Communication method, terminal, network device, communication system and storage medium

Abstract

The invention relates to a communication method, a terminal, network equipment, a communication system and a storage medium. The method is executed by a terminal and comprises the following steps: sending first information to network equipment; wherein the first information comprises at least one of a first AI processing capability and a second AI processing capability, the first AI processing capability is different from the second AI processing capability, and the first AI processing capability and the second AI processing capability represent processing capabilities of different AI processing units. Through the embodiment of the invention, the accuracy of information reporting can be improved.

Description

Communication methods, terminals, network equipment, communication systems and storage media Technical Field

[0001] This disclosure relates to the field of communication technology, and in particular to communication methods, terminals, network devices, communication systems and storage media. Background Technology

[0002] With the rapid development of Artificial Intelligence (AI) technology, its applications are becoming increasingly widespread. AI models can be used to perform tasks such as image recognition, speech recognition, natural language processing, and replace traditional wireless communication algorithms. Network devices can perform AI tasks based on the AI ​​processing capabilities of the terminal.

[0003] Summary of the Invention

[0004] Improving the accuracy of AI processing capabilities reported by terminals is a problem that needs to be solved.

[0005] This disclosure provides embodiments of a communication method, a terminal, a network device, a communication system, and a storage medium.

[0006] According to a first aspect of the present disclosure, a communication method is proposed, executed by a terminal, the method comprising: sending first information to a network device; wherein the first information includes at least one of a first AI processing capability and a second AI processing capability, the first AI processing capability and the second AI processing capability being different, and the first AI processing capability and the second AI processing capability representing the processing capabilities of different AI processing units.

[0007] According to a second aspect of the present disclosure, a communication method is proposed, executed by a network device, the method comprising: receiving first information sent by a terminal; wherein the first information includes at least one of a first AI processing capability and a second AI processing capability, the first AI processing capability and the second AI processing capability being different, the first AI processing capability and the second AI processing capability representing the processing capabilities of different AI processing units.

[0008] According to a third aspect of the present disclosure, a terminal is provided, comprising: a transceiver module for sending first information to a network device; wherein the first information includes at least one of a first AI processing capability and a second AI processing capability, the first AI processing capability and the second AI processing capability being different, and the first AI processing capability and the second AI processing capability representing the processing capabilities of different AI processing units.

[0009] According to a fourth aspect of the present disclosure, a network device is provided, comprising: a transceiver module for receiving first information sent by a terminal; wherein the first information includes at least one of a first AI processing capability and a second AI processing capability, the first AI processing capability and the second AI processing capability being different, and the first AI processing capability and the second AI processing capability representing the processing capabilities of different AI processing units.

[0010] According to a fifth aspect of the present disclosure, a terminal is provided, comprising: one or more processors; wherein the terminal is configured to perform the communication method of the first aspect.

[0011] According to a sixth aspect of the present disclosure, a network device is provided, comprising: one or more processors; wherein the network device is configured to perform the communication method of the second aspect.

[0012] According to a seventh aspect of the present disclosure, a communication system is provided, including a terminal and a network device, wherein the terminal is configured to implement the communication method of the first aspect, and the network device is configured to implement the communication method of the second aspect.

[0013] According to an eighth aspect of the present disclosure, a storage medium is provided that stores instructions, characterized in that, when the instructions are executed on a communication device, the communication device performs the method of the first aspect or the second aspect.

[0014] According to a ninth aspect of the present disclosure, a computer program is provided that, when executed by a communication device, causes the communication device to perform the communication method of the first aspect or the second aspect.

[0015] In this embodiment of the present disclosure, the terminal sends first information to the network device, the first information including a first AI processing capability and / or a second AI processing capability; that is, when the terminal reports its AI processing capability to the network device, it reports the AI ​​processing capability corresponding to different AI processing units of the terminal, which can improve the accuracy of information reporting and thus improve the efficiency of AI-based processing. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this disclosure, the accompanying drawings required for the description of the embodiments are introduced below. The following drawings are only some embodiments of this disclosure and do not impose specific limitations on the protection scope of this disclosure.

[0017] Figure 1 is a schematic diagram of the architecture of a communication system according to an embodiment of the present disclosure.

[0018] Figure 2 is an interactive schematic diagram of a communication method according to an embodiment of the present disclosure.

[0019] Figure 3 is a flowchart illustrating a communication method according to an embodiment of the present disclosure.

[0020] Figure 4 is a flowchart illustrating a communication method according to an embodiment of the present disclosure.

[0021] Figure 5 is an interactive schematic diagram of a communication method according to an embodiment of the present disclosure.

[0022] Figure 6A is a schematic diagram of the structure of the terminal proposed in an embodiment of this disclosure.

[0023] Figure 6B is a schematic diagram of the structure of the network device proposed in an embodiment of this disclosure.

[0024] Figure 7A is a schematic diagram of the structure of the communication device proposed in an embodiment of this disclosure.

[0025] Figure 7B is a schematic diagram of the chip structure proposed in an embodiment of this disclosure. Detailed Implementation

[0026] This disclosure provides embodiments of a communication method, a terminal, a network device, a communication system, and a storage medium.

[0027] In a first aspect, embodiments of this disclosure propose a communication method executed by a terminal, the method comprising: sending first information to a network device; wherein the first information includes at least one of a first AI processing capability and a second AI processing capability, the first AI processing capability and the second AI processing capability being different, the first AI processing capability and the second AI processing capability representing the processing capabilities of different AI processing units.

[0028] In the above embodiments, when the terminal reports its AI processing capabilities to the network device, it reports the AI ​​processing capabilities corresponding to different AI processing units of the terminal, which can improve the accuracy of information reporting and thus improve the efficiency of AI-based processing.

[0029] In conjunction with some embodiments of the first aspect, in some embodiments, the first AI processing capability includes capability parameters corresponding to at least one capability type, and the second AI processing capability includes capability parameters corresponding to at least one capability type; wherein, the capability type includes at least one of the following: supported AI task types; supported AI processing speeds; supported AI use cases; supported ML use cases; supported minimum processing latency; supported AI model types; and supported AI model update methods.

[0030] In the above embodiments, the first AI processing capability and the second AI processing capability reported by the terminal include capability parameters corresponding to at least one of the above capability types, which can improve the accuracy of information reporting, facilitate network devices to allocate tasks according to the capability types supported by different AI processing units of the terminal, and improve AI processing efficiency.

[0031] In conjunction with some embodiments of the first aspect, in some embodiments, the first AI processing capability and the second AI processing capability include different types of capabilities.

[0032] In the above embodiments, the first AI processing capability and the second AI processing capability reported by the terminal include different capability types, which facilitates network devices to allocate tasks according to the capability types supported by different AI processing units of the terminal, thereby improving AI processing efficiency.

[0033] In conjunction with some embodiments of the first aspect, in some embodiments, the first AI processing capability includes a first capability parameter corresponding to a first capability type, and the second AI processing capability includes a second capability parameter corresponding to the first capability type, wherein the first capability parameter and the second capability parameter are different.

[0034] In the above embodiments, the first AI processing capability and the second AI processing capability reported by the terminal include the same capability type and support different capability parameters under the capability type. This can improve the accuracy of information reporting, facilitate network devices to allocate tasks according to the capability parameters supported by different AI processing units of the terminal, and improve AI processing efficiency.

[0035] In conjunction with some embodiments of the first aspect, in some embodiments, the first capability type includes supported AI task types, the first capability parameter includes supporting AI model inference tasks, and the second capability parameter includes supporting AI model training tasks and supporting AI model inference tasks.

[0036] In conjunction with some embodiments of the first aspect, in some embodiments, the first capability type includes supported AI processing speed, the first capability parameter includes a first AI processing speed, and the second capability parameter includes a second AI processing speed.

[0037] In conjunction with some embodiments of the first aspect, in some embodiments, the first capability type includes supported AI use cases, the first capability parameter includes supporting specific AI use cases, and the second capability parameter includes supporting all AI use cases.

[0038] In conjunction with some embodiments of the first aspect, in some embodiments, the first capability type includes a supported minimum processing latency, the first capability parameter includes a first minimum processing latency, and the second capability parameter includes a second minimum processing latency.

[0039] In some embodiments, in conjunction with the first aspect, the method further includes: the terminal receiving second information sent by the network device, the second information being used to instruct the terminal to report the first information.

[0040] In conjunction with some embodiments of the first aspect, in some embodiments, the different AI processing units include modems and general-purpose AI processors.

[0041] Secondly, embodiments of this disclosure propose a communication method executed by a network device, the method comprising: receiving first information sent by a terminal; wherein the first information includes at least one of a first AI processing capability and a second AI processing capability, the first AI processing capability and the second AI processing capability being different, the first AI processing capability and the second AI processing capability representing the processing capabilities of different AI processing units.

[0042] In conjunction with some embodiments of the second aspect, in some embodiments, the first AI processing capability includes capability parameters corresponding to at least one capability type, and the second AI processing capability includes capability parameters corresponding to at least one capability type; wherein, the capability type includes at least one of the following: supported AI task types; supported AI processing speeds; supported AI use cases; supported ML use cases; supported minimum processing latency; supported AI model types; and supported AI model update methods.

[0043] In conjunction with some embodiments of the second aspect, in some embodiments, the first AI processing capability and the second AI processing capability include different types of capabilities.

[0044] In conjunction with some embodiments of the second aspect, in some embodiments, the first AI processing capability includes a first capability parameter corresponding to a first capability type, and the second AI processing capability includes a second capability parameter corresponding to the first capability type, wherein the first capability parameter and the second capability parameter are different.

[0045] In conjunction with some embodiments of the second aspect, in some embodiments, the first capability type includes supported AI task types, the first capability parameter includes supporting AI model inference tasks, and the second capability parameter includes supporting AI model training tasks and supporting AI model inference tasks.

[0046] In conjunction with some embodiments of the second aspect, in some embodiments, the first capability type includes supported AI processing speed, the first capability parameter includes a first AI processing speed, and the second capability parameter includes a second AI processing speed.

[0047] In conjunction with some embodiments of the second aspect, in some embodiments, the first capability type includes supported AI use cases, the first capability parameter includes supporting specific AI use cases, and the second capability parameter includes supporting all AI use cases.

[0048] In conjunction with some embodiments of the second aspect, in some embodiments, the first capability type includes a supported minimum processing latency, the first capability parameter includes a first minimum processing latency, and the second capability parameter includes a second minimum processing latency.

[0049] In some embodiments, in conjunction with the second aspect, the method further includes: the network device sending second information to the terminal, the second information being used to instruct the terminal to report the first information.

[0050] In conjunction with some embodiments of the second aspect, in some embodiments, the different AI processing units include modems and general-purpose AI processors.

[0051] Thirdly, this disclosure provides a terminal, including: a transceiver module for sending first information to a network device; wherein the first information includes at least one of a first AI processing capability and a second AI processing capability, the first AI processing capability and the second AI processing capability are different, and the first AI processing capability and the second AI processing capability represent the processing capabilities of different AI processing units.

[0052] Fourthly, this disclosure provides a network device, including: a transceiver module for receiving first information sent by a terminal; wherein the first information includes at least one of a first AI processing capability and a second AI processing capability, the first AI processing capability and the second AI processing capability being different, and the first AI processing capability and the second AI processing capability representing the processing capabilities of different AI processing units.

[0053] Fifthly, embodiments of this disclosure provide a terminal, comprising: one or more processors; wherein the terminal is configured to execute the communication method of the first aspect.

[0054] In a sixth aspect, embodiments of this disclosure provide a network device comprising: one or more processors; wherein the network device is configured to perform the communication method of the second aspect.

[0055] In a seventh aspect, embodiments of this disclosure provide a communication system including a terminal and a network device, wherein the terminal is configured to implement the communication method of the first aspect, and the network device is configured to implement the communication method of the second aspect.

[0056] Eighthly, embodiments of this disclosure provide a storage medium storing instructions, characterized in that, when the instructions are executed on a communication device, the communication device performs the method of the first aspect or the second aspect.

[0057] Ninthly, embodiments of this disclosure provide a program product that, when executed by a communication device, causes the communication device to perform the method as described in the optional implementations of the first or second aspect.

[0058] In a tenth aspect, embodiments of this disclosure provide a computer program that, when executed by a communication device, causes the communication device to perform any of the aforementioned communication methods.

[0059] Eleventhly, embodiments of this disclosure provide a chip or chip system. The chip or chip system includes processing circuitry configured to perform the methods described in optional implementations of the first or second aspect.

[0060] It is understood that the aforementioned terminals, network devices, communication systems, storage media, program products, computer programs, chips, or chip systems are all used to execute the methods proposed in the embodiments of this disclosure. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects in the corresponding methods, and will not be repeated here.

[0061] This disclosure provides communication methods, terminals, network devices, communication systems, and storage media. In some embodiments, the terms "communication method" and "information sending method," "information receiving method," etc., can be used interchangeably.

[0062] This disclosure is not exhaustive, but merely illustrative of some embodiments, and is not intended to limit the scope of protection of this disclosure. Unless otherwise specified, each step in a particular embodiment can be implemented as an independent embodiment, and the steps can be arbitrarily combined. For example, a solution after removing some steps in a particular embodiment can also be implemented as an independent embodiment, and the order of the steps in a particular embodiment can be arbitrarily interchanged. Furthermore, the optional implementation methods in a particular embodiment can be arbitrarily combined; moreover, the embodiments can be arbitrarily combined, for example, some or all steps of different embodiments can be arbitrarily combined, and a particular embodiment can be arbitrarily combined with the optional implementation methods of other embodiments.

[0063] In each of the disclosed embodiments, unless otherwise specified or in case of logical conflict, the terminology and / or descriptions of the embodiments are consistent and can be referenced by each other. Technical features in different embodiments can be combined to form new embodiments based on their inherent logical relationships.

[0064] The terminology used in the embodiments of this disclosure is for the purpose of describing particular embodiments only and is not intended to limit the scope of this disclosure.

[0065] In this disclosure, unless otherwise stated, elements expressed in the singular form, such as "a," "an," "the," "the," "the," "the," "the," "this," etc., can mean "one and only one," or "one or more," "at least one," etc. For example, when using articles such as "a," "an," "the," etc. in translation, the noun following the article can be understood as either a singular or a plural expression.

[0066] In the embodiments of this disclosure, "multiple" refers to two or more.

[0067] In some embodiments, the terms “at least one of”, “one or more”, “a plurality of”, “multiple”, etc., may be used interchangeably.

[0068] In some embodiments, the notation "at least one of A and B", "A and / or B", "A in one case, B in another", "in response to one case A, in response to another case B", etc., may include the following technical solutions depending on the situation: in some embodiments, A (execute A regardless of B); in some embodiments, B (execute B regardless of A); in some embodiments, execution is selected from A and B (A and B are selectively executed); in some embodiments, A and B (both A and B are executed). The same applies when there are more branches such as A, B, C, etc.

[0069] In some embodiments, the notation "A or B" may include the following technical solutions, depending on the situation: in some embodiments, A (execution of A regardless of B); in some embodiments, B (execution of B regardless of A); in some embodiments, execution is selected from A and B (A and B are selectively executed). The same applies when there are more branches such as A, B, C, etc.

[0070] The prefixes "first," "second," etc., used in the embodiments of this disclosure are merely for distinguishing different descriptive objects and do not impose restrictions on the position, order, priority, quantity, or content of the descriptive objects. The description of the descriptive objects is found in the claims or the context of the embodiments, and the use of prefixes should not constitute unnecessary restrictions. For example, if the descriptive object is a "field," the ordinal numbers preceding "field" in "first field" and "second field" do not restrict the position or order of the "fields." "First" and "second" do not restrict whether the "fields" they modify are in the same message, nor do they restrict the order of "first field" and "second field." Similarly, if the descriptive object is a "level," the ordinal numbers preceding "level" in "first level" and "second level" do not restrict the priority between "levels." Furthermore, the number of descriptive objects is not limited by ordinal numbers and can be one or more. For example, in "first device," the number of "devices" can be one or more. Furthermore, the objects modified by different prefixes can be the same or different. For example, if the object being described is "device", then "first device" and "second device" can be the same device or different devices, and their types can be the same or different. Similarly, if the object being described is "information", then "first information" and "second information" can be the same information or different information, and their content can be the same or different.

[0071] In some embodiments, “including A,” “containing A,” “for indicating A,” and “carrying A” can be interpreted as directly carrying A or indirectly indicating A.

[0072] In some embodiments, the terms “in response to…”, “in response to determining…”, “in the case of…”, “when…”, “if…”, “if…”, etc., can be used interchangeably.

[0073] In some embodiments, the terms “greater than,” “greater than or equal to,” “not less than,” “more than,” “more than or equal to,” “not less than,” “higher than,” “higher than or equal to,” “not lower than,” and “above” can be used interchangeably, as can the terms “less than,” “less than or equal to,” “not greater than,” “less than,” “less than or equal to,” “not more than,” “lower than,” “lower than or equal to,” “not higher than,” and “below”.

[0074] In some embodiments, devices, etc., can be interpreted as physical or virtual, and their names are not limited to the names recorded in the embodiments. Terms such as “device”, “equipment”, “circuit”, “network element”, “node”, “function”, “unit”, “section”, “system”, “network”, “chip”, “chip system”, “entity”, and “subject” can be used interchangeably.

[0075] In some embodiments, "network" can be interpreted as devices included in a network (e.g., access network devices, core network devices, etc.).

[0076] In some embodiments, the terms "access network device (AN device)," "radio access network device (RAN device)," "base station (BS)," "radio base station," "fixed station," "node," "access point," "transmission point (TP)," "reception point (RP)," "transmission / reception point (TRP)," "panel," "antenna panel," "antenna array," "cell," "macro cell," "small cell," "femto cell," "pico cell," "sector," "cell group," "serving cell," "carrier," "component carrier," and "bandwidth part (BWP)" can be used interchangeably.

[0077] In some embodiments, the terms "terminal", "terminal device", "user equipment (UE)", "user terminal", "mobile station (MS)", "mobile terminal (MT)", "subscriber station", "mobile unit", "subscriber unit", "wireless unit", "remote unit", "mobile device", "wireless device", "wireless communication device", "remote device", "mobile subscriber station", "access terminal", "mobile terminal", "wireless terminal", "remote terminal", "handset", "user agent", "mobile client", and "client" can be used interchangeably.

[0078] In some embodiments, access network devices, core network devices, or network devices can be replaced by terminals. For example, embodiments of this disclosure can also be applied to structures where communication between access network devices, core network devices, or network devices and terminals is replaced by communication between multiple terminals (e.g., device-to-device (D2D), vehicle-to-everything (V2X), etc.). In this case, the structure can also be configured such that the terminal has all or part of the functions of the access network device. Furthermore, terms such as "uplink" and "downlink" can be replaced with terms corresponding to communication between terminals (e.g., "sidelink"). For example, uplink channel, downlink channel, etc., can be replaced with sidelink channel, and uplink link, downlink, etc., can be replaced with sidelink link.

[0079] In some embodiments, the terminal may be replaced by an access network device, a core network device, or a network device. In this case, the access network device, core network device, or network device may also be configured to have all or some of the functions of the terminal.

[0080] In some embodiments, the acquisition of data, information, etc., may comply with the laws and regulations of the country where the location is situated.

[0081] In some embodiments, data, information, etc., may be obtained with the user's consent.

[0082] Furthermore, each element, each row, or each column in the table of this disclosure can be implemented as an independent embodiment, and any combination of any element, any row, or any column can also be implemented as an independent embodiment.

[0083] Figure 1 is a schematic diagram of the architecture of a communication system according to an embodiment of the present disclosure.

[0084] As shown in Figure 1, the communication system 100 includes a terminal 101 and a network device 102.

[0085] In some embodiments, terminal 101 may be user equipment (UE), and terminal 101 includes, for example, at least one of the following: mobile phone, wearable device, Internet of Things device, car with communication function, smart car, tablet computer, computer with wireless transceiver function, virtual reality (VR) terminal device, augmented reality (AR) terminal device, wireless terminal device in industrial control, wireless terminal device in self-driving, wireless terminal device in remote medical surgery, wireless terminal device in smart grid, wireless terminal device in transportation safety, wireless terminal device in smart city, and wireless terminal device in smart home, but is not limited thereto.

[0086] In some embodiments, network device 102 may be a functional network element in a core network device. The core network device may be a single device, including a first network element, a second network element, etc., or it may be multiple devices or a group of devices, each including all or part of the first network element, the second network element, etc. Network elements may be virtual or physical. The core network may include, for example, at least one of an Evolved Packet Core (EPC), a 5G Core Network (5GCN), and a Next Generation Core (NGC).

[0087] In some embodiments, network device 102 may include at least one of access network device and core network device.

[0088] In some embodiments, the access network device is, for example, a node or device that connects a terminal to a wireless network. The access network device may include, but is not limited to, at least one of the following in a 5G communication system: evolved Node B (eNB), next-generation eNB (ng-eNB), next-generation Node B (gNB), node B (NB), home node B (HNB), home evolved node B (HeNB), radio backhaul device, radio network controller (RNC), base station controller (BSC), base transceiver station (BTS), base band unit (BBU), mobile switching center, base station in a 6G communication system, open RAN, cloud RAN, base station in other communication systems, and access node in a Wi-Fi system.

[0089] In some embodiments, the technical solutions of this disclosure can be applied to the Open RAN architecture. In this case, the interfaces between or within access network devices involved in the embodiments of this disclosure can be transformed into internal interfaces of Open RAN. The processes and information interactions between these internal interfaces can be implemented by software or programs.

[0090] In some embodiments, the access network device may be composed of a central unit (CU) and a distributed unit (DU). The CU may also be called a control unit. The CU-DU structure can separate the protocol layer of the access network device. Some of the protocol layer functions are centrally controlled by the CU, while the remaining part or all of the protocol layer functions are distributed in the DU and centrally controlled by the CU. However, this is not the only possibility.

[0091] In some embodiments, a core network device may be a single device comprising one or more network elements, or it may be multiple devices or a group of devices, each comprising all or part of the aforementioned one or more network elements. Network elements may be virtual or physical. The core network may include, for example, at least one of an Evolved Packet Core (EPC), a 5G Core Network (5GCN), or a Next Generation Core (NGC).

[0092] It is understood that the communication system described in this disclosure is for the purpose of more clearly illustrating the technical solutions of this disclosure, and does not constitute a limitation on the technical solutions proposed in this disclosure. As those skilled in the art will know, with the evolution of system architecture and the emergence of new business scenarios, the technical solutions proposed in this disclosure are also applicable to similar technical problems.

[0093] The following embodiments of this disclosure can be applied to the communication system 100 shown in FIG1, or to some of the main bodies, but are not limited thereto. The main bodies shown in FIG1 are illustrative. The communication system may include all or some of the main bodies in FIG1, or may include other main bodies outside of FIG1. ​​The number and form of each main body are arbitrary. Each main body may be physical or virtual. The connection relationship between the main bodies is illustrative. The main bodies may not be connected or may be connected. The connection can be in any way, it can be a direct connection or an indirect connection, it can be a wired connection or a wireless connection.

[0094] The embodiments disclosed herein can be applied to Long Term Evolution (LTE), LTE-Advanced (LTE-A), LTE-Beyond (LTE-B), SUPER 3G, IMT-Advanced, 4th generation mobile communication system (4G), 5th generation mobile communication system (5G), 5G new radio (NR), 6th generation mobile communication system (6G), Future Radio Access (FRA), New-Radio Access Technology (RAT), New Radio (NR), New radio access (NX), Future generation radio access (FX), Global System for Mobile communications (GSM), CDMA2000, Ultra Mobile Broadband (UMB), IEEE 802.11 (Wi-Fi), IEEE 802.16 (WiMAX), and IEEE 802.20, Ultra-Wideband (UWB), Bluetooth (a registered trademark), Public Land Mobile Network (PLMN) networks, Device-to-Device (D2D) systems, Machine-to-Machine (M2M) systems, Internet of Things (IoT) systems, Vehicle-to-Everything (V2X) systems, systems utilizing other communication methods, and next-generation systems built upon them, etc. Furthermore, multiple systems can be combined (e.g., a combination of LTE or LTE-A with 5G).

[0095] In some embodiments, the artificial intelligence (AI) applications supported by the mobile phone include AI-assisted communication, and the AI ​​processor module for this purpose is integrated into the mobile phone modem. Besides this, there are numerous other AI applications, such as image enhancement and AI assistants, for which general-purpose AI processors are typically used. With the increasing prevalence of AI, the AI ​​hardware and software capabilities of general-purpose hardware on the terminal side will be greatly enhanced, potentially far exceeding the AI ​​hardware and software capabilities of dedicated modems. Therefore, AI resources within the modem and AI resources on general-purpose AI chips can be coordinated and shared to provide services for AI use cases.

[0096] Since the AI ​​processor inside the modem is independent of the general-purpose AI processor, the processing power and interaction latency provided by the two may be different. Therefore, the terminal should distinguish between them when reporting AI processing capabilities.

[0097] In view of this, the present disclosure provides a communication method in which a terminal sends first information to a network device. The terminal includes a first AI processing unit and a second AI processing unit. The first information includes the first AI processing capability of the first AI processing unit and / or the second AI processing capability of the second AI processing unit. That is, when the terminal reports its AI processing capability to the network device, it reports the AI ​​processing capabilities corresponding to different AI processing units of the terminal, which can improve the accuracy of information reporting and thus improve the efficiency of AI-based processing.

[0098] Figure 2 is an interactive schematic diagram of a communication method according to an embodiment of the present disclosure. As shown in Figure 2, the embodiments of the present disclosure relate to a communication method, which includes:

[0099] Step S2101: The network device sends the second information to the terminal.

[0100] In some embodiments, the terminal receives second information sent by the network device.

[0101] In some embodiments, the terminal may include multiple AI processing units, which may have different AI processing capabilities or the same AI processing capability. For example, the terminal may include a first AI processing unit and a second AI processing unit, where the first AI processing unit has a first AI processing capability and the second AI processing unit has an AI processing capability; the first AI processing capability and the second AI processing capability may be different, or the first AI processing capability and the second AI processing capability may be the same.

[0102] In some embodiments, the second information is used to instruct the terminal to report the first information.

[0103] In some embodiments, the first information includes at least one of a first AI processing capability and a second AI processing capability. The first AI processing capability and the second AI processing capability may be the same or different. The first AI processing capability and the second AI processing capability may represent the processing capability of the same AI processing unit, or they may represent the processing capability of different AI processing units.

[0104] In some embodiments, the first information includes at least one of the first AI processing capability of the first AI processing unit and the second AI processing capability of the second AI processing unit. For example, the first information may only include the first AI processing capability of the first AI processing unit, or the first information may only include the second AI processing capability of the second AI processing unit, or the first information may include both the first AI processing capability of the first AI processing unit and the second AI processing capability of the second AI processing unit.

[0105] In some embodiments, the second information may directly indicate the AI ​​processing unit corresponding to the AI ​​processing capability that the terminal needs to report. The second information may indicate at least one of a first AI processing unit and a second AI processing unit. For example, the second information indicates the first AI processing unit, and the terminal reports the first AI processing capability of the first AI processing unit. As another example, the second information indicates both a first AI processing unit and a second AI processing unit, and the terminal reports the first AI processing capability of the first AI processing unit and the second AI processing capability of the second AI processing unit.

[0106] In other embodiments, the network device can determine the AI ​​processing capabilities that the terminal needs to report based on the AI ​​use case. For example, when the network device wants to enable AI-based communication enhancement, it can trigger the terminal to report the first AI processing capability of the first AI processing unit. As another example, when the network device wants the terminal to open up computing power to assist in performing corresponding computing tasks, it can trigger the terminal to report the second AI processing capability of the second AI processing unit.

[0107] In step S2102, the terminal sends the first information to the network device.

[0108] In some embodiments, the network device receives first information sent by the terminal.

[0109] In some embodiments, the first information includes at least one of a first AI processing capability and a second AI processing capability. The first AI processing capability and the second AI processing capability may be the same or different.

[0110] In some embodiments, the first AI processing capability and the second AI processing capability can represent the processing capability of the same AI processing unit, or the first AI processing capability and the second AI processing capability can represent the processing capability of different AI processing units.

[0111] For example, the terminal includes a first AI processing unit and a second AI processing unit, and the first information includes at least one of the first AI processing capability of the first AI processing unit and the second AI processing capability of the second AI processing unit, wherein the first AI processing capability and the second AI processing capability are different.

[0112] In some embodiments, different AI processing units may include a modem and a general-purpose AI processor. For example, the first AI processing unit may be a modem, and the second AI processing unit may be a general-purpose AI processor.

[0113] In some embodiments, the terminal may proactively send first information to the network device, or the terminal may send first information to the network device based on second information sent by the network device.

[0114] In some embodiments, the first AI processing capability includes capability parameters corresponding to at least one capability type, and the second AI processing capability includes capability parameters corresponding to at least one capability type.

[0115] The capability type includes at least one of the following: supported AI task types; supported AI processing speeds; supported AI use cases; supported machine learning (ML) use cases; supported minimum processing latency; supported AI model types; and supported AI model update methods.

[0116] For example, AI task types can include AI model training tasks, AI model inference tasks, etc.

[0117] For example, AI use cases could include AI-based beam management, AI-based positioning, and so on.

[0118] For example, ML use cases can include ML-based beam management, ML-based positioning, etc.

[0119] For example, AI models include Convolutional Neural Networks (CNN) models, Transformer models, and so on.

[0120] For example, AI model update methods include updating the model structure, updating the model parameters, and simultaneously supporting updates to both the model structure and model parameters.

[0121] In some embodiments, the first AI processing capability and the second AI processing capability include different types of capabilities.

[0122] In some embodiments, the first AI processing capability includes capability parameters corresponding to a first capability type, and the second AI processing capability includes capability parameters corresponding to a second capability type. The first capability type and the second capability type can both be at least one of the aforementioned capability types, and the first capability type and the second capability type are different.

[0123] For example, the first AI processing capability includes the AI ​​use cases supported by the first AI processing unit, and the second AI processing capability includes the AI ​​task types supported by the second AI processing unit.

[0124] For example, the first AI processing capability includes the AI ​​use cases supported by the first AI processing unit; the second AI processing capability includes the processing speed, processing latency, etc. supported by the second AI processing unit.

[0125] In some embodiments, the network device may allocate AI tasks based on the first AI processing capability and the second AI processing capability reported by the terminal.

[0126] For example, the first AI processing capability includes a first AI processing unit supporting AI-based beam management, and the second AI processing capability includes a second AI processing unit supporting AI model training tasks; when performing AI-based beam management tasks, the network device can assign the task to the first AI processing unit of the terminal for execution; when performing tasks supporting AI model training, the network device can assign the task to the second AI processing unit of the terminal for execution.

[0127] In the above embodiments, the first AI processing capability and the second AI processing capability reported by the terminal include different capability types, which facilitates network devices to allocate tasks according to the capability types supported by different AI processing units of the terminal, thereby improving AI processing efficiency.

[0128] In some embodiments, the first AI processing capability and the second AI processing capability include the same capability type. For example, the same capability type in the first AI processing capability and the second AI processing capability is referred to as the first capability type.

[0129] In some embodiments, the first AI processing capability and the second AI processing capability include the same capability type, and under this capability type, the first AI processing capability and the second AI processing capability include the same capability parameters.

[0130] In other embodiments, the first AI processing capability includes a first capability parameter corresponding to a first capability type, and the second AI processing capability includes a second capability parameter corresponding to a first capability type, wherein the first capability parameter and the second capability parameter are different.

[0131] In other embodiments, the first AI processing capability and the second AI processing capability include the same capability type, under which the first AI processing capability and the second AI processing capability include different capability parameters.

[0132] In one example, the first capability type includes supported AI task types, the first capability parameter includes supporting AI model inference tasks, and the second capability parameter includes supporting AI model training tasks and supporting AI model inference tasks.

[0133] For example, if the first AI processing unit and the second AI processing unit support different types of AI tasks, with the first AI processing unit only supporting AI model inference tasks and the second AI processing unit supporting both AI model training tasks and AI model inference tasks, then in the first information reported by the terminal, the first AI processing capability includes supporting AI model inference tasks, and the second AI processing capability includes supporting both AI model training tasks and AI model inference tasks.

[0134] For example, the network device allocates AI tasks based on the types of AI tasks supported by the first AI processing unit and the second AI processing unit. When performing an AI model inference task, the network device instructs the first AI processing unit and / or the second AI processing unit to execute it; when performing an AI model training task, the network device instructs the second AI processing unit to execute it.

[0135] In one example, the first capability type includes the supported AI processing speed, the first capability parameter includes the first AI processing speed, and the second capability parameter includes the second AI processing speed.

[0136] For example, the first AI processing unit and the second AI processing unit support different AI processing speeds. The first AI processing unit supports an AI processing speed of X floating point operations per second (FLOPS), while the second processing unit supports an AI processing speed of Y FLOPS, where X and Y are different.

[0137] For example, network devices can allocate AI tasks based on the AI ​​processing speeds supported by the first AI processing unit and the second AI processing unit.

[0138] In one example, the first capability type includes supported AI use cases, the first capability parameter includes supporting specific AI use cases, and the second capability parameter includes supporting all AI use cases.

[0139] For example, the first AI processing unit and the second AI processing unit support different AI use cases. The first AI processing unit only supports specific AI use cases, such as AI-based beam management or AI-based positioning, while the second processing unit supports all AI use cases.

[0140] For example, the network device assigns AI tasks based on the AI ​​use cases supported by the first AI processing unit and the second AI processing unit. When performing AI-based beam management or supporting AI-based positioning, the network device instructs the first AI processing unit and / or the second AI processing unit to execute; when performing other AI use cases, the network device instructs the second AI processing unit to execute.

[0141] In one example, the first capability type includes the supported minimum processing latency, the first capability parameter includes a first minimum processing latency, and the second capability parameter includes a second minimum processing latency.

[0142] For example, the minimum processing latency supported by the first AI processing unit and the second AI processing unit are different. The minimum processing latency supported by the first AI processing unit is at least X ms, and the minimum processing latency supported by the second processing unit is at least Y ms, where X and Y are different.

[0143] For example, network devices can allocate AI tasks based on the minimum processing latency supported by the first AI processing unit and the second AI processing unit.

[0144] In one example, the first capability type includes the type of AI model supported, the first capability parameter includes support for CNN models, and the second capability parameter includes support for both CNN models and transformer models.

[0145] For example, network devices can assign AI tasks based on the types of AI models supported by the first AI processing unit and the second AI processing unit.

[0146] In the above embodiments, the first AI processing capability and the second AI processing capability reported by the terminal include the same capability type and support different capability parameters under the capability type. This can improve the accuracy of information reporting, facilitate network devices to allocate tasks according to the capability parameters supported by different AI processing units of the terminal, and improve AI processing efficiency.

[0147] The communication method involved in the embodiments of this disclosure may include at least one of steps S2101 to S2102. For example, step S2101 may be implemented as a separate embodiment, and step S2102 may be implemented as a separate embodiment, but are not limited thereto.

[0148] In some embodiments, steps S2101 and S2102 may be performed in an alternate order or simultaneously.

[0149] In some embodiments, step S2101 is optional, and one or more of these steps may be omitted or substituted in different embodiments.

[0150] In some embodiments, step S2102 is optional, and one or more of these steps may be omitted or substituted in different embodiments.

[0151] In some embodiments, other optional implementations may be described before or after the specification corresponding to FIG2.

[0152] In some embodiments, the names of information, etc., are not limited to the names described in the embodiments. Terms such as "information", "message", "signal", "signaling", "report", "configuration", "indication", "instruction", "command", "channel", "parameter", "domain", "field", "symbol", "symbol", "codebook", "codeword", "codepoint", "bit", "data", "program", and "chip" can be used interchangeably.

[0153] In some embodiments, terms such as “moment,” “point in time,” “time,” and “time location” can be used interchangeably, as can terms such as “duration,” “segment,” “time window,” “window,” and “time.”

[0154] In some embodiments, “get,” “obtain,” “receive,” “transmit,” “bidirectional transmission,” and “send and / or receive” can be used interchangeably and can be interpreted as receiving from other entities, obtaining from protocols, obtaining from higher layers, obtaining through self-processing, or autonomous implementation, among other meanings.

[0155] In some embodiments, terms such as “send,” “transmit,” “report,” “distribute,” “transfer,” “bidirectional transmission,” “send and / or receive” can be used interchangeably.

[0156] In some embodiments, terms such as "certain," "preset," "default," "set," "indicated," "a certain," "any," and "first" can be used interchangeably. "Certain A," "preset A," "default A," "set A," "indicated A," "a certain A," "any A," and "first A" can be interpreted as A pre-defined in a protocol or the like, or as A obtained through setting, configuration, or instruction, or as specific A, a certain A, any A, or first A, but are not limited thereto.

[0157] In some embodiments, the determination or judgment can be made by a value represented by 1 bit (0 or 1), or by a true or false value (Boolean value (bool)) represented by true or false, or by a numerical comparison (e.g., a comparison with a predetermined value), but is not limited thereto.

[0158] In some embodiments, "not expecting to receive" can be interpreted as not receiving on time domain resources and / or frequency domain resources, or as not performing subsequent processing on the data after receiving it; "not expecting to send" can be interpreted as not sending, or as sending but not expecting the receiver to respond to the sent content.

[0159] Figure 3 is a flowchart illustrating a communication method according to an embodiment of the present disclosure. As shown in Figure 3, the embodiments of the present disclosure relate to a communication method executed by a terminal, the method including:

[0160] Step S3101: Obtain the second information.

[0161] The optional implementation of step S3101 can be found in the optional implementation of step S2101 in Figure 2 and other related parts in the embodiments involved in Figure 2, which will not be repeated here.

[0162] In some embodiments, the terminal receives second information sent by a network device, but is not limited thereto; it may also receive second information sent by other entities.

[0163] In some embodiments, step S3101 is omitted, and the terminal does not need to receive the second information sent by the network device.

[0164] Step S3102: Send the first message.

[0165] The optional implementation of step S3102 can be found in the optional implementation of step S2102 in Figure 2 and other related parts in the embodiments involved in Figure 2, which will not be repeated here.

[0166] In some embodiments, the terminal sends first information to a network device, but is not limited thereto; it may also send first information to other entities.

[0167] The communication method involved in the embodiments of this disclosure may include at least one of steps S3101 to S3102. For example, step S3101 may be implemented as a separate embodiment, and step S3102 may be implemented as a separate embodiment, but are not limited thereto.

[0168] In some embodiments, step S3101 is optional, and one or more of these steps may be omitted or substituted in different embodiments.

[0169] In some embodiments, step S3102 is optional, and one or more of these steps may be omitted or substituted in different embodiments.

[0170] Figure 4 is a flowchart illustrating a communication method according to an embodiment of the present disclosure. As shown in Figure 4, the embodiments of the present disclosure relate to a communication method executed by a network device, the method including:

[0171] Step S4101: Send the second message.

[0172] The optional implementation of step S4101 can be found in the optional implementation of step S2101 in Figure 2 and other related parts in the embodiments involved in Figure 2, which will not be repeated here.

[0173] In some embodiments, the network device sends second information to the terminal, but is not limited thereto; it may also send second information to other entities.

[0174] In some embodiments, step S4101 is omitted, and the network device does not need to send the second information to the terminal.

[0175] Step S4102: Obtain the first information.

[0176] The optional implementation of step S4102 can be found in the optional implementation of step S2102 in Figure 2 and other related parts in the embodiments involved in Figure 2, which will not be repeated here.

[0177] In some embodiments, the network device receives first information sent by the terminal, but is not limited thereto; it may also receive first information sent by other entities.

[0178] The communication method involved in the embodiments of this disclosure may include at least one of steps S4101 to S4102. For example, step S4101 may be implemented as a separate embodiment, and step S4102 may be implemented as a separate embodiment, but are not limited thereto.

[0179] In some embodiments, step S4101 is optional, and one or more of these steps may be omitted or substituted in different embodiments.

[0180] In some embodiments, step S4102 is optional, and one or more of these steps may be omitted or substituted in different embodiments.

[0181] Figure 5 is an interactive schematic diagram of a communication method according to an embodiment of the present disclosure. As shown in Figure 5, the embodiments of the present disclosure relate to a communication method, which includes:

[0182] Step S5101: The terminal sends the first information to the network device.

[0183] The optional implementation of step S5101 can be found in the optional implementation of step S2102 in Figure 2 and other related parts in the embodiments involved in Figure 2, which will not be repeated here.

[0184] In some embodiments, the above methods may include the methods of the embodiments described above on the communication system side, terminal side, network device side, etc., which will not be repeated here.

[0185] This disclosure provides a communication method in which, when a terminal reports its AI processing capabilities on the terminal side, it separately reports the AI ​​processing capabilities on the modem and the processing capabilities of the general-purpose AI processor.

[0186] In some embodiments, the terminal sends a first message to the network, the first message being used to report a first AI capability and / or a second AI capability on the terminal side. The first AI capability and the second AI capability are used to characterize the processing capabilities of the first AI processing unit (e.g., an AI processor in a modem) and the second AI processing unit (e.g., a general-purpose processor) on the terminal side for AI tasks. The first AI capability corresponding to the first AI processing unit and the second AI capability corresponding to the second AI processing unit differ in at least one parameter.

[0187] In some embodiments, the AI ​​capability is used to characterize one of the following:

[0188] Supported AI task types, such as model inference and model training;

[0189] Supported AI processing speed;

[0190] Supported AI / ML use cases, such as AI / ML-based beam management and AI / ML-based localization;

[0191] The minimum processing latency supported;

[0192] The types of AI models supported, such as Convolutional Neural Networks (CNN) and Transformers;

[0193] Supported methods for updating AI models, such as supporting updates to the model structure and model parameters, or supporting only updates to the model structure.

[0194] In some embodiments, the types of AI parameters included in the first AI capability and the second AI capability are different. For example, the first AI capability only indicates the supported AI / ML use cases, while the second AI capability indicates the processing speed, processing latency, supported AI / ML task types, etc., supported by the second processing unit.

[0195] In some embodiments, the different parameters of the first AI capability and the second AI capability include different indications for parameters of the same type, including at least one of the following parameters:

[0196] The types of AI tasks that can be processed are different. For example, the first AI capability only supports AI model inference tasks, while the second AI capability can support both AI model training tasks and AI model inference tasks.

[0197] The processing speed of AI tasks varies. For example, the processing speed of the first AI capability is X floating point operations per second (FLOPS), while the processing speed of the second AI capability is Y FLOPS.

[0198] The AI ​​use cases they support are different. For example, the first AI capability only supports specific AI use cases, such as AI-based beam management or AI-based positioning, while the second AI capability can support all AI use cases.

[0199] The supported processing latency varies; for example, the minimum processing latency for the first AI capability is at least X ms, and the minimum processing latency for the second AI capability is at least Y ms.

[0200] The types of AI models that can be processed are different. For example, the first AI capability only supports CNN model structures, while the second AI capability can support both CNN models and transformer model structures.

[0201] In some embodiments, the terminal may report a first AI capability or a second AI capability or both based on instructions from the network.

[0202] For example, when the network side wants to enable AI-based communication enhancement, the network can trigger the terminal to report the first AI capability.

[0203] For example, when the network wants the terminal to open up its computing power to assist in performing the corresponding computing tasks, the network can trigger the terminal to report the second AI capability.

[0204] In some embodiments, the network device may indicate which processor's AI capabilities to report, for example, instructing the terminal to report the AI ​​capabilities of the processor on the modem or the AI ​​capabilities of a general-purpose AI processor.

[0205] In some embodiments, the network device can allocate AI tasks based on the AI ​​capabilities reported by the terminal. For example, it can determine whether to allocate an AI task to the terminal, or how much processing power to allocate.

[0206] In the embodiments disclosed herein, some or all of the steps and their optional implementations may be arbitrarily combined with some or all of the steps in other embodiments, or may be arbitrarily combined with the optional implementations in other embodiments.

[0207] This disclosure also provides an apparatus for implementing any of the above methods. For example, an apparatus is provided that includes units or modules for implementing the steps performed by the terminal in any of the above methods. Alternatively, another apparatus is provided that includes units or modules for implementing the steps performed by a network device (e.g., an access network device, a core network functional node, a core network device, etc.) in any of the above methods.

[0208] It should be understood that the division of units or modules in the above device is only a logical functional division. In actual implementation, they can be fully or partially integrated into a single physical entity, or they can be physically separated. Furthermore, the units or modules in the device can be implemented by a processor calling software: for example, the device includes a processor connected to a memory containing instructions. The processor calls the instructions stored in the memory to implement any of the above methods or to implement the functions of the units or modules in the above device. The processor can be, for example, a general-purpose processor, such as a Central Processing Unit (CPU) or a microprocessor, and the memory can be internal or external to the device. Alternatively, the units or modules in the device can be implemented in the form of hardware circuits. The functionality of some or all of the units or modules can be achieved through the design of these hardware circuits, which can be understood as one or more processors. For example, in one implementation, the hardware circuit is an application-specific integrated circuit (ASIC). The functionality of some or all of the units or modules is achieved through the design of the logical relationships between the components within the circuit. In another implementation, the hardware circuit can be implemented using a programmable logic device (PLD). Taking a field-programmable gate array (FPGA) as an example, it can include a large number of logic gates. The connection relationships between the logic gates are configured through configuration files, thereby achieving the functionality of some or all of the units or modules. All units or modules of the above device can be implemented entirely through processor-called software, entirely through hardware circuits, or partially through processor-called software with the remaining parts implemented through hardware circuits.

[0209] In this embodiment, the processor is a circuit with signal processing capabilities. In one implementation, the processor can be a circuit with instruction read and execute capabilities, such as a Central Processing Unit (CPU), a microprocessor, a graphics processing unit (GPU) (which can be understood as a microprocessor), or a digital signal processor (DSP). In another implementation, the processor can implement certain functions through the logical relationships of hardware circuits. The logical relationships of the aforementioned hardware circuits are fixed or reconfigurable. For example, the processor is a hardware circuit implemented using an application-specific integrated circuit (ASIC) or a programmable logic device (PLD), such as an FPGA. In a reconfigurable hardware circuit, the process of the processor loading a configuration document and configuring the hardware circuit can be understood as the process of the processor loading instructions to implement the functions of some or all of the above units or modules. Furthermore, it can also be a hardware circuit designed for artificial intelligence, which can be understood as an ASIC, such as a Neural Network Processing Unit (NPU), a Tensor Processing Unit (TPU), or a Deep Learning Processing Unit (DPU).

[0210] Figure 6A is a schematic diagram of the structure of a terminal according to an embodiment of this disclosure. As shown in Figure 6A, the terminal 6100 may include a transceiver module 6101. In some embodiments, the transceiver module 6101 is used to send first information. Optionally, the transceiver module is used to perform at least one of the processing steps (such as step S2101, but not limited thereto) performed by the terminal in any of the above methods, which will not be described in detail here.

[0211] In some embodiments, the terminal may further include a processing module.

[0212] In some embodiments, the first AI processing capability includes capability parameters corresponding to at least one capability type, and the second AI processing capability includes capability parameters corresponding to at least one capability type; wherein, the capability type includes at least one of the following: supported AI task types; supported AI processing speeds; supported AI use cases; supported ML use cases; supported minimum processing latency; supported AI model types; and supported AI model update methods.

[0213] In some embodiments, the first AI processing capability and the second AI processing capability include different types of capabilities.

[0214] In some embodiments, the first AI processing capability includes a first capability parameter corresponding to a first capability type, and the second AI processing capability includes a second capability parameter corresponding to the first capability type, wherein the first capability parameter and the second capability parameter are different.

[0215] In some embodiments, the first capability type includes supported AI task types, the first capability parameter includes supporting AI model inference tasks, and the second capability parameter includes supporting AI model training tasks and supporting AI model inference tasks.

[0216] In some embodiments, the first capability type includes supported AI processing speeds, the first capability parameter includes a first AI processing speed, and the second capability parameter includes a second AI processing speed.

[0217] In some embodiments, the first capability type includes supported AI use cases, the first capability parameter includes supporting specific AI use cases, and the second capability parameter includes supporting all AI use cases.

[0218] In some embodiments, the first capability type includes a supported minimum processing latency, the first capability parameter includes a first minimum processing latency, and the second capability parameter includes a second minimum processing latency.

[0219] In some embodiments, the transceiver module is further configured to receive second information sent by the network device, the second information being used to instruct the terminal to report the first information.

[0220] In some embodiments, the different AI processing units include modems and general-purpose AI processors.

[0221] Figure 6B is a schematic diagram of the structure of a network device according to an embodiment of this disclosure. As shown in Figure 6B, the network device 6200 may include a transceiver module 6201. In some embodiments, the transceiver module 6201 is used to determine first information. Optionally, the transceiver module is used to perform at least one of the processing steps performed by the network device in any of the above methods, which will not be described in detail here.

[0222] In some embodiments, the network device may further include a processing module.

[0223] In some embodiments, the first AI processing capability includes capability parameters corresponding to at least one capability type, and the second AI processing capability includes capability parameters corresponding to at least one capability type; wherein, the capability type includes at least one of the following: supported AI task types; supported AI processing speeds; supported AI use cases; supported ML use cases; supported minimum processing latency; supported AI model types; and supported AI model update methods.

[0224] In some embodiments, the first AI processing capability and the second AI processing capability include different types of capabilities.

[0225] In some embodiments, the first AI processing capability includes a first capability parameter corresponding to a first capability type, and the second AI processing capability includes a second capability parameter corresponding to the first capability type, wherein the first capability parameter and the second capability parameter are different.

[0226] In some embodiments, the first capability type includes supported AI task types, the first capability parameter includes supporting AI model inference tasks, and the second capability parameter includes supporting AI model training tasks and supporting AI model inference tasks.

[0227] In some embodiments, the first capability type includes supported AI processing speeds, the first capability parameter includes a first AI processing speed, and the second capability parameter includes a second AI processing speed.

[0228] In some embodiments, the first capability type includes supported AI use cases, the first capability parameter includes supporting specific AI use cases, and the second capability parameter includes supporting all AI use cases.

[0229] In some embodiments, the first capability type includes a supported minimum processing latency, the first capability parameter includes a first minimum processing latency, and the second capability parameter includes a second minimum processing latency.

[0230] In some embodiments, the transceiver module is further configured to send second information to the terminal, the second information being used to instruct the terminal to report the first information.

[0231] In some embodiments, the different AI processing units include modems and general-purpose AI processors.

[0232] In some embodiments, the processing module may be a single module or may include multiple sub-modules. Optionally, the multiple sub-modules may each perform all or part of the steps required by the processing module. Optionally, the processing module may be interchangeable with a processor.

[0233] Figure 7A is a schematic diagram of the structure of the communication device 7100 proposed in an embodiment of this disclosure. The communication device 7100 can be a network device (e.g., access network device, core network device, etc.), a terminal (e.g., user equipment, etc.), a chip, chip system, or processor that supports the network device in implementing any of the above methods, or a chip, chip system, or processor that supports the terminal in implementing any of the above methods. The communication device 7100 can be used to implement the methods described in the above method embodiments; for details, please refer to the descriptions in the above method embodiments.

[0234] As shown in Figure 7A, the communication device 7100 includes one or more processors 7101. The processor 7101 can be a general-purpose processor or a dedicated processor, such as a baseband processor or a central processing unit (CPU). The baseband processor can be used to process communication protocols and communication data, while the CPU can be used to control communication devices (e.g., base stations, baseband chips, terminal devices, terminal device chips, DUs or CUs, etc.), execute programs, and process program data. Optionally, the communication device 7100 can be used to execute any of the above methods. Optionally, one or more processors 7101 can be used to invoke instructions to cause the communication device 7100 to execute any of the above methods.

[0235] In some embodiments, the communication device 7100 further includes one or more transceivers 7102. When the communication device 7100 includes one or more transceivers 7102, the transceiver 7102 performs at least one of the communication steps (e.g., steps S2101, S2102, but not limited thereto) in the above method, such as sending and / or receiving, while the processor 7101 performs at least one of the other steps. In optional embodiments, the transceiver may include a receiver and / or a transmitter, which may be separate or integrated. Optionally, the terms transceiver, transceiver unit, transceiver, transceiver circuit, interface circuit, interface, etc., can be used interchangeably; the terms transmitter, sending unit, transmitter, sending circuit, etc., can be used interchangeably; and the terms receiver, receiving unit, receiver, receiving circuit, etc., can be used interchangeably.

[0236] In some embodiments, the communication device 7100 further includes one or more memories 7103 for storing data. Optionally, all or part of the memories 7103 may be located outside the communication device 7100. In optional embodiments, the communication device 7100 may include one or more interface circuits 7104. Optionally, the interface circuits 7104 are connected to the memories 7103 and can be used to receive data from the memories 7103 or other devices, and to send data to the memories 7103 or other devices. For example, the interface circuits 7104 can read data stored in the memories 7103 and send the data to the processor 7101.

[0237] The communication device 7100 described in the above embodiments may be a network device or a terminal, but the scope of the communication device 7100 described in this disclosure is not limited thereto, and the structure of the communication device 7100 may not be limited by FIG. 7A. The communication device may be a standalone device or a part of a larger device. For example, the communication device may be: (1) a standalone integrated circuit IC, or chip, or chip system or subsystem; (2) a collection of one or more ICs, optionally, the IC collection may also include storage components for storing data and programs; (3) an ASIC, such as a modem; (4) a module that can be embedded in other devices; (5) a receiver, terminal device, smart terminal device, cellular phone, wireless device, handheld device, mobile unit, vehicle device, network device, cloud device, artificial intelligence device, etc.; (6) others, etc.

[0238] Figure 7B is a schematic diagram of the structure of the chip 7200 according to an embodiment of this disclosure. For cases where the communication device 7100 can be a chip or a chip system, the schematic diagram of the chip 7200 shown in Figure 7B can be referenced, but is not limited thereto.

[0239] Chip 7200 includes one or more processors 7201. Chip 7200 is used to perform any of the above methods.

[0240] In some embodiments, chip 7200 further includes one or more interface circuits 7202. Optionally, terms such as interface circuit, interface, and transceiver pin can be used interchangeably. In some embodiments, chip 7200 further includes one or more memories 7203 for storing data. Optionally, all or part of the memories 7203 may be located outside chip 7200. Optionally, interface circuit 7202 is connected to memory 7203, and interface circuit 7202 can be used to receive data from memory 7203 or other devices, and interface circuit 7202 can be used to send data to memory 7203 or other devices. For example, interface circuit 7202 can read data stored in memory 7203 and send the data to processor 7201.

[0241] In some embodiments, the interface circuit 7202 performs at least one of the communication steps such as sending and / or receiving in the above-described method (e.g., steps S2101 and S2102, but not limited thereto). For example, the interface circuit 7202 performing the communication steps such as sending and / or receiving in the above-described method means that the interface circuit 7202 performs data interaction between the processor 7201, the chip 7200, the memory 7203, or the transceiver device. In some embodiments, the processor 7201 performs at least one of the other steps.

[0242] The modules and / or devices described in the various embodiments, such as virtual devices, physical devices, and chips, can be combined or separated arbitrarily as needed. Optionally, some or all steps can also be performed collaboratively by multiple modules and / or devices, which is not limited here.

[0243] This disclosure also proposes a storage medium storing instructions that, when executed on the communication device 7100, cause the communication device 7100 to perform any of the above methods. Optionally, the storage medium is an electronic storage medium. Optionally, the storage medium is a computer-readable storage medium, but not limited thereto; it may also be a storage medium readable by other devices. Optionally, the storage medium may be a non-transitory storage medium, but not limited thereto; it may also be a temporary storage medium.

[0244] This disclosure also provides a program product that, when executed by the communication device 7100, causes the communication device 7100 to perform any of the above methods. Optionally, the program product is a computer program product.

[0245] This disclosure also proposes a computer program that, when run on a computer, causes the computer to perform any of the above methods.

Claims

1. A communication method characterized by comprising: The method is performed by a terminal and includes: sending first information to a network device; wherein the first information includes at least one of a first AI processing capability and a second AI processing capability, the first AI processing capability and the second AI processing capability are different, and the first AI processing capability and the second AI processing capability represent processing capabilities of different AI processing units.

2. The method of claim 1, wherein, The first AI processing capability includes at least one capability parameter corresponding to a capability type, and the second AI processing capability includes at least one capability parameter corresponding to a capability type. The capability type includes at least one of the following: a supported AI task type; a supported AI processing speed; a supported AI use case; a supported machine learning (ML) use case; a supported minimum processing latency; a supported AI model type; and a supported AI model update mode.

3. The method according to claim 1 or 2, characterized in that, The first AI processing capability and the second AI processing capability include different capability types.

4. The method according to claim 1 or 2, characterized in that, The first AI processing capability includes a first capability parameter corresponding to a first capability type, and the second AI processing capability includes a second capability parameter corresponding to the first capability type, and the first capability parameter and the second capability parameter are different.

5. The method of claim 4, wherein, The first capability type includes a supported AI task type, the first capability parameter includes support for an AI model inference task, and the second capability parameter includes support for an AI model training task and support for an AI model inference task.

6. The method of claim 4, wherein, The first capability type includes a supported AI processing speed, the first capability parameter includes a first AI processing speed, and the second capability parameter includes a second AI processing speed.

7. The method of claim 4, wherein, The first capability type includes a supported AI use case, the first capability parameter includes support for a specific AI use case, and the second capability parameter includes support for all AI use cases.

8. The method of claim 4, wherein, The first capability type includes a supported minimum processing latency, the first capability parameter includes a first minimum processing latency, and the second capability parameter includes a second minimum processing latency.

9. The method according to any one of claims 1 to 8, characterized in that, The method further includes: The terminal receives second information sent by the network device, and the second information is used to instruct the terminal to report the first information.

10. The method according to any one of claims 1 to 8, characterized in that, The different AI processing units include a modem and a general AI processor.

11. A communication method, comprising: The method is performed by a network device and includes: receiving first information sent by a terminal; wherein the first information includes at least one of a first AI processing capability and a second AI processing capability, the first AI processing capability and the second AI processing capability are different, and the first AI processing capability and the second AI processing capability represent processing capabilities of different AI processing units.

12. The method of claim 11, wherein, The first AI processing capability includes at least one capability parameter corresponding to a capability type, and the second AI processing capability includes at least one capability parameter corresponding to a capability type. The capability type includes at least one of the following: a supported AI task type; a supported AI processing speed; a supported AI use case; a supported machine learning (ML) use case; a supported minimum processing latency; a supported AI model type; and a supported AI model update mode.

13. The method according to claim 11 or 12, characterized in that, The first AI processing capability and the second AI processing capability include different capability types.

14. The method of claim 11 or 12, wherein, The first AI processing capability includes a first capability parameter corresponding to a first capability type, and the second AI processing capability includes a second capability parameter corresponding to the first capability type, and the first capability parameter and the second capability parameter are different.

15. The method of claim 14, wherein, The first capability type includes a supported AI task type, the first capability parameter includes support for an AI model inference task, and the second capability parameter includes support for an AI model training task and support for an AI model inference task.

16. The method of claim 14, wherein, The first capability type includes a supported AI processing speed, the first capability parameter includes a first AI processing speed, and the second capability parameter includes a second AI processing speed.

17. The method of claim 14, wherein, The first capability type includes a supported AI use case, the first capability parameter includes support for a specific AI use case, and the second capability parameter includes support for all AI use cases.

18. The method of claim 14, wherein, The first capability type includes a supported minimum processing latency, the first capability parameter includes a first minimum processing latency, and the second capability parameter includes a second minimum processing latency.

19. The method according to any one of claims 11 to 18, characterized in that, The method further includes: The network device sends second information to the terminal, and the second information is used to instruct the terminal to report the first information.

20. The method of any one of claims 11 to 18, wherein, The different AI processing units include a modem and a general AI processor.

21. A terminal, characterized by Comprising: a transceiver module, configured to send first information to a network device; The first information includes at least one of a first AI processing capability and a second AI processing capability, the first AI processing capability and the second AI processing capability are different, and the first AI processing capability and the second AI processing capability represent the processing capabilities of different AI processing units.

22. A network device, comprising: Comprising: a transceiver module, configured to receive first information sent by a terminal; The first information includes at least one of a first AI processing capability and a second AI processing capability, the first AI processing capability and the second AI processing capability are different, and the first AI processing capability and the second AI processing capability represent the processing capabilities of different AI processing units.

23. A terminal, characterized by Comprising: one or more processors; The terminal is configured to perform the method of any one of claims 1-10.

24. A network device, comprising: Comprising: one or more processors; The network device is configured to perform the method of any one of claims 11-20.

25. A communication system, characterized by The terminal and the network device are configured to implement the method of any one of claims 1-10 and the method of any one of claims 11-20.

26. A storage medium, the storage medium storing instructions, wherein, When the instructions run on a communication device, the communication device is caused to perform the method of any one of claims 1-10 or the method of any one of claims 11-20.

27. A program product, characterized by Comprising: a computer program, when executed by a communication device, causes the communication device to perform the method of any one of claims 1-10 or the method of any one of claims 11-20.

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