Methods for processing channel state information report, communication node and storage medium

Abstract

Disclosed in the present application are methods for processing a channel state information report, a communication node, and a storage medium. A method for processing a channel state information report comprises: receiving configuration information of a second communication node; determining the concurrent number of channel state information (CSI) processing units according to the configuration information; and processing a CSI report by using CSI processing units corresponding to the concurrent number.

Description

Method, communication node and storage medium for processing channel state information report Technical Field

[0001] The present application relates to the field of communication technology, for example, to a method for processing channel state information reports, a communication node, and a storage medium. Background Art

[0002] In 4G and 5G wireless communication technologies, base stations can determine data transmission strategies based on Channel State Information (CSI) reports fed back by terminals and transmit data according to the determined strategies, thereby improving data transmission efficiency. The interaction between the base station and the terminal can be as follows: the base station sends a reference signal; the terminal measures the reference signal, determines the base station-to-terminal CSI, and generates a CSI report for the base station; the base station receives the CSI report sent by the terminal. The base station determines a data transmission strategy based on the channel state represented by the received CSI report and transmits data, thereby improving data transmission efficiency. The accuracy of the channel state represented by the CSI affects the base station's transmission strategy, and thus data transmission efficiency. The more comprehensive the CSI the base station has, the more conducive it is to formulating appropriate data transmission strategies, thereby improving system performance. Therefore, the base station hopes that the terminal can report multiple CSI reports in a short period of time.

[0003] The terminal uses the CSI processing unit to determine the CSI report. However, how to manage the CSI processing unit to process the CSI report to improve the processing efficiency of the CSI report is a problem that needs to be solved.

[0004] Summary of the Invention

[0005] This embodiment of the present application provides a method for processing a channel state information report, which is applied to a first communication node. The method includes:

[0006] Receive configuration information of a second communication node; determine the concurrent number of channel state information (CSI) processing units based on the configuration information; and use the CSI processing units corresponding to the concurrent number to process CSI reports.

[0007] This embodiment of the present application provides a method for processing a channel state information report, which is applied to a second communication node. The method includes:

[0008] Send configuration information to a first communication node; receive a channel state information CSI report processed by the first communication node according to the configuration information; wherein the CSI report is a report formed after the first communication node determines the concurrent number of CSI processing units according to the configuration information and uses the CSI processing units corresponding to the concurrent number for processing.

[0009] An embodiment of the present application provides a first communication node, comprising: a processor; the processor is configured to implement the method for processing channel state information reports of any of the above embodiments when executing a computer program.

[0010] An embodiment of the present application provides a second communication node, comprising: a processor; the processor is configured to implement the method for processing channel state information reports of any of the above embodiments when executing a computer program.

[0011] An embodiment of the present application further provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the method for processing channel state information reports in any of the above embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] FIG1 is a schematic diagram of a network of a wireless communication system provided by an embodiment;

[0013] FIG2 is a schematic flow chart of a method for processing a channel state information report according to an embodiment;

[0014] FIG3 is a flow chart of another method for processing channel state information reports provided by an embodiment;

[0015] FIG4 is an interactive diagram of another method for processing channel state information reports provided by an embodiment;

[0016] FIG5 is a schematic structural diagram of an apparatus for processing a channel state information report provided by an embodiment;

[0017] FIG6 is a schematic structural diagram of another apparatus for processing channel state information reports provided by an embodiment;

[0018] FIG7 is a schematic structural diagram of a terminal provided by an embodiment;

[0019] FIG8 is a schematic structural diagram of a base station provided by an embodiment. DETAILED DESCRIPTION

[0020] The specific embodiments described herein are intended solely to illustrate the present application. The embodiments of the present application will be described below in conjunction with the accompanying drawings. The terms "first" and "second" in this application are used to distinguish similar objects and are not necessarily used to describe a specific order or precedence. Such use of terms is interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in sequences other than those illustrated or described herein.

[0021] The method for processing channel state information reports provided in this application can be applied to various wireless communication systems, such as long term evolution (LTE) systems, fourth generation mobile communication technology (4th-generation, 4G) systems, fifth generation mobile communication technology (5th-generation, 5G) systems, LTE and 5G hybrid architecture systems, 5G new radio (NR) systems, and new communication systems emerging in future communication developments, such as sixth generation mobile communication technology (6th-generation, 6G) systems. Figure 1 is a networking diagram of a wireless communication system provided in one embodiment. As shown in Figure 1, the wireless communication system includes a first communication node 110 and a second communication node 120. In a wireless communication scenario, the first communication node 110 communicates with the second communication node 120 through a wireless channel.

[0022] For example, the first communication node is a terminal, and the second communication node is an access network device, such as a base station. The base station and the terminal communicate via a wireless channel. Another example is the first communication node is a terminal, and the second communication node is a wireless router. The wireless router and the terminal communicate via a wireless channel. Another example is the first communication node is a first base station, and the second communication node is a second base station. The first base station and the second base station communicate via a wireless channel. Another example is the first communication node is a first terminal, and the second communication node is a second terminal. The first terminal and the second terminal communicate via a wireless channel. Another example is the first communication node is a repeater, and the second communication node is a base station. The base station and the repeater communicate via a wireless channel. Another example is the first communication node is a terminal, and the second communication node is a repeater. The repeater and the terminal communicate via a wireless channel. Another example is the first communication node is a first repeater, and the second communication node is a second repeater. The first repeater and the second repeater communicate via a wireless channel. Another example is the first communication node is a base station, and the second communication node is a satellite. The satellite and the base station communicate via a wireless channel. In another example, the first communication node is a satellite, the second communication node is a base station, and the base station and the satellite communicate via a wireless channel. In another example, the first communication node is a terminal, the second communication node is a satellite, and the satellite and the terminal communicate via a wireless channel. In another example, the first communication node is a satellite, the second communication node is a terminal, and the terminal and the satellite communicate via a wireless channel. In another example, the first communication node is a ground device, the second communication node is an aircraft, and the aircraft and the ground device communicate via a wireless channel. In another example, the first communication node is a first aircraft, the second communication node is a second aircraft, and the first and second aircraft communicate via a wireless channel.

[0023] When the first communication node is a terminal, the terminal can be a device with wireless transceiver functions, which can be deployed on land (such as indoors or outdoors, handheld, wearable or vehicle-mounted, etc.); it can also be deployed on the water surface (such as ships, etc.); it can also be deployed in the air (such as airplanes, balloons and satellites, etc.). Some examples of terminals include: wireless terminals, user equipment (UE), mobile phones, mobile stations, tablet computers, laptop computers, ultra-mobile personal computers (UMPC), handheld computers, netbooks, personal digital assistants (PDAs), and other user devices that can be connected to the Internet, or virtual reality (VR) terminals, augmented reality (AR) terminals, wireless terminals in industrial control, wireless terminals in self-driving, wireless terminals in remote medical, wireless terminals in smart grids, wireless terminals in transportation safety, wireless terminals in smart cities, wireless terminals in smart homes, etc., or Internet of Things nodes in the Internet of Things, or vehicle-mounted communication devices in the Internet of Vehicles, or entertainment, gaming equipment or systems, or global positioning system equipment, etc. The embodiments of the present application do not limit the technology and device form adopted by the terminal. In addition, the terminal can also be referred to as a terminal device.

[0024] When the second communication node is an access network device, the access network device can be a reader, a base station, an evolved NodeB (eNB or eNodeB) in Long Term Evolution Advanced (LTEA), a transmission reception point (TRP), a base station in a 5G mobile communication system or a next generation NodeB (gNB), a base station in a future mobile communication system or an access node in a Wireless Fidelity (WiFi) system, etc. The base station may include various macro base stations, micro base stations, home base stations, wireless remote stations, routers, WIFI devices, or various network-side devices such as primary cells and secondary cells, and location management function (LMF) devices. It can also be a module or unit that completes part of the functions of the base station, for example, it can be a centralized unit (CU) or a distributed unit (DU). The embodiments of the present application do not limit the technology and device form adopted by the access network device. In addition, the access network device can be referred to as a base station.

[0025] The wireless communication system may further include a core network device 130. The second communication node 120 may be connected to the core network device 130. The core network device 130 may include an access and mobility management network element and a session management network element. For example, the first communication node 110 may access the core network through the second communication node 120 to achieve data transmission.

[0026] In an embodiment of the present application, a method for processing CSI reports that can be operated in the above-mentioned wireless communication system is provided. By receiving configuration information of a second communication node, the concurrent number of CSI processing units is determined based on the configuration information, and the CSI processing units corresponding to the concurrent number are used to process the CSI reports, thereby realizing concurrent processing of the CSI reports, thereby improving the processing efficiency of the CSI reports and, in turn, improving the efficiency of data transmission.

[0027] The following describes the method for processing CSI reports, the communication nodes, and the technical effects thereof.

[0028] Figure 2 is a flowchart of a method for processing a channel state information report according to one embodiment. The method provided in this embodiment is applicable to a first communication node. In this example, the first communication node (also referred to as a first communication node device) may be a terminal device, such as a UE. The method includes S201-S203.

[0029] S201: Receive configuration information of a second communication node.

[0030] In this embodiment, the second communication node may be an access network device, such as a base station.

[0031] Before S201, the first communication node may send capability information to the second communication node. The second communication node may determine configuration information based on the capability information sent by the first communication node and send the configuration information to the first communication node. The capability information in this embodiment refers to information about the capabilities supported by the first communication node.

[0032] For example, the capability information in this embodiment may include at least one of the following: the number of CSI processing units, the type of CSI processing unit, and the number of CSI processing units corresponding to the type of CSI processing unit. The first communication node utilizes the CSI processing unit to process CSI reports. The number of CSI processing units, i.e., the number of concurrent CSI calculations supported by the first communication node, i.e., the number of concurrent CSI calculations supported by the first communication node, i.e., the number of concurrent CSI calculations supported by the first communication node. The type of CSI processing unit, i.e., the type of CSI processing unit.

[0033] One method for classifying the types of CSI processing units is to classify them according to the method of determining the concurrent number of CSI calculations: for example, the type in which the corresponding concurrent number is determined according to the number of CSI-RS resources, for example, the type in which the corresponding concurrent number is determined according to the number of precoding matrices, for example, the type in which the corresponding concurrent number is determined according to the number of ranks of the precoding matrix, for example, the type in which the corresponding concurrent number is determined according to the number of layers of the precoding matrix, for example, the type in which the corresponding concurrent number is determined according to the number of precoding matrix codebooks, for example, the type in which the corresponding concurrent number is determined according to the number of machine learning models, for example, the type in which the corresponding concurrent number is determined according to the number of precoding matrix overheads, for example, the type in which the corresponding concurrent number is determined according to the number of frequency domain units, for example, the type in which the corresponding concurrent number is determined according to the number of methods for obtaining the precoding matrix.

[0034] Another method of dividing the types of CSI processing units is to divide them according to the content of the CSI report: for example, the type of precoding matrix corresponding to the report content of a single transmitting panel, for example, the type of precoding matrix corresponding to the report content of 2 transmitting panels, for example, the type of precoding matrix corresponding to the report content of Y transmitting panels, for example, the type of precoding matrix corresponding to the report content of a single codebook type, for example, the type of precoding matrix corresponding to the report content of 2 codebook types, for example, the type of precoding matrix corresponding to the report content of Y codebook types, for example, the type of precoding matrix corresponding to the report content of a single overhead, for example, the type of precoding matrix corresponding to the report content of 2 overheads, for example, the type of precoding matrix corresponding to the report content of Y overheads, for example, the type of precoding matrix corresponding to the report content of a single frequency domain unit, for example For example, the corresponding report content is the type of precoding matrix corresponding to 2 frequency domain units, for example, the corresponding report content is the type of precoding matrix corresponding to Y frequency domain units, for example, the corresponding report content is the type of precoding matrix corresponding to a single machine learning model, for example, the corresponding report content is the type of precoding matrix corresponding to 2 machine learning models, for example, the corresponding report content is the type of precoding matrix corresponding to Y machine learning models, for example, the corresponding report content is the type of precoding matrix corresponding to a single method of obtaining a precoding matrix, for example, the corresponding report content is the type of precoding matrix corresponding to 2 methods of obtaining precoding matrices, for example, the corresponding report content is the type of precoding matrix corresponding to Y methods of obtaining precoding matrices, for example, the corresponding report content is the type of a combination of a precoding matrix determined according to a codebook and a precoding matrix determined by a machine learning model; wherein Y is a non-negative integer.

[0035] The type of a CSI processing unit expresses the content of a CSI calculation process in the CSI calculation concurrency, that is, it describes the content corresponding to a CSI processing unit in the CSI calculation concurrency structure.

[0036] The number of CSI processing units corresponding to a CSI processing unit type, that is, the number of concurrent CSI calculations supported by this CSI processing unit type. For example, if the number of CSI processing units for CSI processing unit type 1 is Z1, it means that the number of concurrent CSI calculations supported by this CSI processing unit type 1 is Z1; for example, if the number of CSI processing units for CSI processing unit type 1 is 5, it means that the number of concurrent CSI calculations supported by this CSI processing unit type 1 is 5. Another example is as follows: if the number of CSI processing units for CSI processing unit type 2 is Z2, it means that the number of concurrent CSI calculations supported by this CSI processing unit type 2 is Z2; for example, if the number of CSI processing units for CSI processing unit type 2 is 7, it means that the number of concurrent CSI calculations supported by this CSI processing unit type 2 is 7.

[0037] The number of CSI processing units of CSI processing unit type 1 is Z1, and the number of CSI processing units of CSI processing unit type 2 is Z2. One of the ways is that the first communication node has Z1 CSI processing units of CSI processing unit type 1 and Z2 CSI processing units of CSI processing unit type 2; or, the first communication node can simultaneously support CSI calculations with a concurrent number of Z1 corresponding to CSI processing unit type 1 and CSI calculations with a concurrent number of Z2 corresponding to CSI processing unit type 2. The number of CSI processing units of CSI processing unit type 1 is Z1, and the number of CSI processing units of CSI processing unit type 2 is Z2. In another embodiment, the first communication node has Z1 CSI processing units of CSI processing unit type 1, or Z2 CSI processing units of CSI processing unit type 2; or, the first communication node can support both Z1 concurrent CSI calculations corresponding to CSI processing unit type 1 and Z2 concurrent CSI calculations corresponding to CSI processing unit type 2, but can only support concurrent CSI calculations corresponding to one of the CSI processing unit types at a time. Where Z1 and Z2 are non-negative integers.

[0038] In one embodiment, the configuration information may include at least one of the following information: information about CSI-RS resources, grouping of CSI-RS resources, precoding matrix codebook, grouping of precoding matrix codebook, rank of precoding matrix, grouping of rank of precoding matrix, layer of precoding matrix, grouping of layer of precoding matrix, overhead of precoding matrix, grouping of overhead of precoding matrix, machine learning model, grouping of machine learning model, frequency domain unit, grouping of frequency domain unit, way of obtaining precoding matrix, grouping of way of obtaining precoding matrix, and information on monitoring way of obtaining precoding matrix.

[0039] The CSI-RS resource information is used to indicate at least one of the following information: the CSI-RS resources in the CSI-RS resource set corresponding to the CSI report, the number of CSI-RS resources in the CSI resource set corresponding to the CSI report, the number of CSI-RS resources in the CSI report, and the candidate range of CSI-RS resource index numbers in the CSI report. The difference between the CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the CSI-RS resources in the CSI report is that the CSI-RS resources in the CSI-RS resource set corresponding to the CSI report refer to the candidate CSI-RS resources corresponding to the CSI report, while the CSI-RS resources in the CSI report refer to the CSI-RS resources selected in the CSI report. The CSI-RS resources in the CSI report are a subset of the CSI-RS resources in the CSI-RS resource set corresponding to the CSI report.

[0040] The overhead of the precoding matrix refers to the resources required after the precoding matrix is ​​compressed. For example, the overhead of the precoding matrix can be expressed as the number of bits after the precoding matrix is ​​compressed.

[0041] The machine learning model is used to output a precoding matrix. The machine learning model in this embodiment can be a model trained using various machine learning methods. For example, the machine learning model can be an artificial intelligence model such as a neural network or a convolutional neural network. The machine learning model in this embodiment can be pre-configured in the first communication node, or can be sent to the first communication node by a second communication node when the first communication node needs to use the machine learning model, or can be sent to the first communication node by a third communication node when the first communication node needs to use the machine learning model. The third communication node here can be a device such as a server that is communicatively connected to the first communication node.

[0042] The frequency domain unit in this embodiment may be a frequency domain unit defined according to requirements. For example, the frequency domain unit in this embodiment may be a resource block (RB), a subband, or a bandwidth block.

[0043] The information on monitoring the method for obtaining the precoding matrix includes at least one of the following information: whether to perform a monitoring report on the method for obtaining the precoding matrix, the content of the monitoring report, the format of the monitoring report, and the like.

[0044] S202: Determine the concurrent number of CSI processing units according to the configuration information.

[0045] S203: Use CSI processing units corresponding to the concurrent number to process the CSI report.

[0046] The first communication node can perform one CSI calculation at the same time, or perform multiple CSI calculations at the same time. Performing multiple CSI calculations at the same time is called CSI calculation concurrency or CSI calculation concurrent execution, or concurrent CSI calculation, or concurrent execution of CSI calculation. The first communication node performs M CSI calculations at the same time, which is called M CSI calculation concurrency, or the concurrent number of CSI calculations is M, or CSI calculations are performed with a concurrent number M; where M is a non-negative integer. For example, the first communication node performs 1 CSI calculation at the same time, which is called the concurrent number of CSI calculations is 1, or CSI calculations are performed with a concurrent number of 1. For example, the first communication node performs 2 CSI calculations at the same time, which is called the concurrent number of CSI calculations is 2, or CSI calculations are performed with a concurrent number of 2. For example, the first communication node performs 3 CSI calculations at the same time, which is called the concurrent number of CSI calculations is 3, or CSI calculations are performed with a concurrent number of 3. Corresponding to M being 0, no CSI calculation is performed.

[0047] A first communication node can perform CSI calculations with a concurrent number N. This means the first communication node supports CSI calculations with a concurrent number N. It is also said that the first communication node has N CSI processing units, where N is a non-negative integer. If there are L concurrent CSI calculations, this means L CSI processing units are occupied, where L is a non-negative integer. If a first communication node has N CSI processing units and L of them are occupied, then the first communication node has NL unoccupied CSI processing units. This means that the first communication node can still perform CSI calculations with a concurrent number NL, or can still support CSI calculations with a concurrent number NL.

[0048] In this embodiment, processing a CSI report using a CSI processing unit corresponding to the concurrent number refers to performing CSI calculations using the CSI processing unit corresponding to the concurrent number. The CSI processing unit corresponding to the concurrent number means that the number of CSI processing units is the concurrent number. Processing a CSI report in this embodiment can also be described as generating a CSI report or determining a CSI report. The result of performing the CSI calculation is a CSI report. Performing CSI calculations using a CSI processing unit corresponding to the concurrent number 0 can result in one CSI report or a group of CSI reports; wherein a group of CSI reports includes multiple CSI reports. This embodiment is not limited to this.

[0049] In this embodiment, the first communication node may perform multiple CSI calculations. For example, the first communication node measures multiple CSI-RS resources, or measures reference signals on multiple CSI-RS resources. For another example, the first communication node calculates multiple precoding matrices. For another example, the first communication node processes precoding matrices of multiple ranks. For another example, the first communication node processes precoding matrices of multiple layers. For another example, the first communication node calculates precoding matrices based on multiple precoding matrix codebooks. For another example, the first communication node uses multiple machine learning models, such as neural networks, to process precoding matrices. For another example, the first communication node processes precoding matrices with multiple different overheads. For another example, the first communication node processes CSI on multiple frequency domain units. For another example, the first communication node uses multiple methods to obtain precoding matrices. For another example, the first communication node monitors multiple methods for obtaining precoding matrices. The first communication node adopts multiple methods to obtain the precoding matrix: for example, one method is to obtain the precoding matrix according to the first precoding matrix codebook, another method is to obtain the precoding matrix according to the second precoding matrix codebook, another method is to obtain the precoding matrix by adopting the first machine learning model, another method is to obtain the precoding matrix by adopting the second machine learning model, another method is to obtain the precoding matrix based on the first overhead, and another method is to obtain the precoding matrix based on the second overhead; for another example, one method is to obtain the precoding matrix according to the first precoding matrix codebook and the first overhead, another method is to obtain the precoding matrix according to the first precoding matrix codebook and the second overhead, another method is to obtain the precoding matrix according to the second precoding matrix codebook and the first overhead, and another method is to obtain the precoding matrix according to the second precoding matrix codebook and the second overhead; for another example, one method is to obtain the precoding matrix according to the first overhead and using the first machine learning model, another method is to obtain the precoding matrix according to the first overhead and using the second machine learning model, another method is to obtain the precoding matrix according to the second overhead and using the first machine learning model, and another method is to obtain the precoding matrix according to the second overhead and using the second machine learning model.

[0050] In S202, according to different contents of the configuration information, the first communication node may determine the concurrent number of CSI processing units in different ways.

[0051] In one implementation, the type and concurrent number of CSI processing units may be determined based on the configuration information in S202. Correspondingly, S203 may be to concurrently process CSI reports using the CSI processing units corresponding to the type and concurrent number of CSI processing units.

[0052] In another implementation, in S202, when determining the number of concurrent CSI units, the type of CSI unit may also be determined. Accordingly, in S203, the CSI processing unit corresponding to the number of concurrent CSI units may be used to process the CSI report, where the CSI processing unit may be a CSI processing unit corresponding to the determined type of CSI unit.

[0053] The following uses several examples to illustrate the implementation process of determining the concurrent number of CSI processing units.

[0054] Example 2.1

[0055] In the case that the configuration information includes information of CSI-RS resources or grouping of CSI-RS resources, the implementation process of S202 is: determining the concurrency number according to the number of CSI-RS resources or the number of groups of CSI-RS resources.

[0056] Correspondingly, the implementation process of S203 may be that the first communication node determines the concurrent number of CSI processing units according to the CSI-RS resources, concurrently measures M CSI-RS resources with the concurrent number, or measures the reference signal on the M CSI-RS resources.

[0057] One way to determine the concurrency number O is to use the number of CSI-RS resources as the concurrency number. That is, the concurrency number O equals the number of CSI-RS resources. For example, one CSI calculation corresponds to one CSI-RS resource, and M CSI calculations correspond to M CSI-RS resources. That is, the first communication node performs O CSI calculations simultaneously, where O equals the number of CSI-RS resources M, and one CSI calculation corresponds to one CSI-RS resource.

[0058] Another way to determine the concurrent number O is to determine the sum of the number of CSI-RS resources and a preset first value as the concurrent number. That is, the concurrent number O is equal to the number of CSI-RS resources plus the first value, or the sum of the number of CSI-RS resources and the first value. The first value may be an integer greater than 0. Exemplarily, the first value may be 1. For example, one CSI calculation corresponds to one CSI-RS resource, M CSI calculations correspond to M CSI-RS resources, and another CSI calculation corresponds to another purpose. That is, the first communication node performs O CSI calculations at the same time, O is equal to the number of CSI-RS resources M plus 1, one CSI calculation corresponds to one CSI-RS resource, and the other CSI calculation corresponds to another purpose. The "other purposes" here refer to other processing processes other than measuring CSI resources in the process of processing CSI reports.

[0059] Another way to determine the concurrency number O is to determine the larger of the number of CSI-RS resources and a preset second value as the concurrency number. For example, the second value can be an integer greater than 1, such as 2. That is, the concurrency number O is equal to the larger of the number of CSI-RS resources and 2.

[0060] Another way to determine the concurrency number O is to use the number of CSI-RS resource groups as the concurrency number. That is, the concurrency number O equals the number of CSI-RS resource groups. For example, if M CSI-RS resources are divided into X groups, the concurrency number O equals X. One CSI calculation corresponds to one group of CSI-RS resources, and X CSI calculations correspond to X groups of CSI-RS resources. That is, the first communication node performs O CSI calculations simultaneously, where O equals the number of CSI-RS resource groups, X, and one CSI calculation corresponds to one group of CSI-RS resources.

[0061] The grouping of CSI-RS resources includes each CSI-RS group formed by grouping by an average number distribution method, or each CSI-RS group formed by grouping by an average computing power requirement distribution method, or each CSI-RS group formed by grouping by a method matching the computing power of the CSI processing unit.

[0062] One way to divide M CSI-RS resources into X groups is to divide the M CSI-RS resources evenly into the X groups. For example, 6 CSI-RS resources are divided into 2 groups, each group of resources includes 3 CSI-RS resources. For example, 6 CSI-RS resources are divided into 3 groups, each group of resources includes 2 CSI-RS resources. For example, 7 CSI-RS resources are divided into 2 groups, one of which includes 3 CSI-RS resources and the other includes 4 CSI-RS resources. For example, 7 CSI-RS resources are divided into 3 groups, one of which includes 2 CSI-RS resources, another includes 2 CSI-RS resources, and another includes 3 CSI-RS resources. The M CSI-RS resources are evenly divided into X groups, which can achieve load balancing for each CSI calculation. In other words, it is possible to achieve load balancing for each CSI processing unit, thereby improving the processing efficiency of the CSI report.

[0063] Another way to group the M CSI-RS resources into X groups is to group the M CSI-RS resources unevenly into the X groups. This uneven grouping can be implemented in two ways: grouping by evenly distributing the computing power required, or grouping by matching the computing power of the CSI processing unit.

[0064] For example, six CSI-RS resources are unevenly divided into three resource groups:

[0065] For example, six CSI-RS resources are unevenly divided into three resource groups:

[0066] For example, an example where 6 CSI-RS resources are unevenly divided into 2 resource groups:

[0067] For example, here is another example where 6 CSI-RS resources are unevenly divided into 2 resource groups:

[0068] For example, 7 CSI-RS resources are unevenly divided into 3 resource groups:

[0069] For example, another example where 7 CSI-RS resources are unevenly divided into 3 resource groups:

[0070] For example, another example where 7 CSI-RS resources are unevenly divided into 3 resource groups:

[0071] For example, an example where 7 CSI-RS resources are unevenly divided into 2 resource groups:

[0072] For example, another example where 7 CSI-RS resources are unevenly divided into 2 resource groups:

[0073] Corresponding to the situation where different CSI-RS resources have different computational loads, that is, different CSI-RS resources have different computational power requirements, M CSI-RS resources are divided into X groups in an even distribution manner according to the computational power requirements, which can achieve a balance in the computational power requirements of each group of CSI-RS resources, and thus achieve a load balance in each CSI calculation. In this implementation method, in the case of the above-mentioned division into three resource groups, the difference between the computational power requirements of the CSI-RS resources in CSI-RS resource group 1, the computational power requirements of the CSI-RS resources in CSI-RS resource group 2, and the computational power requirements of the CSI-RS resources in CSI-RS resource group 3 does not exceed the preset difference degree or the preset difference threshold. That is, the computational power requirements of the CSI-RS resources in each resource group are balanced. The computational power requirement of the CSI-RS resources in a CSI-RS resource group refers to the sum of the computational power requirements of each CSI-RS resource in the CSI-RS resource group.

[0074] In the case where the computing power of the CSI processing units responsible for each CSI calculation is unequal, the M CSI-RS resources are divided into X groups in a manner that matches the computing power of the CSI processing units. This can achieve matching of the computing power of the CSI processing units with the computing power requirements of the CSI resource groups, thereby improving the processing efficiency of each CSI processing unit. In this implementation, in the case of the above division into three resource groups, for example, the computing power requirements of the CSI-RS resources in CSI-RS resource group 1 can match the computing power of CSI processing unit 1, the computing power requirements of the CSI-RS resources in CSI-RS resource group 2 can match the computing power of CSI processing unit 2, and the computing power requirements of the CSI-RS resources in CSI-RS resource group 3 can match the computing power of CSI processing unit 3.

[0075] Example 2.2

[0076] S202 may be implemented by: determining the number of precoding matrices or the number of groups of precoding matrices according to configuration information; and determining the concurrency number according to the number of precoding matrices or the number of groups of precoding matrices.

[0077] The first communication node may determine the number of precoding matrices or the number of precoding matrix groups based on the precoding matrix-related information in the configuration information. The precoding matrix-related information here may include, for example, at least one of a precoding matrix codebook, a grouping of a precoding matrix codebook, a rank of a precoding matrix, a grouping of a rank of a precoding matrix, an overhead of a precoding matrix, a grouping of an overhead of a precoding matrix, a machine learning model, and a grouping of a machine learning model.

[0078] Correspondingly, the implementation process of S203 may be that the first communication node determines the concurrent number of CSI processing units according to the precoding matrix, and calculates M precoding matrices based on the concurrent number.

[0079] One way to determine the concurrent number O is to use the number of precoding matrices as the concurrent number. That is, the concurrent number O is equal to the number of precoding matrices. For example, one CSI calculation corresponds to one precoding matrix, and M CSI calculations correspond to M precoding matrices. That is, the first communication node performs O CSI calculations simultaneously, where O is equal to the number of precoding matrices M, and one CSI calculation corresponds to one precoding matrix.

[0080] Another way to determine the concurrent number O is to determine the sum of the number of precoding matrices and a preset third value as the concurrent number. That is, the concurrent number O is equal to the number of precoding matrices plus the third value, or the sum of the number of precoding matrices and the third value. The third value may be an integer greater than 0. Exemplarily, the third value may be 1. For example, one CSI calculation corresponds to one precoding matrix, M CSI calculations correspond to M precoding matrices, and another CSI calculation corresponds to another purpose. That is, the first communication node performs O CSI calculations at the same time, O is equal to the number of precoding matrices M plus 1, one CSI calculation corresponds to one precoding matrix, and the other CSI calculation corresponds to another purpose. The "other purposes" here refer to other processing processes other than calculating the precoding matrix in the process of processing the CSI report.

[0081] Another way to determine the concurrency number O is to use the larger of the number of precoding matrices and a preset fourth value as the concurrency number. For example, the fourth value can be an integer greater than 1, such as 2. That is, the concurrency number O is equal to the larger of the number of precoding matrices and 2.

[0082] Another way to determine the concurrency number O is to use the number of precoding matrix groups as the concurrency number. That is, the concurrency number O equals the number of precoding matrix groups. For example, if M precoding matrices are divided into X groups, the concurrency number O equals X. One CSI calculation corresponds to one group of precoding matrices, and X CSI calculations correspond to X groups of precoding matrices. That is, the first communication node performs O CSI calculations simultaneously, where O equals the number of precoding matrix groups, X, where one CSI calculation corresponds to one group of precoding matrices.

[0083] The grouping of precoding matrices includes each precoding matrix group formed by grouping in a manner of evenly distributing the number of precoding matrices, or each precoding matrix group formed by grouping in a manner of evenly distributing the computing power requirements, or each precoding matrix group formed by grouping in a manner of matching the computing power of the CSI processing unit.

[0084] One way to divide the M precoding matrices into X groups is to divide the M precoding matrices evenly into the X groups. For example, 6 precoding matrices are divided into 2 groups, each group of precoding matrices includes 3 precoding matrices. For example, 6 precoding matrices are divided into 3 groups, each group of precoding matrices includes 2 precoding matrices. For example, 7 precoding matrices are divided into 2 groups, one of which includes 3 precoding matrices and the other includes 4 precoding matrices. For example, 7 precoding matrices are divided into 3 groups, one of which includes 2 precoding matrices, another includes 2 precoding matrices, and another includes 3 precoding matrices. The M precoding matrices are evenly divided into the X groups to achieve load balancing for each CSI calculation. In other words, load balancing can be achieved for each CSI processing unit, improving the processing efficiency of the CSI report.

[0085] Another way to group the M precoding matrices into X groups is to group the M precoding matrices unevenly into the X groups. This uneven grouping can be implemented in two ways: grouping by evenly distributing the computing power required, or grouping by matching the computing power of the CSI processing unit.

[0086] For example, six precoding matrices are unevenly divided into three precoding matrix groups:

[0087] For example, six precoding matrices are unevenly divided into three precoding matrix groups:

[0088] For example, six precoding matrices are unevenly divided into two precoding matrix groups:

[0089] For example, another example where 6 precoding matrices are unevenly divided into 2 precoding matrix groups:

[0090] For example, an example where 7 precoding matrices are unevenly divided into 3 precoding matrix groups:

[0091] For example, another example where 7 precoding matrices are unevenly divided into 3 precoding matrix groups:

[0092] For example, another example where 7 precoding matrices are unevenly divided into 3 precoding matrix groups:

[0093] For example, an example where 7 precoding matrices are unevenly divided into 2 precoding matrix groups:

[0094] For example, another example where 7 precoding matrices are unevenly divided into 2 precoding matrix groups:

[0095] In response to the situation where different precoding matrices have different computational loads, that is, different precoding matrices have different computational power requirements, the M precoding matrices are divided into X groups according to an even distribution of the computational power requirements. This can achieve a balance in the computational power requirements of each group of precoding matrices, and thus achieve a load balance for each CSI calculation. In this implementation, in the case of the aforementioned division into three matrix groups, the difference between the computational power requirements of the precoding matrices in precoding matrix group 1, the computational power requirements of the precoding matrices in precoding matrix group 2, and the computational power requirements of the precoding matrices in precoding matrix group 3 does not exceed a preset difference degree or a preset difference threshold. In other words, the computational power requirements of the precoding matrices in each precoding matrix group are balanced. The computational power requirement of the precoding matrices in a precoding matrix group refers to the sum of the computational power requirements of each precoding matrix in the precoding matrix group.

[0096] In the case where the computing power of the CSI processing units responsible for each CSI calculation is unequal, the M precoding matrices are unevenly divided into X groups. This can achieve matching of the computing power of the CSI processing units with the computing power requirements of the precoding matrix groups, thereby improving the processing efficiency of each CSI processing unit. In this implementation, in the case of the aforementioned division into three matrix groups, for example, the computing power requirements of the precoding matrices in precoding matrix group 1 can match the computing power of CSI processing unit 1, the computing power requirements of the precoding matrices in precoding matrix group 2 can match the computing power of CSI processing unit 2, and the computing power requirements of the precoding matrices in precoding matrix group 3 can match the computing power of CSI processing unit 3.

[0097] Example 2.3

[0098] In the case that the configuration information includes the rank of the precoding matrix or the grouping of the rank of the precoding matrix, the implementation process of S202 is: determining the concurrency number according to the number of the ranks of the precoding matrix or the number of the grouping of the rank of the precoding matrix.

[0099] Correspondingly, the implementation process of S203 may be that the first communication node determines the concurrent number of CSI processing units according to the rank of the precoding matrix, and concurrently calculates precoding matrices of M ranks with the concurrent number.

[0100] One way to determine the concurrency number O is to use the number of ranks of the precoding matrix as the concurrency number. That is, the concurrency number O is equal to the number of ranks. For example, one CSI calculation corresponds to one rank, and M CSI calculations correspond to M ranks. That is, the first communication node performs O CSI calculations simultaneously, where O is equal to the number of ranks M, and one CSI calculation corresponds to one rank.

[0101] Another way to determine the concurrency number O is to use the number of groups of precoding matrix ranks as the concurrency number. That is, the concurrency number O is equal to the number of groupings of ranks. For example, if M ranks are divided into X groups, the concurrency number O is equal to X; one CSI calculation corresponds to one group of ranks, and X CSI calculations correspond to X groups of ranks. That is, the first communication node performs O CSI calculations simultaneously, and O is equal to the number of groupings of ranks, X, where one CSI calculation corresponds to one group of ranks.

[0102] The rank grouping of the precoding matrix includes each rank group formed by grouping in a manner of evenly distributing the number, or each rank group formed by grouping in a manner of evenly distributing the computing power requirements, or each rank group formed by grouping in a manner of matching the computing power of the CSI processing unit.

[0103] One way to divide the M ranks into X groups is to divide the M ranks evenly into the X groups. For example, 6 ranks can be divided into 2 groups, each of which includes 3 ranks. For example, 6 ranks can be divided into 3 groups, each of which includes 2 ranks. For example, 7 ranks can be divided into 2 groups, one of which includes 3 ranks and the other includes 4 ranks. For example, 7 ranks can be divided into 3 groups, one of which includes 2 ranks, another includes 2 ranks, and another includes 3 ranks. Evenly dividing the M ranks into X groups can achieve load balancing for each CSI calculation. In other words, it can achieve load balancing for each CSI processing unit, improving the processing efficiency of CSI reports.

[0104] Another way to group the M ranks into X groups is to group the M ranks unevenly into the X groups. In the uneven grouping method, there are two implementations: grouping by evenly distributing the computing power requirements, or grouping by matching the computing power of the CSI processing units.

[0105] For example, an example where 6 ranks are unevenly divided into 3 rank groups:

[0106] For example, here is another example where 6 ranks are unevenly divided into 3 rank groups:

[0107] For example, an example where 6 ranks are unevenly divided into 2 rank groups:

[0108] For example, here is another example where the 6 ranks are unevenly divided into 2 rank groups:

[0109] For example, an example where 7 ranks are unevenly divided into 3 rank groups:

[0110] For example, here is another example where 7 ranks are unevenly divided into 3 rank groups:

[0111] For example, here is another example where 7 ranks are unevenly divided into 3 rank groups:

[0112] For example, an example where 7 ranks are unevenly divided into 2 rank groups:

[0113] For example, here is another example where 7 ranks are unevenly divided into 2 rank groups:

[0114] In response to the situation where different ranks have different computational loads, that is, different ranks have different computational power requirements, the M ranks are unevenly divided into X groups, which can achieve a balance in the computational power requirements of each group of ranks, and thus achieve a load balance for each CSI calculation. In this implementation, in the case of the above-mentioned division into three rank groups, the difference between the computational power requirements of the ranks in rank group 1, the computational power requirements of the ranks in rank group 2, and the computational power requirements of the ranks in rank group 3 does not exceed a preset difference degree or a preset difference threshold. In other words, the computational power requirements of the ranks in each rank group are balanced. The computational power requirement of the ranks in a rank group refers to the sum of the computational power requirements of each rank in the rank group.

[0115] In the case where the computing power of the CSI processing units responsible for each CSI calculation is unequal, the M ranks are divided into X groups based on a method that matches the computing power of the CSI processing units. This can match the computing power of the CSI processing units with the computing power requirements of the rank groups, thereby improving the processing efficiency of each CSI processing unit. In this implementation, in the case of the above division into three rank groups, for example, the computing power requirements of the ranks in rank group 1 can match the computing power of CSI processing unit 1, the computing power requirements of the ranks in rank group 2 can match the computing power of CSI processing unit 2, and the computing power requirements of the ranks in rank group 3 can match the computing power of CSI processing unit 3.

[0116] Example 2.4

[0117] In the case that the configuration information includes layers of the precoding matrix or groups of layers of the precoding matrix, the implementation process of S202 is: determining the concurrency number according to the number of layers of the precoding matrix or the number of groups of layers of the precoding matrix.

[0118] Correspondingly, the implementation process of S203 may be that the first communication node determines the concurrent number of CSI processing units according to the layers of the precoding matrix, and concurrently calculates the precoding matrices of M layers with the concurrent number.

[0119] One way to determine the concurrency number O is to use the number of layers in the precoding matrix as the concurrency number. The concurrency number O is equal to the number of layers. For example, one CSI calculation corresponds to one layer, and M CSI calculations correspond to M layers. That is, the first communication node performs O CSI calculations simultaneously, where O is equal to the number of layers M, and one CSI calculation corresponds to one layer.

[0120] Another way to determine the concurrency number O is to use the number of groupings of layers in the precoding matrix as the concurrency number. Specifically, the concurrency number O is equal to the number of groupings of layers. For example, if M layers are grouped into X groups, the concurrency number O is equal to X. One CSI calculation corresponds to one group of layers, and X CSI calculations correspond to X groups of layers. That is, the first communication node performs O CSI calculations simultaneously, where O is equal to the number of groupings of layers, X, and one CSI calculation corresponds to one group of layers.

[0121] The grouping of the layers of the precoding matrix includes each layer group formed by grouping in a manner of evenly distributing the number, or each layer group formed by grouping in a manner of evenly distributing the computing power requirements, or each layer group formed by grouping in a manner of matching the computing power of the CSI processing unit.

[0122] One way to divide the M layers into X groups is to divide the M layers evenly into the X groups. For example, 6 layers can be divided into 2 groups, each containing 3 layers. For example, 6 layers can be divided into 3 groups, each containing 2 layers. For example, 7 layers can be divided into 2 groups, one of which contains 3 layers and the other contains 4 layers. For example, 7 layers can be divided into 3 groups, one of which contains 2 layers, another contains 2 layers, and another contains 3 layers. The M layers are evenly divided into the X groups to achieve load balancing for each CSI calculation. In other words, load balancing can be achieved for each CSI processing unit, improving the processing efficiency of the CSI report.

[0123] Another way to group the M layers into X groups is to group the M layers unevenly. This uneven grouping can be implemented in two ways: grouping by evenly distributing the computing power requirements, or grouping by matching the computing power of the CSI processing units.

[0124] For example, an example where 6 layers are unevenly divided into 3 layer groups:

[0125] For example, here is another example where 6 layers are unevenly divided into 3 layer groups:

[0126] For example, here is an example where 6 layers are unevenly divided into 2 layer groups:

[0127] For example, here is another example where 6 layers are unevenly divided into 2 layer groups:

[0128] For example, here is an example where 7 layers are unevenly divided into 3 layer groups:

[0129] For example, here is another example where 7 layers are unevenly divided into 3 layer groups:

[0130] For example, here is another example where 7 layers are unevenly divided into 3 layer groups:

[0131] For example, here is an example where 7 layers are unevenly divided into 2 layer groups:

[0132] For example, here is another example where 7 layers are unevenly divided into 2 layer groups:

[0133] To address the situation where different layers have different computational loads, i.e., different computing power requirements, the M layers are unevenly divided into X groups, which can achieve load balancing for each CSI calculation. This balances the computing power requirements of each layer group, and thus, balances the load of each CSI calculation. In this implementation, in the aforementioned three layer groups, the difference between the computing power requirements of the layers in layer group 1, the computing power requirements of the layers in layer group 2, and the computing power requirements of the layers in layer group 3 does not exceed a preset difference level or a preset difference threshold. In other words, the computing power requirements of the layers in each layer group are balanced. The computing power requirement of a layer in a layer group refers to the sum of the computing power requirements of all layers in the layer group.

[0134] In the case where the computing power of the CSI processing units responsible for each CSI calculation is unequal, the M layers are divided into X groups based on the computing power matching the CSI processing units. This can ensure that the computing power of the CSI processing units matches the computing power requirements of the layer groups, thereby improving the processing efficiency of each CSI processing unit. In this implementation, in the case of the aforementioned three layer groups, for example, the computing power requirements of the layers in layer group 1 can match the computing power of CSI processing unit 1, the computing power requirements of the layers in layer group 2 can match the computing power of CSI processing unit 2, and the computing power requirements of the layers in layer group 3 can match the computing power of CSI processing unit 3.

[0135] Example 2.5

[0136] In the case where the configuration information includes a precoding matrix codebook or a grouping of precoding matrix codebooks, the implementation process of S202 is: determining the concurrency number according to the number of precoding matrix codebooks or the number of groups of precoding matrix codebooks.

[0137] Correspondingly, the implementation process of S203 may be that the first communication node determines the concurrent number of CSI processing units according to the precoding matrix codebook, and concurrently calculates the precoding matrices of M precoding matrix codebooks according to the concurrent number.

[0138] One way to determine the concurrency number O is to use the number of precoding matrix codebooks as the concurrency number. That is, the concurrency number O is equal to the number of precoding matrix codebooks. For example, one CSI calculation corresponds to one precoding matrix codebook, and M CSI calculations correspond to M precoding matrix codebooks. That is, the first communication node performs O CSI calculations simultaneously, where O is equal to the number of precoding matrix codebooks, M, and one CSI calculation corresponds to one precoding matrix codebook.

[0139] Another way to determine the concurrency number O is to determine the concurrency number as the number of groups of the precoding matrix codebook. That is, the concurrency number O is equal to the number of groups of the precoding matrix codebook. For example, if M precoding matrix codebooks are divided into X groups, the concurrency number O is equal to X. One CSI calculation corresponds to one group of precoding matrix codebooks, and X CSI calculations correspond to X groups of precoding matrix codebooks. That is, the first communication node performs O CSI calculations simultaneously, where O is equal to the number of groups of the precoding matrix codebooks, X, and one CSI calculation corresponds to one group of precoding matrix codebooks.

[0140] The grouping of the precoding matrix codebooks includes each precoding matrix codebook group formed by grouping in an average quantity distribution manner, or each precoding matrix codebook group formed by grouping in an average computing power requirement distribution manner, or each precoding matrix codebook group formed by grouping in a manner matching the computing power of the CSI processing unit.

[0141] One way to divide the M precoding matrix codebooks into X groups is to divide the M precoding matrix codebooks evenly into the X groups. For example, 6 precoding matrix codebooks are divided into 2 groups, each group of precoding matrix codebooks includes 3 precoding matrix codebooks. For example, 6 precoding matrix codebooks are divided into 3 groups, each group of precoding matrix codebooks includes 2 precoding matrix codebooks. For example, 7 precoding matrix codebooks are divided into 2 groups, one of which includes 3 precoding matrix codebooks and the other includes 4 precoding matrix codebooks. For example, 7 precoding matrix codebooks are divided into 3 groups, one of which includes 2 precoding matrix codebooks, another group includes 2 precoding matrix codebooks, and another group includes 3 precoding matrix codebooks. The M precoding matrix codebooks are evenly divided into the X groups to achieve load balancing for each CSI calculation. In other words, load balancing can be achieved for each CSI processing unit, improving the processing efficiency of the CSI report.

[0142] Another way to group the M precoding matrix codebooks into X groups is to group the M precoding matrix codebooks unevenly into the X groups. In this uneven grouping approach, there are two implementations: grouping by evenly distributing the computing power requirements, or grouping by matching the computing power of the CSI processing unit.

[0143] For example, an example in which 6 precoding matrix codebooks are unevenly divided into 3 precoding matrix codebook groups:

[0144] For example, another example where 6 precoding matrix codebooks are unevenly divided into 3 precoding matrix codebook groups:

[0145] For example, an example where 6 precoding matrix codebooks are unevenly divided into 2 precoding matrix codebook groups:

[0146] For example, another example where 6 precoding matrix codebooks are unevenly divided into 2 precoding matrix codebook groups:

[0147] For example, an example in which 7 precoding matrix codebooks are unevenly divided into 3 precoding matrix codebook groups:

[0148] For example, another example where 7 precoding matrix codebooks are unevenly divided into 3 precoding matrix codebook groups:

[0149] For example, another example where 7 precoding matrix codebooks are unevenly divided into 3 precoding matrix codebook groups:

[0150] For example, an example where 7 precoding matrix codebooks are unevenly divided into 2 precoding matrix codebook groups:

[0151] For example, another example where 7 precoding matrix codebooks are unevenly divided into 2 precoding matrix codebook groups:

[0152] In response to the situation where different precoding matrix codebooks have different computational loads, that is, different precoding matrix codebooks have different computational power requirements, the M precoding matrix codebooks are unevenly divided into X groups. This can achieve balanced computational power requirements for each precoding matrix codebook group, and thus achieve load balancing for each CSI calculation. In this implementation, in the case of the aforementioned three precoding matrix codebook groups, the difference between the computational power requirements of the precoding matrix codebooks in precoding matrix codebook group 1, the computational power requirements of the precoding matrix codebooks in precoding matrix codebook group 2, and the computational power requirements of the precoding matrix codebooks in precoding matrix codebook group 3 does not exceed a preset degree of difference or a preset difference threshold. In other words, the computational power requirements of the precoding matrix codebooks in each precoding matrix codebook group are balanced. The computational power requirement of the precoding matrix codebooks in a precoding matrix codebook group refers to the sum of the computational power requirements of each precoding matrix codebook in the precoding matrix codebook group.

[0153] In the case where the computing power of the CSI processing units responsible for each CSI calculation is unequal, the M precoding matrix codebooks are unevenly divided into X groups, which can achieve matching of the computing power of the CSI processing units with the computing power requirements of the precoding matrix codebook groups, thereby improving the processing efficiency of each CSI processing unit. In this implementation, in the case of the aforementioned division into three precoding matrix codebook groups, for example, the computing power requirements of the precoding matrix codebooks in precoding matrix codebook group 1 can match the computing power of CSI processing unit 1, the computing power requirements of the precoding matrix codebooks in precoding matrix codebook group 2 can match the computing power of CSI processing unit 2, and the computing power requirements of the precoding matrix codebooks in precoding matrix codebook group 3 can match the computing power of CSI processing unit 3.

[0154] Example 2.6

[0155] In the case where the configuration information includes machine learning models or groups of machine learning models, the implementation process of S202 is: determine the concurrency number based on the number of machine learning models or the number of groups of machine learning models.

[0156] Correspondingly, the implementation process of S203 may be that the first communication node determines the concurrent number of CSI processing units according to the machine learning model, and concurrently calculates the precoding matrices of M machine learning models based on the concurrent number.

[0157] One way to determine the concurrency number O is to use the number of machine learning models as the concurrency number. Specifically, the concurrency number O is equal to the number of machine learning models. For example, one CSI calculation corresponds to one machine learning model, and M CSI calculations correspond to M machine learning models. That is, the first communication node performs O CSI calculations simultaneously, where O is equal to the number of machine learning models, M, and one CSI calculation corresponds to one machine learning model.

[0158] Another way to determine the concurrency O is to use the number of groups of machine learning models as the concurrency. Specifically, the concurrency O equals the number of grouped machine learning models. For example, if M machine learning models are grouped into X groups, the concurrency O equals X. One CSI calculation corresponds to one group of machine learning models, and X CSI calculations correspond to X groups of machine learning models. That is, the first communication node performs O CSI calculations simultaneously, where O equals the number of grouped machine learning models, X, and one CSI calculation corresponds to one group of machine learning models.

[0159] The grouping of machine learning models includes each machine learning model group formed by grouping by an average distribution of quantity, or each machine learning model group formed by grouping by an average distribution of computing power requirements, or each machine learning model group formed by grouping by matching the computing power of the CSI processing unit.

[0160] One way to divide M machine learning models into X groups is to divide them evenly into the X groups. For example, 6 machine learning models can be divided into 2 groups, each of which includes 3 machine learning models. For example, 6 machine learning models can be divided into 3 groups, each of which includes 2 machine learning models. For example, 7 machine learning models can be divided into 2 groups, one of which includes 3 machine learning models and the other includes 4 machine learning models. For example, 7 machine learning models can be divided into 3 groups, one of which includes 2 machine learning models, another includes 2 machine learning models, and another includes 3 machine learning models. The M machine learning models are evenly divided into the X groups to achieve load balancing for each CSI calculation.

[0161] Another way to group the M machine learning models into X groups is to group them unevenly. This uneven grouping can be implemented in two ways: grouping by evenly distributing the computing power requirements, or grouping by matching the computing power of the CSI processing units.

[0162] For example, an example where 6 machine learning models are unevenly divided into 3 machine learning model groups:

[0163] For example, here is another example where 6 machine learning models are unevenly divided into 3 machine learning model groups:

[0164] For example, an example where 6 machine learning models are unevenly divided into 2 machine learning model groups:

[0165] For example, here is another example where 6 machine learning models are unevenly divided into 2 machine learning model groups:

[0166] For example, an example where 7 machine learning models are unevenly divided into 3 machine learning model groups:

[0167] For example, here is another example where 7 machine learning models are unevenly divided into 3 machine learning model groups:

[0168] For example, here is another example where 7 machine learning models are unevenly divided into 3 machine learning model groups:

[0169] For example, an example where 7 machine learning models are unevenly divided into 2 machine learning model groups:

[0170] For example, here is another example where 7 machine learning models are unevenly divided into 2 machine learning model groups:

[0171] Corresponding to the situation where different machine learning models have different computational loads, that is, different machine learning models have different computing power requirements, the M machine learning models are unevenly divided into X groups, which can achieve a balance in the computing power requirements of each group of machine learning models, and thus achieve a load balance for each CSI calculation. In this implementation method, in the case of the above-mentioned division into three machine learning model groups, the difference between the computing power requirements of the machine learning models in machine learning model group 1, the computing power requirements of the machine learning models in machine learning model group 2, and the computing power requirements of the machine learning models in machine learning model group 3 does not exceed the preset difference degree or the preset difference threshold. That is, the computing power requirements of the machine learning models in each machine learning model group are balanced. The computing power requirement of the machine learning models in a machine learning model group refers to the sum of the computing power requirements of each machine learning model in the machine learning model group.

[0172] In the case where the computing power of the CSI processing units responsible for each CSI calculation is unequal, the M machine learning models are unevenly divided into X groups, which can achieve a match between the computing power of the CSI processing units and the computing power requirements of the machine learning model groups, thereby improving the processing efficiency of each CSI processing unit. In this implementation, in the case of the aforementioned division into three machine learning model groups, for example, the computing power requirements of the machine learning models in machine learning model group 1 can match the computing power of CSI processing unit 1, the computing power requirements of the machine learning models in machine learning model group 2 can match the computing power of CSI processing unit 2, and the computing power requirements of the machine learning models in machine learning model group 3 can match the computing power of CSI processing unit 3.

[0173] Example 2.7

[0174] When the configuration information includes the precoding matrix overhead or the grouping of the precoding matrix overhead, the implementation process of S202 is: determining the concurrency number according to the number of precoding matrix overheads or the number of groups of precoding matrix overheads. In this embodiment, the precoding matrix overhead may also be referred to as overhead.

[0175] Correspondingly, the implementation process of S203 may be that the first communication node determines the concurrent number of CSI processing units according to the overhead of the precoding matrix, and concurrently calculates M overhead precoding matrices with the concurrent number.

[0176] One way to determine the concurrency number O is to use the number of overheads as the concurrency number. That is, the concurrency number O equals the number of overheads. For example, one CSI calculation corresponds to one overhead, and M CSI calculations correspond to M overheads. That is, the first communication node performs O CSI calculations simultaneously, where O equals the number of overheads M, and one CSI calculation corresponds to one overhead.

[0177] Another way to determine the concurrency number O is to use the number of overhead groups as the concurrency number. That is, the concurrency number O equals the number of overhead groups. For example, if M overheads are grouped into X groups, the concurrency number O equals X. One CSI calculation corresponds to one overhead group, and X CSI calculations correspond to X overhead groups. That is, the first communication node performs O CSI calculations simultaneously, where O equals the number of overhead groups X, and one CSI calculation corresponds to one overhead group.

[0178] The overhead grouping includes each overhead group formed by grouping by an average distribution of quantity, or each overhead group formed by grouping by an average distribution of computing power requirements, or each overhead group formed by grouping by matching the computing power of the CSI processing unit.

[0179] One way to group M overheads into X groups is to evenly distribute the M overheads into the X groups. For example, 6 overheads can be divided into 2 groups, each containing 3 overheads. For example, 6 overheads can be divided into 3 groups, each containing 2 overheads. For example, 7 overheads can be divided into 2 groups, one containing 3 overheads and the other containing 4 overheads. For example, 7 overheads can be divided into 3 groups, one containing 2 overheads, another containing 2 overheads, and another containing 3 overheads. The M overheads are evenly distributed into the X groups to achieve load balancing for each CSI calculation.

[0180] Another way to group the M overheads into X groups is to group the M overheads unevenly into the X groups. In this uneven grouping approach, there are two implementations: grouping by evenly distributing the computing power requirements, or grouping by matching the computing power of the CSI processing units.

[0181] For example, an example where 6 expenses are unevenly divided into 3 expense groups:

[0182] For example, here is another example where 6 expenses are unevenly divided into 3 expense groups:

[0183] For example, an example where 6 costs are unevenly divided into 2 cost groups:

[0184] For example, here is another example where 6 expenses are unevenly divided into 2 expense groups:

[0185] For example, an example where 7 costs are unevenly divided into 3 cost groups:

[0186] For example, here is another example where 7 expenses are unevenly divided into 3 expense groups:

[0187] For example, here is another example where 7 expenses are unevenly divided into 3 expense groups:

[0188] For example, an example where 7 costs are unevenly divided into 2 cost groups:

[0189] For example, here is another example where 7 expenses are unevenly divided into 2 expense groups:

[0190] To accommodate situations where different overheads have different computational loads, i.e., different computing power requirements, the M overheads are unevenly divided into X groups. This can achieve balanced computing power requirements for each overhead group, and thus, balanced load for each CSI calculation. In this implementation, in the aforementioned three overhead groups, the difference between the computing power requirements for the overheads in overhead group 1, the computing power requirements for the overheads in overhead group 2, and the computing power requirements for the overheads in overhead group 3 does not exceed a preset difference level or a preset difference threshold. In other words, the computing power requirements for the overheads in each overhead group are balanced. The computing power requirement for the overheads in an overhead group refers to the sum of the computing power requirements for each overhead in the overhead group.

[0191] In the case where the computing power of the CSI processing units responsible for each CSI calculation is unequal, the M overheads are unevenly divided into X groups, which can achieve matching of the computing power of the CSI processing units with the computing power requirements of the overhead groups, thereby improving the processing efficiency of each CSI processing unit. In this implementation, in the case of the aforementioned division into three overhead groups, for example, the computing power requirement of the overheads in overhead group 1 can match the computing power of CSI processing unit 1, the computing power requirement of the overheads in overhead group 2 can match the computing power of CSI processing unit 2, and the computing power requirement of the overheads in overhead group 3 can match the computing power of CSI processing unit 3.

[0192] Example 2.8

[0193] In the case that the configuration information includes frequency domain units or groups of frequency domain units, the implementation process of S202 is: determining the concurrency number according to the number of frequency domain units or the number of groups of frequency domain units.

[0194] Correspondingly, the implementation process of S203 may be that the first communication node determines the concurrent number of CSI processing units according to the frequency domain units, and concurrently calculates the precoding matrices of M frequency domain units based on the concurrent number.

[0195] One way to determine the concurrency number O is to use the number of frequency domain units as the concurrency number. That is, the concurrency number O equals the number of frequency domain units. For example, one CSI calculation corresponds to one frequency domain unit, and M CSI calculations correspond to M frequency domain units. That is, the first communication node performs O CSI calculations simultaneously, where O equals the number of frequency domain units M, and one CSI calculation corresponds to one frequency domain unit.

[0196] Another way to determine the concurrency number O is to use the number of frequency domain unit groups as the concurrency number. That is, the concurrency number O equals the number of frequency domain unit groups. For example, if M frequency domain units are divided into X groups, the concurrency number O equals X. One CSI calculation corresponds to one group of frequency domain units, and X CSI calculations correspond to X groups of frequency domain units. That is, the first communication node performs O CSI calculations simultaneously, where O equals the number of frequency domain unit groups, X, and one CSI calculation corresponds to one group of frequency domain units.

[0197] The grouping of frequency domain units includes each frequency domain unit group formed by grouping in a manner of evenly distributing the number, or each frequency domain unit group formed by grouping in a manner of evenly distributing the computing power requirements, or each frequency domain unit group formed by grouping in a manner of matching the computing power of the CSI processing unit.

[0198] One way to divide M frequency domain units into X groups is to divide the M frequency domain units evenly into the X groups. For example, 6 frequency domain units are divided into 2 groups, each of which includes 3 frequency domain units. For example, 6 frequency domain units are divided into 3 groups, each of which includes 2 frequency domain units. For example, 7 frequency domain units are divided into 2 groups, one of which includes 3 frequency domain units and the other includes 4 frequency domain units. For example, 7 frequency domain units are divided into 3 groups, one of which includes 2 frequency domain units, another includes 2 frequency domain units, and another includes 3 frequency domain units. The M frequency domain units are evenly divided into X groups to achieve load balancing for each CSI calculation.

[0199] Another way to group the M frequency domain units into X groups is to group the M frequency domain units unevenly into the X groups. In this uneven grouping approach, there are two implementations: grouping by evenly distributing the computing power requirements, or grouping by matching the computing power of the CSI processing units.

[0200] For example, an example where 6 frequency domain units are unevenly divided into 3 frequency domain unit groups:

[0201] For example, another example where 6 frequency domain units are unevenly divided into 3 frequency domain unit groups:

[0202] For example, an example where 6 frequency domain units are unevenly divided into 2 frequency domain unit groups:

[0203] For example, here is another example where 6 frequency domain units are unevenly divided into 2 frequency domain unit groups:

[0204] For example, an example where 7 frequency domain units are unevenly divided into 3 frequency domain unit groups:

[0205] For example, another example where 7 frequency domain units are unevenly divided into 3 frequency domain unit groups:

[0206] For example, another example where 7 frequency domain units are unevenly divided into 3 frequency domain unit groups:

[0207] For example, an example where 7 frequency domain units are unevenly divided into 2 frequency domain unit groups:

[0208] For example, another example where 7 frequency domain units are unevenly divided into 2 frequency domain unit groups:

[0209] Corresponding to the situation where different frequency domain units have different computational loads, that is, different frequency domain units have different computing power requirements, the M frequency domain units are non-evenly divided into X groups, which can achieve a balance in the computing power requirements of each group of frequency domain units, and thus achieve load balancing of each CSI calculation. In this implementation method, in the case of being divided into three frequency domain unit groups, the difference between the computing power requirements of the frequency domain units in frequency domain unit group 1, the computing power requirements of the frequency domain units in frequency domain unit group 2, and the computing power requirements of the frequency domain units in frequency domain unit group 3 does not exceed the preset difference degree or the preset difference threshold. That is, the computing power requirements of the frequency domain units in each frequency domain unit group are balanced. The computing power requirement of the frequency domain units in a frequency domain unit group refers to the sum of the computing power requirements of each frequency domain unit in the frequency domain unit group.

[0210] In the case where the computing power of the CSI processing units responsible for each CSI calculation is unequal, the M frequency domain units are unevenly divided into X groups, which can match the computing power of the CSI processing units with the computing power requirements of the frequency domain unit groups, thereby improving the processing efficiency of each CSI processing unit. In this implementation, in the case of the above-mentioned division into three frequency domain unit groups, for example, the computing power requirements of the frequency domain units in frequency domain unit group 1 can match the computing power of CSI processing unit 1, the computing power requirements of the frequency domain units in frequency domain unit group 2 can match the computing power of CSI processing unit 2, and the computing power requirements of the frequency domain units in frequency domain unit group 3 can match the computing power of CSI processing unit 3.

[0211] Example 2.9

[0212] In the case that the configuration information includes obtaining precoding matrix modes or obtaining groups of precoding matrix modes, the implementation process of S202 is: determining the concurrency number according to the number of obtaining precoding matrix modes or the number of obtaining groups of precoding matrix modes.

[0213] Correspondingly, the implementation process of S203 may be that the first communication node determines the concurrent number of CSI processing units according to the method of obtaining the precoding matrix, and concurrently calculates M precoding matrices of the method of obtaining the precoding matrix with the concurrent number.

[0214] One way to determine the concurrent number O is to use the number of precoding matrix acquisition methods as the concurrent number. That is, the concurrent number O is equal to the number of precoding matrix acquisition methods. For example, one CSI calculation corresponds to one precoding matrix acquisition method, and M CSI calculations correspond to M precoding matrix acquisition methods. That is, the first communication node performs O CSI calculations simultaneously, where O is equal to the number of precoding matrix acquisition methods M, and one CSI calculation corresponds to one precoding matrix acquisition method.

[0215] Another way to determine the concurrency number O is to determine the concurrency number as the number of groups of precoding matrix methods. That is, the concurrency number O is equal to the number of groups of precoding matrix acquisition methods. For example, if M precoding matrix acquisition methods are divided into X groups, the concurrency number O is equal to X. One CSI calculation corresponds to one group of precoding matrix acquisition methods, and X CSI calculations correspond to X groups of precoding matrix acquisition methods. That is, the first communication node performs O CSI calculations simultaneously, O is equal to the number of groups of precoding matrix acquisition methods, X, and one CSI calculation corresponds to one group of precoding matrix acquisition methods.

[0216] The grouping of the precoding matrix acquisition method includes each precoding matrix acquisition method grouping by adopting an average quantity distribution method, or each precoding matrix acquisition method grouping by adopting an average computing power requirement distribution method, or each precoding matrix acquisition method grouping by adopting a computing power matching method with the CSI processing unit to form each precoding matrix acquisition method grouping.

[0217] One way to divide the M precoding matrix acquisition methods into X groups is to divide the M precoding matrix acquisition methods into X groups evenly. For example, 6 precoding matrix acquisition methods are divided into 2 groups, and each group of precoding matrix acquisition methods includes 3 precoding matrix acquisition methods. For example, 6 precoding matrix acquisition methods are divided into 3 groups, and each group of precoding matrix acquisition methods includes 2 precoding matrix acquisition methods. For example, 7 precoding matrix acquisition methods are divided into 2 groups, one of which includes 3 precoding matrix acquisition methods and the other includes 4 precoding matrix acquisition methods. For example, 7 precoding matrix acquisition methods are divided into 3 groups, one of which includes 2 precoding matrix acquisition methods, another group includes 2 precoding matrix acquisition methods, and another group includes 3 precoding matrix acquisition methods. The M precoding matrix acquisition methods are evenly divided into X groups to achieve load balancing for each CSI calculation.

[0218] Another way to group the M precoding matrix acquisition methods into X groups is to group the M precoding matrix acquisition methods into X groups unevenly. In this uneven grouping approach, there are two implementations: grouping by evenly distributing computing power requirements, or grouping by matching the computing power of the CSI processing unit.

[0219] For example, six precoding matrix acquisition methods are unevenly divided into three precoding matrix acquisition method groups:

[0220] For example, another example in which 6 ways of obtaining precoding matrices are unevenly divided into 3 groups of ways of obtaining precoding matrices:

[0221] For example, an example in which six precoding matrix acquisition methods are unevenly divided into two precoding matrix acquisition method groups:

[0222] For example, another example in which 6 ways of obtaining precoding matrices are unevenly divided into 2 groups of ways of obtaining precoding matrices:

[0223] For example, an example where 7 precoding matrix acquisition methods are unevenly divided into 3 precoding matrix acquisition method groups:

[0224] For example, another example in which 7 ways of obtaining precoding matrices are unevenly divided into 3 groups of ways of obtaining precoding matrices:

[0225] For example, another example in which 7 ways of obtaining precoding matrices are unevenly divided into 3 groups of ways of obtaining precoding matrices:

[0226] For example, an example in which 7 precoding matrix acquisition methods are unevenly divided into 2 precoding matrix acquisition method groups:

[0227] For example, another example in which 7 ways of obtaining precoding matrices are unevenly divided into 2 groups of ways of obtaining precoding matrices:

[0228] In response to the situation where different precoding matrix acquisition methods have different computational loads, that is, different precoding matrix acquisition methods have different computing power requirements, the M precoding matrix acquisition methods are unevenly divided into X groups. This can achieve a balance in the computing power requirements of each group of precoding matrix acquisition methods, and thus achieve a load balance for each CSI calculation. In this implementation, in the case of the aforementioned division into three precoding matrix acquisition method groups, the difference between the computing power requirements of the precoding matrix acquisition methods in precoding matrix acquisition method group 1, the computing power requirements of the precoding matrix acquisition methods in precoding matrix acquisition method group 2, and the computing power requirements of the precoding matrix acquisition methods in precoding matrix acquisition method group 3 does not exceed a preset difference degree or a preset difference threshold. In other words, the computing power requirements of the precoding matrix acquisition methods in each precoding matrix acquisition method group are balanced. The computing power requirement of the precoding matrix acquisition methods in a precoding matrix acquisition method group refers to the sum of the computing power requirements of each precoding matrix acquisition method in the precoding matrix acquisition method group.

[0229] In the case where the computing power of the CSI processing units responsible for each CSI calculation is unequal, the M precoding matrix acquisition methods are unevenly divided into X groups, which can match the computing power of the CSI processing units with the computing power requirements of the precoding matrix acquisition method groups, thereby improving the processing efficiency of each CSI processing unit. In this implementation, in the case of the above-mentioned division into three precoding matrix acquisition method groups, for example, the computing power requirements of the precoding matrix acquisition methods in precoding matrix acquisition method group 1 can match the computing power of CSI processing unit 1, the computing power requirements of the precoding matrix acquisition methods in precoding matrix acquisition method group 2 can match the computing power of CSI processing unit 2, and the computing power requirements of the precoding matrix acquisition methods in precoding matrix acquisition method group 3 can match the computing power of CSI processing unit 3.

[0230] In the above examples 2.3 to 2.9, for ease of description, any one of the precoding matrix codebook, the grouping of the precoding matrix codebook, the rank of the precoding matrix, the grouping of the rank of the precoding matrix, the layer of the precoding matrix, the grouping of the layer of the precoding matrix, the overhead of the precoding matrix, the grouping of the overhead of the precoding matrix, the machine learning model, the grouping of the machine learning model, the frequency domain unit, the grouping of the frequency domain unit, the method for obtaining the precoding matrix, and the grouping of the method for obtaining the precoding matrix is ​​referred to as target data, and the concurrency number is determined based on the number of target data. In addition to determining the number of target data as the concurrency number as described in the above examples, in this embodiment, the value after data processing of the number of target data can also be determined as the concurrency number. The data processing here can be data processing based on at least one of the four arithmetic operations and a preset value, or comparing the number of target data with a preset value and determining the larger or smaller one as the concurrency number. The preset value here can be an integer greater than 0.

[0231] Example 2.10

[0232] The implementation process of S202 may be: determining, based on the configuration information, the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the purpose of the precoding matrix in the CSI report; and determining the concurrency quantity based on the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the purpose of the precoding matrix in the CSI report.

[0233] The first communication node may determine the purpose of the precoding matrix in the CSI report based on information about the monitoring method for obtaining the precoding matrix. Alternatively, the purpose of the precoding matrix may be determined based on the overhead of the precoding matrix. The first communication node may determine the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report based on information about the CSI-RS resources.

[0234] When determining the concurrency number based on the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the purpose of the precoding matrix in the CSI report, it can be implemented in the following manner: determining the corresponding rule based on the purpose of the precoding matrix in the CSI report; determining the concurrency number based on the rule corresponding to the purpose of the precoding matrix in the CSI report and the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report.

[0235] The rule corresponding to the use of the precoding matrix in the CSI report can be to determine the concurrent number by performing data processing on the number of CSI-RS resources. The data processing here can be performed based on at least one of the four arithmetic operations and a preset value, or by comparing the number of CSI-RS resources with a preset value and determining the larger or smaller value as the concurrent number. Alternatively, the number of CSI-RS resources can be determined as the concurrent number. The preset value here can be an integer greater than 0.

[0236] For example, the purpose of the precoding matrix in the CSI report includes monitoring the CSI calculation method, and the concurrent number 0 of the CSI calculation is twice the number of CSI-RS resources. For another example, the purpose of the precoding matrix in the CSI report includes monitoring the CSI calculation method, and the concurrent number 0 of the CSI calculation is the sum of the number of CSI-RS resources and 1, or the concurrent number 0 of the CSI calculation is the number of CSI-RS resources plus 1. For another example, the purpose of the precoding matrix in the CSI report includes monitoring the CSI calculation method, and the concurrent number 0 of the CSI calculation is the larger of the number of CSI-RS resources and 2. For another example, the purpose of the precoding matrix in the CSI report includes monitoring the CSI calculation method, the concurrent number of the CSI calculation corresponding to the first type of CSI processing unit is the number of CSI-RS resources, and the concurrent number of the CSI calculation corresponding to the second type of CSI processing unit is the number of CSI-RS resources; or, the number of the first type of CSI processing units occupied is the number of CSI-RS resources, and the number of the second type of CSI processing units occupied is the number of CSI-RS resources. For another example, the purpose of the precoding matrix in the corresponding CSI report includes monitoring the CSI calculation method, the concurrent number of first-type CSI processing units corresponding to CSI calculation is the number of CSI-RS resources, and the concurrent number of second-type CSI processing units corresponding to CSI calculation is 1; or, the number of first-type CSI processing units occupied is the number of CSI-RS resources, and the number of second-type CSI processing units occupied is 1. For another example, the purpose of the precoding matrix in the corresponding CSI report includes monitoring the CSI calculation method, the concurrent number of first-type CSI processing units corresponding to CSI calculation is the number of CSI-RS resources, and the concurrent number of second-type CSI processing units corresponding to CSI calculation is 2; or, the number of first-type CSI processing units occupied is the number of CSI-RS resources, and the number of second-type CSI processing units occupied is 2.

[0237] For example, the usage of the precoding matrix in the corresponding CSI report does not include monitoring the CSI calculation method, and the concurrent number O of CSI calculations is the number of CSI-RS resources.

[0238] Example 2.11

[0239] The implementation process of S202 may be: determining the number of CSI-RS resources in the CSI report and the number of precoding matrices corresponding to the CSI-RS resources in the CSI report according to the configuration information; determining the concurrency quantity based on the comparison relationship between the number of CSI-RS resources in the CSI report and the number of precoding matrices corresponding to the CSI-RS resources in the CSI report.

[0240] For example, the configuration information includes the number of CSI-RS resources in the CSI report and the number of precoding matrices corresponding to the CSI-RS resources in the CSI report.

[0241] For another example, the first communication node may determine the number of CSI-RS resources in the CSI report based on the information of the CSI-RS resources in the configuration information, and determine the number of precoding matrices corresponding to the CSI-RS resources in the CSI report based on the relevant information of the precoding matrix.

[0242] When determining the concurrency number based on the comparison relationship between the number of CSI-RS resources in the CSI report and the number of precoding matrices corresponding to the CSI-RS resources in the CSI report, it can be implemented in the following manner: when the number of CSI-RS resources in the CSI report is less than the number of precoding matrices corresponding to the CSI-RS resources in the CSI report, the concurrency number is determined according to the first preset rule; when the number of CSI-RS resources in the CSI report is greater than or equal to the number of precoding matrices corresponding to the CSI-RS resources in the CSI report, the concurrency number is determined according to the second preset rule.

[0243] Exemplarily, the first preset rule is: the sum of the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrices corresponding to the CSI-RS resources in the CSI report minus the fifth value. The second preset rule is: the product of the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrices corresponding to the CSI-RS resources in the CSI report.

[0244] The first communication node selects a CSI-RS resource from the CSI-RS resource set, reports the selected CSI-RS resource, and reports the precoding matrix corresponding to the selected CSI-RS resource. The selected CSI-RS resource here is the CSI-RS resource in the CSI report. One way is to calculate different precoding matrices based on the selected CSI-RS resource and report the calculated precoding matrix; that is, one selected CSI-RS resource corresponds to multiple precoding matrices in the report. That is, the number of CSI-RS resources corresponding to the CSI report is less than the number of precoding matrices corresponding to the CSI-RS resource in the CSI report, and the concurrent number O of CSI calculation is the sum of the number of CSI-RS resources in the CSI-RS resource set and the number of precoding matrices corresponding to the CSI-RS resources in the CSI report minus the fifth value. The fifth value can be an integer greater than 0. Exemplarily, the fifth value can be 1. The number of CSI-RS resources corresponding to the CSI report is 1, the number of precoding matrices corresponding to the CSI-RS resources in the CSI report is 2, and the concurrent number O of CSI calculation is the sum of the number of CSI-RS resources in the CSI-RS resource set and 1.

[0245] Another method is that the first communication node selects multiple different CSI-RS resources, calculates different precoding matrices according to the selected different CSI-RS resources, and reports the calculated precoding matrices. That is, the number of CSI-RS resources corresponding to the CSI report is not less than the number of precoding matrices corresponding to the CSI-RS resources in the CSI report, and the concurrent number O of CSI calculations is the product of the number of CSI-RS resources in the CSI-RS resource set and the number of precoding matrices corresponding to the CSI-RS resources in the CSI report. The number of CSI-RS resources corresponding to the report in the CSI is 2, the number of precoding matrices corresponding to the CSI-RS resources in the CSI report is 2, and the concurrent number O of CSI calculations is the product of the number of CSI-RS resources in the CSI-RS resource set and 2.

[0246] In the CSI report, the CSI-RS resource in the CSI-RS resource set is indicated by a CSI-RS resource index number, and the precoding matrix is ​​indicated by a precoding matrix indicator in the report. Therefore, one approach is to determine the concurrent number O of CSI calculations based on the comparison between the number of CSI-RS resource index numbers in the CSI report and the precoding matrix indicators corresponding to the CSI-RS resource index numbers in the CSI report. For example, if the number of CSI-RS resource index numbers in the CSI report is less than the number of precoding matrix indicators corresponding to the CSI-RS resource index numbers in the CSI report, the concurrent number O of CSI calculations is the sum of the number of CSI-RS resource index numbers in the CSI-RS resource set and the number of precoding matrix indicators corresponding to the CSI-RS resource index numbers in the CSI report, minus 1. If the number of CSI-RS resource index numbers in the CSI report is 1 and the number of precoding matrix indicators corresponding to the CSI-RS resource index numbers in the CSI report is 2, the concurrent number O of CSI calculations is the sum of the number of CSI-RS resource index numbers in the CSI-RS resource set and 1.

[0247] For another example, if the number of CSI-RS resource index numbers corresponding to the CSI report is not less than the number of precoding matrix indicators corresponding to the CSI-RS resource index numbers in the CSI report, the concurrent number 0 for CSI calculation is the product of the number of CSI-RS resource index numbers in the CSI-RS resource set and the number of precoding matrix indicators corresponding to the CSI-RS resource index numbers in the CSI report. If the number of CSI-RS resource index numbers in the CSI report is 2 and the number of precoding matrix indicators corresponding to the CSI-RS resource index numbers in the CSI report is 2, the concurrent number 0 for CSI calculation is the product of the number of CSI-RS resource index numbers in the CSI-RS resource set and 2.

[0248] Example 2.11A

[0249] The implementation process of S202 may be: determining, based on the configuration information, the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrices corresponding to the CSI-RS resources in the CSI report; and determining the concurrency number based on the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrices corresponding to the CSI-RS resources in the CSI report.

[0250] For example, the configuration information includes the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrices corresponding to the CSI-RS resources in the CSI report.

[0251] For another example, the first communication node can determine the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report based on the information of the CSI-RS resources in the configuration information, and determine the number of precoding matrices corresponding to the CSI-RS resources in the CSI report based on the relevant information of the precoding matrix.

[0252] For example, the concurrent number 0 of CSI calculations is the sum of the number of CSI-RS resources in the CSI-RS resource set and the number of precoding matrices corresponding to the CSI-RS resources, minus a fifth value. The fifth value may be an integer greater than 0. Exemplarily, the fifth value may be 1. Corresponding to the number of CSI-RS resources in the CSI report being 1 and the number of precoding matrices corresponding to the CSI-RS resources in the CSI report being 2, the concurrent number 0 of CSI calculations is the sum of the number of CSI-RS resources in the CSI-RS resource set and 1.

[0253] For another example, the concurrent number of CSI calculations, O, is the product of the number of CSI-RS resources in the CSI-RS resource set and the number of precoding matrices corresponding to the CSI-RS resources. Given that the number of CSI-RS resources reported in the CSI is 2 and the number of precoding matrices corresponding to the CSI-RS resources is 2, the concurrent number of CSI calculations, O, is the product of the number of CSI-RS resources in the CSI-RS resource set and 2.

[0254] Example 2.12

[0255] The implementation process of S202 may be: determining the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrices in the CSI report according to the configuration information; determining the concurrency number according to the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrices in the CSI report.

[0256] The first communication node may determine the concurrency quantity based on a comparison between the number of CSI-RS resources in a CSI-RS resource set corresponding to the CSI report and the number of precoding matrices in the CSI report.

[0257] The first communication node may determine the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report based on the information of the CSI-RS resources. The first communication node may determine the number of precoding matrices in the CSI report based on the relevant information of the precoding matrices.

[0258] When determining the concurrent number based on the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrices in the CSI report, it can be implemented as follows: the larger of the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrices in the CSI report is determined as the concurrent number; or the larger of the number of processed CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of processed precoding matrices in the CSI report is determined as the concurrent number; or the value of the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report after data processing is determined as the concurrent number of the first type of CSI processing unit, and the value of the number of precoding matrices in the CSI report after data processing is determined as the concurrent number of the second type of CSI processing unit. The data processing here can be data processing based on at least one of the four arithmetic operations and a preset value. The preset value can be an integer greater than 0.

[0259] For example, the larger of the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrices in the CSI report is taken as the concurrent number O of CSI calculation. For another example, the larger of the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the sum of the number of precoding matrices in the CSI report plus 1 is taken as the concurrent number O of CSI calculation. For another example, the concurrent number of CSI calculation corresponding to the first type of CSI processing unit is the number of CSI-RS resources, and the concurrent number of CSI calculation corresponding to the second type of CSI processing unit is the number of precoding matrices in the CSI report. For another example, the concurrent number of CSI calculation corresponding to the first type of CSI processing unit is the number of CSI-RS resources, and the concurrent number of CSI calculation corresponding to the second type of CSI processing unit is the sum of the number of precoding matrices in the CSI report plus 1.

[0260] Example 2.13

[0261] The implementation process of S202 may be: determining, based on the configuration information, the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrix indicators in the CSI report; and determining the concurrency quantity based on the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrix indicators in the CSI report.

[0262] The first communication node determines the concurrency quantity according to a comparison relationship between the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrix indicators in the CSI report.

[0263] The first communication node may determine the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report based on the CSI-RS resource information. The first communication node may determine the number of precoding matrix indicators in the CSI report based on the relevant information of the precoding matrix.

[0264] When determining the concurrent number based on the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrix indicators in the CSI report, it can be implemented as follows: the larger of the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrix indicators in the CSI report is determined as the concurrent number; or the larger of the number of processed CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of processed precoding matrix indicators in the CSI report is determined as the concurrent number; or the value of the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report after data processing is determined as the concurrent number of the first type of CSI processing unit, and the value of the number of precoding matrix indicators in the CSI report after data processing is determined as the concurrent number of the second type of CSI processing unit. The data processing here can be data processing based on at least one of the four arithmetic operations and a preset value. The preset value can be an integer greater than 0.

[0265] For example, the larger of the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrix indicators in the CSI report is taken as the concurrent number O of CSI calculation. For another example, the larger of the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the sum of the number of precoding matrix indicators in the CSI report plus 1 is taken as the concurrent number O of CSI calculation. For another example, the concurrent number of CSI calculation corresponding to the first type of CSI processing unit is the number of CSI-RS resources, and the concurrent number of CSI calculation corresponding to the second type of CSI processing unit is the number of precoding matrix indicators in the CSI report. For another example, the concurrent number of CSI calculation corresponding to the first type of CSI processing unit is the number of CSI-RS resources, and the concurrent number of CSI calculation corresponding to the second type of CSI processing unit is the sum of the number of precoding matrix indicators in the CSI report plus 1.

[0266] Example 2.14

[0267] The implementation process of S202 may be: determining a candidate range of CSI-RS resource index numbers in the CSI report according to the configuration information; and determining the concurrent quantity according to the candidate range of CSI-RS resource index numbers in the CSI report.

[0268] The first communication node may determine a candidate range of CSI-RS resource index numbers in the CSI report according to the information of the CSI-RS resources.

[0269] The first communication node determines a scheme for obtaining the precoding matrix based on the candidate range of the CSI-RS resource index number in the CSI report, and then determines the number corresponding to the scheme for obtaining the precoding matrix based on the mapping relationship between the scheme and the number, and determines it as the concurrent number.

[0270] For a CSI-RS resource, a plurality of different calculation methods can be used to obtain the precoding matrix, and different index numbers corresponding to a CSI-RS are used to indicate that different calculation methods are used to obtain the precoding matrix. Therefore, for the CSI-RS resources in the CSI-RS resource set, different CSI-RS resource index ranges are used to indicate that different calculation methods are used to obtain the precoding matrix. One way to determine the concurrent number O of CSI calculation is to determine the concurrent number O of CSI calculation based on the candidate range of CSI-RS resource index numbers in the CSI report. For example, if the candidate index number is in range 1 and the precoding matrix is ​​obtained using the first scheme, the numerical value mapped to the first scheme or the numerical value included in the first scheme is determined as the concurrent number. If the candidate index number is in range 2 and the precoding matrix is ​​obtained using the second scheme, the numerical value mapped to the second scheme or the numerical value included in the second scheme is determined as the concurrent number. If the candidate index number is in range 3 and the precoding matrix is ​​obtained using the third scheme, the numerical value mapped to the third scheme or the numerical value included in the third scheme is determined as the concurrent number. If the candidate index number is in the range 4, the first scheme is used to obtain the precoding matrix, and the second scheme is used to obtain the precoding matrix. If the candidate index number is in the range 5, the first scheme is used to obtain the precoding matrix, the second scheme is used to obtain the precoding matrix, and the second scheme is used to obtain the precoding matrix. If the candidate index number is in the union of range 1 and range 2, the first scheme is used to obtain the precoding matrix, and the second scheme is used to obtain the precoding matrix. If the candidate index number is in the union of range 1, range 2, and range 3, the first scheme is used to obtain the precoding matrix, the second scheme is used to obtain the precoding matrix, and the second scheme is used to obtain the precoding matrix. Among them, the precoding matrix obtained by using the first scheme, the precoding matrix obtained by using the second scheme, and the precoding matrix obtained by using the third scheme may be the same or different. Each of the above schemes may include a numerical value or be mapped with a numerical value, and the numerical value is determined as the concurrent number.

[0271] Example 2.15

[0272] The implementation process of S202 may include: determining a CSI reporting group according to the configuration information; and determining a concurrent number according to the CSI reporting group, wherein the CSI reports in the CSI reporting group have the same set of candidate CSI-RS resources, or the CSI reports in the CSI reporting group correspond to the same CSI-RS resources, or the CSI reports in the CSI reporting group have the same priority.

[0273] The first communication node may determine the CSI report group according to the CSI-RS resource information or precoding matrix related information in the configuration information. The candidate CSI-RS resource set in this embodiment refers to the CSI-RS resource set corresponding to the CSI report.

[0274] Determining the concurrent number based on the CSI reporting group may involve pre-establishing a mapping relationship between the CSI reporting group and a numerical value. After determining the CSI reporting group to which the CSI report belongs, the numerical value corresponding to the CSI reporting group to which the CSI report belongs is determined based on the mapping relationship, and this numerical value is determined as the concurrent number. The CSI reporting group in this embodiment refers to the CSI reporting group to which the CSI report belongs.

[0275] Multiple CSI reports share some common CSI calculation components. For example, measuring the channel. Another example is calculating the right eigenvector matrix of the channel coefficient matrix based on the channel, where the right eigenvector matrix is ​​the ideal precoding matrix. Another example is selecting a CSI-RS resource as the reported CSI-RS resource. The same calculation components of different reports do not need to be repeatedly calculated, saving computing power or computing units. Therefore, grouping multiple CSI reports into a group and determining the concurrent number O of CSI calculations based on the CSI report group can save computing power and improve computational efficiency. One method for determining the concurrent number O of CSI calculations is to determine the concurrent number O of CSI calculations based on the CSI report group. For example, Y reports measuring the same set of candidate CSI-RS resources are grouped together, and the concurrent number of CSI calculations is determined based on the group. For another example, Y reports selecting the same CSI-RS resource as the reporting resource are grouped together, and the concurrent number of CSI calculations is determined based on the group. For another example, Y reports with the same priority are grouped together, and the concurrent number of CSI calculations is determined based on the group.

[0276] Example 2.16

[0277] The implementation process of S202 may be: determining the processing time requirement of the CSI report according to the configuration information; and determining the concurrency quantity according to the processing time requirement of the CSI report.

[0278] The first communication node may determine the processing time requirement for the CSI report based on the CSI-RS resource information or the precoding matrix-related information in the configuration information.

[0279] When determining the number of concurrent requests based on the processing duration requirement of the CSI report, the number of concurrent requests may be determined based on the processing duration requirement of the CSI report and a preset rule. The processing duration requirement of the CSI report may be referred to as the processing duration of the CSI report, the CSI report processing time, or the length of time for processing the CSI report.

[0280] The preset rule here may be: when the processing time requirement of the CSI report is greater than or equal to the preset time threshold, the concurrent number is a first number; when the processing time requirement of the CSI report is less than the preset time threshold, the concurrent number is a second number. The second number is greater than the first number. Both the first number and the second number are integers greater than 0.

[0281] The CSI report processing time is long, and the required number of concurrent CSI calculations is small; if a larger number of concurrent CSI calculations is used, CSI calculation units will be wasted. The CSI report processing time is short, and the CSI calculation needs to be accelerated, so the required number of concurrent CSI calculations is large; if a smaller number of concurrent CSI calculations is used, the CSI calculation task cannot be completed within the specified time length. A possible method for determining the number of concurrent CSI calculations is to determine the number of concurrent CSI calculations O based on the time length for processing the CSI report. By determining the number of concurrent CSI calculations O based on the time length for processing the CSI report, a number of concurrent calculations that matches the time length for processing the CSI report can be obtained, thereby completing the CSI calculation task within the specified time length and saving processing units for CSI calculation. For example, when the time length for processing the CSI report is T, the number of concurrent CSI calculations O is 1; when the time length for processing the CSI report is T / 2, the number of concurrent CSI calculations is 2. For another example, when the time length for processing the CSI report is 5 time slots, the concurrent number O of CSI calculation is 2; when the time length for processing the CSI report is 3 time slots, the concurrent number of CSI calculation is 4. Here, T is a number greater than 0.

[0282] Example 2.17

[0283] The implementation process of S202 may be: determining the subcarrier spacing size according to the configuration information; and determining the concurrency quantity according to the subcarrier spacing size.

[0284] The first communication node may determine the subcarrier spacing size based on the CSI-RS resource information or precoding matrix related information in the configuration information, or determine the subcarrier spacing size based on other information in the configuration information.

[0285] When determining the number of concurrent operations based on the subcarrier spacing, a mapping relationship between the subcarrier spacing and a numerical value may be pre-established. After determining the subcarrier spacing, the numerical value corresponding to the subcarrier spacing is determined based on the mapping relationship and used as the number of concurrent operations.

[0286] The subcarrier spacing size determines the time length of the time slot in the Orthogonal Frequency Division Multiplexing (OFDM) system. The actual length of the CSI report processing time for a fixed number of time slots is determined by the subcarrier spacing size. One way is to determine the concurrent number O of CSI calculations based on the subcarrier spacing size. For example, for a subcarrier spacing of 15kHz, the CSI report processing time is 4 time slots, and the concurrent number O of CSI calculations is 2; for a subcarrier spacing of 30kHz, the CSI report processing time is 4 time slots, and the concurrent number O of CSI calculations is 4. For example, for a subcarrier spacing of 15kHz, the CSI report processing time is 6 time slots, and the concurrent number O of CSI calculations is 1; for a subcarrier spacing of 30kHz, the CSI report processing time is 6 time slots, and the concurrent number O of CSI calculations is 3.

[0287] The above describes various implementation methods for determining the concurrent number of CSI processing units according to configuration information provided by this embodiment.

[0288] The concurrent number of CSI processing units determined in this embodiment includes the concurrent number of at least two types of CSI processing units. That is, the type of CSI processing unit and the concurrent number corresponding to each type of CSI processing unit can be determined.

[0289] The concurrent number of CSI processing units determined in this embodiment may also include the concurrent number of CSI processing units of only one type.

[0290] In this embodiment, after processing the CSI report, the first communication node may send the CSI report to the second communication node, so that the second communication node determines the channel state information according to the CSI report, and further determines the data transmission strategy.

[0291] The following introduces the relevant contents of the CSI report obtained after executing S203 in this embodiment.

[0292] Wireless communication has evolved to the fifth generation of communication technology. LTE technology in the fourth generation of wireless communication technology and NR technology in the fifth generation of wireless communication technology are both based on OFDM. In OFDM technology, the smallest frequency domain unit is a subcarrier, and the smallest time domain unit is an OFDM symbol. To facilitate the use of frequency domain resources, resource blocks are defined, and a resource block is defined as a specific number of consecutive subcarriers; bandwidth parts (BWPs) are also defined, and a bandwidth block is defined as another specific number of consecutive resource blocks on a carrier. To facilitate the use of time domain resources, time slots are defined, and a time slot is defined as another specific number of consecutive OFDM symbols.

[0293] The second communication node transmits a reference signal; the first communication node measures the reference signal, determines the channel state information (CSI) from the second communication node to the first communication node, and reports a CSI report to the second communication node. The second communication node receives the CSI report from the first communication node. Based on the channel state represented by the received CSI report, the second communication node determines a data transmission strategy and transmits data, thereby improving data transmission efficiency. The accuracy of the channel state represented by the CSI affects the second communication node's transmission strategy, and thus data transmission efficiency. The more comprehensive the CSI information the second communication node has, the more conducive it is to formulating an appropriate data transmission strategy, thereby improving system performance. Therefore, the second communication node desires the first communication node to report multiple CSI reports in a short period of time. For example, reports corresponding to different antenna transmit beams of the second communication node; reports corresponding to different numbers of antenna ports; reports corresponding to different precoding codebooks; reports corresponding to different precoding acquisition methods; reports corresponding to different monitoring acquisition precoding methods; and reports corresponding to different combinations of report content. The method for processing CSI reports provided in this embodiment can improve the processing efficiency of CSI reports and improve the efficiency of the first communication node in reporting CSI reports. In turn, the channel state information mastered by the second communication node becomes more comprehensive, which is conducive to the second communication node to formulate an appropriate data transmission strategy, thereby improving system performance.

[0294] The reference signal sent by the second communication node to the first communication node is a downlink reference signal. The downlink reference signal used for channel state information reporting in the LTE system includes a cell-specific reference signal (CRS) and a channel state information reference signal (CSI-RS). The downlink reference signal used for channel state information reporting in the NR system includes a channel state information reference signal (CSI-RS). The channel state information reference signal (CSI-RS) is carried by a channel state information reference signal resource (CSI-RS Resource), and the channel state information reference signal resource is composed of a CDM group. A CDM group is composed of radio resource elements, and the CSI-RS of a group of CSI-RS ports are multiplexed thereon by code division multiplexing.

[0295] The content of the channel state information transmitted between the second communication node and the first communication node includes a channel quality indicator (CQI) to indicate the quality of the channel. Alternatively, it includes a precoding matrix indicator (PMI) to indicate the precoding matrix applied to the base station antenna. One type of CQI reporting format is wideband CQI reporting, that is, reporting a channel quality for a channel state information reporting band (CSI reporting band), and the channel quality corresponds to the entire channel state information reporting band; another type of CQI reporting format is subband CQI reporting, that is, giving the channel quality for the channel state information reporting band (CSI reporting band) in units of subbands, where one channel quality corresponds to one subband, that is, reporting a channel quality for each subband of the channel state information reporting band. The subband is a frequency domain unit, defined as N consecutive resource blocks (RBs), where N is a positive integer. For ease of description, this application refers to the channel quality indicator subband, or CQI subband, or subband; where N is called the size of the CQI subband, or the CQI subband size, or the subband size. The bandwidth block is divided into subbands, and the channel state information reporting band (CSI reporting band) is defined by a subset of the subbands of the bandwidth part (BWP). The channel state information reporting band (CSI reporting band) is the frequency band on which the channel state information needs to be reported.

[0296] One way to determine channel quality is based on the strength of the reference signal received by the first communication node. Another way to determine channel quality is based on the signal-to-interference-plus-noise ratio of the received reference signal. In the channel state information reporting band, if the channel quality does not vary significantly, reporting CQI using wideband CQI reporting can reduce the resource overhead used for CQI reporting. If the channel quality varies significantly in the frequency domain, reporting CQI using subband CQI reporting can increase the accuracy of CQI reporting.

[0297] One type of PMI reporting format is a wideband PMI report, that is, reporting a PMI for a channel state information reporting band (CSI reporting band), and the PMI corresponds to the entire channel state information reporting band. Another type of PMI reporting format is a subband PMI report, that is, reporting a PMI for each subband of the channel state information reporting band, or reporting a component of a PMI for each subband of the channel state information reporting band. For example, the PMI consists of X1 and X2. One way to report a component of a PMI for each subband of the channel state information reporting band is to report an X1 for the entire band and an X2 for each subband; another way is to report an X1 and an X2 for each subband.

[0298] Another type of PMI reporting format is one in which the reported PMI indicates R precoding matrices for each subband, where R is a positive integer. In terms of the frequency domain granularity of the feedback precoding matrix, R represents the number of precoding matrix subbands included in each subband, or the number of precoding matrix subbands included in each CQI subband.

[0299] In an embodiment of the present application, by receiving configuration information of the second communication node, the concurrent number of CSI processing units is determined according to the configuration information, and the CSI processing units corresponding to the concurrent number are used to process the CSI reports, thereby realizing concurrent processing of the CSI reports, thereby improving the processing efficiency of the CSI reports and, in turn, improving the efficiency of data transmission.

[0300] Figure 3 is a flowchart illustrating another method for processing channel state information reports provided by one embodiment. As shown in Figure 3 , the solution provided by this embodiment is applicable to a second communication node. In this embodiment, the second communication node (also referred to as a second communication node device) may be an access network device, such as a base station. The method includes steps S301-S302.

[0301] S301: Send configuration information to the first communication node.

[0302] S302: Receive a CSI report processed by the first communication node according to the configuration information.

[0303] The CSI report is a report generated by the first communication node determining the concurrent number of CSI processing units according to the configuration information and processing using the CSI processing units corresponding to the concurrent number.

[0304] After receiving the CSI report sent by the first communication node, the second communication node can determine a data transmission strategy based on the CSI report, and transmit data between the first communication node and the second communication node based on the data transmission strategy.

[0305] Prior to S301, the second communication node receives capability information sent by the first communication node. The second communication node may determine configuration information based on the capability information sent by the first communication node and send the configuration information to the first communication node. In this embodiment, the capability information refers to information about the capabilities supported by the first communication node.

[0306] Exemplarily, the capability information in this embodiment may include at least one of the following: the number of CSI processing units, the type of the CSI processing unit, and the number of CSI processing units corresponding to the type of the CSI processing unit.

[0307] In one embodiment, the configuration information may include at least one of the following information: information about CSI-RS resources, grouping of CSI-RS resources, precoding matrix codebook, grouping of precoding matrix codebook, rank of precoding matrix, grouping of rank of precoding matrix, layer of precoding matrix, grouping of layer of precoding matrix, overhead of precoding matrix, grouping of overhead of precoding matrix, machine learning model, grouping of machine learning model, frequency domain unit, grouping of frequency domain unit, way of obtaining precoding matrix, grouping of way of obtaining precoding matrix, and information on monitoring way of obtaining precoding matrix.

[0308] In one embodiment, when the configuration information includes information of CSI-RS resources or grouping of CSI-RS resources, the first communication node determines the concurrency number according to the number of CSI-RS resources or the number of groupings of CSI-RS resources.

[0309] Exemplarily, the first communication node determines the concurrency number according to the following method: determining the number of CSI-RS resources as the concurrency number; or determining the sum of the number of CSI-RS resources and a preset first value as the concurrency number; or determining the larger of the number of CSI-RS resources and a preset second value as the concurrency number; or determining the number of groups of CSI-RS resources as the concurrency number. The grouping of CSI-RS resources includes each CSI-RS group formed by grouping in an average distribution manner, or each CSI-RS group formed by grouping in an average distribution manner according to computing power requirements, or each CSI-RS group formed by grouping in a manner that matches the computing power of the CSI processing unit.

[0310] In one embodiment, the first communication node determines the number of precoding matrices or the number of groups of precoding matrices according to configuration information; and determines the concurrency number according to the number of precoding matrices or the number of groups of precoding matrices.

[0311] Exemplarily, the first communication node determines the concurrency number in the following manner: determining the number of precoding matrices as the concurrency number; or determining the sum of the number of precoding matrices and a preset third value as the concurrency number; or determining the larger of the number of precoding matrices and a preset fourth value as the concurrency number; or determining the number of groups of precoding matrices as the concurrency number. The grouping of precoding matrices includes each precoding matrix group formed by grouping in an average distribution of numbers, or each precoding matrix group formed by grouping in an average distribution of computing power requirements, or each precoding matrix group formed by grouping in a manner that matches the computing power of the CSI processing unit.

[0312] In one embodiment, when the configuration information is target data, the first communication node determines the number of target data as the concurrent number. The target data is any one of a precoding matrix codebook, a grouping of a precoding matrix codebook, a rank of a precoding matrix, a grouping of a rank of a precoding matrix, a layer of a precoding matrix, a grouping of a layer of a precoding matrix, an overhead of a precoding matrix, a grouping of an overhead of a precoding matrix, a machine learning model, a grouping of a machine learning model, a frequency domain unit, a grouping of a frequency domain unit, a method for obtaining a precoding matrix, and a grouping of a method for obtaining a precoding matrix. The grouping of the precoding matrix codebook, the grouping of the rank of the precoding matrix, the grouping of the layer of the precoding matrix, the grouping of the overhead of the precoding matrix, the grouping of the machine learning model, the grouping of the frequency domain unit, and the grouping of the method for obtaining a precoding matrix may include: groups formed by grouping using an average number distribution method, groups formed by grouping using an average computing power requirement distribution method, or groups formed by grouping using a method that matches the computing power of the CSI processing unit.

[0313] In one embodiment, the first communication node determines the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the purpose of the precoding matrix in the CSI report based on the configuration information; and determines the concurrency quantity based on the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the purpose of the precoding matrix in the CSI report.

[0314] Exemplarily, when determining the concurrency number based on the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the purpose of the precoding matrix in the CSI report, the first communication node determines the concurrency number in the following manner: determining the corresponding rules based on the purpose of the precoding matrix in the CSI report; determining the concurrency number based on the rules corresponding to the purpose of the precoding matrix in the CSI report and the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report.

[0315] In one embodiment, the first communication node determines the number of CSI-RS resources in the CSI report and the number of precoding matrices corresponding to the CSI-RS resources in the CSI report based on the configuration information; and determines the concurrency number based on the comparison relationship between the number of CSI-RS resources in the CSI report and the number of precoding matrices corresponding to the CSI-RS resources in the CSI report.

[0316] Exemplarily, when determining the concurrency number based on the comparison relationship between the number of CSI-RS resources in the CSI report and the number of corresponding precoding matrices, the first communication node determines the concurrency number in the following manner: when the number of CSI-RS resources in the CSI report is less than the number of precoding matrices corresponding to the CSI-RS resources in the CSI report, the concurrency number is determined according to the first preset rule; when the number of CSI-RS resources in the CSI report is greater than or equal to the number of precoding matrices corresponding to the CSI-RS resources in the CSI report, the concurrency number is determined according to the second preset rule.

[0317] The first preset rule is: the sum of the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrices corresponding to the CSI-RS resources in the CSI report minus the fifth value. The second preset rule is: the product of the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrices corresponding to the CSI-RS resources in the CSI report.

[0318] In one embodiment, the first communication node determines the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrices in the CSI report based on the configuration information; and determines the concurrency number based on the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrices in the CSI report.

[0319] Exemplarily, when determining the concurrent number based on the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrices in the CSI report, the first communication node determines the concurrent number in the following manner: determining the larger of the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrices in the CSI report as the concurrent number; or, determining the larger of the number of processed CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of processed precoding matrices in the CSI report as the concurrent number; or, determining the value of the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report after data processing as the concurrent number of the first type of CSI processing unit, and determining the value of the number of precoding matrices in the CSI report after data processing as the concurrent number of the second type of CSI processing unit.

[0320] In one embodiment, the first communication node determines the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrix indicators in the CSI report based on the configuration information; and determines the concurrency number based on the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrix indicators in the CSI report.

[0321] In one embodiment, the first communication node determines a candidate range of CSI-RS resource index numbers in the CSI report according to configuration information; and determines a concurrent quantity according to the candidate range of CSI-RS resource index numbers in the CSI report.

[0322] In one embodiment, the first communication node determines a CSI reporting group based on configuration information, and determines a concurrent number based on the CSI reporting group. The CSI reports in the CSI reporting group have the same set of candidate CSI-RS resources, or the CSI reports in the CSI reporting group correspond to the same CSI-RS resources, or the CSI reports in the CSI reporting group have the same priority.

[0323] In one embodiment, the first communication node determines a processing time requirement for the CSI report based on configuration information; and determines a concurrent quantity based on the processing time requirement for the CSI report.

[0324] In one embodiment, the first communication node determines the subcarrier spacing size according to the configuration information; and determines the concurrency quantity according to the subcarrier spacing size.

[0325] In one embodiment, the concurrent number of CSI processing units includes the concurrent number of at least two types of CSI processing units.

[0326] The method for processing CSI reports provided in this embodiment sends configuration information to the first communication node, and receives the channel state information CSI report processed by the first communication node according to the configuration information. The CSI report is a report formed after the first communication node determines the concurrent number of CSI processing units according to the configuration information and uses the CSI processing units corresponding to the concurrent number for processing. The first communication node determines the concurrent number of CSI processing units according to the configuration information, and uses the CSI processing units corresponding to the concurrent number to process the CSI report, and processes the CSI report in a concurrent manner. The second communication node receives the CSI report. Since the processing efficiency of the CSI report is improved, the channel state information mastered by the second communication node becomes more sufficient, which is beneficial for the second communication node to formulate an appropriate data transmission strategy, thereby improving the performance of the system.

[0327] Figure 4 is an interactive diagram of another method for processing channel state information reports provided by an embodiment. This embodiment describes the method for processing CSI reports provided by this embodiment from the perspective of interaction between a first communication node and a second communication node. As shown in Figure 4, the method for processing CSI reports provided by this embodiment includes S401-S406.

[0328] S401: Send configuration information to the first communication node.

[0329] S402: Receive configuration information of the second communication node.

[0330] S403: Determine the concurrent number of CSI processing units according to the configuration information.

[0331] S404: Use CSI processing units corresponding to the concurrent number to process the CSI report.

[0332] S405: Send a CSI report to the second communication node.

[0333] S406: Receive the CSI report processed by the first communication node according to the configuration information.

[0334] The implementation method of the configuration information in this embodiment, the implementation method of determining the concurrent number of CSI processing units based on the configuration information, and the implementation method of processing CSI reports using CSI processing units corresponding to the concurrent number are all similar to the technical principles and implementation processes in the embodiments and various implementation methods shown in Figures 2 and 3, have the same technical effects, and are not further described here.

[0335] FIG5 is a schematic diagram of the structure of an apparatus for processing a channel state information report according to an embodiment. The apparatus may be configured in a first communication node. As shown in FIG5 , the apparatus for processing a CSI report according to this embodiment includes the following modules.

[0336] The receiving module 501 is configured to receive configuration information of a second communication node.

[0337] The determination module 502 is configured to determine the concurrent number of CSI processing units according to the configuration information.

[0338] The processing module 503 is configured to use the CSI processing units corresponding to the concurrent number to process the CSI report.

[0339] In one embodiment, the configuration information may include at least one of the following information: information about CSI-RS resources, grouping of CSI-RS resources, precoding matrix codebook, grouping of precoding matrix codebook, rank of precoding matrix, grouping of rank of precoding matrix, layer of precoding matrix, grouping of layer of precoding matrix, overhead of precoding matrix, grouping of overhead of precoding matrix, machine learning model, grouping of machine learning model, frequency domain unit, grouping of frequency domain unit, way of obtaining precoding matrix, grouping of way of obtaining precoding matrix, and information on monitoring way of obtaining precoding matrix.

[0340] The CSI-RS resource information indicates at least one of the following: the CSI-RS resources in the CSI-RS resource set corresponding to the CSI report, the number of CSI-RS resources in the CSI resource set corresponding to the CSI report, the number of CSI-RS resources in the CSI report, and the candidate range of CSI-RS resource index numbers in the CSI report. The difference between the CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the CSI-RS resources in the CSI report is that the CSI-RS resources in the CSI-RS resource set corresponding to the CSI report refer to the candidate CSI-RS resources corresponding to the CSI report, while the CSI-RS resources in the CSI report refer to the CSI-RS resources selected in the CSI report. The CSI-RS resources in the CSI report are a subset of the CSI-RS resources in the CSI-RS resource set corresponding to the CSI report.

[0341] The overhead of the precoding matrix refers to the resources required after the precoding matrix is ​​compressed. For example, the overhead of the precoding matrix can be expressed as the number of bits after the precoding matrix is ​​compressed.

[0342] The machine learning model is used to output the precoding matrix. The machine learning model in this embodiment can be a model trained using various machine learning methods. For example, the machine learning model can be an artificial intelligence model such as a neural network or a convolutional neural network.

[0343] The frequency domain unit in this embodiment may be a frequency domain unit defined according to requirements. For example, the frequency domain unit in this embodiment may be an RB, or a subband, etc.

[0344] The information on monitoring the method for obtaining the precoding matrix includes at least one of the following information: whether to perform a monitoring report on the method for obtaining the precoding matrix, the content of the monitoring report, the format of the monitoring report, and the like.

[0345] In one embodiment, when the configuration information includes information of CSI-RS resources or grouping of CSI-RS resources, the determination module 502 is configured to determine the concurrency quantity according to the number of CSI-RS resources or the number of groupings of CSI-RS resources.

[0346] Exemplarily, the determination module 502 is configured to determine the concurrency number according to the following manner: determining the number of CSI-RS resources as the concurrency number; or determining the sum of the number of CSI-RS resources and a preset first value as the concurrency number; or determining the larger of the number of CSI-RS resources and a preset second value as the concurrency number; or determining the number of groups of CSI-RS resources as the concurrency number. The grouping of CSI-RS resources includes each CSI-RS group formed by grouping in an average distribution of quantity, or each CSI-RS group formed by grouping in an average distribution of computing power requirements, or each CSI-RS group formed by grouping in a manner matching the computing power of the CSI processing unit.

[0347] In one embodiment, the determination module 502 is configured to determine the number of precoding matrices or the number of groups of precoding matrices according to configuration information; and determine the concurrency number according to the number of precoding matrices or the number of groups of precoding matrices.

[0348] Exemplarily, the determination module 502 is configured to determine the concurrency number according to the following method: determining the number of precoding matrices as the concurrency number; or determining the sum of the number of precoding matrices and a preset third value as the concurrency number; or determining the larger of the number of precoding matrices and a preset fourth value as the concurrency number; or determining the number of groups of precoding matrices as the concurrency number. The grouping of precoding matrices includes each precoding matrix group formed by grouping in an average distribution of numbers, or each precoding matrix group formed by grouping in an average distribution of computing power requirements, or each precoding matrix group formed by grouping in a manner that matches the computing power of the CSI processing unit.

[0349] In one embodiment, when the configuration information is target data, the determination module 502 is configured to determine the number of target data as the concurrent number. The target data is any one of a precoding matrix codebook, a grouping of precoding matrix codebooks, a rank of a precoding matrix, a grouping of ranks of a precoding matrix, a layer of a precoding matrix, a grouping of layers of a precoding matrix, an overhead of a precoding matrix, a grouping of overhead of a precoding matrix, a machine learning model, a grouping of machine learning models, a frequency domain unit, a grouping of frequency domain units, a method for obtaining a precoding matrix, and a grouping of a method for obtaining a precoding matrix. The grouping of the precoding matrix codebook, the grouping of the rank of the precoding matrix, the grouping of the layers of the precoding matrix, the grouping of the overhead of the precoding matrix, the grouping of the machine learning model, the grouping of the frequency domain unit, and the grouping of the method for obtaining a precoding matrix may all include: groups formed by grouping using an average number distribution method, groups formed by grouping using an average computing power distribution method, or groups formed by grouping using a method that matches the computing power of the CSI processing unit.

[0350] In one embodiment, the determination module 502 is configured to determine, based on the configuration information, the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the purpose of the precoding matrix in the CSI report; and determine the concurrency quantity based on the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the purpose of the precoding matrix in the CSI report.

[0351] Exemplarily, when determining the concurrent number based on the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the purpose of the precoding matrix in the CSI report, the determination module 502 is configured to determine the concurrent number in the following manner: determining the corresponding rules based on the purpose of the precoding matrix in the CSI report; determining the concurrent number based on the rules corresponding to the purpose of the precoding matrix in the CSI report and the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report.

[0352] In one embodiment, the determination module 502 is configured to determine the number of CSI-RS resources in the CSI report and the number of precoding matrices corresponding to the CSI-RS resources in the CSI report based on the configuration information; and determine the concurrency quantity based on the comparison relationship between the number of CSI-RS resources in the CSI report and the number of precoding matrices corresponding to the CSI-RS resources in the CSI report.

[0353] Exemplarily, when determining the concurrency number based on the comparison relationship between the number of CSI-RS resources in the CSI report and the number of corresponding precoding matrices, the determination module 502 is configured to determine the concurrency number in the following manner: when the number of CSI-RS resources in the CSI report is less than the number of precoding matrices corresponding to the CSI-RS resources in the CSI report, the concurrency number is determined according to the first preset rule; when the number of CSI-RS resources in the CSI report is greater than or equal to the number of precoding matrices corresponding to the CSI-RS resources in the CSI report, the concurrency number is determined according to the second preset rule.

[0354] The first preset rule is: the sum of the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrices corresponding to the CSI-RS resources in the CSI report minus the fifth value. The second preset rule is: the product of the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrices corresponding to the CSI-RS resources in the CSI report.

[0355] In one embodiment, the determination module 502 is configured to determine the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrices in the CSI report based on the configuration information; and determine the concurrency quantity based on the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrices in the CSI report.

[0356] Exemplarily, when determining the concurrent number based on the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrices in the CSI report, the determination module 502 is configured to determine the concurrent number in the following manner: determining the larger of the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrices in the CSI report as the concurrent number; or, determining the larger of the number of processed CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of processed precoding matrices in the CSI report as the concurrent number; or, determining the value of the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report after data processing as the concurrent number of the first type of CSI processing unit, and determining the value of the number of precoding matrices in the CSI report after data processing as the concurrent number of the second type of CSI processing unit.

[0357] In one embodiment, the determination module 502 is configured to determine, based on the configuration information, the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrix indicators in the CSI report; and determine the concurrency quantity based on the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrix indicators in the CSI report.

[0358] In one embodiment, the determining module 502 is configured to determine a candidate range of CSI-RS resource index numbers in the CSI report according to configuration information; and determine the concurrent quantity according to the candidate range of CSI-RS resource index numbers in the CSI report.

[0359] In one embodiment, the determining module 502 is configured to determine a CSI reporting group based on configuration information, and determine the concurrent quantity based on the CSI reporting group. The CSI reports in the CSI reporting group have the same set of candidate CSI-RS resources, or the CSI reports in the CSI reporting group correspond to the same CSI-RS resources, or the CSI reports in the CSI reporting group have the same priority.

[0360] In one embodiment, the determining module 502 is configured to determine a processing time requirement for the CSI report according to configuration information; and determine a concurrent quantity according to the processing time requirement for the CSI report.

[0361] In one embodiment, the determining module 502 is configured to determine the subcarrier spacing size according to the configuration information; and determine the number of concurrent operations according to the subcarrier spacing size.

[0362] In one embodiment, the concurrent number of CSI processing units includes the concurrent number of at least two types of CSI processing units.

[0363] The apparatus for processing CSI reports provided in this embodiment is for implementing the method for processing CSI reports in the above embodiment. The implementation principle and technical effects of the apparatus for processing CSI reports provided in this embodiment are similar to those in the above embodiment and will not be repeated here.

[0364] FIG6 is a schematic diagram of the structure of another apparatus for processing a channel state information report according to an embodiment. The apparatus may be configured in a second communication node. As shown in FIG6 , the apparatus for processing a CSI report according to this embodiment includes the following modules.

[0365] The sending module 601 is configured to send configuration information to the first communication node.

[0366] The receiving module 602 is configured to receive a channel state information CSI report processed by the first communication node according to the configuration information.

[0367] The CSI report is a report generated by the first communication node determining the concurrent number of CSI processing units according to the configuration information and processing using the CSI processing units corresponding to the concurrent number.

[0368] In one embodiment, the configuration information includes at least one of the following information: information of CSI-reference signal RS resources, grouping of CSI-RS resources, precoding matrix codebook, grouping of precoding matrix codebook, rank of precoding matrix, grouping of rank of precoding matrix, layer of precoding matrix, grouping of layer of precoding matrix, overhead of precoding matrix, grouping of overhead of precoding matrix, machine learning model, grouping of machine learning model, frequency domain unit, grouping of frequency domain unit, method for obtaining precoding matrix, grouping of method for obtaining precoding matrix, and information on monitoring method for obtaining precoding matrix.

[0369] The apparatus for processing CSI reports provided in this embodiment is for implementing the method for processing CSI reports in the above embodiment. The implementation principle and technical effects of the apparatus for processing CSI reports provided in this embodiment are similar to those in the above embodiment and will not be repeated here.

[0370] An embodiment of the present application also provides a communication node, comprising: a processor, the processor being used to implement the method provided in any embodiment of the present application when executing a computer program. The communication node may be a first communication node or a second communication node. The first communication node comprises: a processor, the processor being used to implement the method for processing channel state information reports provided in any embodiment of the present application when executing a computer program; the second communication node comprises: a processor, the processor being used to implement the method for processing channel state information reports provided in any embodiment of the present application when executing a computer program. Exemplarily, the first communication node may be a terminal device provided in any embodiment of the present application, such as a UE; the second communication node may be an access network device provided in any embodiment of the present application, such as a base station, and the present application does not impose any limitation on this.

[0371] Illustratively, the following embodiments respectively provide structural schematic diagrams in which a communication node is a terminal and a base station.

[0372] FIG7 is a schematic diagram of the structure of a terminal provided by an embodiment. The terminal can be implemented in various forms. The terminal in this application may include, but is not limited to, mobile terminal devices such as mobile phones, smart phones, laptop computers, digital broadcast receivers, personal digital assistants (PDAs), tablet computers (PADs), portable multimedia players (PMPs), navigation devices, vehicle-mounted terminal devices, vehicle-mounted display terminals, vehicle-mounted electronic rearview mirrors, etc., as well as fixed terminal devices such as digital televisions (TVs) and desktop computers.

[0373] As shown in FIG7 , the terminal 50 may include a wireless communication unit 51, an audio / video (A / V) input unit 52, a user input unit 53, a sensing unit 54, an output unit 55, a memory 56, an interface unit 57, a processor 58, and a power supply unit 59, among others. FIG7 illustrates a terminal including various components, but implementation of all illustrated components is not required. More or fewer components may be implemented instead.

[0374] In this embodiment, the wireless communication unit 51 allows radio communication between the terminal 50 and a base station or network. The A / V input unit 52 is configured to receive audio or video signals. The user input unit 53 generates key input data based on user input commands to control various operations of the terminal 50. The sensing unit 54 monitors the current state of the terminal 50, its location, the presence or absence of user touch input to the terminal 50, its orientation, the acceleration or deceleration movement and direction of the terminal 50, and generates commands or signals for controlling the operations of the terminal 50. The interface unit 57 serves as an interface through which at least one external device can connect to the terminal 50. The output unit 55 is configured to provide output signals in a visual, audio, and / or tactile manner. The memory 56 can store software programs, etc., for processing and control operations executed by the processor 58, or can temporarily store data that has been output or is to be output. The memory 56 may include at least one type of storage medium. Furthermore, the terminal 50 may cooperate with a network storage device that performs the storage function of the memory 56 via a network connection. The processor 58 generally controls the overall operation of the terminal 50. The power supply unit 59 receives external power or internal power and provides appropriate power required to operate various elements and components under the control of the processor 58 .

[0375] The processor 58 executes at least one functional application and data processing by running the program stored in the memory 56, such as implementing the method provided in the embodiment of the present application.

[0376] Figure 8 is a schematic diagram of the structure of a base station provided by one embodiment. As shown in Figure 8 , the base station includes a processor 60, a memory 61, and a communication interface 62. The base station can have one or more processors 60, with Figure 8 using one processor 60 as an example. The processor 60, memory 61, and communication interface 62 in the base station can be connected via a bus or other means, with Figure 8 using a bus as an example. The term "bus" refers to one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, or a local bus using any of a variety of bus structures.

[0377] The memory 61, as a computer-readable storage medium, can be configured to store software programs, computer-executable programs, and modules, such as program instructions / modules corresponding to the methods in the embodiments of the present application. The processor 60 executes the software programs, instructions, and modules stored in the memory 61 to execute at least one functional application and data processing of the base station, thereby implementing the above-mentioned method.

[0378] The memory 61 may include a program storage area and a data storage area. The program storage area may store an operating system and at least one application required for a function; the data storage area may store data generated based on the use of the terminal. Furthermore, the memory 61 may include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state memory device. In some instances, the memory 61 may include memory remotely located relative to the processor 60, and such remote memory may be connected to a base station via a network. Examples of such networks include, but are not limited to, the Internet, an intranet, a network, a mobile communication network, and combinations thereof.

[0379] The communication interface 62 can be configured to receive and send data.

[0380] An embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the method for processing CSI reports as provided in any embodiment of the present application is implemented.

[0381] The computer storage medium of the embodiment of the present application may adopt any combination of one or more computer-readable media. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may be, for example, but not limited to: an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or component, or any combination thereof. Computer-readable storage media include (a non-exhaustive list): an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by an instruction execution system, device or device or used in combination with it.

[0382] A computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, the data signal carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transfer a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0383] The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wire, optical cable, radio frequency (RF), etc., or any suitable combination of the foregoing.

[0384] Computer program code for performing the operations of the present disclosure may be written in one or more programming languages ​​or a combination of multiple programming languages, including object-oriented programming languages ​​(such as Java, Smalltalk, C++, Ruby, Go), and conventional procedural programming languages ​​(such as "C" or similar programming languages). The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0385] It will be appreciated by those skilled in the art that the term user terminal encompasses any suitable type of wireless user equipment, such as a mobile phone, a portable data processing device, a portable web browser or a vehicle-mounted mobile station.

[0386] In general, various embodiments of the present application may be implemented in hardware or dedicated circuits, software, logic, or any combination thereof. For example, some aspects may be implemented in hardware, while other aspects may be implemented in firmware or software that can be executed by a controller, microprocessor, or other computing device, although the present application is not limited thereto.

[0387] Embodiments of the present application may be implemented by executing computer program instructions by a data processor of a mobile device, for example, in a processor entity, or by hardware, or by a combination of software and hardware. The computer program instructions may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages.

[0388] Any block diagram of a logical flow in the drawings of this application may represent program operations, or may represent interconnected logical circuits, modules and functions, or may represent a combination of program operations and logical circuits, modules and functions. A computer program may be stored on a memory. The memory may be of any type suitable for the local technical environment and may be implemented using any suitable data storage technology, such as, but not limited to, read-only memory (ROM), random access memory (RAM), optical memory devices and systems (digital versatile discs DVD or CD), etc. Computer-readable media may include non-transitory storage media. A data processor may be of any type suitable for the local technical environment, such as, but not limited to, a general-purpose computer, a special-purpose computer, a microprocessor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a programmable logic device (FPGA), and a processor based on a multi-core processor architecture.

Claims

1. A method for processing a channel state information report, applied to a first communication node, comprising: receiving configuration information of a second communication node; Determine the concurrent number of channel state information CSI processing units according to the configuration information; Use the CSI processing units corresponding to the concurrent number to process the CSI reports.

2. The method according to claim 1, wherein: The configuration information includes at least one of the following information: Information of CSI-reference signal RS resources, grouping of CSI-RS resources, precoding matrix codebook, grouping of precoding matrix codebook, rank of precoding matrix, grouping of rank of precoding matrix, layers of precoding matrix, grouping of layers of precoding matrix, overhead of precoding matrix, grouping of overhead of precoding matrix, machine learning model, grouping of machine learning model, frequency domain unit, grouping of frequency domain unit, way of obtaining precoding matrix, grouping of way of obtaining precoding matrix, information on monitoring way of obtaining precoding matrix.

3. The method according to claim 2, wherein: In a case where the configuration information includes information about the CSI-RS resources or a grouping of the CSI-RS resources, determining the concurrent number of CSI processing units according to the configuration information includes: The concurrency quantity is determined according to the quantity of the CSI-RS resources or the quantity of groups of the CSI-RS resources.

4. The method according to claim 3, wherein: The determining the concurrent quantity according to the quantity of the CSI-RS resources or the quantity of the groups of the CSI-RS resources includes: Determine the number of the CSI-RS resources as the concurrent number; or, Determine the sum of the number of the CSI-RS resources and a preset first value as the concurrent number; or, Determine the larger of the number of the CSI-RS resources and a preset second value as the concurrent number; or, The number of groups of the CSI-RS resources is determined as the concurrent number; wherein the grouping of the CSI-RS resources includes a plurality of CSI-RS groups formed by grouping in a manner of evenly distributing the number, or a plurality of CSI-RS groups formed by grouping in a manner of evenly distributing the computing power requirements, or a plurality of CSI-RS groups formed by grouping in a manner of matching the computing power of the CSI processing unit.

5. The method according to claim 2, wherein: The determining, according to the configuration information, the concurrent number of CSI processing units includes: Determine the number of the precoding matrix or the division of the precoding matrix according to the configuration information. The number of groups; The concurrency quantity is determined according to the quantity of the precoding matrices or the quantity of groups of the precoding matrices.

6. The method according to claim 5, wherein: The determining the concurrency quantity according to the number of the precoding matrices or the number of groups of the precoding matrices includes: Determine the number of the precoding matrices as the concurrent number; or, Determine the sum of the number of the precoding matrix and a preset third value as the concurrent number; or, Determine the larger one of the number of the precoding matrices and a preset fourth value as the concurrent number; or, The number of groups of the precoding matrix is ​​determined as the concurrent number; wherein the grouping of the precoding matrix includes a plurality of precoding matrix groups formed by grouping in a manner of evenly distributing the number, or a plurality of precoding matrix groups formed by grouping in a manner of evenly distributing the computing power requirements, or a plurality of precoding matrix groups formed by grouping in a manner of matching the computing power of the CSI processing unit.

7. The method according to claim 2, wherein: In a case where the configuration information is target data, determining the concurrent number of CSI processing units according to the configuration information includes: Determine the number of target data as the concurrent number; wherein the target data is one of the precoding matrix codebook, the grouping of the precoding matrix codebook, the rank of the precoding matrix, the grouping of the rank of the precoding matrix, the layer of the precoding matrix, the grouping of the layer of the precoding matrix, the overhead of the precoding matrix, the grouping of the overhead of the precoding matrix, the machine learning model, the grouping of the machine learning model, the frequency domain unit, the grouping of the frequency domain unit, the method for obtaining the precoding matrix, and the grouping of the method for obtaining the precoding matrix.

8. The method according to claim 2, wherein: The determining, according to the configuration information, the concurrent number of CSI processing units includes: Determine, according to the configuration information, the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the purpose of the precoding matrix in the CSI report; The concurrent quantity is determined according to the number of CSI-RS resources in a CSI-RS resource set corresponding to the CSI report and the purpose of a precoding matrix in the CSI report.

9. The method according to claim 8, wherein: The determining the concurrent quantity according to the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the usage of the precoding matrix in the CSI report includes: Determine a corresponding rule according to the purpose of the precoding matrix in the CSI report; The concurrent quantity is determined according to a rule corresponding to the use of the precoding matrix in the CSI report and the quantity of CSI-RS resources in a CSI-RS resource set corresponding to the CSI report.

10. The method according to claim 2, wherein: The determining, according to the configuration information, the concurrent number of CSI processing units includes: Determine, according to the configuration information, the number of CSI-RS resources in the CSI report and the number of precoding matrices corresponding to the CSI-RS resources in the CSI report; The concurrent quantity is determined according to a comparison relationship between the quantity of CSI-RS resources in the CSI report and the quantity of precoding matrices corresponding to the CSI-RS resources in the CSI report.

11. The method according to claim 10, wherein: The determining the concurrent quantity according to a comparison relationship between the quantity of CSI-RS resources in the CSI report and the quantity of corresponding precoding matrices includes: In a case where the number of CSI-RS resources in the CSI report is less than the number of precoding matrices corresponding to the CSI-RS resources in the CSI report, determining the concurrency number according to a first preset rule; In a case where the number of CSI-RS resources in the CSI report is greater than or equal to the number of precoding matrices corresponding to the CSI-RS resources in the CSI report, the concurrent number is determined according to a second preset rule.

12. The method according to claim 11, wherein: The first preset rule is: the sum of the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrices corresponding to the CSI-RS resources in the CSI report minus a fifth value; The second preset rule is: the product of the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrices corresponding to the CSI-RS resources in the CSI report.

13. The method according to claim 2, wherein: The determining, according to the configuration information, the concurrent number of CSI processing units includes: Determine, according to the configuration information, the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrices in the CSI report; The concurrent quantity is determined according to the number of CSI-RS resources in a CSI-RS resource set corresponding to the CSI report and the number of precoding matrices in the CSI report.

14. The method according to claim 13, wherein: The determining the concurrent quantity according to the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrices in the CSI report includes: Determine the larger of the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrices in the CSI report as the concurrent number; or, Determine the larger of the number of processed CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of processed precoding matrices in the CSI report as the concurrent number; or The value of the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report after data processing is determined as the concurrent number of CSI processing units of the first type, and the value of the number of precoding matrices in the CSI report after data processing is determined as the concurrent number of CSI processing units of the second type.

15. The method according to claim 2, wherein: The determining, according to the configuration information, the concurrent number of CSI processing units includes: Determine, according to the configuration information, the number of CSI-RS resources in the CSI-RS resource set corresponding to the CSI report and the number of precoding matrix indicators in the CSI report; The concurrent quantity is determined according to the number of CSI-RS resources in a CSI-RS resource set corresponding to the CSI report and the number of precoding matrix indicators in the CSI report.

16. The method according to claim 2, wherein: The determining, according to the configuration information, the concurrent number of CSI processing units includes: Determine, according to the configuration information, a candidate range of CSI-RS resource index numbers in the CSI report; The concurrent quantity is determined according to a candidate range of CSI-RS resource index numbers in the CSI report.

17. The method according to claim 2, wherein: The determining, according to the configuration information, the concurrent number of CSI processing units includes: Determine a CSI report group according to the configuration information; wherein the CSI reports in the CSI report group have the same candidate CSI-RS resource set, or the CSI reports in the CSI report group correspond to the same CSI-RS resources, or the CSI reports in the CSI report group have the same priority; The concurrent quantity is determined according to the CSI report group.

18. The method according to claim 2, wherein: The determining, according to the configuration information, the concurrent number of CSI processing units includes: Determining, according to the configuration information, a processing time requirement for the CSI report; The concurrent quantity is determined according to the processing time requirement of the CSI report.

19. The method according to claim 2, wherein: The determining, according to the configuration information, the concurrent number of CSI processing units includes: Determine the subcarrier spacing size according to the configuration information; The concurrent quantity is determined according to the subcarrier spacing size.

20. The method according to any one of claims 1 to 19, wherein: The concurrent number of CSI processing units includes the concurrent number of at least two types of CSI processing units.

21. A method for processing a channel state information report, applied to a second communication node, comprising: Sending configuration information to the first communication node; Receive a channel state information CSI report processed by the first communication node according to the configuration information; wherein the CSI report is a report formed after the first communication node determines the concurrent number of CSI processing units according to the configuration information and uses the CSI processing units corresponding to the concurrent number to process.

22. The method according to claim 21, wherein: The configuration information includes at least one of the following information: Information of CSI-reference signal RS resources, grouping of CSI-RS resources, precoding matrix codebook, grouping of precoding matrix codebook, rank of precoding matrix, grouping of rank of precoding matrix, layers of precoding matrix, grouping of layers of precoding matrix, overhead of precoding matrix, grouping of overhead of precoding matrix, machine learning model, grouping of machine learning model, frequency domain unit, grouping of frequency domain unit, way of obtaining precoding matrix, grouping of way of obtaining precoding matrix, information on monitoring way of obtaining precoding matrix.

23. A communication node, comprising: processor; The processor is configured to implement the method for processing channel state information reports as claimed in any one of claims 1 to 20 when executing a computer program.

24. A communication node, comprising: processor; The processor is configured to implement the method of processing channel state information reports as claimed in claim 21 or 22 when executing the computer program.

25. A computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, the method for processing a channel state information report as described in any one of claims 1 to 20 is implemented, or the method for processing a channel state information report as described in claim 21 or 22 is implemented.

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