Method and apparatus used in node for wireless communication and artificial intelligence

Abstract

The present application discloses a method and apparatus used in a node for wireless communication and artificial intelligence. A node receives a first information block and a second information block, wherein the first information block and the second information block are respectively used for configuring a first process and a second process, and the first process and the second process respectively occupy a first processing resource set and a second processing resource set; and the node processes a target process. The remaining processing resource set of the node can comprise the first processing resource set or the second processing resource set, and cannot comprise both the first processing resource set and the second processing resource set; whether the target process is the first process or the second process depends on a comparison of priorities corresponding to the first process and the second process; the comparison of the priorities depends on the types of the first process and the second process; and the first process and the second process are used for inference. In the present application, limited computing power resources are preferentially used for a process with a higher priority.

Description

A method and apparatus for use in nodes for wireless communication and artificial intelligence

[0001] This application claims priority to Chinese Patent Application No. 202411926609.1, filed on December 23, 2024, entitled "A Method and Apparatus Used in a Node for Wireless Communication and Artificial Intelligence", the entire contents of which are incorporated herein by reference. Technical Field

[0002] This application relates to signal transmission methods and apparatus in wireless communication systems, and more particularly to methods and apparatus for the integration of AI and communication. Background Technology

[0003] Leveraging AI / ML (Artificial Intelligence / Machine Learning) technologies to improve 5G network performance is a crucial component of achieving deep integration of 5G and AI / ML and building intelligent dimensions for 5G-Advanced (5.5G) networks. Starting with 5G Rel-17 (Release-17), the 3GPP (3rd Generation Partnership Project) RAN (Radio Access Networks) has been researching the AI / ML functional framework and typical high-level use cases for AI / ML, including Network Energy Saving (NES), load balancing, and mobility enhancement. Rel-18 further investigated AI / ML physical layer use cases, including AI / ML-based localization, AI / ML-based beam management, and AI / ML-based CSI (Channel State Information) prediction and compression, and standardized high-level AI / ML use cases (NES, load balancing, mobility enhancement). Rel-19 will complete the standardization of AI / ML-related physical layer use cases and further explore new use cases of AI / ML in RAN L2 / L3 (Layer 2 / Layer 3), such as AI / ML-based network slicing, AI / ML-based coverage, and AI / ML-based mobility.

[0004] It is foreseeable that AI / ML will be one of the most pervasive core technologies in future 6G, involving all levels of air interface, network, protocol, and algorithm, and will also profoundly impact network functions such as sensing, communication, computing, and control. Currently, the development of AI / ML has entered the large-scale model stage. Large-scale communication models can realize autonomous networks and intelligent services, support network operation optimization, and improve network efficiency. The deep integration of communication and AI is an important direction for the future evolution of communication. AI will empower the development and upgrade from 5G and 5.5G to 6G, bringing new management models such as automated management of frequency bands and traffic, real-time analysis of user data and network load, and prediction of network status. Summary of the Invention

[0005] The current Rel-18 standard provides a clear definition of resource consumption and corresponding priority design for physical layer channel information processing. That is, when the remaining CPU (CSI Processing Unit) resources are insufficient to meet the number of CPUs required for channel information processing, the processing of the corresponding channel information will be abandoned. In the future, a large number of intelligent agents in the network will jointly execute complex AI / ML training and inference tasks. AI / ML functions need to consider supporting the application needs of AI / ML at different time scales and at different levels to serve the entire communication system in the future and improve the overall performance and efficiency of the network. AI / ML computing and inference will have more stringent requirements on hardware and resource consumption. Therefore, how to reasonably define AI / ML computing power or resources is a problem that needs to be considered.

[0006] To address the aforementioned issues, this application discloses a solution. It should be noted that while this application is initially intended for AI / ML scenarios, it can also be applied to other non-AI / ML scenarios. Furthermore, adopting a unified design scheme for different scenarios (such as other non-AI / ML scenarios, including but not limited to Vehicle to Everything (V2X), capacity enhancement systems, short-range communication systems, NTN (Non-Terrestrial Network), IoT (Internet of Things), and URLLC (Ultra-Reliable Low-Latency Communication) networks) helps reduce hardware complexity and cost. Where there is no conflict, embodiments and features in any node of this application can be applied to any other node. Where there is no conflict, embodiments and features in any embodiment of this application can be arbitrarily combined with each other.

[0007] In particular, the interpretation of terms, nouns, functions, and variables in this application (unless otherwise specified) can be found in the definitions of the TS38 and TS37 series of 3GPP (3rd Generation Partnership Project) Technical Specifications (TS). Where necessary, reference can be made to TS38.211, TS38.212, TS38.213, TS38.214, TS38.215, TS38.300, TS38.304, TS38.305, TS38.321, TS38.331, TS37.355, and TS38.423 in the 3GPP technical specifications to aid in understanding this application.

[0008] As an example, the interpretation of terms in this application is based on the definitions in the 3GPP specification protocol TS38 series.

[0009] As an example, the interpretation of terms in this application is based on the definitions in the 3GPP specification protocol TS37 series.

[0010] As an example, the interpretation of the terms used in this application is based on the definitions in 3GPP specification protocol Rel-17.

[0011] As an example, the interpretation of the terms used in this application is based on the definitions in 3GPP specification protocol Rel-18.

[0012] This application discloses a method for a first node in wireless communication and artificial intelligence, comprising:

[0013] Receive a first information block and a second information block, the first information block and the second information block respectively configure a first process and a second process; the first process and the second process respectively occupy a first processing resource set and a second processing resource set;

[0014] Process the target process, wherein the target process is one of the first process and the second process;

[0015] Wherein, the remaining processing resource set of the first node is equal to the total processing resource set of the first node minus the portion that has been occupied; the remaining processing resource set of the first node can include either the first processing resource set or the second processing resource set, and the remaining processing resource set of the first node cannot include both the first processing resource set and the second processing resource set simultaneously; whether the target process is the first process or the second process depends on a comparison of the priorities corresponding to the first process and the second process; the comparison of the priorities corresponding to the first process and the second process depends on the types of the first process and the second process; both the first process and the second process are for inference.

[0016] As an example, the problem this application aims to solve includes: the priority of inference processing resource usage.

[0017] As an example, the problem this application aims to solve includes: how the first node allocates the remaining processing resources to ensure the normal operation of the system when the remaining processing resources of the first node are limited.

[0018] As an example, the problem this application aims to solve includes: how to improve the reliability of a communication system.

[0019] As an example, the features of the above method include: In this application, when the remaining processing resources of the first node are limited, the first node determines the process to be processed based on the priority of the processes to be processed, thereby solving the above problem.

[0020] As an example, the features of the above method include: In this application, when the remaining processing resources of the first node can only process one of the first process and the second process, which process the first node processes depends on the comparison between the priority corresponding to the first process and the priority corresponding to the second process, thereby solving the above problem.

[0021] As an example, the features of the above method include: the first node is a terminal.

[0022] As an example, the features of the above method include: the remaining processing resources of the first node refer to the set of remaining processing resources of the first node on a given symbol.

[0023] As an example, the features of the above method include: the first process and the second process are configured or instructed to occupy the same start time.

[0024] As an example, the advantages of the above method include: this application supports the deep integration of AI and communication, improves the adaptability and intelligence level of the communication system, and thus enhances the performance, efficiency and user experience of the communication system.

[0025] As an example, the advantages of the above method include: providing a solution for handling resource-constrained situations and ensuring normal system operation.

[0026] As an example, the advantages of the above method include: avoiding the impact of insufficient resource allocation on the terminal's communication functions and network stability.

[0027] As an example, the advantages of the above method include: defining a mechanism for handling resource contention, balancing AI computing load and terminal energy efficiency.

[0028] According to one aspect of this application, the method is characterized in that the priority corresponding to the first process is higher than the priority corresponding to the second process, and the target process is the first process; or the priority corresponding to the first process is lower than the priority corresponding to the second process, and the target process is the second process.

[0029] As an example, the features of the above method include: when the priority corresponding to the first process is higher than the priority corresponding to the second process, the first node processes the first process; when the priority corresponding to the first process is lower than the priority corresponding to the second process, the first node processes the second process.

[0030] As an example, the features of the above method include: when computing power is insufficient, the first node abandons processing processes with lower priority.

[0031] As an example, the features of the above method include: when computing power is insufficient, the first node delays processing processes with lower priority.

[0032] As an example, the advantages of the above method include: ensuring that higher-priority processes are executed first, and avoiding insufficient resource allocation from affecting the terminal's communication functions and network stability.

[0033] As an example, the advantages of the above method include: rationally allocating limited computing resources.

[0034] According to one aspect of this application, the above method is characterized in that the type of process includes at least one of the following:

[0035] - Whether the process is used for encoding / decoding;

[0036] - The layer corresponding to the process;

[0037] - The cell corresponding to the process.

[0038] As an example, the features of the above method include: this application supports processes used for encoding and decoding, processes used for different protocol layers, and processes used for different cells occupying the same type of processing resources.

[0039] As an example, the advantages of the above method include: considering the situation where multiple types of processes occupy the same type of processing resource set, it is beneficial to the unified management of processing resources.

[0040] As an example, the advantages of the above method include: avoiding unbalanced processing resource load caused by predefined resource occupancy types.

[0041] As an example, the benefits of the above method include: unified resource management can ensure that more urgent and critical process tasks can be prioritized.

[0042] According to one aspect of this application, the method is characterized in that the priority of the process used for the physical layer in the first process and the second process is higher than the priority of the process used for layers other than the physical layer.

[0043] As an example, the features of the above method include: the physical layer process includes operations such as wireless signal generation, modulation, encoding, and power control, which is the basis for data transmission, ensuring that the physical layer process enjoys a high priority in resource contention, and the system can ensure that even under high network load and resource shortage, the transmission of physical signals will not be interrupted or blocked.

[0044] As an example, the characteristics of the above method include: the physical layer requires low-latency operations, and the higher priority can ensure the timely execution of physical layer processes.

[0045] As an example, the characteristics of the above method include: the physical layer signal quality and the stability and reliability of processing directly affect the performance of upper layer protocols, and thus the physical layer process enjoys a higher priority, which can ensure the smooth progress of network access and connection establishment.

[0046] As an example, the advantages of the above method include: standardizing the priority of the process ensures that the base station and the terminal have a consistent understanding of the priority, which is beneficial for commercial deployment.

[0047] As an example, the advantages of the above method include: limited computing resources will be prioritized for processing physical layer processes, ensuring the normal operation of the system.

[0048] As an example, the benefits of the above method include: low signal transmission latency, improved system response speed, and improved user experience.

[0049] According to one aspect of this application, the method is characterized in that the priority of the process used for encoding and decoding in the first process and the second process is higher than the priority of the process used for measurement.

[0050] As an example, the features of the above method include: compared to measurement, encoding and decoding are latency-sensitive tasks, and delaying or canceling the encoding and decoding process may cause system transmission interruption due to bit errors or inability to decode. Therefore, in this application, the priority of the process used for encoding and decoding is defined to be higher than the priority of the process used for measurement.

[0051] As an example, the features of the above method include: the encoding and decoding includes at least one or more of channel encoding and decoding, source encoding and decoding, and source-channel joint encoding and decoding.

[0052] As an example, the characteristics of the above method include: the measurement includes at least one or more of channel measurement, interference measurement, and mobility measurement.

[0053] As an example, the advantages of the above method include: prioritizing the execution of the encoding and decoding process can ensure that the terminal's processing resources are prioritized for the most critical tasks, avoiding delays or errors in the encoding and decoding process due to insufficient processing resources.

[0054] As an example, the advantages of the above method include: the system can correct errors in a timely manner when the signal is weak or the interference is strong, ensuring that the signal is not lost and the transmission quality is guaranteed.

[0055] As an example, the advantages of the above method include: improving system stability and ensuring signal robustness.

[0056] According to one aspect of this application, the method is characterized in that the priority of the process used for serving the cell in the first process and the second process is higher than the priority of the process used for cells other than serving the cell.

[0057] As an example, the features of the above method include: the serving cell is the cell in which the user actually establishes an RRC connection, and the terminal realizes the communication connection through data transmission within the serving cell. If a process in a non-serving cell is given too high a priority, it may cause a decrease in the communication quality of the serving cell. Therefore, in this application, the process in the serving cell enjoys a higher priority, which can ensure that the core communication tasks of the system are not greatly interfered with.

[0058] As an example, the features of the above method include: the cells other than the serving cell include one or more of neighboring cells, candidate cells, and additional cells.

[0059] As an example, the features of the above method include: the process for cells other than the serving cell includes one or more of the following: neighbor cell handover and reselection, neighbor cell channel measurement, and candidate cell handover.

[0060] As an example, the advantages of the above method include: ensuring the priority completion of communication tasks within the serving cell, thereby improving user experience, reducing interference, and optimizing network efficiency.

[0061] As an example, the benefits of the above method include ensuring that the communication quality and experience of users within the serving cell are not affected by interference or resource contention from non-serving cells.

[0062] As an example, the advantages of the above method include: processes of non-serving cells are often used to provide auxiliary functions or additional network coverage, but they can also cause inter-cell interference. By setting a higher priority for processes of the serving cell, the system can prioritize interference suppression tasks from within the serving cell.

[0063] According to one aspect of this application, the above method is characterized in that the first processing resource set and the second processing resource set each correspond only to computing resources, and the remaining processing resource set of the first node includes only remaining computing resources; the number of remaining computing resources of the first node is not less than the number of computing resources corresponding to the first processing resource set or the number of computing resources corresponding to the second processing resource set, and the number of remaining computing resources of the first node is less than the sum of the number of computing resources corresponding to the first processing resource set and the number of computing resources corresponding to the second processing resource set.

[0064] As an example, the features of the above method include: the number of computing resources refers to the number of computing units included in the computing resources, and the operation performed by the first node in the computing unit in this application is atomic or predefined.

[0065] As an example, the features of the above method include: both the first processing resource set and the second processing resource set include at least one computing unit; the first node occupies at least one computing unit for processing the first process, and the first node occupies at least one computing unit for processing the second process.

[0066] As an example, the characteristics of the above method include: the computing resources are used for the processing of inference-based processes.

[0067] As an example, the advantages of the above method include: atomizing and quantifying the processing power of the terminal is conducive to standardization.

[0068] As an example, the advantages of the above method include: simplicity of implementation, ease of deployment, and commercialization.

[0069] As an example, the advantages of the above method include: minimal impact on standards and good compatibility.

[0070] According to one aspect of this application, the method is characterized in that either the first processing resource set or the second processing resource set corresponds to computing resources and storage resources, and the remaining processing resource set of the first node includes remaining computing resources and remaining storage resources; the number of remaining computing resources of the first node is not less than the number of computing resources corresponding to the first processing resource set or the number of computing resources corresponding to the second processing resource set, and the number of remaining storage resources of the first node is not less than the number of storage resources corresponding to the first processing resource set or the number of storage resources corresponding to the second processing resource set; and the number of remaining computing resources of the first node is less than the sum of the number of computing resources corresponding to the first processing resource set and the number of computing resources corresponding to the second processing resource set, or the number of remaining storage resources of the first node is less than the sum of the number of storage resources corresponding to the first processing resource set and the number of storage resources corresponding to the second processing resource set.

[0071] As an example, the features of the above method include: latency and throughput are the two most important performance indicators for measuring processor computing power. In this application, when allocating processing resources for the inference process, both memory access constraints and computation constraints are considered as major performance bottlenecks. Processing resources are only allocated when both memory access and computation requirements are met.

[0072] As an example, the characteristics of the above method include: memory access constraints and computing power constraints will cause the first node to be unable to execute the first process and the second process simultaneously.

[0073] As an example, the features of the above method include: the number of computing resources refers to the number of computing units included in the computing resources, and the operation performed by the first node in the computing unit in this application is atomic or predefined.

[0074] As an example, the features of the above method include: the number of storage resources refers to the number of storage units included in the storage resources, and the operation performed by the first node in the storage unit in this application is atomic or predefined.

[0075] As an example, the advantages of the above method include: fully considering the characteristics of AI / ML models and the differences in hardware performance within the 3GPP communication framework, and promoting the deep integration of AI and communication.

[0076] As an example, the advantages of the above method include: it helps the terminal determine whether the processing capacity meets the scheduling requirements, and quantifying processing resources helps reduce implementation complexity.

[0077] As an example, the advantages of the above method include: fully considering the two major performance indicators of memory access and computation, and rationally allocating processing resources.

[0078] According to one aspect of this application, the above method is characterized in that the first node is a user equipment.

[0079] According to one aspect of this application, the above method is characterized in that the first node is a terminal.

[0080] This application discloses a method for a second node in wireless communication and artificial intelligence, comprising:

[0081] Send a first information block and a second information block, wherein the first information block and the second information block respectively configure the first process and the second process;

[0082] In this system, the receivers of the first and second information blocks are the first node; the first process and the second process occupy the first and second processing resource sets of the first node, respectively; the first node processes a target process, which is one of the first and second processes; the remaining processing resource set of the first node is equal to the total processing resource set of the first node minus the portion that has been occupied; the remaining processing resource set of the first node can include either the first or the second processing resource set, but cannot simultaneously include both the first and the second processing resource sets; whether the target process is the first or the second process depends on a comparison of the priorities corresponding to the first and second processes; the comparison of the priorities corresponding to the first and second processes depends on the types of the first and second processes; both the first and second processes are for inference.

[0083] As an example, the features of the above method include: the second node includes a base station and a core network.

[0084] As an example, the features of the above method include: the second node includes a core network.

[0085] As an example, the features of the above method include: the second node includes an entity for deploying AI / ML models.

[0086] As an example, the features of the above method include: the second node includes a node for deploying AI / ML models.

[0087] As an example, the features of the above method include: the second node includes a base station.

[0088] As an example, the features of the above method include: the second node is a base station.

[0089] As an example, the features of the above method include: the second node is an eNB.

[0090] As an example, the features of the above method include: the second node is a gNB.

[0091] As an example, the features of the above method include: the second node is a network device, which includes at least one of a core network device and an access network device.

[0092] As an example, the features of the above method include: the second node is a device that provides wireless communication function services, can communicate with terminal devices, and is usually located on the network side.

[0093] As an example, the features of the above method include: the base station in this application includes a core network.

[0094] As an example, the features of the above method include: the base station in this application includes core network equipment.

[0095] As an example, the features of the above method include: the base station in this application includes an entity for deploying AI / ML models.

[0096] As an example, the features of the above method include: the base station in this application includes nodes for deploying AI / ML models.

[0097] According to one aspect of this application, the method is characterized in that the priority corresponding to the first process is higher than the priority corresponding to the second process, and the target process is the first process; or the priority corresponding to the first process is lower than the priority corresponding to the second process, and the target process is the second process.

[0098] According to one aspect of this application, the above method is characterized in that the type of process includes at least one of the following:

[0099] - Whether the process is used for encoding / decoding;

[0100] - The layer corresponding to the process;

[0101] - The cell corresponding to the process.

[0102] According to one aspect of this application, the method is characterized in that the priority of the process used for the physical layer in the first process and the second process is higher than the priority of the process used for layers other than the physical layer.

[0103] According to one aspect of this application, the method is characterized in that the priority of the process used for encoding and decoding in the first process and the second process is higher than the priority of the process used for measurement.

[0104] According to one aspect of this application, the method is characterized in that the priority of the process for the serving cell of the first node in the first process and the second process is higher than the priority of the process for cells other than the serving cell of the first node.

[0105] According to one aspect of this application, the above method is characterized in that the first processing resource set and the second processing resource set each correspond only to computing resources, and the remaining processing resource set of the first node includes only remaining computing resources; the number of remaining computing resources of the first node is not less than the number of computing resources corresponding to the first processing resource set or the number of computing resources corresponding to the second processing resource set, and the number of remaining computing resources of the first node is less than the sum of the number of computing resources corresponding to the first processing resource set and the number of computing resources corresponding to the second processing resource set.

[0106] According to one aspect of this application, the method is characterized in that either the first processing resource set or the second processing resource set corresponds to computing resources and storage resources, and the remaining processing resource set of the first node includes remaining computing resources and remaining storage resources; the number of remaining computing resources of the first node is not less than the number of computing resources corresponding to the first processing resource set or the number of computing resources corresponding to the second processing resource set, and the number of remaining storage resources of the first node is not less than the number of storage resources corresponding to the first processing resource set or the number of storage resources corresponding to the second processing resource set; and the number of remaining computing resources of the first node is less than the sum of the number of computing resources corresponding to the first processing resource set and the number of computing resources corresponding to the second processing resource set, or the number of remaining storage resources of the first node is less than the sum of the number of storage resources corresponding to the first processing resource set and the number of storage resources corresponding to the second processing resource set.

[0107] According to one aspect of this application, the method described above is characterized in that the second node is a base station.

[0108] This application discloses a device for a first node in wireless communication and artificial intelligence, comprising:

[0109] A first receiver receives a first information block and a second information block, wherein the first information block and the second information block are respectively configured with a first process and a second process; the first process and the second process respectively occupy a first processing resource set and a second processing resource set.

[0110] A first processor processes a target process, wherein the target process is one of the first process and the second process;

[0111] Wherein, the remaining processing resource set of the first node is equal to the total processing resource set of the first node minus the portion that has been occupied; the remaining processing resource set of the first node can include either the first processing resource set or the second processing resource set, and the remaining processing resource set of the first node cannot include both the first processing resource set and the second processing resource set simultaneously; whether the target process is the first process or the second process depends on a comparison of the priorities corresponding to the first process and the second process; the comparison of the priorities corresponding to the first process and the second process depends on the types of the first process and the second process; both the first process and the second process are for inference.

[0112] This application discloses a device for a second node in wireless communication and artificial intelligence, comprising:

[0113] A first transmitter sends a first information block and a second information block, wherein the first information block and the second information block are respectively configured with a first process and a second process;

[0114] In this system, the receivers of the first and second information blocks are the first node; the first process and the second process occupy the first and second processing resource sets of the first node, respectively; the first node processes a target process, which is one of the first and second processes; the remaining processing resource set of the first node is equal to the total processing resource set of the first node minus the portion that has been occupied; the remaining processing resource set of the first node can include either the first or the second processing resource set, but cannot simultaneously include both the first and the second processing resource sets; whether the target process is the first or the second process depends on a comparison of the priorities corresponding to the first and second processes; the comparison of the priorities corresponding to the first and second processes depends on the types of the first and second processes; both the first and second processes are for inference.

[0115] As an example, compared with conventional solutions, this application has the following advantages, but is not limited to:

[0116] This application supports the deep integration of AI and communication to improve the adaptability and intelligence of communication systems, thereby enhancing the performance, efficiency, and user experience of communication systems.

[0117] Define a mechanism to handle resource contention and balance AI computing load with terminal energy efficiency;

[0118] The standardization process, with its corresponding priorities, ensures that base stations and terminals have a consistent understanding of these priorities, which is beneficial for commercial deployment.

[0119] Limited computing resources will be prioritized for higher-priority processes to ensure the normal operation of the system. Attached Figure Description

[0120] Other features, objects, and advantages of this application will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0121] Figure 1 illustrates a flowchart of the first node transmission according to an embodiment of this application;

[0122] Figure 2 shows a schematic diagram of a network architecture according to an embodiment of this application;

[0123] Figure 3 illustrates a schematic diagram of an embodiment of a wireless protocol architecture for the user plane and control plane according to an embodiment of this application;

[0124] Figure 4 shows a schematic diagram of a first communication device and a second communication device according to an embodiment of this application;

[0125] Figure 5 illustrates a flowchart of the transmission between a first node and a second node according to an embodiment of this application;

[0126] Figure 6 shows a first schematic diagram of the processing resource set of a first node according to an embodiment of this application;

[0127] Figure 7 shows a second schematic diagram of the processing resource set of a first node according to an embodiment of this application;

[0128] Figure 8 illustrates a schematic diagram showing the relationship between the priorities of the target process, the first process, and the second process according to an embodiment of this application;

[0129] Figure 9 shows a first schematic diagram comparing the priorities of processes according to an embodiment of this application;

[0130] Figure 10 shows a second schematic diagram comparing the priorities of processes according to an embodiment of this application;

[0131] Figure 11 shows a third schematic diagram comparing the priorities of processes according to an embodiment of this application;

[0132] Figure 12 shows a schematic diagram of RAN domain AI / ML function deployment according to an embodiment of this application;

[0133] Figure 13 shows a schematic diagram of the AI / ML function deployment of a UE according to an embodiment of this application;

[0134] Figure 14 shows a schematic diagram of a processing system based on artificial intelligence or machine learning according to an embodiment of this application;

[0135] Figure 15 illustrates a schematic diagram of artificial intelligence or machine learning according to an embodiment of this application;

[0136] Figure 16 shows a structural block diagram of a processing apparatus for a first node according to an embodiment of the present application;

[0137] Figure 17 shows a structural block diagram of a processing apparatus for a second node according to an embodiment of the present application. Detailed Implementation

[0138] The technical solutions of this application will be further described in detail below with reference to the accompanying drawings. It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of this application can be arbitrarily combined with each other. Considering performance, flexibility, complexity, overhead, and compatibility, those skilled in the art are motivated to flexibly combine the embodiments in different drawings without conflict, including but not limited to the embodiments in Figure 1 and the embodiments in Figures 5-17, the embodiments in Figure 5 and the embodiments in Figures 6-17, etc.

[0139] Example 1

[0140] (1) Example 1 illustrates a flowchart of the first node transmission according to an embodiment of this application, as shown in Figure 1. In Figure 1, each block represents a step. In particular, the order of the steps in the blocks does not represent a specific temporal relationship between the steps.

[0141] In step 101, the first node receives a first information block and a second information block, which respectively configure a first process and a second process; the first process and the second process respectively occupy a first processing resource set and a second processing resource set; in step 102, the target process is processed, which is one of the first process and the second process.

[0142] In Embodiment 1, the remaining processing resource set of the first node is equal to the total processing resource set of the first node minus the portion that has been occupied; the remaining processing resource set of the first node can include either the first processing resource set or the second processing resource set, and the remaining processing resource set of the first node cannot simultaneously include both the first processing resource set and the second processing resource set; whether the target process is the first process or the second process depends on a comparison of the priority corresponding to the first process and the priority corresponding to the second process; the comparison of the priority corresponding to the first process and the priority corresponding to the second process depends on the types of the first process and the second process; both the first process and the second process are for inference.

[0143] As one example, the first node is a user equipment (UE).

[0144] As one example, the first node is a terminal.

[0145] As an example, the first node is the first node in this application.

[0146] As one embodiment, the first node receives the first information block.

[0147] As one embodiment, the first information block is carried by higher layer signaling.

[0148] As an example, the first information block is carried by an RRC (Radio Resource Control) message.

[0149] As an example, the first information block is carried by RRC signaling.

[0150] As an example, the first information block includes one or more RRC IEs (Information Elements).

[0151] As one embodiment, the first information block includes some or all of the fields in one or more RRC IEs.

[0152] As one embodiment, the first information block includes part or all of the fields of each of the plurality of RRC IEs.

[0153] As one example, the first information block indicates higher-level parameters.

[0154] As one example, the first information block includes some or all of the domains in the ServingCellConfigCommon IE.

[0155] As one embodiment, the first information block includes some or all of the domains in the ServingCellConfig IE.

[0156] As one embodiment, the first information block includes some or all of the domains in the PUSCH-Config IE.

[0157] As one embodiment, the first information block includes some or all of the domains in the PDSCH-Config IE.

[0158] As one embodiment, the first information block includes some or all of the domains in the CSI-MeasConfig IE.

[0159] As one embodiment, the first information block includes some or all of the fields in a CSI-ReportConfig IE.

[0160] As one example, the first information block includes some or all of the fields in a LocationInfo IE.

[0161] As one example, the first information block includes some or all of the fields in a LocationMeasurementInfo IE.

[0162] As one example, the first information block includes some or all of the domains in a MeasConfig IE.

[0163] As one example, the first information block includes some or all of the domains in a MeasConfig IE.

[0164] As one embodiment, the first information block includes some or all of the fields in a MeasObjectCLI IE.

[0165] As one embodiment, the first information block includes some or all of the fields in a MeasObjectEUTRA IE.

[0166] As one embodiment, the first information block includes some or all of the fields in a MeasObjectNR IE.

[0167] As one example, the first information block includes some or all of the fields in a MeasObjectToAddModList IE.

[0168] As an example, the first information block includes some or all of the fields in a MobilityStateParameters IE.

[0169] As one example, the first information block includes some or all of the domains in a MeasConfig IE.

[0170] As one example, the first information block includes some or all of the fields in a SelectedPSCellForCHO-WithSCG IE.

[0171] As one embodiment, the first information block includes some or all of the fields in an LTM-Candidate IE.

[0172] As one embodiment, the first information block includes some or all of the domains in an LTM-Config IE.

[0173] As one embodiment, the first information block includes some or all of the fields in an LTM-CSI-ReportConfig IE.

[0174] As one embodiment, the first information block includes some or all of the domains in an LTM-CSI-ResourceConfig IE.

[0175] As one example, the first information block includes some or all of the fields in a CondReconfigToAddModList IE.

[0176] As one example, the first information block includes some or all of the fields in a ConditionalReconfiguration IE.

[0177] As an example, the name of the RRC signaling carrying the first information block includes: CSI.

[0178] As an example, the name of the RRC signaling carrying the first information block includes: Report.

[0179] As an example, the name of the RRC signaling carrying the first information block includes: Config.

[0180] As an example, the name of the RRC signaling carrying the first information block includes: Meas.

[0181] As an example, the name of the RRC signaling carrying the first information block includes: CSI-Report.

[0182] As an example, the name of the RRC signaling carrying the first information block includes: Location.

[0183] As an example, the name of the RRC signaling carrying the first information block includes: Mobility.

[0184] As an example, the name of the RRC signaling carrying the first information block includes: CHO.

[0185] As an example, the name of the RRC signaling carrying the first information block includes: LTM.

[0186] As an example, the name of the RRC signaling carrying the first information block includes: Cond.

[0187] As an example, the name of the RRC signaling carrying the first information block includes: Conditional.

[0188] As an example, the name of the RRC signaling carrying the first information block includes: Modulation.

[0189] As an example, the name of the RRC signaling carrying the first information block includes: Coding.

[0190] As an example, the name of the RRC signaling carrying the first information block includes: Demodulation.

[0191] As an example, the name of the RRC signaling carrying the first information block includes: Decoding.

[0192] As an example, the name of the RRC signaling carrying the first information block includes: AI.

[0193] As one embodiment, the first node receives the second information block.

[0194] As one embodiment, the second information block is carried by higher-level signaling.

[0195] As one example, the second information block is carried by an RRC message.

[0196] As one embodiment, the second information block is carried by RRC signaling.

[0197] As one embodiment, the second information block includes one or more RRC IEs.

[0198] As one embodiment, the second information block includes some or all of the fields in one or more RRC IEs.

[0199] As one example, the second information block indicates higher-level parameters.

[0200] As one embodiment, the second information block includes part or all of the fields of each of the plurality of RRC IEs.

[0201] As one embodiment, the second information block includes some or all of the domains in the ServingCellConfigCommon IE.

[0202] As one embodiment, the second information block includes some or all of the domains in the ServingCellConfig IE.

[0203] As one embodiment, the second information block includes some or all of the fields in the PUSCH-Config IE.

[0204] As one embodiment, the second information block includes some or all of the fields in the PDSCH-Config IE.

[0205] As one embodiment, the second information block includes some or all of the domains in the CSI-MeasConfig IE.

[0206] As one embodiment, the second information block includes some or all of the fields in a CSI-ReportConfig IE.

[0207] As one embodiment, the second information block includes some or all of the fields in a LocationInfo IE.

[0208] As one embodiment, the second information block includes some or all of the fields in a LocationMeasurementInfo IE.

[0209] As one embodiment, the second information block includes some or all of the domains in a MeasConfig IE.

[0210] As one embodiment, the second information block includes some or all of the domains in a MeasConfig IE.

[0211] As one embodiment, the second information block includes some or all of the fields in a MeasObjectCLI IE.

[0212] As one embodiment, the second information block includes some or all of the fields in a MeasObjectEUTRA IE.

[0213] As one embodiment, the second information block includes some or all of the fields in a MeasObjectNR IE.

[0214] As one example, the second information block includes some or all of the fields in a MeasObjectToAddModList IE.

[0215] As one example, the second information block includes some or all of the fields in a MobilityStateParameters IE.

[0216] As one embodiment, the second information block includes some or all of the domains in a MeasConfig IE.

[0217] As one embodiment, the second information block includes some or all of the fields in a SelectedPSCellForCHO-WithSCG IE.

[0218] As one embodiment, the second information block includes some or all of the fields in an LTM-Candidate IE.

[0219] As one embodiment, the second information block includes some or all of the domains in an LTM-Config IE.

[0220] As one embodiment, the second information block includes some or all of the fields in an LTM-CSI-ReportConfig IE.

[0221] As one embodiment, the second information block includes some or all of the domains in an LTM-CSI-ResourceConfig IE.

[0222] As one example, the second information block includes some or all of the fields in a CondReconfigToAddModList IE.

[0223] As one embodiment, the second information block includes some or all of the fields in a ConditionalReconfiguration IE.

[0224] As an example, the name of the RRC signaling carrying the second information block includes: CSI.

[0225] As an example, the name of the RRC signaling carrying the second information block includes: Report.

[0226] As an example, the name of the RRC signaling carrying the second information block includes: Config.

[0227] As an example, the name of the RRC signaling carrying the second information block includes: Meas.

[0228] As an example, the name of the RRC signaling carrying the second information block includes: CSI-Report.

[0229] As an example, the name of the RRC signaling carrying the second information block includes: Location.

[0230] As an example, the name of the RRC signaling carrying the second information block includes: Mobility.

[0231] As an example, the name of the RRC signaling carrying the second information block includes: CHO.

[0232] As an example, the name of the RRC signaling carrying the second information block includes: LTM.

[0233] As an example, the name of the RRC signaling carrying the second information block includes: Cond.

[0234] As an example, the name of the RRC signaling carrying the second information block includes: Conditional.

[0235] As an example, the name of the RRC signaling carrying the second information block includes: Modulation.

[0236] As an example, the name of the RRC signaling carrying the second information block includes: Coding.

[0237] As an example, the name of the RRC signaling carrying the second information block includes: Demodulation.

[0238] As an example, the name of the RRC signaling carrying the second information block includes: Decoding.

[0239] As an example, the name of the RRC signaling carrying the second information block includes: AI.

[0240] As one embodiment, the first information block and the second information block include different RRC IEs.

[0241] As one example, the first information block and the second information block belong to different domains of the same RRC IE.

[0242] As one embodiment, the first information block and the second information block include different fields of the same RRC IE.

[0243] As an example, the first information block configures the first process.

[0244] As an example, the first information block enables the first process.

[0245] As an example, the first information block triggers the first process.

[0246] As an example, the first information block activates the first process.

[0247] As one embodiment, the first information block carries higher-level parameters of the first process.

[0248] As an example, the first information block indicates the associated ID of the first process.

[0249] As an example, the associated ID described in this application is used to indicate the generalization ability of the model.

[0250] As an example, the associated ID described in this application is used to ensure the consistency of network-side (NW-side) additional conditions during model training and model inference.

[0251] As an example, multiple beams, multiple beam sets, or multiple beam lists that are associated with the same association ID described in this application have similar properties.

[0252] As an example, the ID mentioned in this application refers to IDentify, proof.

[0253] As an example, the ID mentioned in this application refers to: IDentification, identity verification.

[0254] As an example, the ID mentioned in this application refers to: IDentity, identity, or identifier.

[0255] As an example, the ID mentioned in this application refers to: Identifier, identifier.

[0256] As an example, the ID mentioned in this application refers to: InDex, index.

[0257] As an example, the ID mentioned in this application refers to: InDicator, indicator.

[0258] As an example, the first information block indicates the set of RS (Reference Signal) resources associated with the first process.

[0259] As an example, the first information block indicates the triggering conditions of the first process.

[0260] As one embodiment, the first information block indicates the type corresponding to the first process.

[0261] As one embodiment, the first information block indicates the reporting period corresponding to the first process.

[0262] As an example, the first process corresponds to an AI / ML (Artificial Intelligence / Machine Learning) model.

[0263] As an example, the first process corresponds to an AI / ML model ID (model-Id).

[0264] As an example, the first process corresponds to the model ID (model-Id) of an activated AI model.

[0265] As an example, the first process corresponds to a Functionality.

[0266] As an example, the first process corresponds to a Functionality ID.

[0267] As an example, the Functionality described in this application refers to a feature or feature group (FG) that supports AI / ML enabled by configuration, wherein the configuration is supported according to conditions indicated by UE capabilities.

[0268] As an example, the first process corresponds to an AI Entity.

[0269] As an example, the second node in this application forwards the AI / ML model-related data it collects or the data reported by the first node to the AI ​​entity in this application. The AI ​​entity then performs AI / ML-related operations such as constructing the training dataset and training the model. The output of the trained AI / ML model, model evaluation, test results, and other AI / ML-related operations is forwarded to each terminal through the second node in this application.

[0270] As an example, the first node forwards the AI / ML model-related data it collects or the data issued by the second node in this application to the AI ​​entity in this application. The AI ​​entity then performs AI / ML-related operations such as constructing the training dataset and training the model. The first node forwards the output of the AI / ML-related operations, such as the trained AI / ML model, model evaluation, and test results, to the second node in this application.

[0271] As an example, to support AI / ML functions in a wireless network, AI / ML network elements or modules can be introduced into the network. If an AI / ML network element is introduced, the AI ​​entity described in this application corresponds to an independent network element; if an AI / ML module is introduced, the second node in this application can be located inside a network element, such as inside a terminal device or network device.

[0272] As an example, the AI ​​entity described in this application is located inside a base station.

[0273] As an example, the AI ​​entity described in this application is a module or function of a base station.

[0274] As an example, the AI ​​entity described in this application is located inside the terminal.

[0275] As an example, the AI ​​entity described in this application is a module or function of a terminal.

[0276] As an example, one possible implementation of the AI ​​entity described in this application is that the AI ​​entity is deployed in a server or cloud device of an Over The Top (OTT) system. Optionally, the cloud device is located on one or more of the user equipment side, network equipment side, or core network side.

[0277] As one embodiment, the second information block configures the second process.

[0278] As one embodiment, the second information block enables the second process.

[0279] As one example, the second information block triggers the second process.

[0280] As one example, the second information block activates the second process.

[0281] As one embodiment, the second information block carries higher-level parameters of the second process.

[0282] As one example, the second information block indicates the associated ID of the second process.

[0283] As one embodiment, the second information block indicates the set of RS resources associated with the second process.

[0284] As one example, the second information block indicates the triggering conditions of the second process.

[0285] As one example, the second information block indicates the type corresponding to the second process.

[0286] As one embodiment, the second information block indicates the reporting period corresponding to the second process.

[0287] As an example, the second process corresponds to an AI / ML model.

[0288] As an example, the second process corresponds to the model ID of an activated AI model.

[0289] As an example, the second process corresponds to a Functionality.

[0290] As an example, the second process corresponds to a Functionality ID.

[0291] As an example, the second process corresponds to an Entity.

[0292] As an example, the first process and the second process correspond to different AI / ML models.

[0293] As an example, the first process and the second process correspond to different AI / ML model IDs.

[0294] As an example, the first process and the second process correspond to different functions.

[0295] As an example, the first process and the second process correspond to the same Entity.

[0296] As an example, the first process and the second process correspond to different Entities.

[0297] As an example, the first process or the second process is used for CSI (Channel State Information) generation.

[0298] As one embodiment, the first process or the second process is used for encoding or decoding.

[0299] As one embodiment, the first process or the second process is used for modulation or demodulation.

[0300] As one example, the first process or the second process is used for mobility management.

[0301] As one embodiment, the first process or the second process is used for positioning.

[0302] As one embodiment, the first process or the second process is used for cell handover (HO).

[0303] As one embodiment, the first process or the second process is used for cell selection.

[0304] As one example, the first process occupies the first set of processing resources.

[0305] As one embodiment, the first set of processing resources includes at least one processing resource.

[0306] As one embodiment, the first set of processing resources includes at least one computing resource.

[0307] As one embodiment, the first set of processing resources includes at least one computing resource and at least one storage resource.

[0308] As an example, the first set of processing resources includes K1 computing resources, and the processing of the first process requires the K1 computing resources, where K1 is a positive integer.

[0309] As an example, the processing of the first process requires K1 computing resources, and the first processing resource set includes the K1 computing resources, where K1 is a positive integer.

[0310] As an example, the first processing resource set includes K2 computing resources and K3 storage resources. The processing of the first process requires the K2 computing resources and the K3 storage resources, where K2 is a positive integer and K3 is a positive integer.

[0311] As an example, the processing of the first process requires K2 computing resources and K3 storage resources, and the first processing resource set includes the K2 computing resources and the K3 storage resources; K2 is a positive integer and K3 is a positive integer.

[0312] As one embodiment, the second process occupies the second set of processing resources.

[0313] As one embodiment, the second set of processing resources includes at least one processing resource.

[0314] As one embodiment, the second set of processing resources includes at least one computing resource.

[0315] As one embodiment, the second set of processing resources includes at least one computing resource and at least one storage resource.

[0316] As one embodiment, the second processing resource set includes L1 computing resources, and the processing of the second process requires the L1 computing resources, where L1 is a positive integer.

[0317] As an example, the processing of the second process requires L1 computing resources, and the second processing resource set includes the L1 computing resources, where L1 is a positive integer.

[0318] As an example, the second processing resource set includes L2 computing resources and L3 storage resources. The processing of the second process requires the L2 computing resources and the L3 storage resources, where L2 is a positive integer and L3 is a positive integer.

[0319] As an example, the processing of the second process requires L2 computing resources and L3 storage resources. The second processing resource set includes the L2 computing resources and the L3 storage resources; L2 is a positive integer and L3 is a positive integer.

[0320] As an example, the processing of the first process and the processing of the second process overlap in the time domain.

[0321] As an example, the processing of the first process and the processing of the second process occupy at least the same time-domain start symbol.

[0322] As an example, the processing of the first process and the processing of the second process occupy at least one or more symbols in the time domain.

[0323] As an example, the set of processing resources described in this application is used for at least one of processing, computation, or inference.

[0324] As an example, the processing resource set described in this application is used for storage.

[0325] As an example, the processing resource set described in this application is used for reading and writing.

[0326] As an example, the set of processing resources described in this application is used for data interaction.

[0327] As an example, the set of processing resources described in this application includes a Calculation Unit.

[0328] As an example, the set of processing resources described in this application includes a CPU.

[0329] As an example, the CPU mentioned in this application refers to: Central Processing Unit.

[0330] As an example, the CPU mentioned in this application refers to: CSI Processing Unit, CSI processor.

[0331] As an example, the set of processing resources described in this application includes an APU.

[0332] As an example, the APU mentioned in this application refers to: Accelerated Processing Unit.

[0333] As an example, the APU mentioned in this application refers to: AI / ML Processing Unit, AI / ML processor.

[0334] As an example, the set of processing resources described in this application includes CPUs and APUs.

[0335] As an example, the set of processing resources described in this application includes GPUs (Graphics Processing Units).

[0336] As an example, the set of processing resources described in this application includes CPU and GPU.

[0337] As an example, the set of processing resources described in this application includes an NPU (Neural-network Processing Unit).

[0338] As an example, the set of processing resources described in this application includes AI-PU (AI Processing Unit).

[0339] As an example, the processing resource set described in this application includes a CPU Set.

[0340] As an example, the processing resource set in this application includes an APU Set.

[0341] As an example, the processing resource set described in this application includes CPUs and APU sets.

[0342] As an example, the processing resource set described in this application includes a GPU Set.

[0343] As an example, the computing resource set described in this application includes a CPU and a GPU set.

[0344] As an example, the processing resource set described in this application includes an AI-PU Set.

[0345] As an example, the first node processes the target process.

[0346] As one embodiment, the first node processing the target process includes: the first node performing the computations required by the target process.

[0347] As one embodiment, the first node processing the target process includes: the first node performing measurements required by the target process.

[0348] As one embodiment, the first node processing the target process includes: the first node performing the read and write operations required by the target process.

[0349] As one embodiment, the first node processing the target process includes: the first node performing the data interaction required by the target process.

[0350] As one embodiment, the first node processing the target process includes: the first node performing the inference required by the target process.

[0351] As an example, the target process is one of the first process and the second process.

[0352] As an example, the target process is the first process, the first node processes the first process, and the first node abandons processing the second process; the advantage of the above scheme is its simplicity.

[0353] As an example, the target process is the first process, the first node processes the first process, and the first node processes the second process after a delay; the advantage of the above method is that it ensures system stability.

[0354] As an example, the target process is the second process, the first node processes the second process, and the first node abandons processing the first process; the advantage of the above scheme is its simplicity.

[0355] As an example, the target process is the second process, the first node processes the second process, and the first node processes the first process with a delay; the advantage of the above method is that it ensures system stability.

[0356] As an example, the remaining processing resource set of the first node is equal to the total processing resource set of the first node minus the portion that has been occupied.

[0357] As one embodiment, the set of remaining processing resources of the first node includes: the remaining computing resources of the first node.

[0358] As one embodiment, the set of remaining processing resources of the first node includes: the remaining storage resources of the first node.

[0359] As an example, the set of remaining processing resources of the first node includes: the remaining computing resources and remaining storage resources of the first node.

[0360] As an example, the set of remaining processing resources of the first node refers to the remaining power of the first node.

[0361] As an example, the set of remaining processing resources of the first node refers to the remaining AI models of the first node.

[0362] As an example, the set of remaining processing resources of the first node refers to the set of remaining processing resources when the first node receives the first information block and the second information block.

[0363] As an example, the set of remaining processing resources of the first node refers to the set of remaining processing resources of the first node before processing the first process and the second process.

[0364] As an example, the set of remaining processing resources of the first node refers to the set of processing resources that the first node can use to process the target process before processing the target process.

[0365] As an example, the set of remaining processing resources of the first node refers to the set of remaining processing resources of the first node before starting the first process and the second process.

[0366] As an example, the set of remaining processing resources of the first node refers to the set of processing resources that the first node can use to start the target process before starting the target process.

[0367] As an example, the set of remaining processing resources of the first node refers to the processing resources in the set of processing resources that the first node can use for AI that are not used to perform AI behavior.

[0368] As an example, the set of remaining processing resources of the first node refers to the processing resources in the set of processing resources that the first node can use for ML that are not used to perform ML behavior.

[0369] As an example, the set of remaining processing resources of the first node refers to the set of unoccupied processing resources of the first node.

[0370] As an example, "unoccupied" means: free.

[0371] As an example, "unoccupied" means: not used for storage.

[0372] As an example, "unoccupied" means "unallocated".

[0373] As an example, "unoccupied" means: available but not used.

[0374] As an example, the total set of processing resources included in the first node refers to the set of processing resources that the first node can be used for AI.

[0375] As an example, the total set of processing resources included in the first node refers to the set of processing resources that the first node can be used for ML.

[0376] As an example, the total set of processing resources included in the first node refers to the set of processing resources that the first node can use for inference.

[0377] As an example, the total set of processing resources included in the first node refers to the set of processing resources that the first node can simultaneously use for the processing of the first process and the second process.

[0378] As an example, the total set of processing resources included in the first node refers to the processing resources indicated by the first node that can be used for inference.

[0379] As one embodiment, the total set of processing resources included in the first node depends on the capabilities of the first node.

[0380] As one embodiment, the total set of processing resources included in the first node depends on the feature combination of the first node.

[0381] As an example, the total set of processing resources included in the first node depends on the UECapabilityInformation of the first node.

[0382] As an example, the total set of processing resources included in the first node depends on the UEInformationResponse of the first node.

[0383] As an example, the total set of processing resources included in the first node depends on the first node's UAI (UE Assistance Information).

[0384] As an example, the total set of processing resources included in the first node depends on the UEAssistanceInformation of the first node.

[0385] As an example, the already occupied portion includes: the AI ​​model being used for inference.

[0386] As one example, the already occupied portion includes: a set of processing resources that cannot be used for the target process.

[0387] As one embodiment, the already occupied portion includes: a set of processing resources that cannot be used for the first process.

[0388] As one embodiment, the already occupied portion includes: a set of processing resources that cannot be used for the second process.

[0389] As one embodiment, the already occupied portion includes: the set of processing resources occupied by the process that has been activated by the first node.

[0390] As one embodiment, the already occupied portion includes: the set of processing resources occupied by the process being processed by the first node.

[0391] As an example, the remaining processing resource set of the first node may include either the first processing resource set or the second processing resource set, but the remaining processing resource set of the first node may not include both the first processing resource set and the second processing resource set at the same time.

[0392] As an example, whether the target process is the first process or the second process depends on a comparison of the priorities corresponding to the first process and the second process.

[0393] As an example, whether the target process is the first process or the second process depends on which of the first process and the second process has a higher priority.

[0394] As an example, whether the target process is the first process or the second process depends on which of the first process and the second process has a lower priority.

[0395] As an example, the comparison of the priority corresponding to the first process and the priority corresponding to the second process depends on the type of the first process and the type of the second process.

[0396] As an example, the comparison between the priority corresponding to the first process and the priority corresponding to the second process depends on the comparison between the priority corresponding to the type of the first process and the priority corresponding to the type of the second process.

[0397] As an example, the type of process in this application includes at least one of whether the process is used for encoding / decoding, the layer to which the process corresponds, and the cell to which the process corresponds.

[0398] As an example, the type of process in this application includes whether the process is used for encoding and decoding.

[0399] As a sub-example of this embodiment, the encoding and decoding includes channel coding and channel decoding.

[0400] As a sub-example of this embodiment, the encoding and decoding includes source-channel joint coding and source-channel joint decoding.

[0401] As a sub-example of this embodiment, the physical layer processing of the transmission channel includes the encoding and decoding.

[0402] As a sub-example of this embodiment, the uplink physical layer processing of the transmission channel includes the encoding.

[0403] As a sub-example of this embodiment, the downlink physical layer processing of the transmission channel includes the decoding.

[0404] As a sub-implementation of this embodiment, the priority of the process used for encoding and decoding is higher than the priority of the process not used for encoding and decoding.

[0405] As an example, the type of process in this application includes: the layer corresponding to the process.

[0406] As a sub-implementation of this embodiment, the layers corresponding to the process include the physical layer and higher layers.

[0407] As a sub-implementation of this embodiment, the layers corresponding to the process include the MAC (Medium Access Control) layer and the RRC layer.

[0408] As a sub-implementation of this embodiment, the priority corresponding to the lower-level process is higher than the priority corresponding to the higher-level process.

[0409] As an example, the type of process in this application includes: the cell corresponding to the process.

[0410] As a sub-implementation of this embodiment, the cell corresponding to the process includes a primary cell (PCell) or a secondary cell (SCell).

[0411] As a sub-implementation of this embodiment, the cell corresponding to the process includes a cell in the MCG (Master Cell Group) or a cell in the SCG (Secondary Cell Group).

[0412] As a sub-example of this embodiment, the cell corresponding to the process includes a serving cell or a non-serving cell.

[0413] As a sub-implementation of this embodiment, the cell corresponding to the process includes SpCell (Special Cell) or SCell.

[0414] As a sub-example of this embodiment, the priority of the process used for the current serving cell is higher than the priority of the process used for cells other than the current serving cell.

[0415] As a sub-implementation of this embodiment, the priority corresponding to the process used for a larger number of serving cells is higher than the priority corresponding to the process used for a smaller number of serving cells.

[0416] As a sub-implementation of this embodiment, the process for a larger number of serving cells has a higher priority.

[0417] As a sub-implementation of this embodiment, the process used for a smaller number of serving cells has a lower priority.

[0418] As an example, the type of process in this application includes: the functional ID corresponding to the process.

[0419] As a sub-example of this embodiment, the smaller the functionality ID corresponding to the process, the higher the priority of the process.

[0420] As a sub-implementation of this embodiment, the larger the functionality ID corresponding to the process, the higher the priority of the process.

[0421] As an example, both the first process and the second process are for reasoning.

[0422] As an example, the reasoning mentioned in this application refers to infer.

[0423] As an example, the reasoning mentioned in this application refers to inference.

[0424] As an example, the reasoning mentioned in this application refers to prediction.

[0425] As an example, the reasoning mentioned in this application refers to: prediction.

[0426] As an example, the inference described in this application includes AI / ML inference.

[0427] As an example, the statement that both the first process and the second process are for inference means that both the first process and the second process are for AI / ML.

[0428] As an example, the meaning of "both the first process and the second process are for reasoning" includes: both the first process and the second process are for prediction.

[0429] As an example, the meaning of "both the first process and the second process are for inference" includes: the first node processes the AI / ML model that needs to be activated by either the first process or the second process.

[0430] As an example, the meaning of "both the first process and the second process are for inference" includes: the first node processes either the first process or the second process, both of which occupy processing resources for inference.

[0431] As an example, the meaning of "both the first process and the second process are for reasoning" includes that the results generated by the first process and the results generated by the second process are both based on reasoning.

[0432] As an example, the meaning of "both the first process and the second process are for reasoning" includes that the results generated by the first process and the results generated by the second process are both based on prediction.

[0433] As an example, the meaning of "both the first process and the second process are for reasoning" includes that the results generated by the first process and the results generated by the second process are both based on AI / ML.

[0434] Example 2

[0435] Example 2 illustrates a schematic diagram of a network architecture according to an embodiment of this application, as shown in Figure 2.

[0436] Figure 2 illustrates network architecture 200. Network architecture 200 is the network architecture for LTE (Long-Term Evolution), LTE-A (Long-Term Evolution Advanced), 5G systems, 5G-Advanced, and future 6G systems. The network architectures for LTE, LTE-A, 5G systems, 5G-Advanced, and future 6G systems are referred to as EPS (Evolved Packet System). The 5G NR or LTE network architecture may be referred to as 5GS (5G System) / EPS or some other suitable terminology; the 6G network architecture may be referred to as 6GS (6G System) / EPS or some other suitable terminology.

[0437] The network architecture 200 may include one or more UEs 201, a RAN (Radio Access Network) 202, a core network 210, an HSS (Home Subscriber Server) / UDM (Unified Data Management) 220, and an Internet service 230. The network architecture 200 may interconnect with other access networks, but these entities / interfaces are not shown for simplicity.

[0438] As shown in Figure 2, the network architecture 200 provides packet switching services; however, those skilled in the art will readily understand that the various concepts presented throughout this application can be extended to networks providing circuit-switched services or other cellular networks. The RAN 202 includes Node B 203 and other nodes 204. Node B 203 provides user and control plane protocol termination toward the UE 201. Node B 203 may be connected to other nodes 204 via an Xn interface (e.g., backhaul). Node B 203 may also be referred to as eNB (evolved Node B), gNB, base station, base transceiver station, radio base station, radio transceiver, transceiver function, Basic Service Set (BSS), Extended Service Set (ESS), TRP (Transmitter Receiver Point), or some other suitable term. Node B 203 provides UE 201 with an access point to the core network 210; the core network 210 is a 5GC (5G Core network) / EPC (Evolved Packet Core), or the core network 210 is a 6GC (6G Core network). Examples of the UE 201 include cellular phones, smartphones, Session Initiation Protocol (SIP) phones, laptops, personal digital assistants (PDAs), satellite radios, GPS devices, multimedia devices, video devices, digital audio players (e.g., MP3 players), cameras, game consoles, drones, aircraft, narrowband physical network devices, machine-type communication devices, land vehicles, automobiles, wearable devices, or any other similar functional devices. Those skilled in the art may also refer to the UE 201 as a mobile station, subscriber station, mobile unit, subscriber unit, radio unit, remote unit, mobile device, radio device, wireless communication device, remote device, mobile subscriber station, access terminal, mobile terminal, radio terminal, remote terminal, handheld device, user agent, mobile client, client, or any other suitable term. The Node B 203 is connected to the core network 210 via an S1 / NG interface.The core network 210 includes an MME (Mobility Management Entity) / AMF (Authentication Management Field) / SMF (Session Management Function) 211, other MMEs / AMFs / SMFs 214, an S-GW (Service Gateway) / UPF (User Plane Function) 212, and a P-GW (Packet Data Network Gateway) / UPF 213. The MME / AMF / SMF 211 is the control node that handles signaling between the UE 201 and the core network 210. Generally, the MME / AMF / SMF 211 provides bearer and connection management. All user IP (Internet Protocol) packets are transmitted through the S-GW / UPF 212, which is itself connected to the P-GW / UPF 213. The P-GW provides UE IP address allocation and other functions. The P-GW / UPF 213 is connected to the Internet service 230. The Internet service 230 includes carrier-compliant Internet protocol services, specifically including the Internet, intranet, IMS (IP Multimedia Subsystem), and packet-switched streaming services.

[0439] As an example, the first node in this application includes the UE 201.

[0440] As an example, the second node in this application includes node B 203.

[0441] As an example, node B 203 is a macrocell base station.

[0442] As an example, node B 203 is a microcell base station.

[0443] As an example, node B 203 is a pico cell base station.

[0444] As an example, node B 203 is a femtocell.

[0445] As an example, node B 203 is a base station device that supports large latency differences.

[0446] As an example, node B 203 is a flight platform device.

[0447] As an example, node B 203 is a satellite device.

[0448] As one embodiment, the node B 203 is a test device (e.g., a transceiver device simulating part of the base station's functions, a signaling tester).

[0449] As an example, the UE 201 includes a mobile phone.

[0450] As an example, the UE 201 is a vehicle including a car.

[0451] As an example, the wireless link from the UE 201 to the node B 203 is an uplink, which is used to perform uplink transmissions.

[0452] As an example, the radio link from the node B 203 to the UE 201 is a downlink, which is used to perform downlink transmissions.

[0453] As an example, the wireless link between the node B 203 and the UE 201 includes a cellular link.

[0454] As an example, the node B 203 and the UE 201 are connected via the Uu air interface.

[0455] As an example, the sender of the first information block in this application includes the node B 203.

[0456] As an example, the recipient of the first information block in this application includes the UE 201.

[0457] As an example, the sender of the second information block in this application includes the node B 203.

[0458] As an example, the recipient of the second information block in this application includes the UE 201.

[0459] As an example, the node B 203 supports the deployment of network-side (NW-side) AI / ML models.

[0460] As an example, the UE 201 supports the deployment of UE-side AI / ML models.

[0461] As an example, the UE 201 supports a 5G system.

[0462] As an example, the node B 203 supports a 5G system.

[0463] As an example, the UE 201 supports at least a 6G system.

[0464] As an example, the node B 203 supports at least a 6G system.

[0465] Example 3

[0466] Example 3 illustrates a schematic diagram of an embodiment of a wireless protocol architecture for the user plane and control plane according to an embodiment of this application, as shown in Figure 3.

[0467] Figure 3 is a schematic diagram illustrating an embodiment of the wireless protocol architecture for the user plane 350 and the control plane 300. Figure 3 shows the wireless protocol architecture for the control plane 300 between a first communication node device (UE or RSU in V2X, onboard equipment or onboard communication module) and a second node device (gNB, RSU in UE or V2X, onboard equipment or onboard communication module), or between two UEs, using three layers: Layer 1 (L1), Layer 2 (L2), and Layer 3 (L3). L1 is the lowest layer and implements various PHY (Physical layer) signal processing functions. L1 will be referred to herein as PHY 301. L2 305 is above PHY 301 and is responsible for the link between the first node device and the second node device, or between two UEs, through PHY 301. L2 305 includes a MAC (Medium Access Control) sublayer 302, an RLC (Radio Link Control) sublayer 303, and a PDCP (Packet Data Convergence Protocol) sublayer 304, which terminate at the second node device. The PDCP sublayer 304 provides multiplexing between different radio bearers and logical channels. It also provides security through encrypted data packets and supports cross-cell mobility between the second communication node devices and the first communication node device. The RLC sublayer 303 provides upper-layer packet segmentation and reassembly, retransmission of lost packets, and packet reordering to compensate for out-of-order reception due to HARQ (Hybrid Automatic Repeat reQuest). The MAC sublayer 302 provides multiplexing between logical and transport channels. It is also responsible for allocating various radio resources (e.g., resource blocks) within a cell between the first communication node devices. The MAC sublayer 302 is also responsible for HARQ operations. The RRC (Radio Resource Control) sublayer 306 in L3 of the control plane 300 is responsible for obtaining radio resources (i.e., radio bearers) and using RRC signaling between the second communication node device and the first communication node device to configure the lower layer.The wireless protocol architecture of user plane 350 includes Layer 1 (L1) and Layer 2 (L2). The wireless protocol architecture for the first and second communication node devices in user plane 350 is largely the same as the corresponding layers and sublayers in control plane 300 for Physical Layer 351, PDCP sublayer 354 in L2 355, RLC sublayer 353 in L2 355, and MAC sublayer 352 in L2 355. However, PDCP sublayer 354 also provides header compression for upper-layer packets to reduce wireless transmission overhead. L2 355 in user plane 350 also includes SDAP (Service Data Adaptation Protocol) sublayer 356. SDAP sublayer 356 is responsible for mapping between QoS (Quality of Service) streams and Data Radio Bearers (DRBs) to support service diversity. Although not illustrated, the first communication node device may have several upper layers above L2 355, including a network layer (e.g., IP (Internet Protocol) layer) terminating at the P-GW on the network side and an application layer terminating at the other end of the connection (e.g., remote UE, server, etc.).

[0468] As an example, the wireless protocol architecture in Figure 3 is applicable to the first node in this application.

[0469] As an example, the wireless protocol architecture in Figure 3 is applicable to the second node in this application.

[0470] As an example, in this application, the first information block is generated in the RRC 306.

[0471] As an example, the second information block in this application is generated in the RRC 306.

[0472] As an example, the higher layer mentioned in this application refers to the layer above the physical layer.

[0473] As an example, the higher layer described in this application includes the RRC layer.

[0474] As an example, the higher-layer signaling described in this application includes RRC IE.

[0475] As an example, the higher-level signaling described in this application includes RRC messages.

[0476] As an example, the higher layer described in this application includes the MAC layer.

[0477] As an example, the higher-layer signaling described in this application includes MAC CE.

[0478] Example 4

[0479] Example 4 illustrates a schematic diagram of a first communication device and a second communication device according to an embodiment of this application, as shown in Figure 4. Figure 4 is a block diagram of a first communication device 410 and a second communication device 450 communicating with each other in an access network.

[0480] The first communication device 410 includes a controller / processor 475, a memory 476, a receiver processor 470, a transmitter processor 416, a multi-antenna receiver processor 472, a multi-antenna transmitter processor 471, a transmitter / receiver 418, and an antenna 420.

[0481] The second communication device 450 includes a controller / processor 459, a memory 460, a data source 467, a transmitting processor 468, a receiving processor 456, a multi-antenna transmitting processor 457, a multi-antenna receiving processor 458, a transmitter / receiver 454, and an antenna 452.

[0482] In the transmission from the first communication device 410 to the second communication device 450, at the first communication device 410, upper-layer data packets from the core network are provided to the controller / processor 475. The controller / processor 475 implements L2 functionality. In the DL, the controller / processor 475 provides header compression, encryption, packet segmentation and reordering, multiplexing between logical and transport channels, and radio resource allocation to the second communication device 450 based on various priority metrics. The controller / processor 475 is also responsible for HARQ operation, retransmission of lost packets, and signaling to the second communication device 450. The transmit processor 416 and the multi-antenna transmit processor 471 implement various signal processing functions for L1 (i.e., the physical layer). Transmit processor 416 performs encoding and interleaving to facilitate forward error correction (FEC) at the second communication device 450, and mapping of signal clusters based on various modulation schemes (e.g., Binary Phase Shift Keying (BPSK), Quadrature Phase Shift Keying (QPSK), M-PSK, and M-Quadrature Amplitude Modulation (M-QAM)). Multi-antenna transmit processor 471 performs digital spatial precoding on the encoded and modulated symbols, including codebook-based precoding and non-codebook-based precoding, and beamforming processing, generating one or more parallel streams. The transmit processor 416 then maps each parallel stream to a subcarrier, multiplexes the modulated symbols with a reference signal (e.g., a pilot) in the time and / or frequency domains, and then uses an inverse fast fourier transform (IFFT) to generate a physical channel carrying the time-domain multicarrier symbol stream. The multi-antenna transmit processor 471 then performs transmit analog precoding / beamforming operations on the time-domain multicarrier symbol stream. Each transmitter 418 converts the baseband multicarrier symbol stream provided by the multi-antenna transmit processor 471 into an RF stream, which is then provided to a different antenna 420.

[0483] In the transmission from the first communication device 410 to the second communication device 450, at the second communication device 450, each receiver 454 receives a signal through its corresponding antenna 452. Each receiver 454 recovers the information modulated onto the radio frequency carrier and converts the radio frequency stream into a baseband multicarrier symbol stream, which is then provided to the receiver processor 456. The receiver processor 456 and the multi-antenna receiver processor 458 implement various L1 signal processing functions. The multi-antenna receiver processor 458 performs receive analog precoding / beamforming operations on the baseband multicarrier symbol stream from the receiver 454. The receiver processor 456 uses a Fast Fourier Transform (FFT) to convert the baseband multicarrier symbol stream after the receive analog precoding / beamforming operations from the time domain to the frequency domain. In the frequency domain, the physical layer data signal and the reference signal are demultiplexed by the receiver processor 456, where the reference signal is used for channel estimation, and the data signal is recovered in the multi-antenna receiver processor 458 after multi-antenna detection to recover any parallel stream destined for the second communication device 450. Symbols on each parallel stream are demodulated and recovered in the receive processor 456, generating soft decisions. The receive processor 456 then decodes and deinterleaves the soft decisions to recover the upper-layer data and control signals transmitted by the first communication device 410 over the physical channel. The upper-layer data and control signals are then provided to the controller / processor 459. The controller / processor 459 implements L2 functionality. The controller / processor 459 may be associated with a memory 460 storing program code and data. The memory 460 may be referred to as computer-readable media. In the DL, the controller / processor 459 provides multiplexing, packet reassembly, decryption, header decompression, and control signal processing between the transmission and logical channels to recover upper-layer packets from the core network. The upper-layer packets are then provided to all protocol layers above L2. Various control signals may also be provided to L3 for L3 processing. The controller / processor 459 is also responsible for error detection using ACK and / or NACK protocols to support HARQ operation.

[0484] In the transmission from the second communication device 450 to the first communication device 410, at the second communication device 450, a data source 467 is used to provide upper-layer data packets to the controller / processor 459. The data source 467 represents all protocol layers above L2. Similar to the transmission functions at the first communication device 410 described in the DL, the controller / processor 459 implements header compression, encryption, packet segmentation and reordering, and multiplexing between logical and transport channels based on the radio resource allocation of the first communication device 410, implementing L2 functions for the user plane and control plane. The controller / processor 459 is also responsible for HARQ operations, retransmission of lost packets, and signaling to the first communication device 410. Transmit processor 468 performs modulation mapping and channel coding processing, while multi-antenna transmit processor 457 performs digital multi-antenna spatial precoding, including codebook-based and non-codebook-based precoding, and beamforming processing. Subsequently, transmit processor 468 modulates the generated parallel stream into a multi-carrier / single-carrier symbol stream. After analog precoding / beamforming operations in multi-antenna transmit processor 457, the stream is provided to different antennas 452 via transmitter 454. Each transmitter 454 first converts the baseband symbol stream provided by multi-antenna transmit processor 457 into a radio frequency symbol stream before providing it to antenna 452.

[0485] In the transmission from the second communication device 450 to the first communication device 410, the function at the first communication device 410 is similar to the receiving function at the second communication device 450 described in the transmission from the first communication device 410 to the second communication device 450. Each receiver 418 receives radio frequency signals through its corresponding antenna 420, converts the received radio frequency signals into baseband signals, and provides the baseband signals to the multi-antenna receiving processor 472 and the receiving processor 470. The receiving processor 470 and the multi-antenna receiving processor 472 jointly implement the L1 function. The controller / processor 475 implements the L2 function. The controller / processor 475 may be associated with a memory 476 storing program code and data. The memory 476 may be referred to as computer-readable media. The controller / processor 475 provides multiplexing, packet reassembly, decryption, header decompression, and control signal processing between the transmission and logical channels to recover upper-layer data packets from the second communication device 450. The upper-layer data packets from the controller / processor 475 may be provided to the core network. The controller / processor 475 is also responsible for error detection using ACK and / or NACK protocols to support HARQ operation.

[0486] As one embodiment, the second communication device 450 includes: at least one processor and at least one memory, the at least one memory including computer program code; the at least one memory and the computer program code are configured to be used with the at least one processor. The second communication device 450 receives at least the first information block and the second information block of this application, the first information block and the second information block respectively configuring the first process and the second process of this application; the first process and the second process respectively occupy the first processing resource set and the second processing resource set; it processes the target process described in this application, the target process being one of the first process and the second process; the remaining processing resource set of the second communication device 450 is equal to the total processing resource set included in the second communication device 450 minus the portion that has been occupied; the remaining processing resource set of the second communication device 450 can include either the first processing resource set or the second processing resource set, and the remaining processing resource set of the second communication device 450 cannot simultaneously include both the first processing resource set and the second processing resource set; whether the target process is the first process or the second process depends on a comparison of the priority corresponding to the first process and the priority corresponding to the second process; the comparison of the priority corresponding to the first process and the priority corresponding to the second process depends on the types of the first process and the second process; both the first process and the second process are for inference.

[0487] As one embodiment, the second communication device 450 includes: a memory storing a computer-readable instruction program that produces actions when executed by at least one processor, the actions including: receiving the first information block and the second information block in this application; and processing the target process in this application.

[0488] As one embodiment, the first communication device 410 includes: at least one processor and at least one memory, the at least one memory including computer program code; the at least one memory and the computer program code are configured to be used with the at least one processor. The first communication device 410 transmits at least the first information block and the second information block of this application, the first information block and the second information block respectively configuring the first process and the second process of this application; the receiver of the first information block and the second information block is the second communication device 450, the first process and the second process respectively occupy a first processing resource set and a second processing resource set of the second communication device 450; the second communication device 450 processes a target process, the target process being one of the first process and the second process; the remaining processing resource set of the second communication device 450 is equal to the total processing resources included in the second communication device 450. The already occupied portion is removed from the processing resource set; the remaining processing resource set of the second communication device 450 can include either the first processing resource set or the second processing resource set, and the remaining processing resource set of the second communication device 450 cannot simultaneously include both the first processing resource set and the second processing resource set; whether the target process is the first process or the second process depends on a comparison of the priority corresponding to the first process and the priority corresponding to the second process; the comparison of the priority corresponding to the first process and the priority corresponding to the second process depends on the types of the first process and the second process; both the first process and the second process are for reasoning.

[0489] As one embodiment, the first communication device 410 includes: a memory storing a computer-readable instruction program that produces an action when executed by at least one processor, the action including: sending the first information block and the second information block of this application.

[0490] As an example, the first node in this application includes the second communication device 450.

[0491] As an example, the second node in this application includes the first communication device 410.

[0492] As an example, at least one of {the antenna 420, the transmitter 418, the transmitter processor 416, the multi-antenna transmitter processor 471, the controller / processor 475, and the memory 476} is used to transmit the first information block and the second information block of this application; at least one of {the antenna 452, the receiver 454, the receiver processor 456, the multi-antenna receiver processor 458, the controller / processor 459, the memory 460, and the data source 467} is used to receive the first information block and the second information block of this application.

[0493] As an example, at least one of the following is used to process the target process described in this application: {antenna 452, transmitter / receiver 454, transmitter processor 468, receiver processor 456, multi-antenna transmitter processor 457, multi-antenna receiver processor 458, controller / processor 459, memory 460, data source 467}.

[0494] As an example, at least one of {the antenna 452, the receiver 454, the receiver processor 456, the multi-antenna receiver processor 458, the controller / processor 459, the memory 460, and the data source 467} is used to process the target process described in this application.

[0495] Example 5

[0496] Example 5 illustrates a flowchart of transmission between a first node and a second node according to an embodiment of this application, as shown in Figure 5. In Figure 5, the first node U1 and the second node N2 communicate via a wireless link. It should be noted that the order in this embodiment does not limit the signal transmission order or the order of implementation in this application.

[0497] For the first node U1, the first information block and the second information block are received in step S510; the target process is processed in step S511.

[0498] For the second node N2, the first information block and the second information block are sent in step S520.

[0499] In embodiment 5, the first information block and the second information block are configured with a first process and a second process, respectively; the first process and the second process occupy a first processing resource set and a second processing resource set, respectively; the target process is one of the first process and the second process; the remaining processing resource set of the first node U1 is equal to the total processing resource set included in the first node U1 minus the portion that has been occupied; the remaining processing resource set of the first node U1 can include either the first processing resource set or the second processing resource set, and the remaining processing resource set of the first node U1 cannot simultaneously include both the first processing resource set and the second processing resource set; whether the target process is the first process or the second process depends on a comparison of the priority corresponding to the first process and the priority corresponding to the second process; the comparison of the priority corresponding to the first process and the priority corresponding to the second process depends on the types of the first process and the second process; both the first process and the second process are for inference.

[0500] As an example, the first node U1 is the first node in this application.

[0501] As an example, the second node N2 is the second node in this application.

[0502] As one embodiment, the air interface between the second node N2 and the first node U1 includes a wireless interface between the base station equipment and the user equipment.

[0503] As one embodiment, the air interface between the second node N2 and the first node U1 includes a wireless interface between the relay node device and the user equipment.

[0504] As one embodiment, the air interface between the second node N2 and the first node U1 includes a wireless interface between user equipment and user equipment.

[0505] As one example, the second node N2 and the first node U1 communicate via the Uu interface.

[0506] As one example, the second node N2 is the maintenance base station of the serving cell of the first node U1.

[0507] As an example, the transmission channel occupied by the first information block includes DL-SCH (DownLink-Shared Channel).

[0508] As one embodiment, the transmission channel occupied by the second information block includes DL-SCH.

[0509] As an example, the physical layer channel occupied by the first information block includes PDSCH (Physical Downlink Shared Channel).

[0510] As one embodiment, the physical layer channel occupied by the second information block includes PDSCH.

[0511] As an example, the first information block and the second information block occupy the same PDSCH.

[0512] As an example, step S510 is performed before step S511.

[0513] Example 6

[0514] Example 6 illustrates a first schematic diagram of the processing resource set of a first node according to an embodiment of this application, as shown in Figure 6. In Figure 6, the rectangles with thick outlines represent the total processing resource set included in the first node, wherein the gray-filled rectangles represent the occupied portions, and the unfilled portions represent the remaining processing resource set of the first node; the diamond-shaped rectangles represent the processing resources included in the first processing resource set, and the cross-shaped rectangles represent the processing resources included in the second processing resource set.

[0515] In Example 6, the processing resources refer only to computing resources.

[0516] As one embodiment, the first processing resource set and the second processing resource set each correspond only to computing resources, and the remaining processing resource set of the first node only includes the remaining computing resources; the number of the remaining computing resources of the first node is not less than the number of computing resources corresponding to the first processing resource set or the number of computing resources corresponding to the second processing resource set, and the number of the remaining computing resources of the first node is less than the sum of the number of computing resources corresponding to the first processing resource set and the number of computing resources corresponding to the second processing resource set.

[0517] As an example, one of the computing resources belongs to one processing unit.

[0518] As an example, one of the computing resources is a processing unit.

[0519] As an example, one of the computing resources is a process.

[0520] As an example, one of the computing resources is a storage unit.

[0521] As an example, one of the computing resources is a computing unit.

[0522] As an example, one of the computing resources is an Arithmetic and Logic Unit (ALU).

[0523] As an example, one of the computing resources is a Special Function Unit (SFU).

[0524] As an example, one computing resource corresponds to one NPU.

[0525] As an example, one computing resource corresponds to one IPU (Inference Processing Unit).

[0526] As an example, one computing resource corresponds to one CPU.

[0527] As an example, one computing resource corresponds to one APU.

[0528] Example 7

[0529] Example 7 illustrates a second schematic diagram of the processing resource set of a first node according to an embodiment of this application, as shown in Figure 7. In Figure 7, case (a) shows the relationship between the remaining computing resource set of the first node and the first processing resource set and the second processing resource set when computing is limited. The rectangles with thick lines represent the total computing resource set included in the first node, where the gray-filled rectangles represent the occupied portion and the unfilled portion represents the remaining portion of the first node; the rectangles filled with upward diagonal lines represent the computing resources corresponding to the first processing resource set, and the rectangles filled with vertical lines represent the computing resources included in the second processing resource set; case (b) shows the relationship between the remaining storage resource set of the first node and the first processing resource set and the second processing resource set when memory access is limited. The rectangles with thick lines represent the total storage resource set included in the first node, where the gray-filled rectangles represent the occupied portion and the unfilled portion represents the remaining storage resource set of the first node; the rectangles filled with downward diagonal lines represent the storage resources corresponding to the first processing resource set, and the rectangles filled with horizontal lines represent the storage resources corresponding to the second processing resource set.

[0530] In Embodiment 7, either the first processing resource set or the second processing resource set corresponds to computing resources and storage resources, and the remaining processing resource set of the first node includes remaining computing resources and remaining storage resources; the number of remaining computing resources of the first node is not less than the number of computing resources corresponding to the first processing resource set or the number of computing resources corresponding to the second processing resource set, and the number of remaining storage resources of the first node is not less than the number of storage resources corresponding to the first processing resource set or the number of storage resources corresponding to the second processing resource set; and the number of remaining computing resources of the first node is less than the sum of the number of computing resources corresponding to the first processing resource set and the number of computing resources corresponding to the second processing resource set, or the number of remaining storage resources of the first node is less than the sum of the number of storage resources corresponding to the first processing resource set and the number of storage resources corresponding to the second processing resource set.

[0531] As one embodiment, either the first processing resource set or the second processing resource set corresponds to computing resources and storage resources.

[0532] As one embodiment, the first set of processing resources includes computing resources and storage resources.

[0533] As an example, the processing resources required by the first node to process the first process include computing resources and storage resources.

[0534] As one embodiment, the second set of processing resources includes computing resources and storage resources.

[0535] As an example, the processing resources required by the first node to process the second process include computing resources and storage resources.

[0536] As an example, the set of remaining processing resources of the first node includes remaining computing resources and remaining storage resources.

[0537] As an example, the total processing resource set of the first node includes total computing resources and total storage resources.

[0538] As an example, the remaining computing resources of the first node are equal to the total computing resource set of the first node minus the set of computing resources that have already been occupied.

[0539] As an example, the remaining storage resources of the first node are equal to the total processing resource set of the first node minus the storage resources that have already been occupied.

[0540] As an example, the number of remaining computing resources of the first node is not less than the number of computing resources corresponding to the first processing resource set, and the number of remaining computing resources of the first node is not less than the number of computing resources corresponding to the second processing resource set; the number of remaining computing resources of the first node is less than the sum of the number of computing resources corresponding to the first processing resource set and the number of computing resources corresponding to the second processing resource set.

[0541] As a sub-implementation of this embodiment, the number of remaining storage resources of the first node is not less than the number of storage resources corresponding to the first processing resource set.

[0542] As a sub-implementation of this embodiment, the number of remaining storage resources of the first node is not less than the number of storage resources corresponding to the second processing resource set.

[0543] As a sub-implementation of this embodiment, the number of remaining storage resources of the first node is less than the sum of the number of storage resources corresponding to the first processing resource set and the number of storage resources corresponding to the second processing resource set.

[0544] As a sub-implementation of this embodiment, the number of remaining storage resources of the first node is not less than the sum of the number of storage resources corresponding to the first processing resource set and the number of storage resources corresponding to the second processing resource set.

[0545] As an example, the number of remaining storage resources of the first node is not less than the number of storage resources corresponding to the first processing resource set, and the number of remaining storage resources of the first node is not less than the number of storage resources corresponding to the second processing resource set; the number of remaining storage resources of the first node is less than the sum of the number of storage resources corresponding to the first processing resource set and the number of storage resources corresponding to the second processing resource set.

[0546] As a sub-implementation of this embodiment, the number of remaining computing resources of the first node is not less than the number of computing resources corresponding to the first processing resource set.

[0547] As a sub-example of this embodiment, the number of remaining computing resources of the first node is not less than the number of computing resources corresponding to the second processing resource set.

[0548] As a sub-implementation of this embodiment, the number of remaining computing resources of the first node is less than the sum of the number of computing resources corresponding to the first processing resource set and the number of computing resources corresponding to the second processing resource set.

[0549] As a sub-implementation of this embodiment, the number of remaining computing resources of the first node is not less than the sum of the number of computing resources corresponding to the first processing resource set and the number of computing resources corresponding to the second processing resource set.

[0550] As an example, at least one of the computing resources or the storage resources includes resources required for computing.

[0551] As one embodiment, at least one of the computing resources or the storage resources includes resources required for storage.

[0552] As an example, at least one of the computing resources or the storage resources includes resources required for reading and writing.

[0553] As an example, at least one of the computing resources or the storage resources includes resources required for process control.

[0554] As an example, at least one of the computing resources or the storage resources includes memory bandwidth.

[0555] As an example, at least one of the computing resources or the storage resources includes a cache resource.

[0556] As an example, at least one of the computing resources or the storage resources includes bandwidth resources.

[0557] As an example, at least one of the computing resources or the storage resources includes read / write resources.

[0558] As an example, at least one of the computing resources or the storage resources includes a cache resource.

[0559] As an example, at least one of the computing resources or the storage resources includes register resources.

[0560] As an example, at least one of the computing resources or the storage resources includes data interaction resources.

[0561] As one embodiment, at least one of the computing resources or the storage resources includes computing power resources.

[0562] As an example, at least one of the computing resources or the storage resources is used for at least one of processing, computing, or inference.

[0563] As one embodiment, at least one of the computing resources or the storage resources is used for storage.

[0564] As one embodiment, at least one of the computing resources or the storage resources is used for reading and writing.

[0565] As an example, at least one of the computing resources or the storage resources is used for data interaction.

[0566] As an example, at least one of the computing resources or the storage resources is used for at least addition and multiplication operations.

[0567] As an example, at least one of the computing resources or the storage resources is used for at least convolution operations.

[0568] As one example, the computing resources include the resources required for computing.

[0569] As one embodiment, the computing resources include computing resources.

[0570] As one example, the computing resources include computing power resources.

[0571] As an example, the computing resources are used for at least one of processing, computation, or inference.

[0572] As an example, the computing resources are used for at least addition and multiplication operations.

[0573] As an example, the computing resources are used for at least convolution operations.

[0574] As an example, one of the computing resources is a computing unit.

[0575] As an example, one of the computing resources is an arithmetic logic unit.

[0576] As an example, one of the computing resources is a special function unit.

[0577] As an example, one of the computing resources is an NPU.

[0578] As an example, one of the computing resources is an IPU.

[0579] As an example, one of the computing resources is a CPU.

[0580] As an example, one of the computing resources is an APU.

[0581] As an example, an operation on one of the computing resources is atomic.

[0582] As one embodiment, the storage resources include resources needed to store inference parameters or intermediate variables.

[0583] As one embodiment, the storage resources include resources that store at least one of the inference inputs, inference outputs, inference intermediate results, or AI models corresponding to AI / ML functions.

[0584] As one example, the storage resources include the resources required for storing process control parameters.

[0585] As one example, the storage resources include those required for reading and writing.

[0586] As one example, the storage resources include those required for data interaction.

[0587] As one example, the storage resources include bandwidth resources.

[0588] As one example, the storage resources include read / write resources.

[0589] As one example, the storage resources include memory bandwidth.

[0590] As one example, the storage resources include cache resources.

[0591] As one example, the storage resources include register resources.

[0592] As one embodiment, the storage resources include multi-level storage resources.

[0593] As one embodiment, one of the storage resources includes a portion of each level of storage resources in a multi-level storage resource.

[0594] As an example, one of the storage resources is a storage unit.

[0595] As an example, one of the storage resources is a cache resource.

[0596] As an example, one of the storage resources is a register.

[0597] As one embodiment, one of the storage resources includes at least one register.

[0598] As an example, the storage resources of the first node are divided into L levels; L is a positive integer greater than 1, and L is predefined or the value of L depends on the capabilities of the first node.

[0599] As a sub-example of this embodiment, the L levels of storage resources include one or more of registers, local memory, shared memory, L1 cache, and L2 cache.

[0600] As a sub-example of this embodiment, the L levels of storage resources include one or more of private memory, local memory, and global memory.

[0601] As a sub-example of this embodiment, the total set of storage resources included in the first node refers to the sum of the L levels of storage resources included in the first node.

[0602] As a sub-example of this embodiment, one of the storage resources includes a portion of the storage resources of each of the L levels of storage resources included in the first node.

[0603] As a sub-example of this embodiment, the total set of storage resources included in the first node refers to the storage resources of one level among the L levels of storage resources included in the first node.

[0604] As a sub-example of this embodiment, one of the storage resources includes a portion of the storage resources of one of the L levels of storage resources included in the first node.

[0605] As an additional embodiment of the above two sub-implementations, the level is any one of the L levels.

[0606] As an additional embodiment of the above two sub-implementations, the level is the lowest level among the L levels.

[0607] As an additional embodiment of the above two sub-implementations, the level is the highest level among the L levels.

[0608] As an additional embodiment of the above two sub-implementations, the level is a predefined level among the L levels.

[0609] As an additional embodiment of the two sub-implementations described above, the level is a level indicated by the base station.

[0610] As an example, in implementation, the resource corresponding to the storage resource can be a physical device or component; specifically, it can be a hard disk, memory, disk drive, or CPU, etc.

[0611] As an example, one of the storage resources is a storage unit.

[0612] As an example, one storage resource corresponds to one storage size.

[0613] As one embodiment, one computing resource and one storage resource constitute a processing unit.

[0614] As one embodiment, a computing resource and a storage resource constitute a process.

[0615] As an example, one computing resource and one storage resource constitute an ALU.

[0616] As an example, one computing resource and one storage resource constitute an SFU.

[0617] As one embodiment, one computing resource and one storage resource constitute an NPU.

[0618] As one embodiment, one computing resource and one storage resource constitute an IPU.

[0619] As one embodiment, one computing resource and one storage resource constitute a CPU.

[0620] As one embodiment, one computing resource and one storage resource constitute an APU.

[0621] Example 8

[0622] Example 8 illustrates a schematic diagram of the relationship between the priorities of a target process and a first process and a second process according to an embodiment of this application, as shown in Figure 8. In Figure 8, case (a) indicates that the priority corresponding to the first process is higher than the priority corresponding to the second process, and the target process is the first process; case (b) indicates that the priority corresponding to the first process is lower than the priority corresponding to the second process, and the target process is the second process.

[0623] As an example, the priority of the first process is higher than the priority of the second process, and the target process is the first process.

[0624] As an example, the priority of the first process is higher than the priority of the second process, and the first node processes the first process.

[0625] As an example, the priority of the first process is lower than the priority of the second process, and the target process is the second process.

[0626] As an example, the priority of the first process is lower than the priority of the second process, and the first node processes the second process.

[0627] As one example, the priority includes Priority.

[0628] As one example, the priority includes Order.

[0629] As one example, the priority includes Level.

[0630] As one example, the priority includes a priority index.

[0631] As a sub-example of this embodiment, the smaller the priority index corresponding to the process, the higher the priority of the process.

[0632] As a sub-example of this embodiment, the larger the priority index corresponding to the process, the higher the priority of the process.

[0633] As an example, the priority is predefined.

[0634] As an example, the priority is configurable.

[0635] As one embodiment, the priority is configured by the first information block and the second information block.

[0636] As one example, the priority of the priority process.

[0637] As an example, the priority is the physical layer priority.

[0638] As an example, the priority is a priority other than the physical layer priority.

[0639] Example 9

[0640] Example 9 illustrates a first schematic diagram of a comparison of process priorities according to an embodiment of this application, as shown in Figure 9. In Figure 9, the priority corresponding to a process used in the physical layer is higher than the priority corresponding to a process used in layers other than the physical layer.

[0641] As an example, when the first process is a process for the physical layer and the second process is a process for a layer other than the physical layer, the priority of the first process is higher than the priority of the second process; when the first process is a process for a layer other than the physical layer and the second process is a process for the physical layer, the priority of the first process is lower than the priority of the second process.

[0642] As an example, when the first process is a process for the physical layer and the second process is a process for a layer other than the physical layer, the target process is the first process; when the first process is a process for a layer other than the physical layer and the second process is a process for the physical layer, the target process is the second process.

[0643] As one embodiment, the physical layer includes Layer 1.

[0644] As one embodiment, the physical layer includes L1.

[0645] As one embodiment, the process for the physical layer includes signal modulation and demodulation.

[0646] As one example, the process for the physical layer includes encoding and decoding.

[0647] As one embodiment, the process for the physical layer includes beamforming.

[0648] As one embodiment, the process for the physical layer includes: channel estimation and compensation.

[0649] As one embodiment, the process for the physical layer includes uplink / downlink synchronization.

[0650] As one example, the layers beyond the physical layer include higher layers.

[0651] As one example, the layers outside the physical layer include Layer 2.

[0652] As one embodiment, the layer outside the physical layer includes L2.

[0653] As one example, the layers outside the physical layer include the MAC layer.

[0654] As one example, the layers outside the physical layer include Layer 3.

[0655] As one example, the layer outside the physical layer includes L3.

[0656] As one embodiment, the layers outside the physical layer include the RRC layer.

[0657] As one embodiment, the process for layers outside the physical layer includes: allocating resources according to uplink / downlink scheduling.

[0658] As one embodiment, the process for layers other than the physical layer includes: data encapsulation and decapsulation.

[0659] As one embodiment, the process for layers other than the physical layer includes: HARQ-based uplink or downlink data retransmission control.

[0660] As one example, the processes for layers other than the physical layer include: network performance optimization and management.

[0661] As one example, the process for layers outside the physical layer includes: L3 measurement.

[0662] As one example, the process for layers outside the physical layer includes: mobility management.

[0663] As one embodiment, the process for layers outside the physical layer includes: RLF (Radio Link Failure) prediction.

[0664] As one example, the process for layers outside the physical layer includes: HOF (HandOver Failure) prediction.

[0665] As one example, the process for layers outside the physical layer includes: RRM (Radio Resource Management) prediction.

[0666] Example 10

[0667] Example 10 illustrates a second schematic diagram of comparing process priorities according to an embodiment of this application, as shown in Figure 10. In Figure 10, the priority of the process used for encoding / decoding is higher than the priority of the process used for measurement.

[0668] As an example, when the first process is a process with the priority corresponding to a process used for encoding and decoding, and the second process is a process used for measurement, the priority corresponding to the first process is higher than the priority corresponding to the second process; when the first process is a process used for measurement, and the second process is a process with the priority corresponding to a process used for encoding and decoding, the priority corresponding to the first process is lower than the priority corresponding to the second process.

[0669] As an example, when the first process is a process with the priority corresponding to a process used for encoding and decoding, and the second process is a process used for measurement, the target process is the first process; when the first process is a process used for measurement, and the second process is a process with the priority corresponding to a process used for encoding and decoding, the target process is the second process.

[0670] As one example, the encoding / decoding includes: encoding.

[0671] As one embodiment, the encoding / decoding includes: decoding.

[0672] As one example, the encoding and decoding includes: channel coding and channel decoding.

[0673] As one embodiment, the encoding and decoding includes: source encoding and source decoding.

[0674] As one embodiment, the encoding and decoding includes: joint coding of the source channel and joint decoding of the source channel.

[0675] As one embodiment, the encoding / decoding includes: modulation.

[0676] As one embodiment, the encoding / decoding includes: demodulation.

[0677] As one example, the encoding / decoding includes: equalization.

[0678] As one example, the encoding / decoding includes: channel estimation.

[0679] As one example, the encoding / decoding includes: inference-based encoding / decoding.

[0680] As one example, the encoding / decoding includes: prediction-based encoding / decoding.

[0681] As one example, the encoding / decoding includes: encoding / decoding for AI / ML based applications.

[0682] As one example, the measurement includes: generating CSI.

[0683] As one example, the measurement includes: a measurement for CSI prediction.

[0684] As one example, the measurement includes: a measurement of CSI compression.

[0685] As one example, the measurement includes: a measurement based on reasoning.

[0686] As one example, the measurement includes: a prediction-based measurement.

[0687] As one example, the measurement includes: measurement based on AI / ML.

[0688] As one example, the measurement includes: AI / ML-based mobility measurement.

[0689] As one embodiment, the measurement includes: LTM (L1 / L2 Triggered Mobility) measurement.

[0690] As one example, the measurement includes: a measurement for BFR (Beam Failure Recovery) prediction.

[0691] As one example, the measurement includes: a measurement for RRM prediction.

[0692] As one example, the measurement includes: a measurement for RLF prediction.

[0693] As one example, the measurement includes: a measurement for HOF prediction.

[0694] As one embodiment, the measurement includes: a measurement for predicting a measurement event.

[0695] As one embodiment, the measurement includes: a measurement for predicting cell-level mobility.

[0696] As one embodiment, the measurement includes: a measurement for beam level mobility prediction.

[0697] As one example, the measurement includes: a measurement for beam management (BM) prediction.

[0698] As an example, the CSI in this application includes LI (layer indicator).

[0699] As an example, the CSI in this application includes RI (rank indicator).

[0700] As an example, the CSI in this application includes CQI (Channel Quality Indicator).

[0701] As an example, the CSI in this application includes PMI (Precoding Matrix Indicator).

[0702] As an example, the CSI in this application includes CRI (CSI-RS resource indicator, Channel State Information Reference Signal Resource Indicator).

[0703] As an example, the CSI in this application includes SSBRI (SS / PBCH Block Resource indicator).

[0704] As an example, the CSI in this application includes L1-RSRP (Layer 1 Reference Signal Received Power).

[0705] As an example, the CSI in this application includes SNR (Signal to Noise Ratio).

[0706] As an example, the CSI mentioned in this application includes SINR (Signal to Interference plus Noise Ratio).

[0707] As an example, the CSI in this application includes BLER (Block Error Rate).

[0708] Example 11

[0709] Example 11 illustrates a third schematic diagram of comparing process priorities according to an embodiment of this application, as shown in Figure 11. In Figure 11, the priority of the process serving the cell is higher than the priority of the process serving a cell other than the serving cell.

[0710] In Example 11, the serving cell is the serving cell of the first node.

[0711] As an example, the priority of the process serving the cell in the first process and the second process is higher than the priority of the process serving cells other than the serving cell.

[0712] As an example, when the first process is a process for serving a cell and the second process is a process for serving a cell other than the serving cell, the priority of the first process is higher than the priority of the second process; when the first process is a process for serving a cell other than the serving cell and the second process is a process for serving a cell, the priority of the first process is lower than the priority of the second process.

[0713] As an example, when the first process is a process for serving a cell and the second process is a process for serving a cell other than the serving cell, the target process is the first process; when the first process is a process for serving a cell other than the serving cell and the second process is a process for serving a cell, the target process is the second process.

[0714] As an example, the serving cell refers to the Serving Cell.

[0715] As one example, the serving cell includes PCell.

[0716] As one example, the serving cell includes SCell.

[0717] As an example, the serving cell includes a PSCell (Primary Secondary Cell).

[0718] As one example, the serving cell includes SpCell.

[0719] As one example, the serving cell includes cells in the MCG.

[0720] As one example, the serving cell includes cells in the SCG.

[0721] As an example, the first node performed secondary serving cell addition for the serving cell.

[0722] As an example, the serving cell is configured via sCellToAddModList IE.

[0723] As an example, the first node is assigned an SCellIndex for the serving cell.

[0724] As an example, the first node is assigned a ServCellIndex for the serving cell.

[0725] As an example, the SCellIndex in this application is a positive integer not greater than 31.

[0726] As an example, the ServCellIndex in this application is a non-negative integer not greater than 31.

[0727] As an example, an RRC connection has been established between the first node and the serving cell.

[0728] As an example, the C (Cell)-RNTI (Radio Network Temporary Identifier) ​​of the first node is assigned by the serving cell.

[0729] As one example, the cells outside the serving cell include neighboring cells.

[0730] As one example, the cells outside the serving cell include inactive cells.

[0731] As one example, the cells other than the serving cell include candidate cells.

[0732] As one example, the cells other than the serving cell include additional cells.

[0733] As an example, the cells outside the serving cell are cells used for inter-cell mobility.

[0734] As an example, the cells outside the serving cell are cells used for inter-cell beam management.

[0735] As an example, the cells outside the serving cell are cells used for inter-cell mobility in L1 / L2.

[0736] As an example, the cells outside the serving cell are cells used for inter-cell beam management of L1 / L2.

[0737] As an example, the PCI of a cell other than the serving cell is different from the PCI of the serving cell.

[0738] As an example, PCI in this application refers to Physical Cell Identifier.

[0739] As an example, PCI in this application refers to Physical Cell Identity.

[0740] As an example, PCI in this application refers to Physical-layer Cell Identity.

[0741] As an example, PCI in this application refers to physCellId.

[0742] As an example, the first node does not perform secondary serving cell addition for cells other than the serving cell.

[0743] As an example, the latest sCellToAddModList received by the first node does not include cells other than the serving cell.

[0744] As an example, neither the most recently received sCellToAddModList nor sCellToAddModListSCG by the first node includes cells outside the serving cell.

[0745] As an example, the first node is not assigned an SCellIndex for a cell outside the serving cell.

[0746] As an example, the first node is not assigned a ServCellIndex for a cell other than the serving cell.

[0747] As an example, no RRC connection is established between the first node and cells other than the serving cell.

[0748] As an example, the C-RNTI of the first node is not assigned by a cell outside the serving cell.

[0749] As an example, when a cell is configured via sCellToAddModList IE, the cell is the serving cell; when a cell is an SpCell, the cell is the serving cell.

[0750] As an example, when a cell is neither configured via sCellToAddModList IE nor SpCell, the cell is a cell outside the serving cell.

[0751] As one example, the process outside the serving cell includes: neighboring cell signal quality measurement.

[0752] As one example, the process outside the serving cell includes: neighboring cell measurement reports.

[0753] As one example, the processes outside the serving cell include: neighbor cell handover and reselection.

[0754] As one example, the processes outside the serving cell include auxiliary measurements for cell selection and reselection.

[0755] As one example, the process outside the serving cell includes: monitoring broadcast information of non-serving cells.

[0756] As one example, the process outside the serving cell includes: carrier aggregation monitoring.

[0757] Example 12

[0758] Example 12 illustrates a schematic diagram of RAN domain AI / ML function deployment according to one embodiment of this application, as shown in Figure 12. In Figure 12, the gNB can be replaced with, for example, an eNB, or a network device such as a 6G base station.

[0759] In Example 12, the management of ML inference functions of multiple base stations is completed by the RAN domain management function 1202, that is, data interaction with the RAN domain MnS (Management Service) consumer / cross-domain management 1201 (as shown by the dashed arrow in Figure 12). The RAN domain ML training function 1203 is located in the RAN domain management function 1202; while the ML inference functions are located in the base stations, that is, the AI / ML inference function 1204 is located in gNB 1205, the AI / ML inference function 1206 is located in gNB 1207, and so on.

[0760] AI / ML related functions include ML training (also known as AI training or AI / ML training), ML testing, and ML inference (also known as AI inference or AI / ML inference), etc. ML training, ML testing, and ML inference functions can be deployed independently or co-located. Deployment of AI / ML related functions can be implemented through software, such as downloading and / or running executable files; or it can be implemented through a combination of software and hardware, such as accelerating specific computing units through hardware to improve computing speed or save power.

[0761] ML training functions can be deployed in a cross-domain management system or a domain-specific management system; the domain-specific management system is used to manage the RAN domain or the CN (Core Network) domain. For example, ML training functions for MDA (Management Data Analytics) can be deployed in MDAF (Management Data Analytic Function); ML training for network data analytics can be deployed in NWDAF (Network Data Analytics Function), meaning the ML training function is an MTLF (Model Training Logical Function).

[0762] The ML inference function can also be deployed in a cross-domain management system or a domain-specific management system; for example, the ML inference function is MDAF, or the ML inference function is AnLF (Analytics Logical Function) located in NWDAF.

[0763] Similarly, ML testing capabilities can also be deployed in cross-domain management systems or domain-specific management systems.

[0764] Optionally, the management of ML inference function can also be completed by the base station itself, that is, each base station can independently interact with the RAN domain MnS consumer / cross-domain management 1201.

[0765] It should be noted that Example 12 is merely a non-limiting implementation; optionally, the ML training function of the RAN domain may also be deployed at the base station; or optionally, some base stations may deploy both the ML inference function and the ML training function of the RAN domain, while some base stations may only deploy the ML inference function.

[0766] As an example, one of the gNBs (or base stations) in Example 12 is the second node of this application.

[0767] Example 13

[0768] Example 13 illustrates a schematic diagram of the deployment of AI / ML functionality in a UE according to one embodiment of this application, as shown in Figure 13. In Figure 13, the RAN domain ML training function 1304 is optional.

[0769] UE function 1303 is deployed in the first node of this application, and the UE function 1303 includes AI / ML inference function 1305; the AI / ML inference function 1305 uses an ML model (also called an AI model) for inference; an ML model is typically trained before being used for AI / ML inference.

[0770] As an example, the UE function 1303 includes a RAN domain ML training function 1304, which runs training data through an ML model to obtain a relevant loss and adjusts the parameters of the ML model based on the calculated loss; the ML training includes at least one of ML initial training, ML re-training, and reinforcement learning.

[0771] The above embodiments can reduce the complexity of the base station, or save air interface resources caused by reporting training data; however, the above embodiments place high demands on the processing capabilities of the UE side.

[0772] Optionally, the UE function 1303 also includes a CN domain ML training function (not shown in Figure 13).

[0773] Optionally, the UE function 1303 also includes an AI / ML deployment function—not shown in Figure 13—for loading ML models and data.

[0774] As an example, the first node indicates whether it supports ML training function (RAN domain or CN domain) through capability reporting. The capability reporting is RRC signaling or NAS (Non-Access Stratum) signaling.

[0775] As an example, the ML model and the associated metadata are loaded by the first node from a network device or a remote server.

[0776] Optionally, the UE function 1303 is an MnS producer that provides data to the CN domain MnF (Management Function) and / or the RAN domain MnF and / or the cross-domain management system 1301 for management or analysis (as shown by the double arrow 1302).

[0777] Optionally, the UE function 1303 is an MnS consumer that loads data from the CN domain MnF and / or RAN domain MnF and / or cross-domain management system 1301 for AI / ML-related management, such as managing data requests, ML model activation, and / or ML training (as shown by double arrow 1302).

[0778] As an example, both the first process and the second process in this application belong to the processes in the AI / ML inference function 1305.

[0779] As an example, both the first process and the second process in this application require the participation of the AI / ML inference function.

[0780] As an example, the ML model is based on NN (Neural Networks).

[0781] As an example, the ML model is based on ANN (Artificial Neural Networks).

[0782] As an example, the ML model is based on CNN (Convolutional Neural Networks).

[0783] As an example, the ML model is based on the LLM (Large Language Model) architecture.

[0784] As an example, the ML model is based on the Transformer architecture.

[0785] As an example, the ML model is based on the GPT (Generative Pre-Trained) architecture.

[0786] As an example, the ML model is based on LSTM (Long Short-Term Memory network).

[0787] As an example, the ML model is based on MLP (MultiLayer Perceptron).

[0788] As an example, the ML model is based on GAN (Generative Adversarial Nets).

[0789] As an example, the ML model is based on a lightweight neural network.

[0790] As a sub-example of this embodiment, the lightweight neural network includes one or more of MobileNet, ShuffleNet, and SqueezeNet.

[0791] Example 14

[0792] Example 14 illustrates a schematic diagram of a processing system based on artificial intelligence or machine learning according to an embodiment of this application, as shown in Figure 14. In Figure 14, the processing system based on artificial intelligence or machine learning includes a first processor, a second processor, a third processor, and a fourth processor.

[0793] In Example 14, the first processor sends a first dataset to the second processor and a second dataset to the third processor; the second processor generates a target first-class parameter set based on the first dataset, and sends the generated target first-class parameter set to the third processor; the third processor processes the second dataset using the target first-class parameter set to obtain a first-class output, and optionally, the third processor sends the first-class output to the fourth processor. In Figure 14, the first-class feedback and the second-class feedback are optional; the second processor includes ML training functionality; the third processor includes ML inference functionality.

[0794] As one embodiment, the fourth processor includes ML testing functionality.

[0795] As one embodiment, the fourth processor includes performance monitoring / evaluation of the ML model.

[0796] As an example, the third processor sends a first type of feedback to the second processor; the first type of feedback is used to trigger the recalculation or update of the target first type of parameter set, that is, to trigger ML initial training or ML retraining.

[0797] As one embodiment, the fourth processor sends a second type of feedback to the first processor; the second type of feedback is used to generate the first dataset or the second dataset, or the second type of feedback is used to trigger the sending of the first dataset or the sending of the second dataset.

[0798] As one embodiment, the third processor processes the first process.

[0799] As one embodiment, the third processor processes the second process.

[0800] As one embodiment, the third processor processes the target process.

[0801] As one embodiment, the third processor belongs to the first node, and the fourth processor belongs to the second node.

[0802] As an example, the third processor belongs to the first node.

[0803] As an example, the first dataset includes training data.

[0804] As one embodiment, the second processor is used to train an ML model, and the trained model is described by the target first class of parameter sets.

[0805] As an example, the second processor belongs to the first node; the above method avoids passing the first dataset to the second node.

[0806] As an example, the second processor belongs to the second node in this application; the above method supports joint training and optimizes system performance.

[0807] As an example, the second processor belongs to the core network; the above method supports network-wide joint training, further optimizing system performance.

[0808] As an example, the second dataset includes inference data.

[0809] As an example, the third processor constructs a model based on the target first type of parameter group, and then inputs the second dataset into the constructed model to obtain the first type of output.

[0810] As an example, the third processor generates a recovery dataset based on the first type of output, and the error between the recovery dataset and the second dataset is used to generate the first type of feedback.

[0811] As an example, the first type of feedback is used to reflect the performance of the trained model; when the performance of the trained model fails to meet the requirements, the second processing opportunity will recalculate the target first type of parameter set.

[0812] As an example, when the error is too large or the update has not been performed for too long, the performance of the trained model is considered to be unsatisfactory.

[0813] As an example, the target first type of parameter group includes one or more of the following: convolution kernel, pooling kernel, pooling function, activation function, parameters of the pooling function, or parameters of the activation function.

[0814] As an example, the target first type of parameter group includes one or more of the following: convolution kernel size, number of convolution layers, convolution stride, pooling kernel size, pooling kernel stride, pooling function, activation function, or number of feature maps.

[0815] Example 15

[0816] Example 15 illustrates a schematic diagram based on artificial intelligence or machine learning according to an embodiment of this application, as shown in Figure 15. In Figure 15, the first and second operations belong to a first stage, the third operation belongs to a second stage, the fourth operation belongs to a third stage, and the fifth operation belongs to a fourth stage; the arrowed lines indicate the sequence of processes.

[0817] As an example, the first operation includes AI / ML training, the second operation includes AI / ML testing, the third operation includes AI / ML emulation, the fourth operation includes AI / ML entity loading, and the fifth operation includes AI / ML inference.

[0818] As an example, the first stage includes a training phase, the second stage includes an emulation phase, the third stage includes a deployment phase, and the fourth stage includes an inference phase.

[0819] As an example, the first stage includes AI / ML model training.

[0820] As an example, the first stage includes AI / ML model training and AI / ML testing.

[0821] As an example, the AI / ML model training includes initial training and re-training of one or a group of AI / ML entities.

[0822] As an example, the training of the AI / ML model depends on training data.

[0823] As an example, the AI / ML model training includes AI / ML entity validation.

[0824] As an example, the AI / ML entity verification is used to evaluate the performance of the AI / ML entity.

[0825] As an example, the AI / ML entity verification relies on verification data.

[0826] As an example, if the AI / ML entity verification results do not meet expectations, the AI / ML model will be retrained.

[0827] As an example, the AI / ML testing includes testing the validated AI / ML entities to estimate the performance of the trained AI / ML model.

[0828] As an example, if the AI / ML test results meet expectations, the AI / ML entity proceeds to the next stage; otherwise, the AI / ML model will be retrained.

[0829] As an example, the AI / ML test relies on test data.

[0830] As one embodiment, the second stage includes AI / ML simulation, which performs AI / ML entity reasoning in a simulation environment.

[0831] As an example, the AI / ML simulation estimates the performance of AI / ML entity reasoning in a simulation environment before using AI / ML entities.

[0832] As one embodiment, the second stage is optional.

[0833] As an example, the third stage includes AI / ML entity loading, which is to obtain trained AI / ML entities to obtain the desired AI / ML inference function.

[0834] As an example, the third stage is optional.

[0835] As an example, the third stage is no longer needed when the training and inference functions are co-located.

[0836] As an example, the fourth stage includes AI / ML inference.

[0837] As an example, the first process belongs to the fourth stage.

[0838] As an example, the second process belongs to the fourth stage.

[0839] Example 16

[0840] Example 16 illustrates a structural block diagram of a processing apparatus for a first node according to an embodiment of the present application, as shown in Figure 16. In Figure 16, the processing apparatus 1600 in the first node includes a first receiver 1601 and a first processor 1602.

[0841] In embodiment 16, the first receiver 1601 receives a first information block and a second information block, the first information block and the second information block are respectively configured with a first process and a second process; the first process and the second process occupy a first processing resource set and a second processing resource set respectively; the first processor 1602 processes a target process, the target process being one of the first process and the second process.

[0842] In embodiment 16, the remaining processing resource set of the first node is equal to the total processing resource set of the first node minus the portion that has been occupied; the remaining processing resource set of the first node can include either the first processing resource set or the second processing resource set, and the remaining processing resource set of the first node cannot include both the first processing resource set and the second processing resource set simultaneously; whether the target process is the first process or the second process depends on a comparison of the priority corresponding to the first process and the priority corresponding to the second process; the comparison of the priority corresponding to the first process and the priority corresponding to the second process depends on the types of the first process and the second process; both the first process and the second process are for inference.

[0843] In one embodiment, the priority corresponding to the first process is higher than the priority corresponding to the second process, and the target process is the first process; or the priority corresponding to the first process is lower than the priority corresponding to the second process, and the target process is the second process.

[0844] As an example, the type of process includes at least one of the following:

[0845] - Whether the process is used for encoding / decoding;

[0846] - The layer corresponding to the process;

[0847] - The cell corresponding to the process.

[0848] As an example, the priority of the process used for the physical layer in the first process and the second process is higher than the priority of the process used for layers other than the physical layer.

[0849] As an example, the priority of the process used for encoding and decoding in the first process and the second process is higher than the priority of the process used for measurement.

[0850] As an example, the priority of the process serving the cell in the first process and the second process is higher than the priority of the process serving cells other than the serving cell.

[0851] As one embodiment, the first processing resource set and the second processing resource set each correspond only to computing resources, and the remaining processing resource set of the first node only includes the remaining computing resources; the number of the remaining computing resources of the first node is not less than the number of computing resources corresponding to the first processing resource set or the number of computing resources corresponding to the second processing resource set, and the number of the remaining computing resources of the first node is less than the sum of the number of computing resources corresponding to the first processing resource set and the number of computing resources corresponding to the second processing resource set.

[0852] As one embodiment, either the first processing resource set or the second processing resource set corresponds to computing resources and storage resources, and the remaining processing resource set of the first node includes remaining computing resources and remaining storage resources; the number of remaining computing resources of the first node is not less than the number of computing resources corresponding to the first processing resource set or the number of computing resources corresponding to the second processing resource set, and the number of remaining storage resources of the first node is not less than the number of storage resources corresponding to the first processing resource set or the number of storage resources corresponding to the second processing resource set; and the number of remaining computing resources of the first node is less than the sum of the number of computing resources corresponding to the first processing resource set and the number of computing resources corresponding to the second processing resource set, or the number of remaining storage resources of the first node is less than the sum of the number of storage resources corresponding to the first processing resource set and the number of storage resources corresponding to the second processing resource set.

[0853] As an example, the first process and the second process correspond to different AI / ML models.

[0854] As an example, the first process and the second process correspond to different AI / ML model IDs.

[0855] As an example, the first process and the second process correspond to different functions.

[0856] As an example, the first process and the second process correspond to the same Entity.

[0857] As an example, the first process and the second process correspond to different Entities.

[0858] As an example, both the first process and the second process are for AI / ML.

[0859] As an example, both the first process and the second process are for prediction.

[0860] As an example, the first node processes the AI / ML model that needs to be activated for either the first process or the second process.

[0861] As an example, the first node consumes processing resources for inference when processing either the first process or the second process.

[0862] As an example, the results generated by the first process and the results generated by the second process are both based on reasoning.

[0863] As an example, the results generated by the first process and the results generated by the second process are both based on predictions.

[0864] As an example, the results generated by the first process and the results generated by the second process are both based on AI / ML.

[0865] As an example, the first node 1600 is a user equipment.

[0866] As an example, the first node 1600 is a terminal.

[0867] As an example, the first node 1600 is a relay node device.

[0868] As an example, the first receiver 1601 includes at least one of the following in embodiment 4: the antenna 452, the receiver 454, the receiver processor 456, the multi-antenna receiver processor 458, the controller / processor 459, the memory 460, and the data source 467.

[0869] As an example, the first processor 1602 includes at least one of the following in embodiment 4: {the antenna 452, the receiver 454, the transmitter 454, the receiver processor 456, the transmitter processor 468, the multi-antenna receiver processor 458, the multi-antenna transmitter processor 457, the controller / processor 459, the memory 460, and the data source 467}.

[0870] Example 17

[0871] Example 17 illustrates a structural block diagram of a processing apparatus for a second node according to an embodiment of the present application, as shown in Figure 17. In Figure 17, the processing apparatus 1700 in the second node includes a first transmitter 1701.

[0872] In embodiment 17, the first transmitter 1701 sends a first information block and a second information block, and the first information block and the second information block are respectively configured with a first process and a second process.

[0873] In embodiment 17, the receivers of the first information block and the second information block are the first node. The first process and the second process occupy the first processing resource set and the second processing resource set of the first node, respectively. The first node processes a target process, which is one of the first process and the second process. The remaining processing resource set of the first node is equal to the total processing resource set of the first node minus the portion that has been occupied. The remaining processing resource set of the first node can include either the first processing resource set or the second processing resource set, but the remaining processing resource set of the first node cannot include both the first processing resource set and the second processing resource set simultaneously. Whether the target process is the first process or the second process depends on a comparison of the priority corresponding to the first process and the priority corresponding to the second process. The comparison of the priority corresponding to the first process and the priority corresponding to the second process depends on the types of the first process and the second process. Both the first process and the second process are for inference.

[0874] In one embodiment, the priority corresponding to the first process is higher than the priority corresponding to the second process, and the target process is the first process; or the priority corresponding to the first process is lower than the priority corresponding to the second process, and the target process is the second process.

[0875] As an example, the type of process includes at least one of the following:

[0876] - Whether the process is used for encoding / decoding;

[0877] - The layer corresponding to the process;

[0878] - The cell corresponding to the process.

[0879] As an example, the priority of the process used for the physical layer in the first process and the second process is higher than the priority of the process used for layers other than the physical layer.

[0880] As an example, the priority of the process used for encoding and decoding in the first process and the second process is higher than the priority of the process used for measurement.

[0881] As an example, the priority of the process for the serving cell of the first node in the first process and the second process is higher than the priority of the process for cells other than the serving cell of the first node.

[0882] As one embodiment, the first processing resource set and the second processing resource set each correspond only to computing resources, and the remaining processing resource set of the first node only includes the remaining computing resources; the number of the remaining computing resources of the first node is not less than the number of computing resources corresponding to the first processing resource set or the number of computing resources corresponding to the second processing resource set, and the number of the remaining computing resources of the first node is less than the sum of the number of computing resources corresponding to the first processing resource set and the number of computing resources corresponding to the second processing resource set.

[0883] As one embodiment, either the first processing resource set or the second processing resource set corresponds to computing resources and storage resources, and the remaining processing resource set of the first node includes remaining computing resources and remaining storage resources; the number of remaining computing resources of the first node is not less than the number of computing resources corresponding to the first processing resource set or the number of computing resources corresponding to the second processing resource set, and the number of remaining storage resources of the first node is not less than the number of storage resources corresponding to the first processing resource set or the number of storage resources corresponding to the second processing resource set; and the number of remaining computing resources of the first node is less than the sum of the number of computing resources corresponding to the first processing resource set and the number of computing resources corresponding to the second processing resource set, or the number of remaining storage resources of the first node is less than the sum of the number of storage resources corresponding to the first processing resource set and the number of storage resources corresponding to the second processing resource set.

[0884] As an example, the first process and the second process correspond to different AI / ML models.

[0885] As an example, the first process and the second process correspond to different AI / ML model IDs.

[0886] As an example, the first process and the second process correspond to different functions.

[0887] As an example, the first process and the second process correspond to the same Entity.

[0888] As an example, the first process and the second process correspond to different Entities.

[0889] As an example, both the first process and the second process are for AI / ML.

[0890] As an example, both the first process and the second process are for prediction.

[0891] As an example, the first node processes the AI / ML model that needs to be activated for either the first process or the second process.

[0892] As an example, the first node consumes processing resources for inference when processing either the first process or the second process.

[0893] As an example, the results generated by the first process and the results generated by the second process are both based on reasoning.

[0894] As an example, the results generated by the first process and the results generated by the second process are both based on predictions.

[0895] As an example, the results generated by the first process and the results generated by the second process are both based on AI / ML.

[0896] As one example, the second node 1700 is a base station device.

[0897] As one embodiment, the second node 1700 is a user equipment.

[0898] As an example, the second node 1700 is a TRP.

[0899] As an example, the first transmitter 1701 includes at least one of the following in embodiment 4: the antenna 420, the transmitter 418, the transmission processor 417, the multi-antenna transmission processor 471, the controller / processor 475, and the memory 476.

[0900] Those skilled in the art will understand that all or part of the steps in the above methods can be implemented by a program instructing related hardware, and the program can be stored in a computer-readable storage medium, such as a read-only memory, hard disk, or optical disk. Optionally, all or part of the steps in the above embodiments can also be implemented using one or more integrated circuits. Correspondingly, each module unit in the above embodiments can be implemented in hardware or in the form of software functional modules. This application is not limited to any specific combination of software and hardware. The user equipment, terminal, and UE in this application include, but are not limited to, drones, communication modules on drones, remote-controlled aircraft, aircraft, small aircraft, mobile phones, tablets, laptops, vehicle-mounted communication equipment, vehicles, RSUs, wireless sensors, internet cards, IoT terminals, RFID (Radio Frequency Identification) terminals, NB-IoT (Narrow Band Internet of Things) terminals, MTC (Machine Type Communication) terminals, eMTC (enhanced MTC) terminals, data cards, internet cards, vehicle-mounted communication equipment, low-cost mobile phones, low-cost tablets, and other wireless communication devices. The base station or system equipment in this application includes, but is not limited to, macrocell base stations, microcell base stations, small cell base stations, home base stations, relay base stations, eNB (evolved Node B), gNB, TRP, GNSS (Global Navigation Satellite System), relay satellites, satellite base stations, airborne base stations, RSUs, unmanned aerial vehicles, and test equipment, such as transceivers or signaling testers that simulate some functions of a base station, and other wireless communication equipment.

[0901] Those skilled in the art will understand that the present invention can be practiced in other specified forms without departing from its core or essential characteristics. Therefore, the embodiments disclosed herein should in any way be considered descriptive rather than restrictive. The scope of the invention is defined by the appended claims rather than the foregoing description, and all modifications within their equivalent meaning and scope are considered to be included therein.

Claims

1. A method in a terminal for wireless communication with artificial intelligence, characterized by, Comprising: receiving a first information block and a second information block, the first information block and the second information block configuring a first process and a second process respectively; the first process and the second process occupying a first processing resource set and a second processing resource set respectively; processing a target process, the target process being one of the first process and the second process; wherein a remaining processing resource set of the terminal is equal to a total processing resource set included by the terminal removing a part that has been occupied; the remaining processing resource set of the terminal can include the first processing resource set or the second processing resource set, and the remaining processing resource set of the terminal cannot include the first processing resource set and the second processing resource set at the same time; whether the target process is the first process or the second process depends on a comparison of a priority corresponding to the first process and a priority corresponding to the second process; the comparison of the priority corresponding to the first process and the priority corresponding to the second process depends on types of the first process and the second process; the first process and the second process are both for reasoning.

2. The method of claim 1, wherein, the priority corresponding to the first process is higher than the priority corresponding to the second process, and the target process is the first process; the priority corresponding to the first process is lower than the priority corresponding to the second process, and the target process is the second process.

3. The method according to claim 1 or 2, characterized in that, The type of the process includes at least one of the following: - whether the process is used for coding and decoding; - a layer corresponding to the process; - a cell corresponding to the process.

4. The method according to any one of claims 1 to 3, characterized in that, The priority corresponding to the process used in the first process and the second process for a physical layer is higher than the priority corresponding to the process used in a layer other than the physical layer.

5. The method according to any one of claims 1 to 3, characterized in that, The priority corresponding to the process used in the first process and the second process for coding and decoding is higher than the priority corresponding to the process used for measurement.

6. The method of any one of claims 1 to 3, wherein, The priority corresponding to the process used in the first process and the second process for a serving cell is higher than the priority corresponding to the process used for a cell other than the serving cell.

7. The method according to any one of claims 1 to 6, characterized in that, The first processing resource set and the second processing resource set respectively only correspond to computing resources, and the remaining processing resource set of the terminal only includes remaining computing resources; the number of the remaining computing resources of the terminal is not less than the number of computing resources corresponding to the first processing resource set or the number of computing resources corresponding to the second processing resource set, and the number of the remaining computing resources of the terminal is less than the sum of the number of computing resources corresponding to the first processing resource set and the number of computing resources corresponding to the second processing resource set.

8. The method according to any one of claims 1 to 6, characterized in that, Any of the first processing resource set and the second processing resource set corresponds to computing resource and storage resource, the remaining processing resource set of the terminal includes remaining computing resource and remaining storage resource; the number of the remaining computing resource of the terminal is not less than the number of computing resource corresponding to the first processing resource set or the number of computing resource corresponding to the second processing resource set, the number of the remaining storage resource of the terminal is not less than the number of storage resource corresponding to the first processing resource set or the number of storage resource corresponding to the second processing resource set; and the number of the remaining computing resource of the terminal is less than the sum of the number of computing resource corresponding to the first processing resource set and the number of computing resource corresponding to the second processing resource set, or the number of the remaining storage resource of the terminal is less than the sum of the number of storage resource corresponding to the first processing resource set and the number of storage resource corresponding to the second processing resource set.

9. A terminal, comprising: one or more processors and a memory; the memory is coupled to the one or more processors, and the memory is configured to store computer program codes including computer instructions, and the one or more processors are configured to invoke the computer instructions to cause the terminal to perform the method according to any one of claims 1-8. 10.A method in a base station for wireless communication and artificial intelligence, the method comprising: including: sending a first information block and a second information block, the first information block and the second information block configuring a first process and a second process respectively; wherein the receiver of the first information block and the second information block is a terminal, the first process and the second process occupying a first processing resource set and a second processing resource set of the terminal respectively; the terminal processes a target process, the target process being one of the first process and the second process; the remaining processing resource set of the terminal is equal to the total processing resource set included in the terminal excluding the occupied part; the remaining processing resource set of the terminal can include the first processing resource set or the second processing resource set, and the remaining processing resource set of the terminal cannot include the first processing resource set and the second processing resource set at the same time; whether the target process is the first process or the second process depends on the comparison of the priority corresponding to the first process and the priority corresponding to the second process; the comparison of the priority corresponding to the first process and the priority corresponding to the second process depends on the type of the first process and the second process; the first process and the second process are both for reasoning.

11. The method of claim 10, wherein, the priority corresponding to the first process is higher than the priority corresponding to the second process, and the target process is the first process; the priority corresponding to the first process is lower than the priority corresponding to the second process, and the target process is the second process.

12. The method according to claim 10 or 11, characterized in that, The type of a process includes at least one of the following: whether the process is used for coding and decoding; - a layer corresponding to the process; - a cell corresponding to the process.

13. The method according to any one of claims 10 to 12, characterized in that, The priority corresponding to the process in the first process and the second process for a physical layer is higher than the priority corresponding to the process for a layer other than the physical layer.

14. The method of any one of claims 10-12, wherein, The priority corresponding to the process in the first process and the second process for coding is higher than the priority corresponding to the process for measurement.

15. The method of any one of claims 10-12, wherein, The priority corresponding to the process in the first process and the second process for a serving cell of the terminal is higher than the priority corresponding to the process for a cell other than the serving cell of the terminal.

16. The method according to any one of claims 10 to 15, characterized in that, The first processing resource set and the second processing resource set respectively only correspond to computing resources, and the remaining processing resource set of the terminal only includes remaining computing resources; the number of the remaining computing resources of the terminal is not less than the number of computing resources corresponding to the first processing resource set or the number of computing resources corresponding to the second processing resource set, and the number of the remaining computing resources of the terminal is less than the sum of the number of computing resources corresponding to the first processing resource set and the number of computing resources corresponding to the second processing resource set.

17. The method of any one of claims 10-15, wherein, Any one of the first processing resource set and the second processing resource set corresponds to computing resources and storage resources, and the remaining processing resource set of the terminal includes remaining computing resources and remaining storage resources; the number of the remaining computing resources of the terminal is not less than the number of computing resources corresponding to the first processing resource set or the number of computing resources corresponding to the second processing resource set, the number of the remaining storage resources of the terminal is not less than the number of storage resources corresponding to the first processing resource set or the number of storage resources corresponding to the second processing resource set; and the number of the remaining computing resources of the terminal is less than the sum of the number of computing resources corresponding to the first processing resource set and the number of computing resources corresponding to the second processing resource set, or the number of the remaining storage resources of the terminal is less than the sum of the number of storage resources corresponding to the first processing resource set and the number of storage resources corresponding to the second processing resource set.

18. A base station, comprising: one or more processors and a memory; the memory is coupled to the one or more processors, and the memory is configured to store computer program codes, the computer program codes comprising computer instructions, and the one or more processors are configured to invoke the computer instructions to enable the base station to perform the method according to any one of claims 10-17.

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