Communication method and device, communication equipment and communication system

Abstract

The invention relates to a communication method and device, communication equipment and a communication system. The communication method comprises the following steps: when an AI function or an AI model of a terminal is updated, carrying out a first test on the updated AI function or AI model; according to the invention, the updated AI function or AI model can be tested in time, and the communication efficiency is improved.

Description

Communication method and device, communication equipment, and communication system Technical Field

[0001] The present disclosure relates to the field of communication technologies, and in particular to communication methods and devices, communication equipment, and communication systems. Background Art

[0002] Artificial Intelligence (AI) technology has achieved continuous breakthroughs in multiple fields. By applying AI technology to wireless air interfaces for communication processing, including AI model training and model reasoning applications, it can assist in improving wireless air interface transmission technology.

[0003] Summary of the Invention

[0004] Updates to the terminal's AI function or AI model may affect communication performance.

[0005] The embodiments of the present disclosure provide a communication method and apparatus, a communication device, and a communication system.

[0006] According to a first aspect of an embodiment of the present disclosure, a communication method is provided, comprising: updating an AI function or an AI model of a terminal, and performing a first test on the updated AI function or AI model.

[0007] According to a second aspect of an embodiment of the present disclosure, a communication method is provided, comprising: sending first information, where the first information is used to indicate a first test for an updated AI function or AI model.

[0008] According to a third aspect of an embodiment of the present disclosure, a communication method is provided, comprising: a network device sending first information, wherein the first information is used to indicate a first test for an updated AI function or AI model; a terminal receives the first information; and the terminal performs a first test on the updated AI function or AI model based on the first information.

[0009] According to a fourth aspect of an embodiment of the present disclosure, a terminal is provided, comprising: a processing module for updating an AI function or an AI model of the terminal and performing a first test on the updated AI function or AI model.

[0010] According to a fifth aspect of an embodiment of the present disclosure, a network device is provided, comprising: a communication module for sending first information, wherein the first information is used to indicate a first test of an updated AI function or AI model of a terminal.

[0011] According to a sixth aspect of an embodiment of the present disclosure, a terminal is provided, comprising: one or more processors; the processors are configured to call instructions so that the terminal executes the communication method described in the first aspect.

[0012] According to a seventh aspect of an embodiment of the present disclosure, a network device is provided, comprising: one or more processors; the processors are configured to call instructions so that the network device executes the communication method described in the second aspect.

[0013] According to an eighth aspect of an embodiment of the present disclosure, a communication system is provided, comprising a terminal and a network device, wherein the terminal is configured to implement the communication method described in any one of the first aspects, and the network device is configured to implement the communication method described in the second aspect.

[0014] According to a ninth aspect of an embodiment of the present disclosure, a storage medium is provided, wherein the storage medium stores instructions, and wherein when the instructions are executed on a communication device, the communication device executes the communication method described in any one of the first and second aspects.

[0015] Through the solution provided by the embodiments of the present disclosure, the network device can determine whether the AI ​​function supported by the terminal has passed the test or whether the performance of the AI ​​function meets the performance indicators, thereby improving communication performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the following drawings required for describing the embodiments are introduced. The following drawings are merely some embodiments of the present disclosure and do not impose specific limitations on the protection scope of the present disclosure.

[0017] FIG1 is a schematic diagram showing the architecture of a communication system according to an embodiment of the present disclosure.

[0018] FIG2 is a schematic diagram showing interaction of a communication method according to an embodiment of the present disclosure.

[0019] FIG3 a is a flow chart showing a communication method according to an embodiment of the present disclosure.

[0020] FIG3 b is a flow chart of a communication method according to an embodiment of the present disclosure.

[0021] FIG3 c is a flow chart of a communication method according to an embodiment of the present disclosure.

[0022] FIG3 d is a flow chart of a communication method according to an embodiment of the present disclosure.

[0023] FIG4 a is a flow chart of a communication method according to an embodiment of the present disclosure.

[0024] FIG4 b is a flow chart of a communication method according to an embodiment of the present disclosure.

[0025] FIG5 a is a flow chart of a communication method according to an embodiment of the present disclosure.

[0026] FIG5 b is a flow chart of a communication method according to an embodiment of the present disclosure.

[0027] FIG6 a is a schematic diagram of a terminal according to an embodiment of the present disclosure.

[0028] FIG6 b is a schematic diagram of a network device according to an embodiment of the present disclosure.

[0029] Fig. 7a is a schematic diagram showing a communication device according to an exemplary embodiment.

[0030] FIG7 b is a schematic diagram showing a chip structure according to an exemplary embodiment. DETAILED DESCRIPTION

[0031] The embodiments of the present disclosure provide a communication method and apparatus, a communication device, and a communication system.

[0032] In a first aspect, an embodiment of the present disclosure proposes a communication method, which includes: an AI function or an AI model of a terminal is updated, and a first test is performed on the updated AI function or AI model.

[0033] In the above embodiment, the AI ​​function or AI model of the terminal is updated, and a first test is performed on the updated AI function or AI model, so that the updated AI function or AI model can be tested in a timely manner, thereby improving communication efficiency.

[0034] In combination with some embodiments of the first aspect, in some embodiments, first information is received, where the first information is used to indicate that a first test is to be performed on an updated AI function or AI model; and based on the first information, a first test is performed on the updated AI function or AI model.

[0035] In the above embodiment, the terminal receives the first information and tests the updated AI function or AI model based on the first information to implement the test of the updated AI function or AI model, and find out whether the updated AI function or AI model meets the performance indicators, thereby improving communication efficiency.

[0036] In combination with some embodiments of the first aspect, in some embodiments, the method also includes: when the AI ​​function or AI model of the terminal is updated, second information is sent, and the second information is used by the network device to determine whether to perform a first test on the updated AI function or AI model.

[0037] In the above embodiment, the terminal sends the second information to facilitate the network device to determine whether to perform the first test on the updated AI function or AI model of the terminal, so as to avoid performing the first test when the updated AI function or AI model has actually been tested and the performance meets the performance indicators, resulting in repeated testing and waste of resources.

[0038] In combination with some embodiments of the first aspect, in some embodiments, the second information includes at least one of the following: the updated AI function or AI model undergoes a second test; the updated AI function or AI model does not undergo a second test; the performance indicator value corresponding to the performance of the updated AI function or AI model; the updated AI function or AI model undergoes a second test, and the performance of the updated AI function or AI model meets the performance indicator; the updated AI function or AI model undergoes a second test, and the performance of the updated AI function or AI model does not meet the performance indicator; the identifier corresponding to the updated AI function or AI model; the application scenario and / or corresponding application cell corresponding to the updated AI function or AI model.

[0039] In the above embodiment, the second information sent by the terminal includes whether the updated AI function or AI model undergoes a second test and if the second test is performed, whether its performance meets the performance index, so that the network device can determine whether to perform a first test on the updated AI function or AI model on this basis. In this way, repeated testing can be avoided to waste resources. The second information sent by the terminal includes an identifier of the updated AI function or AI model, so that the network device can determine the updated AI function or AI model based on the identifier. The second information sent by the terminal includes the application scenario and / or application cell of the updated AI function or AI model to assist in determining whether to perform a first test on the updated AI function or AI model.

[0040] In combination with some embodiments of the first aspect, in some embodiments, the first information is used to indicate that a first test is performed on the updated AI function or AI model using at least one of the following: using the updated AI model to perform reasoning based on actual communication data to obtain an reasoning result; using the updated AI model to perform reasoning based on preset data to obtain an reasoning result.

[0041] In the above embodiment, the terminal uses the updated AI function or AI model to perform reasoning based on the actual communication data according to the instruction of the first information, so as to test the updated AI function or AI model. In addition, by performing reasoning with the actual communication data, more accurate reasoning results can be obtained, and the test effect is better. In accordance with the instruction of the first information, the terminal uses the updated AI function or AI model to perform reasoning based on the preset data to test the updated AI function or AI model. In addition, by performing reasoning with the preset data, the problem of inaccurate data caused by some uncontrollable situations during actual communication can be avoided, and the preset data can be quickly reasoned without the need to perform actual communication to obtain data, thereby improving efficiency.

[0042] In combination with some embodiments of the first aspect, in some embodiments, the method further includes: determining an actual communication result, where the actual communication result is a result obtained by the terminal based on an actual communication environment.

[0043] In the above embodiment, the terminal determines the actual communication result in order to determine whether the performance of the updated AI function or AI model meets the performance indicators in combination with the reasoning result, thereby testing the updated AI function or AI model.

[0044] In combination with some embodiments of the first aspect, in some embodiments, the method further includes sending at least one of the following information: an inference result; actual communication data; an actual communication result; a comparison result between the actual communication result and the inference result.

[0045] In the above embodiment, the terminal sends at least one of the inference result, the actual communication result, and the comparison result between the actual communication result and the inference result, so that the network device determines the test result of the first test performed by the terminal.

[0046] In combination with some embodiments of the first aspect, in some embodiments, the method further includes: receiving third information, wherein the third information is used to indicate confirmation of use of the updated AI function or AI model, or to indicate refusal to use the updated AI function or AI model.

[0047] In the above embodiment, by receiving the third information, the terminal can use the updated AI function or refuse to use the updated AI function or AI model, thereby avoiding the use of AI functions or AI models that have not been tested or whose performance does not meet the performance indicators.

[0048] In a second aspect, an embodiment of the present disclosure proposes a communication method, which includes: sending first information, where the first information is used to indicate a first test for an updated AI function or AI model.

[0049] In combination with some embodiments of the second aspect, in some embodiments, before sending the first information, the method further includes: receiving second information, where the second information is used to determine whether to perform a first test on the updated AI function or AI model of the terminal.

[0050] In combination with some embodiments of the second aspect, in some embodiments, the second information includes at least one of the following: the updated AI function or AI model undergoes a second test; the updated AI function or AI model does not undergo a second test; the performance indicator value corresponding to the performance of the updated AI function or AI model; the updated AI function or AI model undergoes a second test, and the performance of the updated AI function or AI model meets the performance indicator; the updated AI function or AI model undergoes a second test, and the performance of the updated AI function or AI model does not meet the performance indicator; the identifier corresponding to the AI ​​function or AI model before the update; the application scenario corresponding to the updated AI function or AI model.

[0051] In combination with some embodiments of the second aspect, in some embodiments, the first information is used to indicate that a first test is performed on the updated AI function or AI model using at least one of the following: using the updated AI model to perform reasoning based on actual communication data to obtain an reasoning result; using the updated AI model to perform reasoning based on preset data to obtain an reasoning result.

[0052] In combination with some embodiments of the second aspect, in some embodiments, the method further includes receiving at least one of the following information: an inference result; actual communication data; an actual communication result; a comparison result between the actual communication result and the inference result.

[0053] In combination with some embodiments of the second aspect, in some embodiments, the method further includes: sending third information, wherein the third information is used to indicate confirmation of use of the updated AI function or AI model, or to indicate refusal to use the updated AI function or AI model.

[0054] In combination with some embodiments of the second aspect, in some embodiments, the first information is sent to terminals selected from at least one of the following: all terminals that send the second information; some terminals among the terminals that send the second information; and terminals in a predefined terminal set.

[0055] In the above embodiment, the network device sends the first information to all terminals that send the second information, and all terminals test the updated AI function or AI model, which can obtain more accurate test results. By sending the first information to some terminals that send the second information, the network device can save resources while testing the updated AI function or AI model. By sending the first information to terminals in a predefined terminal set, the network device can efficiently test the AI ​​function or AI model, thereby improving efficiency.

[0056] In combination with some embodiments of the second aspect, in some embodiments, the third information is sent to all terminals that sent the second information.

[0057] In the above embodiment, the network device sends the third information to all terminals that sent the second information, so as to enable all terminals that instruct the AI ​​function or AI model to use or refuse to use the updated AI function or AI model.

[0058] In a third aspect, an embodiment of the present disclosure provides a communication method, comprising: a network device sends first information, wherein the first information is used to indicate a first test for an updated AI function or AI model; a terminal receives the first information; and the terminal performs a first test on the updated AI function or AI model based on the first information.

[0059] In a fourth aspect, an embodiment of the present disclosure proposes a terminal, which includes at least one of a communication module and a processing module; wherein the terminal is used to execute the first aspect and the optional implementation method of the first aspect.

[0060] In a fifth aspect, an embodiment of the present disclosure proposes a network device, including a communication module; wherein the above-mentioned network device is used to execute the second aspect and the optional implementation method of the second aspect.

[0061] In a sixth aspect, an embodiment of the present disclosure proposes a terminal, comprising: one or more processors; wherein the above-mentioned terminal is used to execute the first aspect and the optional implementation method of the first aspect.

[0062] In a seventh aspect, an embodiment of the present disclosure proposes a network device, comprising: one or more processors; wherein the above-mentioned network device is used to execute the second aspect and the optional implementation method of the second aspect.

[0063] In the eighth aspect, an embodiment of the present disclosure proposes a communication system, which includes: a terminal and a network device; wherein the terminal is configured to execute the method described in the first and third aspects, and the optional implementation methods of the first and third aspects, and the network device is configured to execute the method described in the second and third aspects, and the optional implementation methods of the second and third aspects.

[0064] In the ninth aspect, an embodiment of the present disclosure proposes a storage medium, which stores instructions. When the instructions are executed on a communication device, the communication device executes the method described in the optional implementation of the first and third aspects, and the second and third aspects.

[0065] In a tenth aspect, an embodiment of the present disclosure proposes a program product. When the program product is executed by a communication device, the communication device executes the method described in the optional implementation of the first and third aspects, and the second and third aspects.

[0066] In an eleventh aspect, an embodiment of the present disclosure proposes a computer program, which, when executed on a computer, enables the computer to execute the method as described in the first and third aspects, and the optional implementation of the second and third aspects.

[0067] It is understandable that the above-mentioned terminals, network devices, communication devices, communication systems, storage media, program products, and computer programs are all used to execute the methods proposed in the embodiments of the present disclosure. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects of the corresponding methods and will not be repeated here.

[0068] In some embodiments, the terms communication method and information processing method are interchangeable, the terms communication device and information processing device are interchangeable, and the terms information processing system and communication system are interchangeable.

[0069] The embodiments of the present disclosure are not exhaustive and are merely illustrative of some embodiments, and are not intended to be a specific limitation on the scope of protection of the present disclosure. In the absence of contradiction, 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 exchanged. In addition, the optional implementations in a particular embodiment can be arbitrarily combined; in addition, the embodiments can be arbitrarily combined. For example, some or all of the steps of different embodiments can be arbitrarily combined, and a particular embodiment can be arbitrarily combined with the optional implementations of other embodiments.

[0070] In each embodiment of the present disclosure, unless otherwise specified or provided for by logic, the terms and / or descriptions between the embodiments are consistent and can be referenced by each other. The technical features in different embodiments can be combined to form a new embodiment based on their inherent logical relationships.

[0071] The terms used in the embodiments of the present disclosure are only for the purpose of describing specific embodiments and are not intended to limit the present disclosure.

[0072] In the embodiments of the present disclosure, unless otherwise specified, elements expressed in the singular, such as "a", "an", "the", "above", "said", "the", "the", etc., may mean "one and only one", or "one or more", "at least one", etc. For example, when using articles such as "a", "an", "the" in English in translation, the noun following the article may be understood as a singular expression or a plural expression.

[0073] In the embodiments of the present disclosure, “plurality” refers to two or more.

[0074] In some embodiments, the terms "at least one," "one or more," "a plurality of," "multiple," etc. may be used interchangeably.

[0075] In some embodiments, descriptions such as "at least one of A and B," "A and / or B," "A in one case, B in another case," or "in response to one case A, in response to another case B" may include the following technical solutions depending on the situation: in some embodiments, A (A is executed independently of B); in some embodiments, B (B is executed independently of A); in some embodiments, execution is selected from A and B (A and B are selectively executed); and in some embodiments, A and B (both A and B are executed). The above is also applicable when there are more branches such as A, B, and C.

[0076] In some embodiments, "A or B" and other descriptions may include the following technical solutions depending on the situation: in some embodiments, A (A is executed independently of B); in some embodiments, B (B is executed independently of A); in some embodiments, execution is selected from A and B (A and B are selectively executed). The above is also applicable when there are more branches such as A, B, C, etc.

[0077] The prefixes such as "first" and "second" in the embodiments of the present disclosure are only used to distinguish different description objects and do not constitute any restriction on the position, order, priority, quantity or content of the description objects. For the statement of the description object, please refer to the description in the context of the claims or embodiments, and no unnecessary restriction should be constituted due to the use of prefixes. For example, if the description object is a "field", the ordinal number before the "field" in the "first field" and the "second field" does not limit the position or order between the "fields". "First" and "second" do not limit whether the "fields" they modify are in the same message, nor do they limit the order of the "first field" and the "second field". For another example, if the description object is a "level", the ordinal number before the "level" in the "first level" and the "second level" does not limit the priority between the "levels". For another example, the number of description objects is not limited by the ordinal number and can be one or more. Taking "first device" as an example, the number of "devices" can be one or more. In addition, the objects modified by different prefixes can be the same or different. For example, if the description object is "device", then the "first device" and the "second device" can be the same device or different devices, and their types can be the same or different; for another example, if the description object is "information", then the "first information" and the "second information" can be the same information or different information, and their contents can be the same or different.

[0078] In some embodiments, “including A,” “comprising A,” “used to indicate A,” and “carrying A” can be interpreted as directly carrying A or indirectly indicating A.

[0079] In some embodiments, terms such as "in response to...", "in response to determining...", "in the case of...", "at the time of...", "when...", "if...", "if...", etc. can be used interchangeably.

[0080] In some embodiments, terms such as "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 less than", and "above" can be replaced with each other, and terms such as "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" can be replaced with each other.

[0081] 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", "device", "circuit", "network element", "node", "function", "unit", "section", "system", "network", "chip", "chip system", "entity", and "subject" can be used interchangeably.

[0082] In some embodiments, "network" can be interpreted as devices included in the network (eg, access network equipment, core network equipment, etc.).

[0083] 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", "bandwidth part (BWP)" and the like may be used interchangeably.

[0084] 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, client, etc. can be used interchangeably.

[0085] In some embodiments, the access network device, the core network device, or the network device can be replaced by a terminal. For example, the various embodiments of the present disclosure can also be applied to a structure in which the communication between the access network device, the core network device, or the network device and the terminal is replaced by communication between multiple terminals (for example, device-to-device (D2D), vehicle-to-everything (V2X), etc.). In this case, it is also possible to set the structure in which the terminal has all or part of the functions of the access network device. In addition, terms such as "uplink" and "downlink" can also be replaced by terms corresponding to communication between terminals (for example, "side"). For example, uplink channels, downlink channels, etc. can be replaced by side channels, and uplinks, downlinks, etc. can be replaced by side links.

[0086] 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, the core network device, or the network device may have a structure that has all or part of the functions of the terminal.

[0087] In some embodiments, obtaining data, information, etc. may comply with the laws and regulations of the country where the data is obtained.

[0088] In some embodiments, data, information, etc. may be obtained with the user's consent.

[0089] In addition, each element, each row, or each column in the table of the embodiment of the present disclosure can be implemented as an independent embodiment, and the combination of any elements, any rows, and any columns can also be implemented as an independent embodiment.

[0090] FIG1 is a schematic diagram showing the architecture of a communication system according to an embodiment of the present disclosure.

[0091] As shown in FIG1 , a communication system 100 includes a terminal 101 and a network device 102 .

[0092] In some embodiments, the terminal 101 includes, for example, a mobile phone, a wearable device, an Internet of Things device, a car with communication function, a smart car, a tablet computer, a computer with wireless transceiver function, a virtual reality (VR) terminal device, an augmented reality (AR) terminal device, a wireless terminal device in industrial control, a wireless terminal device in self-driving, a wireless terminal device in remote medical surgery, a wireless terminal device in a smart grid, a wireless terminal device in transportation safety, a wireless terminal device in a smart city, and at least one of a wireless terminal device in a smart home, but is not limited thereto.

[0093] In some embodiments, the network device 102 may include at least one of an access network device and a core network device.

[0094] In some embodiments, the terminal 101 includes, for example, a mobile phone, a wearable device, an Internet of Things device, a car with communication function, a smart car, a tablet computer, a computer with wireless transceiver function, a virtual reality (VR) terminal 101 device, an augmented reality (AR) terminal 101 device, a wireless terminal 101 device in industrial control, a wireless terminal 101 device in self-driving, a wireless terminal 101 device in remote medical surgery, a wireless terminal 101 device in a smart grid, a wireless terminal 101 device in transportation safety, a wireless terminal 101 device in a smart city, and at least one of a wireless terminal 101 device in a smart home, but is not limited thereto.

[0095] In some embodiments, the access network device is, for example, a node or device that accesses the terminal 101 to the wireless network. The access network device may include an evolved NodeB (eNB), a next generation evolved NodeB (ng-eNB), a next generation NodeB (gNB), a node B (NB), a home node B (HNB), a home evolved nodeB (HeNB), a wireless backhaul device, a radio network controller (RNC), a base station controller (BSC), a base transceiver station (BTS), a base band unit (BBU), a mobile switching center, a base station in a 6G communication system, an open base station (Open RAN), a cloud base station (Cloud RAN), a base station in other communication systems, and at least one of an access node in a wireless fidelity (WiFi) system, but is not limited thereto.

[0096] In some embodiments, the technical solution of the present disclosure can be applied to the Open RAN architecture. In this case, the interfaces between or within the access network devices involved in the embodiments of the present disclosure can be transformed into internal interfaces of the Open RAN, and the processes and information interactions between these internal interfaces can be implemented through software or programs.

[0097] In some embodiments, the access network device can be composed of a centralized unit (CU) and a distributed unit (DU), where the CU can also be called a control unit. The CU-DU structure can be used to split the protocol layer of the access network device, with the functions of some protocol layers centrally controlled by the CU, and the functions of the remaining part or all of the protocol layers distributed in the DU, which is centrally controlled by the CU, but is not limited to this.

[0098] In some embodiments, the core network device may be a device including one or more network elements, or may be multiple devices or a group of devices including one or more network elements, or may be 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).

[0099] It can be understood that the communication system described in the embodiment of the present disclosure is for the purpose of more clearly illustrating the technical solution of the embodiment of the present disclosure, and does not constitute a limitation on the technical solution proposed in the embodiment of the present disclosure. Ordinary technicians in this field can know that with the evolution of the system architecture and the emergence of new business scenarios, the technical solution proposed in the embodiment of the present disclosure is also applicable to similar technical problems.

[0100] The following embodiments of the present disclosure may be applied to the communication system 100 shown in FIG1 , or a portion thereof, but are not limited thereto. The entities shown in FIG1 are illustrative only. The communication system may include all or part of the entities shown in FIG1 , or may include other entities outside of FIG1 . The number and form of the entities are arbitrary, and the entities may be physical or virtual. The connection relationships between the entities are illustrative only. The entities may be connected or disconnected, and the connection may be in any manner, including direct or indirect, wired or wireless.

[0101] The embodiments of the present disclosure 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), 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 (registered trademark)), CDMA2000, Ultra Mobile Broadband (UMB), IEEE 802.11 (Wi-Fi (registered trademark)), IEEE 802.16 (WiMAX (registered trademark)), IEEE 802.20, Ultra-WideBand (UWB), Bluetooth (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 utilizing other communication methods, and next-generation systems based on and extending these methods. Furthermore, multiple systems may be combined (for example, a combination of LTE or LTE-A with 5G).

[0102] In recent years, artificial intelligence (AI) technology has achieved continuous breakthroughs in numerous fields. The continued development of fields such as intelligent voice and computer vision has not only brought a rich variety of applications to smart terminals, but has also found widespread application in education, transportation, home living, healthcare, retail, security, and other fields. This has brought convenience to people's lives while also promoting industrial upgrading across various industries. AI technology is also rapidly interpenetrating with other disciplines, integrating knowledge from different disciplines while also providing new directions and methods for their development.

[0103] In the disclosed embodiments, a research project on AI technology in the radio air interface is established in the Radio Access Network (RAN) to introduce artificial intelligence technology in the radio air interface and assist in improving the transmission technology of the radio air interface. Furthermore, the application of AI technology in the radio air interface for communication processing is currently supported, including AI model training and model reasoning applications. For example, AI-based CSI enhancement, AI-based beamforming enhancement, and AI-based positioning are implemented.

[0104] In some embodiments, multiple AI functionalities are defined, such as AI-based time-domain prediction, AI-based positioning, etc.

[0105] In the embodiment of the present disclosure, before a terminal accesses a network device, it is necessary to test the AI ​​function, for example, to test whether the nominal performance of the AI ​​function meets the performance index.

[0106] Optionally, after the performance of the AI ​​function meets the performance indicator, the terminal can report the AI ​​function it supports or the function parameters associated with the AI ​​function to the network device when accessing the network device.

[0107] However, because AI functions rely on AI models, the AI ​​models supported by terminals may be updated. Therefore, how to test the updated AI functions or AI models is a problem that needs to be solved.

[0108] Based on this, an embodiment of the present disclosure provides a communication method, where a terminal receives first information and tests an updated AI function or AI model based on the first information to implement testing of the updated AI function or AI model, determine whether the performance of the updated AI function or AI model meets performance indicators, and improve communication efficiency.

[0109] FIG2 is an interactive diagram of a communication method according to an embodiment of the present disclosure. As shown in FIG2 , the embodiment of the present disclosure relates to a communication method for use in a communication system 100, the method comprising:

[0110] Step S2101 , the terminal 101 sends second information to the network device 102 .

[0111] In some embodiments, network device 102 receives second information.

[0112] In some embodiments, when an AI function or AI model is updated, the terminal sends a second message to the network device. The AI ​​function update can be understood as an update of the AI ​​model corresponding to the AI ​​function. The AI ​​model update can be understood as an update of the structure of the AI ​​model or the parameters of the AI ​​model. Of course, the above example of an AI model update being an update of the structure of the AI ​​model or the parameters of the AI ​​model is merely an illustrative example, and this disclosure does not limit this.

[0113] In some embodiments, terms such as "send", "transmit", "report", "download", "transmit", "bidirectional transmission", "send and / or receive" can be used interchangeably.

[0114] In some embodiments, "obtain", "get", "get", "receive", "transmit", "bidirectional transmission", "send and / or receive" can be interchangeable, and can be interpreted as receiving from other entities, obtaining from protocols, obtaining from higher layers, obtaining by self-processing, autonomous implementation, etc.

[0115] In some embodiments, the second information is used by the network device to determine whether to perform a first test on the updated AI function or AI model. The first test may be a test configured by the network device for the terminal.

[0116] Optionally, the second information is used to indicate that the updated AI function or AI model has not undergone the second test.

[0117] The second test may be a local test of the terminal. Of course, the second test may also be a test configured by the network device for the terminal, which is not limited in the present disclosure.

[0118] In some cases, the updated AI function or AI model is not subjected to the second test, and the performance of the updated AI function or AI model meets the performance indicator.

[0119] In other cases, the updated AI function or AI model is not subjected to the second test, and the performance of the updated AI function or AI model does not meet the performance index.

[0120] It is understandable that since the updated AI function or AI model has not undergone the second test, it is impossible to determine whether the performance of the updated AI function or AI model meets the performance indicator. The terminal sends the second information indicating that the AI ​​function or AI model has not undergone the second test to the core network device, so that the core network device can test the updated AI function or AI model without being sure whether the performance of the updated AI function or AI model meets the performance indicator.

[0121] Optionally, the second information is used to indicate that the updated AI function or AI model undergoes a second test.

[0122] Optionally, the second information is used to represent a performance indicator value corresponding to the performance of the updated AI function or AI model.

[0123] For example, in AI-based beam prediction, the performance of the AI ​​model can be the accuracy of the prediction, and the performance indicator value can be a threshold value of the accuracy.

[0124] Optionally, the second information is used to indicate that the updated AI function or AI model undergoes a second test, and the performance of the updated AI function or AI model meets the performance index.

[0125] For example, if the AI ​​function is AI-based beam prediction, the performance of the AI ​​function may be the accuracy of the beam prediction, and the performance indicator may be a threshold value for the accuracy. That is, if the accuracy of the AI-based beam prediction is greater than the accuracy threshold, the performance of the AI ​​function may be considered to meet the performance indicator; if the accuracy of the AI-based beam prediction is less than the accuracy threshold, the performance of the AI ​​function may be considered to not meet the performance indicator.

[0126] Optionally, the second information is used to indicate that the updated AI function or AI model undergoes a second test, and the performance of the updated AI function or AI model does not meet the performance index.

[0127] Optionally, the second information is used to indicate an identity document (ID) corresponding to the updated AI function or AI model.

[0128] The ID corresponding to the AI ​​function or AI model can be used to indicate the AI ​​function or AI model. The network device receives the ID of the updated AI function or AI model to determine which AI function or AI model to test.

[0129] Optionally, the second information is used to indicate the application scenario corresponding to the updated AI function or AI model.

[0130] The scenarios corresponding to the AI ​​functions or AI models may be base station sites supported by the AI ​​functions or AI models, data sets supported by the AI ​​functions or AI models, wireless scenarios supported by the AI ​​functions or AI models, etc. Of course, the scenarios corresponding to the AI ​​functions or AI models listed above are merely illustrative examples, and this disclosure does not limit them.

[0131] In some embodiments, the name of the second information is not limited, and it can be, for example, "test information", "update information", etc.

[0132] In some embodiments, the names of information, etc. are not limited to the names described in the embodiments, and terms such as "information", "message", "signal", "signaling", "report", "configuration", "indication", "instruction", "command", "channel", "parameter", "domain", "field", "symbol", "symbol", "codeword", "codebook", "codeword", "codepoint", "bit", "data", "program", etc. can be used interchangeably.

[0133] In some embodiments, terms such as "certain", "preset", "preset", "setting", "indicated", "a certain", "any", and "first" can be interchangeable. "Specific A", "preset A", "preset A", "setting A", "indicated A", "a certain A", "any A", and "first A" can be interpreted as A pre-specified in a protocol, etc., or as A obtained through setting, configuration, or indication, etc., or as specific A, a certain A, any A, or first A, etc., but not limited to this.

[0134] Step S2102 , the network device 102 sends first information to the terminal 101 .

[0135] In some embodiments, terminal 101 receives first information.

[0136] Optionally, if the second information indicates that the updated AI function or AI model has not undergone the second test, the network device sends the first information to the terminal.

[0137] Optionally, if the second information indicates that the updated AI function or AI model undergoes a second test, and the performance of the updated AI function or AI model does not meet the performance indicator, the network device sends the first information to the terminal.

[0138] In some embodiments, the network device may also directly send the first information to the terminal without receiving the second information to test the updated AI function or AI model of the terminal.

[0139] In some embodiments, the AI ​​function or AI model undergoes a second test, which may also be referred to as the AI ​​function or AI model undergoing a second test.

[0140] In some embodiments, the first information is used to instruct a first test to be performed on the updated AI function or AI model.

[0141] Optionally, the first information is used to indicate the use of the updated AI model to perform reasoning based on actual communication data to obtain a reasoning result.

[0142] For example, the actual communication data may be data generated by actual channel measurement.

[0143] For example, the actual communication data may be an actual channel state or actual terminal coordinates, which is not limited in the present disclosure.

[0144] For example, in AI-based beam prediction, a terminal can measure X beams, input the measured data into an AI model, and perform inference based on the AI ​​model to obtain an inference result. The inference result is the measurement result for Y beams, where X is less than Y.

[0145] That is to say, in AI-based beam prediction, the AI ​​model can predict the measurement results of a large number of beams based on the measurement results of a few beams.

[0146] Optionally, the first information is used to instruct the use of the updated AI model to perform reasoning based on preset data to obtain an inference result.

[0147] For example, the preset data may be data generated based on simulation.

[0148] For another example, the preset data may be data collected by other terminals.

[0149] In some embodiments, the inference results can be used to determine whether the performance of the AI ​​function or AI model meets the performance indicators.

[0150] In some embodiments, the inference result can be the final result or a result parameter that can be used to derive the final result. For example, when predicting the optimal beam based on AI, the inference result of the AI ​​model can be "the optimal beam is beam C"; or it can be "beam A corresponds to result parameter 1, beam B corresponds to result parameter 2, and beam C corresponds to result parameter 3." Based on the result parameters, it can be deduced that the optimal beam is beam C.

[0151] Of course, the above-mentioned embodiment of predicting the best beam is merely exemplary and is not limited in the present disclosure.

[0152] In some embodiments, the first information is further used to instruct the terminal to determine an actual communication result, wherein the actual communication result corresponds to an inference result of the AI ​​function or AI model.

[0153] For example, if the AI ​​function is AI-based CSI prediction, that is, the AI ​​model corresponding to the AI ​​function can predict the current CSI value based on CSI values ​​at historical moments. The first information indicates that the actual communication result determined by the terminal may be the CSI value measured at the current moment. In other words, the inference result is the CSI value predicted by the AI ​​model at the current moment, and the actual communication result is the CSI value measured by the terminal at the current moment.

[0154] It can be understood that if the actual communication result corresponds to the inference result, or if the inference result is the same as the actual communication result or the difference is small, the inference result can be considered to be relatively accurate. Alternatively, the performance of the AI ​​function or AI model can be considered to meet the performance indicators. Conversely, if the difference between the inference result and the actual communication result is large, the inference result can be considered to be inaccurate. Alternatively, the performance of the AI ​​function or AI model can be considered to not meet the performance indicators.

[0155] In some embodiments, the name of the first information is not limited, and it can be, for example, "test information", "configuration information", etc.

[0156] Step S2103: Perform a first test on the updated AI function or AI model.

[0157] In some embodiments, the AI ​​function or AI model of the terminal 101 is updated, and a first test is performed on the updated AI function or AI model.

[0158] In some embodiments, the terminal 101 may perform a first test on the updated AI function or AI model based on the first information.

[0159] In some embodiments, the terminal 101 performs a first test on the updated AI function or AI model, including at least one of the following A and B: using the updated AI model to perform reasoning based on actual communication data to obtain a reasoning result; using the updated AI model to perform reasoning based on preset data to obtain a reasoning result.

[0160] Optionally, the terminal can use the updated AI model to perform inference based on actual communication data to obtain inference results.

[0161] Optionally, the terminal can use the updated AI model to perform reasoning based on preset data to obtain reasoning results.

[0162] In step S2104, the terminal 101 sends at least one of the following information to the network device 102:

[0163] Reasoning results;

[0164] Actual communication data;

[0165] Actual communication results;

[0166] Comparison results of the inference results and the actual communication results.

[0167] In some embodiments, the network device 102 receives at least one of the following information:

[0168] Reasoning results;

[0169] Actual communication data;

[0170] Actual communication results;

[0171] Comparison results of the inference results and the actual communication results.

[0172] In some embodiments, terminal 101 determines the actual communication result.

[0173] The actual communication result may also be referred to as a comparison parameter, and the comparison parameter is used to represent a value under an ideal state.

[0174] For example, if the AI ​​function is AI-based CSI prediction, the comparison parameter may be a CSI value under an ideal state at the current moment.

[0175] Optionally, both the actual communication results and the comparison parameters can be used to assist in determining whether the performance of the AI ​​function or AI model meets the performance indicators. For example, if the inference result is the same as the comparison parameter or the difference is small, the inference result can be considered to be relatively accurate. Alternatively, the performance of the AI ​​function or AI model can be considered to meet the performance indicators. Conversely, if the difference between the inference result and the comparison parameter is large, the inference result can be considered to be inaccurate. Alternatively, the performance of the AI ​​function or AI model can be considered to not meet the performance indicators.

[0176] The comparison result between the inference result and the test result may be the difference between the two.

[0177] Step S2105 , the network device 102 sends third information to the terminal 101 .

[0178] In some embodiments, terminal 101 receives third information.

[0179] In some embodiments, the third information is used to indicate confirmation of using the updated AI function or AI model, or to indicate not to use the updated AI function or AI model.

[0180] In some embodiments, the third information may be determined based on the second information.

[0181] Optionally, if the network device determines based on the second information that the updated AI function or AI model is to be tested for the first test, and the performance of the updated AI function or AI model meets the performance indicator, the network device sends third information for instructing the terminal to use the updated AI function or AI model. In this case, the third information is used to determine whether to use the updated AI function or AI model.

[0182] Optionally, if the network device determines based on the second information that the updated AI function or AI model is to be tested for the first test, and the performance of the updated AI function or AI model does not meet the performance indicator, the network device sends third information to instruct the terminal not to use the updated AI function or AI model. In this case, the third information is used to determine not to use the updated AI function or AI model, or the third information is used to determine to use the AI ​​function or AI model before the update.

[0183] In some embodiments, the third information may be determined based on at least one of the following information:

[0184] Reasoning results;

[0185] Actual communication data;

[0186] Actual communication results;

[0187] Comparison results of the inference results and the actual communication results.

[0188] Optionally, if the network device determines that the performance of the updated AI function or AI model meets the performance indicator based on at least one of the received inference result, the actual communication result, or the comparison result of the inference result and the actual communication result, the network device sends third information instructing the terminal to use the updated AI function or AI model. In this case, the third information is used to determine the use of the updated AI function or AI model.

[0189] Optionally, if the network device determines that the performance of the updated AI function or AI model does not meet the performance indicator based on at least one of the received inference result, the actual communication result, or the comparison result of the inference result and the actual communication result, the network device sends third information to instruct the terminal not to use the updated AI function or AI model. In this case, the third information is used to determine not to use the updated AI function or AI model, or to determine to use the AI ​​function or AI model before the update.

[0190] In some embodiments, the network device 102 sends the first information to the terminal 101 of at least one of the following:

[0191] All terminals 101 sending second information;

[0192] Some terminals 101 among the terminals sending the second information;

[0193] Terminal 101 in the predefined terminal set.

[0194] For example, the predefined terminal set may be a terminal set used to test an AI function or an AI model.

[0195] Optionally, multiple terminals send the second information to the network device, and the network device sends the first information to all of the multiple terminals.

[0196] Optionally, multiple terminals send the second information to the network device, and the network device sends the first information to some of the multiple terminals.

[0197] Optionally, multiple terminals send the second information to the network device, and the network device sends the first information to terminals in a predefined terminal set.

[0198] The network device may randomly select some terminals from the plurality of terminals to send the first information to, or may select some terminals from the plurality of terminals according to a preset rule to send the first information to.

[0199] For example, the network device can select some terminals from multiple terminals to send the first information based on multiple factors such as the computing power, storage space, AI function or complexity of the AI ​​model of the terminal.

[0200] In some embodiments, the network device 102 sends the third information to all terminals 101 that sent the second information.

[0201] Optionally, the network device may send the first information to all terminals that sent the second information, and send the third information to all terminals that sent the second information.

[0202] Optionally, the network device may send the first information to some of the terminals that sent the second information, and send the third information to all the terminals that sent the second information.

[0203] Optionally, the network device may send the first information to the terminals in the predefined terminal combination, and send the third information to all the terminals that sent the second information.

[0204] In some embodiments, multiple terminals transmit second information to a network device, wherein the second information from X terminals indicates that the performance of an updated AI function or AI model meets a performance indicator. The second information from Y terminals indicates that the performance of the updated AI function or AI model does not meet the performance indicator. If X is greater than or equal to Y, the performance of the updated AI function or AI model is deemed to meet the performance indicator, and the network device may transmit third information to the terminal, instructing the terminal to use the updated AI function or AI model. Conversely, if X is less than Y, the performance of the updated AI function or AI model is deemed to not meet the performance indicator, and the network device may transmit third information to the terminal, instructing the terminal not to use the updated AI function or AI model. In some embodiments, each of the multiple terminals transmits at least one of the following information to the network device: an inference result; actual communication data; an actual communication result; a comparison result of the inference result and the actual communication result. The at least one information from M terminals indicates that the performance of the updated AI function or AI model meets the performance indicator. The at least one information from N terminals indicates that the performance of the updated AI function or AI model does not meet the performance indicator. If M is greater than or equal to N, it can be considered that the performance of the updated AI function or AI model meets the performance indicator, and the network device can send third information to the terminal to instruct the terminal to use the updated AI function or AI model. Conversely, if M is less than N, it can be considered that the performance of the updated AI function or AI model does not meet the performance indicator, and the network device can send third information to the terminal to instruct the terminal not to use the updated AI function or AI model.

[0205] Wherein, X, Y, M, and N are all arbitrary positive integers. The present disclosure only uses X, Y, M, and N for illustrative purposes and does not limit their numerical values.

[0206] In step S2106 , the terminal 101 uses the updated AI function or AI model, or does not use the updated AI function or AI model based on the third information.

[0207] Exemplarily, if the third information indicates the use of an updated AI function or AI model, the terminal uses the updated AI function or AI model; if the first information indicates not to use the updated AI function or AI model, the terminal does not use the updated AI function or AI model, or the terminal uses the AI ​​function or AI model before the update.

[0208] In some implementations, the name of the third information is not limited, and it can be, for example, "update information", "configuration information", etc.

[0209] The communication method involved in the embodiments of the present disclosure may include at least one of steps S2101 to S2103. For example, step S2102 may be implemented as an independent embodiment, step S2103 may be implemented as an independent embodiment, steps S2102+S2103 may be implemented as an independent embodiment, and steps S2104+S2105 may be implemented as independent embodiments, but the present invention is not limited thereto.

[0210] In some embodiments, steps S2101 and S2102 may be executed in an interchanged order or simultaneously.

[0211] In some embodiments, steps S2101, S2104, and S2105 are optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0212] In some embodiments, reference may be made to other optional implementations described before or after the description corresponding to FIG. 2 .

[0213] FIG3a is a flow chart of a communication method according to an embodiment of the present disclosure. As shown in FIG3a, the present disclosure embodiment relates to a communication method, which is executed by terminal 101 and includes:

[0214] Step S3101, sending the second information.

[0215] The optional implementation of step S3101 can refer to the optional implementation of step S2101 in Figure 2 and other related parts in the embodiment involved in Figure 2, which will not be repeated here.

[0216] In some embodiments, the terminal 101 sends the second information to the network device 102, but is not limited thereto and the second information may also be sent to other entities.

[0217] In some embodiments, step S3101 is omitted, and the function indicated by the second information is default or default.

[0218] Step S3102, receiving first information.

[0219] The optional implementation of step S3102 can refer to the optional implementation of step S2102 in Figure 2 and other related parts in the embodiment involved in Figure 2, which will not be repeated here.

[0220] In some embodiments, the terminal 101 receives the first information sent by the network device 102, but is not limited thereto and may also receive the first information sent by other entities.

[0221] Step S3103: Perform a first test on the updated AI function or AI model.

[0222] The optional implementation of step S3103 can refer to the optional implementation of step S2103 in Figure 2 and other related parts in the embodiment involved in Figure 2, which will not be repeated here.

[0223] In some embodiments, the terminal performs a first test on the updated AI function or AI model based on the first information.

[0224] In some embodiments, the terminal performs a first test on the updated AI function or AI model based on the update of the AI ​​function or AI model.

[0225] In some embodiments, the terminal performs a first test on the updated AI function or AI model to obtain at least one of the following:

[0226] Reasoning results;

[0227] Actual communication results;

[0228] Results of the comparison between the actual communication results and the inference results.

[0229] Step S3104: Send at least one of the following information:

[0230] Reasoning results;

[0231] Actual communication data;

[0232] Actual communication results;

[0233] Results of the comparison between the actual communication results and the inference results.

[0234] The optional implementation of step S3104 can refer to the optional implementation of step S2104 in Figure 2 and other related parts in the embodiment involved in Figure 2, which will not be repeated here.

[0235] In some embodiments, the terminal 101 sends the at least one item of the above information to the network device 102, but is not limited thereto, and may also send the at least one item of the above information to other entities.

[0236] Step S3105, receiving the third information.

[0237] For the optional implementation of step S3105, please refer to the optional implementation of step S2105 in Figure 2 and other related parts in the embodiment involved in Figure 2, which will not be repeated here.

[0238] In some embodiments, the terminal receives the third information sent by the network device, but is not limited thereto, and may also receive the third information sent by other entities.

[0239] Step S3106: Based on the third information, use the updated AI function or AI model, or do not use the updated AI function or AI model.

[0240] The optional implementation of step S3106 can refer to the optional implementation of step S2106 in Figure 2 and other related parts in the embodiment involved in Figure 2, which will not be repeated here.

[0241] In some embodiments, the terminal uses an updated AI function or AI model determined based on third information.

[0242] In some embodiments, the terminal's refusal to use the updated AI function or AI model is determined based on the third information.

[0243] The communication method according to the embodiments of the present disclosure may include at least one of steps S3101 to S3106. For example, step S3101 may be implemented as an independent embodiment, step S3102 may be implemented as an independent embodiment, steps S3102+S3103+S3104 may be implemented as an independent embodiment, and steps S3105+S3106 may be implemented as an independent embodiment, but the present invention is not limited thereto.

[0244] In some embodiments, steps S3101 and S3102 may be performed in an interchanged order or simultaneously.

[0245] In some embodiments, steps S3101, S3105, and S3106 are optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0246] In some embodiments, steps S3101, S3102, and S3103 are optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0247] FIG3b is a flow chart of a communication method according to an embodiment of the present disclosure. As shown in FIG3b, the embodiment of the present disclosure relates to a communication method, which is executed by terminal 101 and includes:

[0248] Step S3201, sending the second information.

[0249] The optional implementation of step S3201 can refer to step S2101 in Figure 2, the optional implementation of step S3101 in Figure 3a, and other related parts in the embodiments involved in Figures 2 and 3a, which will not be repeated here.

[0250] Step S3202, receiving third information.

[0251] The optional implementation of step S3202 can refer to step S2105 in FIG. 2 , the optional implementation of step S3105 in FIG. 3 a , and other related parts in the embodiments involved in FIG. 2 and FIG. 3 a , which will not be described in detail here.

[0252] Step S3203: Based on the third information, use the updated AI function or AI model, or do not use the updated AI function or AI model.

[0253] Optional implementations of step S3203 may refer to step S2106 in FIG. 2 , optional implementations of step S3106 in FIG. 3 a , and other related parts in the embodiments involved in FIG. 2 and FIG. 3 a , which will not be described in detail here.

[0254] The communication method involved in the embodiments of the present disclosure may include at least one of steps S3201 to S3203. For example, step S3101 may be implemented as an independent embodiment. Steps S3202 and S3203 may be implemented as separate embodiments, but are not limited thereto.

[0255] In some embodiments, steps S3201 and S3202 may be performed in an interchanged order or simultaneously.

[0256] In some embodiments, in some embodiments, step S3201 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0257] FIG3c is a flow chart of a communication method according to an embodiment of the present disclosure. As shown in FIG3c, the embodiment of the present disclosure relates to a communication method, which is executed by terminal 101 and includes:

[0258] Step S3301, receiving first information.

[0259] The optional implementation of step S3301 can refer to step S2102 in Figure 2, the optional implementation of step S3102 in Figure 3a, and other related parts in the embodiments involved in Figures 2 and 3a, which will not be repeated here.

[0260] Step S3302: Based on the first information, perform a first test on the updated AI function or AI model.

[0261] The optional implementation of step S3302 can refer to step S2103 in Figure 2, the optional implementation of step S3103 in Figure 3a, and other related parts in the embodiments involved in Figures 2 and 3a, which will not be repeated here.

[0262] FIG3 d is a flow chart of a communication method according to an embodiment of the present disclosure. As shown in FIG3 d , the embodiment of the present disclosure relates to a communication method, which is executed by terminal 101 and includes:

[0263] In step S3401, the AI ​​function or AI model of the terminal is updated, and a first test is performed on the updated AI function or AI model.

[0264] Optional implementations of step S3401 can be found in step S2103 of FIG. 2 , optional implementations of step S3103 of FIG. 3 a , and other related parts in the embodiments involved in FIG. 2 and FIG. 3 a , which will not be described in detail here.

[0265] In some embodiments, a first test is performed on an updated AI function or AI model in the following manner: first information is received, where the first information is used to indicate that a first test is performed on the updated AI function or AI model; and based on the first information, a first test is performed on the updated AI function or AI model.

[0266] In some embodiments, before receiving the first information, the method further includes: when the AI ​​function or AI model of the terminal is updated, sending second information, where the second information is used by the network device to determine whether to perform a first test on the updated AI function or AI model.

[0267] In some embodiments, the second information includes at least one of the following: the updated AI function or AI model undergoes a second test; the updated AI function or AI model does not undergo a second test; the performance indicator value corresponding to the performance of the updated AI function or AI model; the updated AI function or AI model undergoes a second test, and the performance of the updated AI function or AI model meets the performance indicator; the updated AI function or AI model undergoes a second test, and the performance of the updated AI function or AI model does not meet the performance indicator; the identifier corresponding to the AI ​​function or AI model before the update; the application scenario and / or corresponding application cell corresponding to the AI ​​function or AI model after the update.

[0268] In some embodiments, the first information is used to indicate that a first test is performed on the updated AI function or AI model using at least one of the following: using the updated AI model to perform reasoning based on actual communication data to obtain a reasoning result; using the updated AI model to perform reasoning based on preset data to obtain a reasoning result.

[0269] In some embodiments, the method further includes: determining an actual communication result, where the actual communication result is a result obtained by the terminal based on an actual communication environment.

[0270] In some embodiments, the method further includes sending at least one of the following information: an inference result; actual communication data; an actual communication result; a comparison result between the actual communication result and the inference result.

[0271] In some embodiments, the method further includes: receiving third information, the third information being used to indicate confirmation of use of the updated AI function or AI model, or to indicate refusal to use the updated AI function or AI model

[0272] FIG4a is a flow chart of a communication method according to an embodiment of the present disclosure. As shown in FIG4a, the embodiment of the present disclosure relates to a communication method, and the method includes:

[0273] Step S4101, receiving second information.

[0274] The optional implementation of step S4101 can refer to the optional implementation of step S2101 in Figure 2 and other related parts in the embodiment involved in Figure 2, which will not be repeated here.

[0275] In some embodiments, the network device receives the second information sent by the terminal, but is not limited thereto and may also receive the first information sent by other entities.

[0276] Optionally, the second information is used by the network device to determine whether to perform a first test on the updated AI function or AI model. For optional implementations, see the optional implementations of step S2103 in FIG. 2 and other related parts of the embodiment involved in FIG. 2 , which will not be described in detail here.

[0277] In some embodiments, step S3101 is omitted, and the second information can autonomously implement the function indicated by the second information, or the above function is default or by default.

[0278] Step S4102, sending the first information.

[0279] The optional implementation of step S4102 can refer to the optional implementation of step S2102 in Figure 2 and other related parts in the embodiment involved in Figure 2, which will not be repeated here.

[0280] In some embodiments, the network device 102 sends the first information to the terminal 101, but is not limited thereto and may also send the first information to other entities.

[0281] Step S4103: Receive at least one of the following information:

[0282] Reasoning results;

[0283] Actual communication data;

[0284] Actual communication results;

[0285] Results of the comparison between the actual communication results and the inference results.

[0286] The optional implementation of step S4103 can refer to the optional implementation of step S2104 in Figure 2 and other related parts in the embodiment involved in Figure 2, which will not be repeated here.

[0287] In some embodiments, the network device 102 receives the at least one item of information sent by the terminal 101, but is not limited thereto and may also receive the first information sent by other entities.

[0288] Step S4104, sending the third information.

[0289] The optional implementation of step S4104 can refer to the optional implementation of step S2105 in Figure 2 and other related parts in the embodiment involved in Figure 2, which will not be repeated here.

[0290] In some embodiments, the network device sends the third information to the terminal, but is not limited thereto, and may also send the at least one item of the above information to other entities.

[0291] The communication method involved in the embodiments of the present disclosure may include at least one of steps S4101 to S4104. For example, step S4101 may be implemented as an independent embodiment, step S4102 may be implemented as an independent embodiment, steps S4101+S4102 may be implemented as an independent embodiment, and steps S4103+S4104 may be implemented as independent embodiments, but the present invention is not limited thereto.

[0292] In some embodiments, steps S4101 and S4102 may be performed in an interchanged order or simultaneously.

[0293] In some embodiments, step S4101 is optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0294] In some embodiments, steps S4103 and S4104 are optional, and one or more of these steps may be omitted or replaced in different embodiments.

[0295] FIG4b is a flow chart of a communication method according to an embodiment of the present disclosure. As shown in FIG4a, the embodiment of the present disclosure relates to a communication method, which includes:

[0296] Step S4201, sending the first information.

[0297] The optional implementation of step S4201 can refer to the optional implementation of step S2102 in Figure 2 and other related parts in the embodiment involved in Figure 2, which will not be repeated here.

[0298] In some embodiments, the network device 102 sends the first information to the terminal 101, but is not limited thereto and may also send the first information to other entities.

[0299] Figure 5a is a flow chart of a communication method according to an embodiment of the present disclosure. As shown in Figure 5a, the embodiment of the present disclosure relates to a communication method, which includes:

[0300] In step S5101, the network device sends first information, where the first information is used to instruct a first test to be performed on an updated AI function or AI model.

[0301] The optional implementation of step S5101 can refer to the optional implementation of S2102 in Figure 2, step S3102 in Figure 3, step S4101 in Figure 4, and other related parts in the embodiments involved in Figures 2, 3a, and 4a, which will not be repeated here.

[0302] In some embodiments, the above method may include the method of the above embodiments related to the communication system 100, the terminal 101, the network device 102, etc., which will not be repeated here.

[0303] FIG5b is a flow chart of a communication method according to an embodiment of the present disclosure. As shown in FIG5b, the embodiment of the present disclosure relates to a communication method, and the method includes:

[0304] Step S5201: The terminal receives first information.

[0305] The optional implementation of step S5201 can refer to the optional implementation of S2102 in Figure 2, step S3102 in Figure 3, step S4102 in Figure 4, and other related parts in the embodiments involved in Figures 2, 3a, and 4a, which will not be repeated here.

[0306] In some embodiments, the above method may include the method of the above embodiments related to the communication system 100, the terminal 101, the network device 102, etc., which will not be repeated here.

[0307] In step S5202, the terminal performs a first test on the updated AI function or AI model based on the first information.

[0308] The optional implementation of step S5202 can refer to the optional implementation of step S2103 in Figure 2, step S3103 in Figure 3, step S4103 in Figure 4, and other related parts in the embodiments involved in Figures 2, 3a, and 4a, which will not be repeated here.

[0309] The present disclosure also provides a communication method as follows:

[0310] In some embodiments, in response to an AI function or AI model being updated locally in the terminal, the terminal reports update information of the AI ​​function or AI model to the network.

[0311] Optionally, whether to perform the test.

[0312] Optionally, if testing was performed, the test results.

[0313] Optionally, if it is an AI model update, the AI ​​model ID before the update.

[0314] Optionally, the application scenarios and / or corresponding application areas corresponding to the updated AI functions or AI models.

[0315] In some embodiments, the network may be a network device.

[0316] In some embodiments, the update information may be the second information.

[0317] In some embodiments, the test result may be that the performance of the updated AI function or AI model meets the performance index.

[0318] In some embodiments, the test result may be that the performance of the updated AI function or AI model does not meet the performance index.

[0319] In some embodiments, in response to receiving a signal that the AI ​​function or AI model has failed a test, the network device configures the terminal to participate in an online test of the AI ​​function or AI model.

[0320] Optionally, the network configuration uses the updated AI model to perform inference based on actual channel measurements and obtain inference results.

[0321] Optionally, the network may configure the terminal to perform other operations to obtain comparison results for the AI ​​operation.

[0322] Optionally, the terminal performs inference based on preset data to obtain an inference result.

[0323] In some embodiments, the online test may be the first test.

[0324] In some embodiments, the other operation may be determining the actual communication result, and the comparison result may be the comparison result.

[0325] In some embodiments, the terminal reports the result of the online test to the network device.

[0326] Optionally, the terminal may report the inference result of the AI ​​model or AI function to the network.

[0327] Optionally, the terminal may report the comparison measurement value or comparison parameter of the AI ​​function to the network.

[0328] Optionally, the terminal reports the result of comparing the inference result of the AI ​​model or AI function with the comparison parameter.

[0329] Optionally, the terminal reports the inference result or the parameters obtained based on the inference result to the network.

[0330] In some embodiments, the comparison measurement value or comparison parameter may be an actual communication result.

[0331] In some embodiments, the result of comparing the inference result of the AI ​​model or AI function with the comparison parameter may be a comparison result between the actual communication result and the inference result.

[0332] In some embodiments, the parameter obtained based on the inference result may be a parameter that can be used to deduce the final result of the inference.

[0333] In some embodiments, the network determines whether to update the AI ​​function or AI model based on the test results of the terminal.

[0334] Optionally, in response to the network determining that the updated AI function or AI model passes the test, the network sends an update confirmation indication to the terminal, and the terminal replaces the original AI function or AI model.

[0335] Optionally, in response to the AI ​​model failing the test, the network does not send an update confirmation message or sends an update failure confirmation message, and the terminal does not replace the original AI function.

[0336] In some embodiments, determining whether to update the AI ​​function or AI model may be determining to use the updated AI function or AI model or refusing to use the updated AI function or AI model.

[0337] In some embodiments, the updated AI function or AI model may be an updated AI function or AI model.

[0338] In some embodiments, the update indication may be third information.

[0339] In some embodiments, the terminal side replaces the original AI function or AI model with an updated AI function or AI model.

[0340] In some embodiments, sending the update failure confirmation information may be sending third information indicating a refusal to use the updated AI function or AI model.

[0341] In some embodiments, the terminal not replacing the original AI function or AI model may mean refusing to use the updated AI function or AI model.

[0342] In some embodiments, the network side allows a group of terminals to participate in the test, and determines whether to update the AI ​​function or AI model based on the test results of this group of terminals.

[0343] In some embodiments, the test result may be at least one of the following:

[0344] Reasoning results;

[0345] Actual communication results;

[0346] Comparison results between actual communication results and inference results.

[0347] In some embodiments, confirming whether to update the AI ​​function or AI model may be determining whether to use the updated AI function or AI model.

[0348] In some embodiments, the terminal reports that the AI ​​function or AI model has not been tested, and the network side selects some terminals to participate in the test. When the test passes, the network sends test pass information to all terminals that have reported the update.

[0349] In some embodiments, the network side selects some terminals to participate in the test by the network device sending the first information to some terminals among the terminals that send the second information.

[0350] In some embodiments, the network sending the test passed information to all terminals that reported the update to the network may be sending the third information to all terminals that sent the second information.

[0351] The embodiments of the present disclosure further provide an apparatus for implementing any of the above methods. For example, an apparatus is provided, comprising units or modules for implementing each step performed by a terminal in any of the above methods. For another example, another apparatus is provided, comprising units or modules for implementing each step performed by a network device (e.g., an access network device, a core network function node, a core network device, etc.) in any of the above methods.

[0352] It should be understood that the division of the various units or modules in the above device is merely a division of logical functions. In actual implementation, they may be fully or partially integrated into a physical entity, or they may be physically separated. In addition, the units or modules in the device may be implemented in the form of a processor calling software: for example, the device includes a processor, the processor is connected to a memory, and the memory stores instructions. The processor calls the instructions stored in the memory to implement any of the above methods or implement the functions of the various units or modules of the above device, wherein the processor is, for example, a general-purpose processor, such as a central processing unit (CPU) or a microprocessor, and the memory is a memory within the device or a memory outside the device. Alternatively, the units or modules in the device can be implemented in the form of hardware circuits, and the functions of some or all of the units or modules can be realized by designing the hardware circuits. The above-mentioned hardware circuits can be understood as one or more processors; for example, in one implementation, the above-mentioned hardware circuit is an application-specific integrated circuit (ASIC), which realizes the functions of some or all of the above units or modules by designing the logical relationship of the components in the circuit; for example, in another implementation, the above-mentioned hardware circuit can be realized by a programmable logic device (PLD). Taking a field programmable gate array (FPGA) as an example, it can include a large number of logic gate circuits, and the connection relationship between the logic gate circuits is configured by configuring the configuration file, thereby realizing the functions of some or all of the above units or modules. All units or modules of the above devices can be realized in the form of software called by the processor, or in the form of hardware circuits, or in part by the form of software called by the processor, and the rest by hardware circuits.

[0353] In the embodiments of the present disclosure, the processor is a circuit with signal processing capabilities. In one implementation, the processor can be a circuit with instruction reading and execution 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 relationship of the hardware circuit. The logical relationship of the above-mentioned hardware circuit is fixed or reconfigurable. For example, the processor is a hardware circuit implemented by 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 implementing the hardware circuit configuration 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. In addition, 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), a deep learning processing unit (DPU), etc.

[0354] Figure 6a is a structural diagram of the terminal proposed in an embodiment of the present disclosure. As shown in Figure 6a, the terminal 6100 may include: a processing module 6101. In some embodiments, the processing module is used for a processing module, which is used to update the AI ​​function or AI model of the terminal and perform a first test on the updated AI function or AI model. In some embodiments, the terminal 6100 may further include a communication module 6102. Optionally, the communication module is used to execute at least one of the communication steps such as sending and / or receiving performed by the terminal 101 in any of the above methods (for example, step S2101, step S2102, step S2104, step S2105, but not limited to this), which will not be repeated here.

[0355] Figure 6b is a structural diagram of a network device proposed in an embodiment of the present disclosure. As shown in Figure 6b, the network device 6200 may include: a communication module 6201. The above-mentioned communication module 6201 is used to send a first message, and the first information is used to indicate a first test for the updated AI function or AI model. Optionally, the above-mentioned communication module is used to execute at least one of the communication steps such as sending and / or receiving (for example, step S2101, step S2102, step S2104, step S2105, but not limited to this) performed by the terminal 101 in any of the above methods, which will not be repeated here.

[0356] In some embodiments, the communication module may include a transmitting module and / or a receiving module, and the transmitting module and the receiving module may be separate or integrated. Optionally, the communication module may be interchangeable with the transceiver.

[0357] In some embodiments, the processing module can be a single module or can include multiple submodules. Optionally, the multiple submodules respectively execute all or part of the steps required to be executed by the processing module. Optionally, the processing module can be interchangeable with the processor.

[0358] Figure 7a is a schematic diagram of the structure of a communication device 7100 proposed in an embodiment of the present disclosure. Communication device 7100 can be a network device (e.g., an access network device, a core network device, etc.), a terminal (e.g., a user equipment, etc.), a chip, a chip system, or a processor that supports a network device to implement any of the above methods, or a chip, a chip system, or a processor that supports a terminal to implement any of the above methods. Communication device 7100 can be used to implement the methods described in the above method embodiments. For details, please refer to the description of the above method embodiments.

[0359] 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, for example, a baseband processor or a central processing unit. The baseband processor can be used to process communication protocols and communication data, and the central processing unit can be used to control the communication device (such as a base station, baseband chip, terminal device, terminal device chip, DU or CU, etc.), execute programs, and process program data. The communication device 7100 is used to perform any of the above methods.

[0360] In some embodiments, the communication device 7100 further includes one or more memories 7102 for storing instructions. Optionally, all or part of the memories 7102 may be located outside the communication device 7100.

[0361] In some embodiments, the communication device 7100 further includes one or more transceivers 7103. When the communication device 7100 includes one or more transceivers 7103, the transceiver 7103 performs at least one of the communication steps such as sending and / or receiving in the above method (for example, step S2101, step S2102, step S2104, step S2105, but not limited thereto), and the processor 7101 performs at least one of the other steps (for example, step S2101, step S2102, step S2104, step S2105, but not limited thereto).

[0362] In some embodiments, a transceiver may include a receiver and / or a transmitter. The receiver and transmitter may be separate or integrated. Optionally, the terms transceiver, transceiver unit, transceiver, and transceiver circuit may be used interchangeably; the terms transmitter, transmitting unit, transmitter, and transmitting circuit may be used interchangeably; and the terms receiver, receiving unit, receiver, and receiving circuit may be used interchangeably.

[0363] In some embodiments, the communication device 7100 may include one or more interface circuits 7104. Optionally, the interface circuit 7104 is connected to the memory 7102. The interface circuit 7104 may be configured to receive signals from the memory 7102 or other devices, and may be configured to send signals to the memory 7102 or other devices. For example, the interface circuit 7104 may read instructions stored in the memory 7102 and send the instructions to the processor 7101.

[0364] The communication device 7100 described in the above embodiment may be a network device or a terminal, but the scope of the communication device 7100 described in the present 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 an independent device or may be part of a larger device. For example, the communication device may be: 1) an independent integrated circuit IC, or a chip, or a chip system or subsystem; (2) a collection of one or more ICs, optionally, the above IC collection may also include a storage component for storing data or programs; (3) an ASIC, such as a modem; (4) a module that can be embedded in other devices; (5) a receiver, a terminal device, an intelligent terminal device, a cellular phone, a wireless device, a handheld device, a mobile unit, an in-vehicle device, a network device, a cloud device, an artificial intelligence device, etc.; (6) others, etc.

[0365] FIG7 b is a schematic diagram of the structure of a chip 7200 according to an embodiment of the present disclosure. If the communication device 7100 can be a chip or a chip system, reference can be made to the schematic diagram of the structure of the chip 7200 shown in FIG7 b , but the present disclosure is not limited thereto.

[0366] The chip 7200 includes one or more processors 7201 , and the chip 7200 is configured to execute any of the above methods.

[0367] In some embodiments, the chip 7200 further includes one or more interface circuits 7202. Optionally, the interface circuit 7202 is connected to the memory 7203. The interface circuit 7202 can be used to receive signals from the memory 7203 or other devices, and can be used to send signals to the memory 7203 or other devices. For example, the interface circuit 7202 can read instructions stored in the memory 7203 and send the instructions to the processor 7201.

[0368] In some embodiments, the interface circuit 7202 executes at least one of the communication steps such as sending and / or receiving in the above method (for example, step S2101, step S2102, step S2104, step S2105, but not limited to these), and the processor 7201 executes at least one of the other steps (for example, step S2101, step S2102, step S2104, step S2105, but not limited to these).

[0369] In some embodiments, terms such as interface circuit, interface, transceiver pin, and transceiver may be used interchangeably.

[0370] In some embodiments, the chip 7200 further includes one or more memories 7203 for storing instructions. Alternatively, all or part of the memories 7203 may be located outside the chip 7200.

[0371] The present disclosure also proposes a storage medium having instructions stored thereon. When the instructions are executed on the communication device 7100, the communication device 7100 executes 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 is not limited thereto and may also be a storage medium readable by other devices. Optionally, the storage medium may be a non-transitory storage medium, but is not limited thereto and may also be a temporary storage medium.

[0372] The present disclosure also provides a program product, which, when executed by the communication device 7100, enables the communication device 7100 to perform any of the above methods. Optionally, the program product is a computer program product.

[0373] The present disclosure also proposes a computer program, which, when executed on a computer, causes the computer to perform any one of the above methods.

Claims

1. A communication method, characterized in that: The method comprises: The AI ​​function or AI model of the terminal is updated, and a first test is performed on the updated AI function or AI model.

2. The method according to claim 1, characterized in that The first test is performed on the updated AI function or AI model in the following manner: receiving first information, where the first information is used to instruct to perform a first test on the updated AI function or AI model; Based on the first information, a first test is performed on the updated AI function or AI model.

3. The method according to claim 2, characterized in that Before receiving the first information, the method further includes: When the AI ​​function or AI model of the terminal is updated, second information is sent, where the second information is used by the network device to determine whether to perform a first test on the updated AI function or AI model.

4. The method according to claim 3, characterized in that The second information includes at least one of the following: The updated AI function or AI model undergoes a second test; The updated AI function or AI model is not subjected to a second test; The performance indicator value corresponding to the performance of the updated AI function or AI model; The updated AI function or AI model undergoes a second test, and the performance of the updated AI function or AI model meets the performance indicator; The updated AI function or AI model undergoes a second test, and the performance of the updated AI function or AI model does not meet the performance indicator; The identifier of the AI ​​function or AI model before the update; The application scenarios and / or corresponding application areas corresponding to the updated AI functions or AI models.

5. The method according to any one of claims 1 to 4, characterized in that: The first information is used to indicate that a first test is performed on the updated AI function or AI model using at least one of the following: Using the updated AI model to perform reasoning based on actual communication data to obtain a reasoning result; The updated AI model is used to perform reasoning based on preset data to obtain reasoning results.

6. The method according to any one of claims 1 to 5, characterized in that: The method further comprises: An actual communication result is determined, where the actual communication result is a result obtained by the terminal based on an actual communication environment.

7. The method according to claim 5 or 6, characterized in that: The method further comprises sending at least one of the following information: Reasoning results; Actual communication data; Actual communication results; Comparison results between actual communication results and inference results.

8. The method according to any one of claims 1 to 7, characterized in that: The method further comprises: Receive third information, where the third information is used to indicate confirmation of using the updated AI function or AI model, or to indicate refusal to use the updated AI function or AI model.

9. A communication method, characterized in that: The method comprises: Sending first information, where the first information is used to instruct a first test to be performed on an updated AI function or AI model.

10. The method according to claim 9, characterized in that Before sending the first information, the method further includes: Second information is received, where the second information is used to determine whether to perform a first test on an updated AI function or AI model of the terminal.

11. The method according to claim 10, characterized in that The second information includes at least one of the following: The updated AI function or AI model undergoes a second test; The updated AI function or AI model is not subjected to a second test; The performance indicator value corresponding to the performance of the updated AI function or AI model; The updated AI function or AI model undergoes a second test, and the performance of the updated AI function or AI model meets the performance indicator; The updated AI function or AI model undergoes a second test, and the performance of the updated AI function or AI model does not meet the performance indicator; The identifier of the AI ​​function or AI model before the update; Application scenarios corresponding to the updated AI functions or AI models.

12. The method according to any one of claims 9 to 11, characterized in that: The first information is used to indicate that a first test is performed on the updated AI function or AI model using at least one of the following: Using the updated AI model to perform reasoning based on actual communication data to obtain a reasoning result; The updated AI model is used to perform reasoning based on preset data to obtain reasoning results.

13. The method according to claim 12, characterized in that The method further includes receiving at least one of the following information: Reasoning results; Actual communication results; Actual communication data; Comparison results between actual communication results and inference results.

14. The method according to any one of claims 9 to 13, characterized in that: The method further comprises: Sending third information, where the third information is used to indicate confirmation of using the updated AI function or AI model, or to indicate refusal to use the updated AI function or AI model.

15. The method according to any one of claims 9 to 14, characterized in that: Sending first information to a terminal selected from at least one of the following: All terminals sending the second information; some of the terminals sending the second information; A terminal from a predefined set of terminals.

16. The method according to any one of claims 8 to 14, characterized in that: The third information is sent to all terminals that sent the second information.

17. A communication method, characterized in that: The method comprises: The network device sends first information, where the first information is used to instruct to perform a first test on the updated AI function or AI model; The terminal receives the first information; The terminal performs a first test on the updated AI function or AI model based on the first information.

18. A terminal, characterized in that: include: The processing module is used for updating the AI ​​function or AI model of the terminal and performing a first test on the updated AI function or AI model.

19. A network device, characterized in that: include: The communication module sends first information, where the first information is used to instruct a first test to be performed on an updated AI function or AI model of the terminal.

20. A terminal, characterized in that: include: one or more processors; The processor is used to execute the communication method according to any one of claims 1 to 8.

21. A network device, characterized in that: include: one or more processors; The processor is used to execute the communication method described in any one of claims 8 to 15.

22. A communication system, characterized in that: The invention comprises a terminal and a network device, wherein the terminal is configured to implement the communication method according to any one of claims 1 to 8, and the network device is configured to implement the communication method according to any one of claims 9 to 16.

23. A storage medium storing instructions, characterized in that: When the instruction is executed on a communication device, the communication device is caused to execute the communication method according to any one of claims 1-8 and 9-16.

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