or transceiver-related circuitry. The transceiver module 1001 can also be referred to as a communication module or communication interface. The storage module can be implemented by at least one memory.

[0288] Figure 9 illustrates a possible structural schematic of a communication device. It will be understood that the communication device 110 includes means of the necessary form, such as modules, units, elements, circuits, or interfaces, appropriately configured together to perform this solution. The communication device 110 may be the first or second device described above, or a component (e.g., a chip) within these devices, used to implement the methods described in the above method embodiments.

[0289] The communication device 110 includes one or more processors 111. These processors 111 can be general-purpose processors or dedicated processors, such as baseband processors or central processing units. The baseband processor can process communication protocols and communication data, while the central processing unit can control the communication device (e.g., RAN node, terminal, or chip), execute software programs, and process data from the software programs.

[0290] Optionally, in one design, the processor 111 may include a program 113 (sometimes referred to as code or instructions) that can be run on the processor 111 to cause the communication device 110 to perform the methods described in the above embodiments.

[0291] Optionally, the communication device 110 may include one or more memories 112 storing a program 114 (sometimes referred to as code or instructions), which can be run on the processor 111 to cause the communication device 110 to perform the methods described in the above method embodiments.

[0292] Optionally, the processor 111 and / or memory 112 may include AI modules 117 and 118, which are used to implement AI-related functions. The AI ​​modules may be implemented through software, hardware, or a combination of both. For example, the AI ​​module may include a RAN intelligent controller (RIC) module. For example, the AI ​​module may be a near real-time RIC or a non-real-time RIC.

[0293] Optionally, the processor 111 and / or memory 112 may also store data. The processor and memory may be configured separately or integrated together.

[0294] Optionally, the communication device 110 may further include a transceiver 115 and / or an antenna 116. The processor 111, sometimes referred to as a processing unit, controls the communication device (e.g., a RAN node or terminal). The transceiver 115, sometimes referred to as a transceiver unit, transceiver, transceiver circuit, or transceiver, is used to realize the transmission and reception functions of the communication device through the antenna 116.

[0295] In this application, when the first device is a terminal, the second device can be a network device; when the first device is a network device, the second device can be a terminal. The following provides exemplary descriptions of terminals and network devices.

[0296] This application also provides a communication device 1200, which can be a terminal, a processor in the terminal, or a chip. The communication device 1200 can be used to perform the operations performed by the terminal in the above method embodiments.

[0297] When the communication device 1200 is a terminal, Figure 10 shows a schematic diagram of the terminal structure. As shown in Figure 10, the terminal includes a processor, a memory, and a transceiver. The memory can store computer program code, and the transceiver includes a transmitter 1231, a receiver 1232, radio frequency circuitry (not shown in the figure), an antenna 1233, and input / output devices (not shown in the figure).

[0298] The processor is mainly used to process communication protocols and communication data; control terminals; execute software programs; and process data from software programs.

[0299] Memory is mainly used to store software programs and data.

[0300] Radio frequency (RF) circuits are mainly used for the conversion between baseband signals and RF signals, as well as for the processing of RF signals.

[0301] Antennas are primarily used for transmitting and receiving radio frequency signals in the form of electromagnetic waves.

[0302] Input / output devices can include touchscreens, displays, or keyboards. They are primarily used to receive user input and output data to the user. It should be noted that some types of terminals may not have input / output devices.

[0303] When data needs to be transmitted, the processor performs baseband processing on the data to be transmitted and outputs a baseband signal to the radio frequency (RF) circuit. The RF circuit then processes the baseband signal and transmits it outwards as electromagnetic waves via an antenna. When data is sent to the terminal, the RF circuit receives the RF signal through the antenna. The RF circuit converts the RF signal back into a baseband signal and outputs it to the processor. The processor converts the baseband signal back into data and processes that data. For ease of explanation, Figure 10 only shows one memory, processor, and transceiver. In actual terminal products, there may be one or more processors and one or more memories. Memory can also be called storage medium or storage device, etc. Memory can be independent of the processor or integrated with it; this embodiment does not limit this.

[0304] In the embodiments of this application, the antenna and radio frequency circuit with transceiver function can be regarded as the transceiver module of the terminal, and the processor with processing function can be regarded as the processing module of the terminal.

[0305] As shown in Figure 10, the terminal includes a processor 1210, a memory 1220, and a transceiver 1230. The processor 1210 can also be referred to as a processing unit, processing board, processing module, or processing device, etc. The transceiver 1230 can also be referred to as a transceiver unit, transceiver, or transceiver device, etc.

[0306] Optionally, the device in transceiver 1230 used to implement the receiving function can be considered a receiving module, and the device in transceiver 1230 used to implement the transmitting function can be considered a transmitting module. That is, transceiver 1230 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.

[0307] The processor 1210 is used to execute the terminal-side processing operations in the embodiments shown in Figures 3A to 6. The transceiver 1230 is used to execute the terminal-side transmission and reception operations in the embodiments shown in Figures 3A to 6.

[0308] It should be understood that Figure 10 is merely an example and not a limitation, and the terminal described above, including the transceiver module and the processing module, may not depend on the structure shown in Figure 8A or Figure 10.

[0309] When the communication device 1200 is a chip, the chip includes a processor, a memory, 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 terminal's sending operation can be understood as the chip's output, and the terminal's receiving operation in the above method embodiments can be understood as the chip's input.

[0310] This application also provides a communication device 1300, which can be an access network device or a chip. The communication device 1300 can be used to perform the operations performed by the network device in the embodiments shown in Figures 3A to 6.

[0311] When the communication device 1300 is a network device, such as a base station, Figure 11 shows a simplified schematic diagram of a base station structure. The base station includes parts 1310, 1320, and 1330.

[0312] The 1310 section is mainly used for baseband processing and controlling the base station; the 1310 section is usually the control center of the base station, which can be called the processor, and is used to control the base station to perform the processing operations on the network device side in the above method embodiments.

[0313] Section 1320 is primarily used to store computer program code and data.

[0314] Section 1330 is primarily used for transmitting and receiving radio frequency (RF) signals, as well as converting RF signals to baseband signals. Section 1330 is commonly referred to as a transceiver module, transceiver, transceiver circuit, or transceiver unit. The transceiver module of section 1330, also known as a transceiver or transceiver unit, includes antenna 1333 and RF circuitry (not shown in the figure), where the RF circuitry is mainly used for RF processing. Optionally, the device in section 1330 that performs the receiving function can be considered a receiver, and the device that performs the transmitting function can be considered a transmitter; that is, section 1330 includes receiver 1332 and transmitter 1331. The receiver can also be called a receiving module, receiver circuit, or receiving circuit, and the transmitter can be called a transmitting module, transmitter, or transmitting circuit.

[0315] Sections 1310 and 1320 may include one or more circuit boards, each of which may include one or more processors and one or more memories. The processors are used to read and execute programs from the memories to implement baseband processing functions and control the base station. If multiple circuit boards exist, they can be interconnected to enhance processing capabilities. As an alternative implementation, multiple circuit boards may share one or more processors, multiple circuit boards may share one or more memories, or multiple circuit boards may simultaneously share one or more processors.

[0316] For example, in one implementation, the transceiver module of section 1330 is used to execute the transceiver-related processes performed by the network device in the embodiments shown in Figures 3A to 6. The processor of section 1310 is used to execute the processing-related processes performed by the network device in the embodiments shown in Figures 3A to 6.

[0317] It should be understood that Figure 11 is merely an example and not a limitation, and the network device described above, including the processor, memory, and transceiver, may not depend on the structure shown in Figure 8B or Figure 11.

[0318] When the communication device 1300 is a chip, the chip includes a processor, which may be an on-chip processor, a microprocessor, or an integrated circuit. Optionally, the communication device 1300 may also include a transceiver, which may be an input / output circuit or a communication interface. Further optionally, the communication device 1300 may also include a memory, which may be built into the chip or be an external memory. In the above method embodiments, the transmitting operation of the network device can be understood as the output of the chip, and the receiving operation of the network device in the above method embodiments can be understood as the input of the chip.

[0319] This application also provides a computer-readable storage medium having stored thereon a computer program or instructions for implementing the method executed by the first device or the second device in the above method embodiments.

[0320] For example, when the computer program or instructions are executed by the computer, the computer can perform the method executed by the first device or the second device in the above method embodiments.

[0321] This application also provides a computer program product containing a program or instructions, which, when executed by a computer, causes the computer to perform the method described in the above method embodiments by the first device or the second device.

[0322] This application also provides a communication system, which includes a first device and a second device. The first device is used to perform some or all of the operations performed by the first device in the embodiments shown in Figures 3A to 6, and the second device is used to perform some or all of the operations performed by the second device in the embodiments shown in Figures 3A to 6.

[0323] This application also provides a chip device, including a processor, for calling computer programs or computer instructions stored in the memory, so that the processor executes the methods provided in the embodiments shown in Figures 3A to 6 above.

[0324] In one possible implementation, the input of the chip device corresponds to the receiving operation in any one of the embodiments shown in Figures 3A to 6, and the output of the chip device corresponds to the transmitting operation in any one of the embodiments shown in Figures 3A to 6.

[0325] Optionally, the processor is coupled to the memory via an interface.

[0326] Optionally, the chip device may also include a memory that stores computer programs or computer instructions.

[0327] The processor mentioned above can be a general-purpose central processing unit, a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits used to control the execution of a program for controlling the method provided in any of the embodiments shown in Figures 3A to 6. The memory mentioned above can be read-only memory (ROM) or other types of static storage devices capable of storing static information and instructions, such as random access memory (RAM).

[0328] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the explanations and beneficial effects of the relevant contents in any of the above-mentioned devices can be referred to the corresponding method embodiments provided above, and will not be repeated here.

[0329] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between apparatuses or units through some interfaces, and may be electrical, mechanical, or other forms.

[0330] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0331] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0332] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the essential contribution of the technical solution of this application, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0333] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit it. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A communication method, characterized in that, For use in a first device, the method includes: Obtain first information, which is used to indicate a first channel reconstruction method, and the first channel reconstruction method corresponds to a first model; Send a second message, the second message being used to indicate the first reference signal pattern corresponding to the first model; Based on the first reference signal pattern, a first reference signal is transmitted.

2. The method of claim 1, wherein, The method further includes: Receive third information from the second device, the third information being used to instruct the second device to support channel reconstruction using a reference signal pattern corresponding to a neural network; The step of obtaining the first information includes: receiving the first information from the second device; Sending the second information includes sending the second information to the second device.

3. The method according to claim 1, characterized in that, Prior to the method, it also includes: Send a fourth message to the second device, the fourth message being used to instruct the first device to support channel reconstruction using a reference signal pattern corresponding to a neural network; The step of obtaining the first information includes: receiving the first information from the second device; Sending the second information includes sending the second information to the second device.

4. The method according to any one of claims 1-3, characterized in that, The method further includes: The fifth information is received, which is used to indicate the first channel information, which is obtained based on the first reference signal and the first channel reconstruction method.

5. The method according to any one of claims 1-4, characterized in that, The method further includes: Based on the first channel reconstruction method, the initial neural network is trained multiple times; The multiple training sessions include the i-th training session, which includes: inputting the i-th channel information into the neural network obtained from the (i-1)-th training session to obtain the i-th reference signal pattern; obtaining the i-th reconstructed channel information based on the i-th reference signal pattern and the first channel reconstruction method; if the i-th training session does not meet the training requirements, adjusting the neural network obtained from the (i-1)-th training session based on the i-th reconstructed channel information and the i-th channel information to obtain the neural network obtained from the i-th training session; if the i-th reconstructed channel information meets the training requirements, determining the neural network obtained from the (i-1)-th training session as the first model, and the first reference signal pattern as the i-th reference signal pattern, where i is a positive integer.

6. The method according to any one of claims 1-5, characterized in that, The method further includes: Based on the first information, a first correspondence is determined, and the first correspondence is used to indicate the neural network corresponding to the first channel reconstruction method; The neural network corresponding to the first channel reconstruction method is determined as the first model.

7. A communication method characterized by comprising: For a second device, the method includes: Send first information, which is used to instruct a first channel reconstruction method, and the first channel reconstruction method corresponds to a first model; Receive second information, the second information being used to indicate the first reference signal pattern corresponding to the first model; Based on the first reference signal pattern, receive the first reference signal; Based on the first reference signal and the first channel reconstruction method, the first channel information is obtained.

8. The method according to claim 7, characterized in that, Prior to the method, it also includes: Send a third message to the first device, the third message being used to instruct the second device to support channel reconstruction using a reference signal pattern corresponding to a neural network; Sending the first information includes: sending the first information to the first device; Receiving the second information includes receiving the second information from the first device.

9. The method of claim 7, wherein, Prior to the method, it also includes: Receive fourth information from the first device, the fourth information being used to indicate that the first device supports channel reconstruction using a reference signal pattern corresponding to a neural network; Sending the first information includes: sending the first information to the first device; Receiving the second information includes receiving the second information from the first device.

10. The method according to any one of claims 7-9, characterized in that, The method further includes: Send a fifth message, which is used to indicate the first channel information.

11. The method according to any one of claims 7-10, characterized in that, The method further includes: A sixth message is sent, which is used to instruct the second channel reconstruction method.

12. A communication method, characterized in that, For a second device, the method includes: Send a second message, the second message being used to indicate the first reference signal pattern corresponding to the first model; Based on the first reference signal pattern, receive the first reference signal; Based on the first reference signal and the first channel reconstruction method, first channel information is obtained, and the first channel reconstruction method corresponds to the first model.

13. The method according to any one of claims 1-12, characterized in that, The first model is trained based on the first channel reconstruction method.

14. The method of any one of claims 1-13, wherein, The first reference signal is a demodulation reference signal, a channel state information reference signal, or a probe reference signal.

15. A communication device, characterized in that, Includes modules or units for performing the method according to any one of claims 1 to 14.

16. 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 and transmit them to the processor or to send signals from the processor to other communication devices, and the processor is used through logic circuits or execution code instructions to cause the communication device to implement the method as described in any one of claims 1 to 14.

17. A readable storage medium, characterized in that, Used to store computer programs or instructions, which are executed by one or more processors, causing an apparatus including the one or more processors to perform the method as described in any one of claims 1 to 14.

18. A computer program product, characterized in that, When the computer program product is run on an electronic device, it causes the electronic device to perform the method as described in any one of claims 1 to 14.

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