Communication method, communication device and communication system

Abstract

The invention provides a communication method, communication equipment and a communication system, and relates to the technical field of communication. The method comprises the following steps: a first network node sends first information to a second network node, the first information can be used for indicating a first AI function, such as a first AI function with an available AI model or a first AI function without the available AI model, so that the second network node can determine whether to activate the first AI function according to the first information; for example, for a first AI function without an available AI model, activation processing may not be performed. Therefore, the situation that the network activates the AI function without the available AI model can be reduced.

Description

Communication method, communication device and communication system TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of communication, and in particular to a communication method, a communication device and a communication system. BACKGROUND

[0002] In recent years, the Artificial Intelligence (AI) technology has made constant breakthroughs in many fields. The continuous development of intelligent voice, computer vision and other fields not only brings a variety of applications to intelligent terminals, but also has wide application in education, transportation, home, medical care, retail, security and other fields, bringing convenience to people's life and promoting the industrial upgrading of various industries. AI technology is also accelerating the cross-penetration with other disciplines, and its development integrates knowledge from different disciplines, and also provides a new direction and method for the development of different disciplines.

[0003] SUMMARY

[0004] The present disclosure provides a communication method, a communication device and a communication system, which can reduce the occurrence of the situation that network activation has no available AI model of AI function.

[0005] The first aspect of the present disclosure provides a communication method, executed by a first network node, comprising: sending first information to a second network node; wherein the first information is used to indicate a first AI function.

[0006] The second aspect of the present disclosure provides a communication method, executed by a second network node, comprising: receiving first information sent by a first network node; wherein the first information is used to indicate a first AI function.

[0007] The third aspect of the present disclosure provides a first network node, comprising: a transceiver module configured to send first information to a second network node; wherein the first information is used to indicate a first AI function.

[0008] The fourth aspect of the present disclosure provides a second network node, comprising: a transceiver module configured to receive first information sent by a first network node; wherein the first information is used to indicate a first AI function.

[0009] The fifth aspect of the present disclosure provides a communication device, comprising: one or more processors; wherein the processor is configured to execute the method of the first aspect, or is configured to execute the method of the second aspect.

[0010] The sixth aspect of the present disclosure provides a communication system, comprising: a first network node and a second network node; the first network node performs the method of the first aspect, and the second network node performs the method of the second aspect.

[0011] The seventh aspect of the present disclosure provides a computer storage medium, wherein the computer storage medium stores computer executable instructions; the computer executable instructions are executed by a processor to implement the method of the first aspect or the second aspect.

[0012] The eighth aspect of the present disclosure provides a computer program product, wherein the computer program product stores a computer program; the computer program is executed by a processor to implement the method of the first aspect or the second aspect.

[0013] Additional aspects and advantages of the present disclosure will be made apparent from the following description of embodiments, which will be given with reference to the attached drawings. BRIEF DESCRIPTION OF DRAWINGS

[0014] The above and / or additional aspects and advantages of the present disclosure will become apparent and be readily appreciated from the following description of embodiments, taken in conjunction with the accompanying drawings.

[0015] Fig. 1 is a schematic diagram of an architecture of a communication system according to an embodiment of the present disclosure;

[0016] Fig. 2 is a schematic diagram of a flow of a communication method according to an embodiment of the present disclosure;

[0017] Fig. 3 is a schematic diagram of a flow of a communication method according to an embodiment of the present disclosure;

[0018] Fig. 4 is a schematic diagram of a flow of a communication method according to an embodiment of the present disclosure;

[0019] Fig. 5 is a schematic diagram of a flow of a communication method according to an embodiment of the present disclosure;

[0020] Fig. 6 is a block diagram of a first network node according to an embodiment of the present disclosure;

[0021] Fig. 7 is a block diagram of a first network node according to an embodiment of the present disclosure;

[0022] Fig. 8 is a schematic diagram of a structure of a communication device according to an embodiment of the present disclosure;

[0023] Fig. 9 is a schematic diagram of a structure of a chip according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0024] Embodiments of the present disclosure are described below in detail, examples of which are shown in the drawings, wherein the same or similar notations represent the same or similar elements or elements having the same or similar functions throughout. The embodiments described below are exemplary and are intended to explain the present disclosure, and are not understood as limiting the present disclosure. It should be noted that the embodiments of the present disclosure and the features in the embodiments can be combined with each other without conflict, if necessary.

[0025] For ease of understanding, first introduce the terms related to the embodiments of the present disclosure.

[0026] 1, Artificial intelligence (AI) model

[0027] Machine learning algorithm is one of the most important implementation methods of artificial intelligence technology. Machine learning can obtain an AI model through a large amount of training data, and the AI model can be used to predict events. In many fields, the AI model trained by machine learning can obtain very accurate prediction results.

[0028] 2, AI functionality

[0029] Wireless communication networks can use AI functionality for prediction and inference to improve system performance. An AI functionality implements a specific function and can include one or more AI models. The training of an AI model requires a large amount of data, and different application scenarios require different data. Application scenarios can include beam management, channel state information (CSI) reporting, CSI compression, positioning, handover, mobility management, and wireless resource management, etc. Each AI model corresponds to a set of metadata, which can include the performance, architecture, parameters, identification, application scenario, and working conditions of the AI model. The inference of the AI model can be run on the terminal side or on the network side. The generalization performance of the AI model is limited, and a specific AI model can only achieve good performance under specific application conditions. The application conditions are determined by the training data used to train the AI model.

[0030] The management of AI functionality includes activation, deactivation, and switching of AI functionality, etc.

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

[0032] In a first aspect, the embodiments of the present disclosure propose a communication method, executed by a first network node, comprising: sending first information to a second network node; wherein the first information is used to indicate a first AI functionality.

[0033] By applying the technical solutions of the present disclosure, the occurrence of the situation that network activation has no available AI model for AI function can be reduced.

[0034] In some embodiments of the first aspect, the first AI function has or has no available AI model.

[0035] In some embodiments of the first aspect, it is determined that the first AI function has no available AI model according to at least one of the following:

[0036] No AI model corresponding to the first AI function is stored in the first network node;

[0037] The AI model corresponding to the first AI function stored in the first network node does not meet the application condition.

[0038] In some embodiments of the first aspect, the method further comprises: sending second information to the second network node; wherein the second information is used to indicate the application condition corresponding to the first AI function.

[0039] In some embodiments of the first aspect, the application condition indicated by the second information comprises one of the following:

[0040] The application condition of part of the AI models of all AI models corresponding to the first AI function;

[0041] The application condition of all AI models corresponding to the first AI function.

[0042] In some embodiments of the first aspect, the application condition comprises at least one of the following:

[0043] Network condition;

[0044] Terminal condition.

[0045] In some embodiments of the first aspect, the information used to determine the network condition comprises at least one of the following:

[0046] Cell type;

[0047] Network deployment scenario;

[0048] Wireless channel quality;

[0049] Frequency where the cell is located;

[0050] Location of the cell;

[0051] Distance between network devices;

[0052] Antenna configuration of the network device;

[0053] Power of the signal sent by the network device;

[0054] Numerology.

[0055] In some embodiments of the first aspect, the information used to determine the terminal condition comprises at least one of:

[0056] a speed of the terminal;

[0057] a power level of the terminal;

[0058] a power of the terminal;

[0059] a computing capability of the terminal;

[0060] a location of the terminal;

[0061] a service type of the terminal;

[0062] an antenna configuration of the terminal;

[0063] a rotation speed of the terminal;

[0064] a storage space of the terminal.

[0065] In some embodiments of the first aspect, the method further comprises: receiving third information sent by the second network node, wherein the third information is used to indicate at least one AI function; and determining whether the at least one AI function has an available AI model.

[0066] In some embodiments of the first aspect, the sending the first information to the second network node comprises: sending the first information to the second network node according to a result of whether the at least one AI function has an available AI model.

[0067] In some embodiments of the first aspect, the method further comprises: receiving fourth information sent by the second network node; and wherein the fourth information is used to indicate an activated AI function.

[0068] In some embodiments of the first aspect, the method further comprises: determining that the activated AI function does not have an available AI model, and performing one of the following behaviors:

[0069] not using any AI function;

[0070] continuing to use the AI function before the fourth information is received.

[0071] In a second aspect, the embodiments of the present disclosure provide a communication method, performed by a second network node, the method comprising: receiving first information sent by a first network node; and wherein the first information is used to indicate a first AI function.

[0072] By applying the technical solutions of the present disclosure, the situation that network activation has no available AI model of AI function can be reduced.

[0073] In combination with some embodiments of the second aspect, the first AI function has or does not have an available AI model.

[0074] In combination with some embodiments of the second aspect, the first AI function does not have an available AI model, which is determined by at least one of the following:

[0075] The first network node does not store an AI model corresponding to the first AI function;

[0076] The AI model corresponding to the first AI function stored in the first network node does not meet an application condition.

[0077] In combination with some embodiments of the second aspect, the method further comprises: receiving second information sent by the first network node; wherein the second information is used to indicate an application condition corresponding to the first AI function.

[0078] In combination with some embodiments of the second aspect, the application condition indicated by the second information comprises one of the following:

[0079] An application condition of part of AI models in all AI models corresponding to the first AI function;

[0080] An application condition of all AI models corresponding to the first AI function.

[0081] In combination with some embodiments of the second aspect, the application condition comprises at least one of the following:

[0082] A network condition;

[0083] A terminal condition.

[0084] In combination with some embodiments of the second aspect, the information used to determine the network condition comprises at least one of the following:

[0085] A cell type;

[0086] A network deployment scenario;

[0087] A wireless channel quality;

[0088] A frequency where the cell is located;

[0089] A location of the cell;

[0090] A distance between network devices;

[0091] An antenna configuration of the network device;

[0092] A power of a signal sent by the network device;

[0093] Numerology.

[0094] In some embodiments of the second aspect, the information used to determine the terminal condition comprises at least one of:

[0095] a speed of the terminal;

[0096] a power level of the terminal;

[0097] a power of the terminal;

[0098] a computing capability of the terminal;

[0099] a location of the terminal;

[0100] a service type of the terminal;

[0101] an antenna configuration of the terminal;

[0102] a rotation speed of the terminal;

[0103] a storage space of the terminal.

[0104] In some embodiments of the second aspect, the method further comprises: sending, to the first network node, third information, wherein the third information is used to indicate at least one AI function and cause the first network node to determine whether the at least one AI function has an available AI model.

[0105] In some embodiments of the second aspect, the first information is sent by the first network node according to a result of whether the at least one AI function has an available AI model.

[0106] In some embodiments of the second aspect, the method further comprises: sending, to the first network node, fourth information; wherein the fourth information is used to indicate an activated AI function.

[0107] In a third aspect, the embodiments of the present disclosure provide a first network node, comprising: a transceiver module configured to send, to a second network node, first information; wherein the first information is used to indicate a first AI function.

[0108] In a fourth aspect, the embodiments of the present disclosure provide a second network node, comprising: a transceiver module configured to receive first information sent by a first network node; wherein the first information is used to indicate a first AI function.

[0109] In a fifth aspect, an embodiment of the present disclosure provides a communication device, which can be a first network node or a second network node, comprising: one or more processors; wherein the processor of the first network node is configured to perform the method in the first aspect, and the processor of the second network node is configured to perform the method in the second aspect.

[0110] In a sixth aspect, an embodiment of the present disclosure provides a communication system, comprising: a first network node or a second network node; the first network node performs the method in the first aspect, and the second network node performs the method in the second aspect.

[0111] In a seventh aspect, an embodiment of the present disclosure provides a computer storage medium, wherein the computer storage medium stores computer executable instructions; when the computer executable instructions are executed by a processor, the method in the first aspect or the second aspect can be implemented.

[0112] In an eighth aspect, an embodiment of the present disclosure provides a computer program product, comprising a computer program, when the computer program is executed by a processor, the method in the first aspect or the second aspect can be implemented.

[0113] In a ninth aspect, an embodiment of the present disclosure provides a computer program, when the computer program is executed on a computer, the computer is enabled to perform the method in the first aspect or the second aspect.

[0114] In a tenth aspect, an embodiment of the present disclosure provides a chip or a chip system. The chip or the chip system comprises processing circuitry configured to perform the method in the first aspect or the second aspect.

[0115] It can be understood that the first network node, the second network node, the communication system and the storage medium are used to perform the method provided by the embodiments of the present disclosure. Therefore, the beneficial effects achieved thereby can refer to the beneficial effects in the corresponding method, which will not be described here.

[0116] In some embodiments, the communication method, the information processing method, the information sending method, the information receiving method and other terms can be replaced with each other, the communication device, the information processing device, the information sending device, the information receiving device and other terms can be replaced with each other, and the information processing system, the communication system, the information sending system, the information receiving system and other terms can be replaced with each other.

[0117] The embodiments of the present disclosure are not exhaustive, but only illustrate some embodiments, and are not specific limitations on the protection scope of the present disclosure. In the case of no contradiction, each step in an embodiment can be implemented as an independent embodiment, and the steps can be combined arbitrarily, for example, the scheme after removing part of the steps in an embodiment can also be implemented as an independent embodiment, and the order of the steps in an embodiment can be exchanged arbitrarily, in addition, the optional implementation in an embodiment can be combined arbitrarily; in addition, the embodiments can be combined arbitrarily, for example, part or all steps of different embodiments can be combined arbitrarily, an embodiment can be combined with optional implementation of other embodiments.

[0118] In each embodiment of the present disclosure, the terms and / or descriptions between the embodiments are consistent if there is no special description and logical conflict, and can be referred to each other, and the technical features in different embodiments can be combined to form new embodiments according to their inherent logical relationship.

[0119] The terms used in the embodiments of the present disclosure are only for the purpose of describing the specific embodiments, and not as a limitation on the present disclosure.

[0120] In the embodiments of the present disclosure, unless otherwise specified, the elements expressed in singular form, such as "one", "a", "the", "above", "said", "preceding", "this" and the like, can represent "one and only one", and can also represent "one or more", "at least one" and the like. For example, in the case of using articles such as "a", "an", "the" and the like in English, the noun after the article can be understood as singular expression, and can also be understood as plural expression.

[0121] In the embodiments of the present disclosure, "a plurality of" means two or more.

[0122] In some embodiments, the terms "at least one of", "at least one of", "at least one of", "one or more", "a plurality of", "multiple" and the like can be replaced with each other.

[0123] The description manner such as "at least one of A, B, C, …", "A and / or B and / or C, …" and the like in the embodiments of the present disclosure includes any one of A, B, C, … existing alone, and also includes any combination of any multiple of A, B, C, …, each of which can exist alone; for example, "at least one of A, B, C" includes a case of A alone, a case of B alone, a case of C alone, a case of combination of A and B, a case of combination of A and C, a case of combination of B and C, and a case of combination of A and B and C; for example, A and / or B includes a case of A alone, a case of B alone, and a case of combination of A and B.

[0124] In some embodiments, the description manner such as "A in a case, B in another case", "in response to a case A, in response to another case B" and the like can include the following technical solutions according to the case: A is executed regardless of B, that is, A in some embodiments; B is executed regardless of A, that is, B in some embodiments; A and B are selectively executed, that is, from A and B, execution is selected in some embodiments; A and B are both executed, that is, A and B in some embodiments. When there are more branches of A, B, C and the like, it is similar to the above.

[0125] The prefix words "first", "second" and the like in the embodiments of the present disclosure are only used to distinguish different description objects, and do not constitute limitation on the position, order, priority, quantity or content of the description objects. The description of the description objects should refer to the description in the context of the claims or embodiments, and should not constitute redundant limitation because of the use of the prefix words. For example, the description object is "field", and the ordinal words before "field" in "first field" and "second field" do not limit the position or order between "fields", and "first" and "second" do not limit whether the "fields" modified thereby are in the same message or not, nor limit the order of "first field" and "second field". For another example, the description object is "level", and the ordinal words before "level" in "first level" and "second level" do not limit the priority between "levels". For another example, the quantity of the description object is not limited by the ordinal words, and can be one or more. For example, "first device", wherein the quantity of "device" can be one or more. In addition, the objects modified by different prefix words can be the same or different, for example, the description object is "device", and "first device" and "second device" can be the same device or different devices, and the types thereof can be the same or different; for another example, the description object is "information", and "first information" and "second information" can be the same information or different information, and the contents thereof can be the same or different.

[0126] In some embodiments, "including A", "containing A", "for indicating A", "carrying A" can be interpreted as directly carrying A, or indirectly indicating A.

[0127] In some embodiments, the terms “in response to,” “in response to determining,” “in the event that,” “when,” “if,” “upon,” and the like can be replaced with each other.

[0128] In some embodiments, the terms “greater than,” “greater than or equal to,” “not less than,” “more than,” “more than or equal to,” “not less than,” “higher than,” “higher than or equal to,” “not lower than,” “above,” and the like can be replaced with each other, and the terms “less than,” “less than or equal to,” “not greater than,” “fewer than,” “fewer than or equal to,” “not more than,” “lower than,” “lower than or equal to,” “not higher than,” “below,” and the like can be replaced with each other.

[0129] In some embodiments, an apparatus and the like can be interpreted as an entity, and can also be interpreted as virtual, and the name thereof is not limited to the name described in the embodiments, and the terms “apparatus,” “equipment,” “device,” “circuit,” “network element,” “node,” “function,” “unit,” “section,” “system,” “network,” “chip,” “chip system,” “entity,” “subject,” and the like can be replaced with each other.

[0130] In some embodiments, “network” can be interpreted as an apparatus (for example, an access network device, a core network device, and the like) included in the network.

[0131] 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,” “carrier,” “component carrier,” “bandwidth part (BWP),” and the like can be used interchangeably.

[0132] 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," "Narrow Band Internet of Things (NB-IoT) device," and the like can be replaced with each other.

[0133] In some embodiments, an access network device, a core network device, or a network device can be replaced with a terminal. For example, for a structure in which communication between an access network device, a core network device, or a network device and a terminal is replaced with communication between a plurality of terminals (for example, also referred to as device-to-device (D2D), vehicle-to-everything (V2X), and the like), embodiments of the present disclosure can also be applied. In this case, a structure in which a terminal has all or part of the functions of an access network device can also be provided. Furthermore, the language of "uplink," "downlink," and the like can also be replaced with language corresponding to communication between terminals (for example, "side"). For example, an uplink channel, a downlink channel, and the like can be replaced with a side channel, and an uplink, a downlink, and the like can be replaced with a sidelink.

[0134] In some embodiments, a terminal can be replaced with an access network device, a core network device, or a network device. In this case, a structure in which an access network device, a core network device, or a network device has all or part of the functions of a terminal can also be provided.

[0135] In some embodiments, the data, information, etc. can be obtained in compliance with the laws and regulations of the country where the location is situated.

[0136] In some embodiments, the data, information, etc. can be obtained after obtaining the consent of the user.

[0137] In some embodiments, the threshold mentioned in the embodiments can be a numerical value, a constant, or some fixed value, etc.

[0138] In addition, each element, each row, or each column in the table of the embodiments of the present disclosure can be implemented as an independent embodiment, and any combination of any element, any row, or any column can also be implemented as an independent embodiment.

[0139] The correspondence shown in each table in the present disclosure can be configured or predefined. The values of the information in each table are merely examples, and other values can be configured, and the present disclosure is not limited thereto. When configuring the correspondence between the information and each parameter, it is not necessarily required to configure all the correspondences shown in each table. For example, the correspondences shown in some rows in the table in the present disclosure can also not be configured. For another example, the above table can be appropriately deformed, adjusted, etc., such as splitting, merging, etc. The names of the parameters shown in the titles of the above tables can also use other names understandable by the communication device, and the values or representations of the parameters can also use other values or representations understandable by the communication device. The above tables can also use other data structures when implemented, such as arrays, queues, containers, stacks, linear tables, pointers, linked lists, trees, graphs, structures, classes, heaps, hash tables, etc.

[0140] The predefinition in the present disclosure can be understood as definition, predefinition, storage, pre-storage, pre-negotiation, pre-configuration, solidification, or pre-burning.

[0141] The communication method, communication device, and communication system provided by the present disclosure will be described in detail below with reference to the accompanying drawings.

[0142] FIG. 1 shows a structure diagram of a communication system according to an embodiment of the present disclosure. As shown in FIG. 1, the system architecture can include a first network node 11 and a second network node 12.

[0143] In some embodiments, the first network node 11 and the second network node 12 can refer to key components in a communication network, can be nodes in a communication network, and can be responsible for data transmission, exchange, routing, or signal processing, etc.

[0144] In some examples, the first network node 11 can be a network device or a terminal, etc.

[0145] In some examples, the second network node 12 can be a network device or a terminal, etc.

[0146] In some examples, the network device can be an entity for transmitting or receiving signals on the network side. For example, the network device can be a base station or a core network node or a server, etc., and specifically can be a communication satellite, an evolved NodeB (eNB), a transmission reception point (TRP), a next generation NodeB (gNB) in an NR system, a base station in other future mobile communication systems, or an access node in a wireless fidelity (WiFi) system, etc. Embodiments of the present disclosure do not limit the specific technology and specific device form adopted by the network device. The network device provided by the embodiments of the present disclosure can be composed of a central unit (CU) and a distributed unit (DU), wherein the CU can also be referred to as a control unit (control unit). The CU-DU structure can split the protocol layers of the network device, for example, the base station, and the functions of part of the protocol layers are controlled by the CU, and the functions of the remaining part or all of the protocol layers are distributed in the DU and controlled by the CU.

[0147] In some examples, the terminal can be referred to as a terminal device, a user equipment, a mobile station (MS), a mobile terminal (MT), an NB-IoT terminal, etc. The terminal can also be a car with communication function, a smart car, a mobile phone, a wearable device, a tablet computer (Pad), a computer with wireless transceiver function, a virtual reality device, an augmented reality 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 smart grid, a wireless terminal device in transportation safety, a wireless terminal device in smart city, a wireless terminal device in smart home, etc. Embodiments of the present disclosure do not limit the specific technology and specific device form adopted by the terminal.

[0148] It can be understood that the communication system described in the embodiments of the present disclosure is for more clearly illustrating the technical solutions of the embodiments of the present disclosure, and does not constitute a limitation on the technical solutions proposed by the embodiments of the present disclosure. Those skilled in the art can know that, with the evolution of system architecture and the appearance of new business scenarios, the technical solutions proposed by the embodiments of the present disclosure are also applicable to similar technical problems.

[0149] The following embodiments of the present disclosure can be applied to the communication system shown in FIG. 1 or part of the subject, but are not limited thereto. The subjects shown in FIG. 1 are illustrative, and the communication processing system can include all or part of the subjects in FIG. 1, or other subjects other than FIG. 1, the number and form of each subject is arbitrary, the connection relationship between each subject is illustrative, each subject can not be connected or can be connected, the connection can be in any way, can be direct connection or indirect connection, can be wired connection or wireless connection.

[0150] Embodiments of the present disclosure can be applied to satellite communication, 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 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 (Bluetooth (registered trademark)), Public Land Mobile Network (PLMN) network, Device-to-Device (D2D) system, Machine to Machine (M2M) system, Internet of Things (IoT) system, Vehicle-to-Everything (V2X), system using other communication methods, next-generation system expanded based on them, and the like. Further, a plurality of systems can be applied in combination (for example, combination of LTE or LTE-A and 5G, and the like).

[0151] In some examples, the first network node 11 can be a terminal, and the second network node 12 can be a network device such as a base station or a core network node or a server.

[0152] The management of the AI function is controlled by the network side, and the terminal cannot control the selection, activation or deactivation of the AI function by itself. Therefore, when the network activates an AI function, the terminal can select a suitable AI model within the corresponding AI function, but the application condition of the AI model in this AI function may not be met, which is determined by the training data of the trained AI model, that is, the AI function does not have a usable AI model, resulting in the network activating an AI function without a usable AI model, and further causing the activated AI function to not work normally and not provide the expected service.

[0153] To solve the above problem, by applying the method of the embodiment, the terminal can send first information to the network device, which can be used to indicate the first AI function, such as indicating whether the first AI function has a usable AI model, and then the network device can determine whether to activate the first AI function according to the first information, such as for the first AI function without a usable AI model, no activation processing can be performed. Thus, the situation of the network activating an AI function without a usable AI model can be reduced.

[0154] Further, in order to illustrate the specific execution process of the above communication system, FIG. 2 shows a schematic diagram of a communication method according to an embodiment of the present disclosure. The method is applied to the above communication system, as shown in FIG. 2, and can include the following steps:

[0155] Step S201, the second network node sends third information to the first network node.

[0156] In some embodiments, the first network node receives the third information sent by the second network node.

[0157] In some embodiments, the third information is used to indicate at least one AI function, which can be applied to the processes of the mobile communication system such as beam management, channel state information (CSI) reporting, CSI compression, terminal positioning, cell switching, mobility management, and wireless resource management. In some examples, the first network node can determine whether the indicated at least one AI function has a usable AI model.

[0158] In some embodiments, the first network node can be a terminal, and the second network node can be a network device such as a base station or a core network node or a server. For example, the network device sends the third information to the terminal, and correspondingly, the terminal receives the third information sent by the network device, which can be indication information or signaling messages, etc. For example, the network device indicates at least one AI function to the terminal through the third information, so that the terminal determines whether these AI functions have a usable AI model. In some examples, the third information can be carried by at least one of the following:

[0159] Radio Resource Control (RRC) message; Downlink Control Information (DCI); Media Access Control (MAC) control element (CE); Master Information Block (MIB); System Information Block (SIB).

[0160] In step S202, the first network node determines whether the at least one AI function indicated by the third information has an available AI model.

[0161] In some embodiments, the first network node can determine the AI model corresponding to the indicated AI function, such as one or more AI models included in the AI function, and determine whether the indicated AI function has an available AI model according to the AI model.

[0162] In some examples, if the AI model corresponding to the AI function is not stored in the first network node, the AI function does not have an available AI model.

[0163] In some examples, if the AI model corresponding to the AI function is stored in the first network node, and the AI model does not meet the application condition, i.e., the condition required by the AI model is inconsistent with the current condition, the AI function does not have an available AI model. The application condition is determined by the training data of the trained AI model.

[0164] In some examples, each AI model has a respective application condition corresponding thereto, wherein the application condition is determined by the training data of the trained AI model.

[0165] For example, the following specific application examples A1 to E1 are given to illustrate the training data of the trained AI model.

[0166] A1. In the beam management process, the terminal can reduce the number of measured beams, and the terminal or network device obtains the optimal beam through AI model inference. Beam prediction includes spatial beam prediction and time domain beam prediction. In spatial beam prediction, the terminal measures a small number of beams and predicts the measurement results of other beams. In time domain beam prediction, the terminal predicts future beam measurement results according to historical beam measurement results. The data for training the AI model can include beam measurement results, beam identifiers, the measurement results of the strongest K beams and beam identifiers, and the time of obtaining the beam measurement results. The measured beams can be configured by the network device.

[0167] B1. In the CSI reporting process, the terminal can compress the CSI measurement result through the AI model, report the compressed CSI measurement result to the network device, and the network device restores the original CSI measurement result through the AI model after receiving it. The number of signaling bits required in the reporting process is reduced. The network device can also predict future CSI according to the historical CSI measurement results reported by the terminal.

[0168] C1. In the positioning process, the terminal can predict the accurate position according to the limited measurement result. The model training data can include channel impulse response measurement result, terminal position information, and positioning reference signal (PRS) measurement result.

[0169] D1. In the mobility management process, the terminal can predict cell measurement results, handover target cells, or mobility events. The terminal can predict future cell measurement results, which can be referred to as time domain prediction. Or, predict the measurement result of an unmeasured cell, which can be referred to as spatial domain prediction. Mobility events include measurement reporting conditions being met, handover failures, cell dwell times, radio link failures, etc. The AI model training data can include measurement results of serving cells, measurement results of target cells, time, terminal position, source and target cells, etc.

[0170] E1. In CSI compression, the AI model training data can include CSI measurement results, time of obtaining CSI measurement results, etc.

[0171] In some examples, if the first network node stores multiple AI models corresponding to an AI function, and the application conditions of these AI models are not met, the AI function has no available AI model. The application condition is determined by the training data of the AI model.

[0172] In some examples, if the first network node stores multiple AI models corresponding to an AI function, and the application conditions of some AI models (such as one or more AI models) in these AI models are not met, the AI function has no available AI model. The application condition is determined by the training data of the AI model. For example, if the application conditions of one or more AI models of the AI function corresponding to these AI models are not met, the AI function has no available AI model.

[0173] In some examples, if multiple AI models corresponding to the AI function are stored in the first network node, and the application condition of part of the AI models (such as one or more AI models) is met, the AI function has available AI models. Wherein, the application condition is determined by the training data of the AI model. For example, part of the AI models corresponding to the AI function do not meet the application condition, and the application condition of the remaining one or more AI models is met, and the AI function has available AI models.

[0174] In some embodiments, the application condition can include at least one of the following A2 to B2:

[0175] A2, network condition, i.e. the condition of the network side.

[0176] B2, terminal condition, i.e. the condition of the terminal side.

[0177] In some examples, the information for determining the network condition (A2) includes at least one of the following A3 to I3:

[0178] A3, cell type, such as Macro, Micro, dense urban, etc.

[0179] B3, network deployment scenario, such as indoor deployment scenario or outdoor deployment scenario. Indoor deployment scenario refers to deploying network equipment inside network buildings, such as offices, shopping malls, hotels, residences or schools, etc. Outdoor deployment scenario: involves deploying network infrastructure in outdoor environments such as open spaces or urban streets, such as urban public Wi-Fi, mobile communication base stations, etc.

[0180] C3, wireless channel quality, such as the wireless channel quality can be determined by Reference Signal Receiving Power (RSRP), Reference Signal Received Quality (RSRQ) or Signal Interference Noise Ratio (SINR), etc.

[0181] D3, frequency of the cell, such as carrier frequency (basic frequency used by the cell to transmit signals), frequency point, frequency band (width of the frequency range used by the cell, which determines the data transmission rate and system capacity), etc.

[0182] E3, location of the cell.

[0183] F3, distance between network devices, such as the distance between base stations.

[0184] G3, an antenna configuration of the network device, such as a number of ports, a number of Multiple-Input Multiple-Output (MIMO) layers, and the like.

[0185] H3, a power at which the network device transmits a signal, such as a power parameter at which a base station transmits a signal to a terminal.

[0186] I3, a numerology, such as a set of underlying physical layer parameters related to a structure of a wireless communication resource, which can be used to determine a Subcarrier Spacing (SCS), a Slot structure, a Symbol length, and the like.

[0187] In some examples, the network condition can be bound with an identification (ID) of the network condition, and the network can indicate the network-side condition, i.e., the network condition, by providing the ID. When the terminal uses the AI model to perform inference, it is determined whether the current network indicates the ID is consistent with the network ID when the AI model training data is collected. If not, it is determined that the network condition is not met, i.e., the application condition of the AI model is not met.

[0188] In some examples, the information used to determine the terminal condition (B2) includes at least one of the following A4 to I4:

[0189] A4, a speed of the terminal.

[0190] B4, an amount of power of the terminal, such as a current remaining amount of power of the terminal.

[0191] C4, a power of the terminal, such as a power level used by the terminal when transmitting a signal.

[0192] D4, a computing capability of the terminal, such as a computing capability of the terminal measured by a number of Floating Point Operations Per Second (FLOPS).

[0193] E4, a location of the terminal, such as a geographic location of the terminal, or a location of the terminal in a cell, and the like.

[0194] F4, a type of service of the terminal, such as a service type of audio, video, multimedia, voice, and the like.

[0195] G4, an antenna configuration of the terminal, such as a number of ports, and the like.

[0196] H4, a rotation speed of the terminal.

[0197] I4, a storage space of the terminal, such as can be measured by bits, and an 8-bit storage unit can store 1 byte of information.

[0198] In some embodiments, whether the application condition of the AI model corresponding to the AI function is met, i.e., whether the condition required by the AI model is consistent with the current condition, can be determined by the information for determining the network condition (A2) and / or the information for determining the terminal condition (B2) described above.

[0199] In step S203, the first network node sends the first information to the second network node.

[0200] In some embodiments, the first information can be used to indicate the first AI function, which can be the AI function in the at least one AI function indicated by the third information.

[0201] In some embodiments, the process of the first network node sending the first information to the second network node can include: the first network node sending the first information to the second network node according to whether the at least one AI function (indicated by the third information) has an available AI model.

[0202] In some examples, the first AI function has or does not have an available AI model. For example, the first network node can indicate to the second network node whether the first AI function has an available AI model through the first information, or the first network node can indicate to the second network node the first AI function having an available AI model through the first information, or the first network node can indicate to the second network node the first AI function not having an available AI model through the first information, etc.

[0203] In some examples, taking the first network node as a terminal and the second network node as a network device as an example, the management of the AI function is controlled by the network device, and the terminal cannot control the selection, activation or deactivation of the AI function by itself. Therefore, when the network device activates an AI function, the terminal can select a suitable AI model within the corresponding AI function, but it is possible that the terminal does not have an AI model meeting the application condition in this AI function, resulting in the network activating an AI function without an available AI model. The present embodiment provides an AI function coordination scheme, and the terminal can send the first information to the network device, which can be used to indicate the first AI function, such as indicating whether the first AI function has an available AI model, and then the network device can determine whether to activate the first AI function according to the first information, such as not activating the first AI function without an available AI model. Thus, the situation of the network activating an AI function without an available AI model can be reduced.

[0204] In some embodiments, the first network node can determine that the first AI function does not have an available AI model according to at least one of A5 to B5 below:

[0205] A5, the AI model corresponding to the first AI function is not stored in the first network node. For example, if the AI model corresponding to the first AI function is not stored in the first network node, it can be determined that the first AI function does not have an available AI model.

[0206] B5, the AI model corresponding to the first AI function stored in the first network node does not meet the application condition. For example, the AI model corresponding to the first AI function is stored in the first network node, but the application condition of the AI model does not meet, i.e. the condition required by the AI model is inconsistent with the current condition, wherein the condition can be network condition and / or terminal condition, then it can be determined that the first AI function does not have an available AI model.

[0207] In some embodiments, the first network node sends second information to the second network node; wherein the second information can be used to indicate the application condition corresponding to the first AI function. In some examples, the application condition can be a network condition, and can be indicated by a corresponding ID.

[0208] In some embodiments, the application condition indicated by the second information includes one of the following A6 to B6:

[0209] A6, the application condition of part of the AI models (such as one or more AI models) in all AI models corresponding to the first AI function. For example, the first network node indicates the application condition corresponding to the first AI function to the second network node through the second information, which can be the application condition of any one AI model (corresponding to the first AI function) already stored in the first network node, or the application condition of any two AI models (corresponding to the first AI function) already stored in the first network node, or the application condition of any three AI models (corresponding to the first AI function) already stored in the first network node, and so on.

[0210] B6, the application condition of all AI models corresponding to the first AI function. For example, the first network node indicates the application condition corresponding to the first AI function to the second network node through the second information, which can be the application condition set of all AI models (corresponding to the first AI function) already stored in the first network node.

[0211] In some embodiments, when the first AI function does not have an available AI model due to the application condition of the AI model corresponding to the first AI function not meeting (i.e. B5 above), the first network node can send second information to the second network node, which can be used to indicate the application condition corresponding to the first AI function.

[0212] In some embodiments, when the first AI function does not have an available AI model due to the first network node not storing an AI model corresponding to the first AI function (i.e., A5 described above), the first network node does not send the second information to the second network node.

[0213] In some embodiments, the first network node can receive fourth information sent by the second network node; wherein the fourth information is used to indicate the activated AI function. For example, taking the first network node as a terminal and the second network node as a network device as an example, the management of AI functions is controlled by the network device, and the network device can send the fourth information to the terminal to indicate the activated AI function.

[0214] In some embodiments, when the first network node determines that the activated AI function does not have an available AI model, one of the following A7 to B7 can be performed:

[0215] A7, the first network node does not use any AI function, avoids making wrong decisions, and reduces resource consumption. For example, if there is no suitable AI model to support a particular function, continuing to use may make decisions based on inaccurate or unverified data, which can lead to wrong actions or outputs, affecting the overall performance and reliability of the system.

[0216] B7, the first network node continues to use the AI function before receiving the fourth information (used to indicate the activated AI function), which can avoid errors and ensure the execution of previous services.

[0217] The communication method related to the present embodiment can include at least one of steps S201-S203. For example, step S201 can be implemented as an independent embodiment, step S202 can be implemented as an independent embodiment, and step S203 can be implemented as an independent embodiment. In addition, part or all of the steps S201-S203 can be combined to implement an independent embodiment, which is not limited by the present embodiment.

[0218] For the present embodiment, the first network node sends the first information to the second network node, wherein the first information can be used to indicate the first AI function, such as the first AI function with an available AI model or the first AI function without an available AI model, and then the second network node can determine whether to activate the first AI function according to the first information, such as for the first AI function without an available AI model, no activation processing can be performed. Thus, the situation that the network activates an AI function without an available AI model can be reduced.

[0219] In order to illustrate the specific execution process of the terminal, FIG. 3 shows a flowchart of a communication method according to an embodiment of the present disclosure. Applied to the execution of the first network node side, it can include the following steps.

[0220] In step S301, the first network node sends first information to the second network node.

[0221] In some embodiments, the first information can be used to indicate the first AI function.

[0222] In some embodiments, the first AI function has or does not have an available AI model.

[0223] In some embodiments, the first network node can determine that the first AI function does not have an available AI model according to at least one of the following:

[0224] The AI model corresponding to the first AI function is not stored in the first network node;

[0225] The AI model corresponding to the first AI function stored in the first network node does not meet the application condition.

[0226] In some embodiments, the first network node sends second information to the second network node; wherein the second information can be used to indicate the application condition corresponding to the first AI function.

[0227] In some embodiments, the application condition indicated by the second information can include one of the following:

[0228] The application condition of part of the AI models of all the AI models corresponding to the first AI function;

[0229] The application condition of all the AI models corresponding to the first AI function.

[0230] In some embodiments, the application condition can include at least one of the following:

[0231] Network condition; terminal condition.

[0232] In some embodiments, the information used to determine the network condition includes at least one of the following:

[0233] Cell type; network deployment scenario; wireless channel quality; frequency where the cell is located; location of the cell; distance between network devices; antenna configuration of the network device; power of the signal sent by the network device; numerology.

[0234] In some embodiments, the information used to determine the terminal condition includes at least one of the following:

[0235] Speed of the terminal; power of the terminal; power of the terminal; computing power of the terminal; location of the terminal; service type of the terminal; antenna configuration of the terminal; rotation speed of the terminal; storage space of the terminal.

[0236] In some embodiments, the first network node receives third information sent by the second network node, wherein the third information is used to indicate at least one AI function; and the first network node determines whether the at least one AI function has an available AI model.

[0237] In some embodiments, the first network node sends the first information to the second network node, comprising: sending the first information to the second network node according to the result of whether the at least one AI function has an available AI model.

[0238] In some embodiments, the first network node receives fourth information sent by the second network node; wherein the fourth information is used to indicate an activated AI function.

[0239] In some embodiments, when it is determined that the activated AI function does not have an available AI model, the first network node performs one of the following behaviors:

[0240] The first network node does not use any AI function; and the first network node continues to use the AI function before receiving the fourth information.

[0241] For a specific example of the present embodiment, refer to the corresponding description of the embodiments in FIGS. 1-2, which will not be repeated here.

[0242] For the present embodiment, the first network node sends the first information to the second network node, wherein the first information can be used to indicate the first AI function, such as the first AI function with an available AI model or the first AI function without an available AI model, so that the second network node can determine whether to activate the first AI function according to the first information, such as not activating the first AI function without an available AI model. Thus, the situation of the network activating an AI function without an available AI model can be reduced.

[0243] FIG. 4 shows a flow diagram of a communication method according to an embodiment of the present disclosure. As shown in FIG. 4, the method is applied to the second network node side and can include the following steps.

[0244] Step S401, the second network node receives first information sent by the first network node.

[0245] In some embodiments, the first information can be used to indicate the first AI function.

[0246] In some embodiments, the first AI function has or does not have an available AI model.

[0247] In some embodiments, the determination that the first AI function does not have an available AI model is made by at least one of the following:

[0248] The first network node does not store an AI model corresponding to the first AI function;

[0249] The AI model corresponding to the first AI function stored in the first network node does not meet an application condition.

[0250] In some embodiments, the second network node receives second information sent by the first network node;

[0251] The second information is used to indicate an application condition corresponding to the first AI function.

[0252] In some embodiments, the application condition indicated by the second information includes one of the following:

[0253] An application condition of part of AI models in all AI models corresponding to the first AI function;

[0254] An application condition of all AI models corresponding to the first AI function.

[0255] In some embodiments, the application condition includes at least one of the following:

[0256] A network condition; a terminal condition.

[0257] In some embodiments, the information used to determine the network condition includes at least one of the following:

[0258] A cell type; a network deployment scenario; a wireless channel quality; a frequency where the cell is located; a location of the cell; a distance between network devices; an antenna configuration of the network device; a power of a signal sent by the network device; a numerology.

[0259] In some embodiments, the information used to determine the terminal condition includes at least one of the following:

[0260] A speed of the terminal; a power of the terminal; a power of the terminal; a computing capability of the terminal; a location of the terminal; a service type of the terminal; an antenna configuration of the terminal; a rotation speed of the terminal; a storage space of the terminal.

[0261] In some embodiments, the first network node sends third information to the first network node, wherein the third information is used to indicate at least one AI function, and causes the first network node to determine whether the at least one AI function has an available AI model.

[0262] In some embodiments, the first information is sent by the first network node according to a result of whether the at least one AI function has an available AI model.

[0263] In some embodiments, the second network node sends fourth information to the first network node; wherein the fourth information is used to indicate an activated AI function.

[0264] The description of the specific examples in this embodiment can be referred to the corresponding description of the embodiments in FIG. 1 to FIG. 3, which will not be repeated here.

[0265] For this embodiment, the first network node sends the first information to the second network node, where the first information can be used to indicate the first AI function, such as the first AI function with available AI model or the first AI function without available AI model, and then the second network node can determine whether to activate the first AI function according to the first information, such as for the first AI function without available AI model, no activation processing can be performed. Thus, the situation that the network activates the AI function without available AI model can be reduced.

[0266] FIG. 5 shows a flow diagram of a communication method according to an embodiment of the present disclosure. Taking the first network node as a terminal and the second network node as a network device as an example, as shown in FIG. 5, the method comprises:

[0267] Step S501, the network device sends the third information to the terminal.

[0268] In some embodiments, the terminal receives the third information sent by the network device.

[0269] In some embodiments, the third information is used to indicate at least one AI function.

[0270] Step S502, the terminal determines whether the at least one AI function indicated by the third information has available AI model.

[0271] In some embodiments, the terminal can determine the AI model corresponding to the indicated AI function, such as one or more AI models included in the AI function, and determine whether the indicated AI function has available AI model according to the AI model.

[0272] Step S503, the terminal sends the first information to the network device.

[0273] In some embodiments, the network device receives the first information sent by the terminal.

[0274] In some embodiments, the first information can be used to indicate the first AI function, and can include whether the first AI function has available AI model.

[0275] In some examples, the terminal can report the first AI function with available AI model to the network device through the first information, and can also report the first AI function without available AI model.

[0276] In some examples, the terminal can determine that the first AI function does not have available AI model according to any of the following conditions,

[0277] The terminal does not store the AI model corresponding to the first AI function;

[0278] The condition required by the AI model corresponding to the first AI function stored by the terminal is inconsistent with the current condition, which can be a network condition or a terminal condition.

[0279] In some examples, the terminal can send the application condition corresponding to the AI model corresponding to the first AI function that has been stored to the network device through the second information. In some examples, the application condition can be a network condition, which can be indicated by an ID.

[0280] In some examples, the application condition indicated by the second information includes one of the following:

[0281] The application condition of part of the AI models in all AI models corresponding to the first AI function;

[0282] The application condition of all AI models corresponding to the first AI function.

[0283] In some embodiments, when there is no available AI model for the first AI function due to the application condition of the AI model corresponding to the first AI function not being met, the terminal can send the second information to the network device, which can be used to indicate the application condition corresponding to the first AI function.

[0284] In some embodiments, when there is no available AI model for the first AI function due to the AI model corresponding to the first AI function not being stored in the first network node, the terminal does not send the second information to the network device.

[0285] In some embodiments, the terminal can receive the fourth information sent by the network device; wherein the fourth information is used to indicate the activated AI function

[0286] In some embodiments, when the activated AI function does not have an available AI model, the terminal adopts any of the following behaviors:

[0287] The terminal does not use any AI function;

[0288] The terminal continues to use the AI function before receiving the fourth information.

[0289] The communication method related to the present embodiment can include at least one of steps S501-S503. For example, step S501 can be implemented as an independent embodiment, step S502 can be implemented as an independent embodiment, and step S503 can be implemented as an independent embodiment. In addition, part or all of the steps S501-S503 can be combined to implement an independent embodiment, which is not limited by the present embodiment.

[0290] For this embodiment, the terminal sends first information to the network device, where the first information can be used to indicate a first AI function, such as a first AI function with an available AI model or a first AI function without an available AI model, and then the network device can determine whether to activate the first AI function according to the first information, such as for a first AI function without an available AI model, no activation processing can be performed. Thus, the situation that the network activates an AI function without an available AI model can be reduced.

[0291] The embodiments of the present disclosure also propose an apparatus for implementing any of the above methods, for example, an apparatus is proposed, which includes units or modules for implementing the steps performed by a first network node such as a terminal in any of the above methods. For another example, another apparatus is proposed, which includes units or modules for implementing the steps performed by a second network node such as a network device (for example, an access network device, a core network function node, a core network device, etc.) in any of the above methods.

[0292] It should be understood that the division of each unit or module in the above apparatus is only a logical function division, and all or part of them can be integrated into a physical entity or physically separated in actual implementation. In addition, the units or modules in the apparatus can be implemented in the form of processor calling software: for example, the apparatus includes a processor, the processor is connected with a memory, the memory stores instructions, and the processor calls the instructions stored in the memory to realize the functions of any of the above methods or the units or modules of the above apparatus, wherein the processor is a general processor such as a central processing unit (CPU) or a microprocessor, and the memory is a memory in the apparatus or a memory outside the apparatus. Alternatively, the units or modules in the apparatus can be implemented in the form of hardware circuit, and the functions of part or all of the units or modules can be realized by the design of the hardware circuit. The above hardware circuit can be understood as one or more processors; for example, in one implementation, the above hardware circuit is an application-specific integrated circuit (ASIC), and the functions of part or all of the units or modules are realized by the design of the logical relationship between the elements in the circuit; for another example, in another implementation, the above hardware circuit is a programmable logic device (PLD), and a field programmable gate array (FPGA) is taken as an example, which can include a large number of logic gate circuits, and the connection relationship between the logic gate circuits is configured by a configuration file, so as to realize the functions of part or all of the units or modules. All units or modules of the above apparatus can be all implemented in the form of processor calling software, or all implemented in the form of hardware circuit, or part implemented in the form of processor calling software and the remaining part implemented in the form of hardware circuit.

[0293] In the embodiments of the present disclosure, the processor is a circuit with signal processing capability. In one implementation, the processor can be a circuit with instruction reading and running capability, such as a central processing unit (CPU), a microprocessor, a graphics processing unit (GPU) (which can be understood as a microprocessor), a digital signal processor (DSP), or the like. In another implementation, the processor can implement certain functions through a logical relationship of a hardware circuit, and the logical relationship of the 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 the reconfigurable hardware circuit, the processor loads a configuration document to implement the configuration of the hardware circuit. It can be understood that the processor loads instructions to implement the functions of the above part or all units or modules. In addition, the hardware circuit can also be 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), and the like.

[0294] FIG. 6 is a structural schematic diagram of a first network node according to an embodiment of the present disclosure. As shown in FIG. 6, the first network node can include a transceiver module 61. In some embodiments, the transceiver module 61 is configured to perform at least one of the communication steps performed by the first network node in any of the above methods (for example, step S301, but not limited thereto), and details are not described herein.

[0295] FIG. 7 is a structural schematic diagram of a second network node according to an embodiment of the present disclosure. As shown in FIG. 7, the second network node can include a transceiver module 71. In some embodiments, the transceiver module 71 is configured to perform at least one of the communication steps performed by the second network node in any of the above methods (for example, step S401, but not limited thereto), and details are not described herein.

[0296] In some embodiments, the transceiver module described above can include a sending module and / or a receiving module, which can be separate or integrated together. Alternatively, the transceiver module can be replaced by a transceiver.

[0297] FIG. 8 is a structural schematic diagram of a communication device 8100 according to an embodiment of the present disclosure. The communication device 8100 can be a network device (for example, an access network device, a core network device, etc.), a terminal (for example, a user equipment, etc.), a chip, a chip system, or a processor supporting the network device to implement any of the above methods, or a chip, a chip system, or a processor supporting the terminal to implement any of the above methods. The communication device 8100 can be used to implement the methods described in the above method embodiments, and details can be referred to the descriptions in the above method embodiments.

[0298] As shown in FIG. 8, the communication device 8100 includes one or more processors 8101. The processor 8101 can be a general processor or a special-purpose 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 (for example, a base station, a baseband chip, a terminal device, a terminal device chip, a DU or a CU, etc.), execute programs, and process data of the programs. Optionally, the communication device 8100 is configured to perform any of the above methods. Optionally, the one or more processors 8101 are configured to invoke instructions to cause the communication device 8100 to perform any of the above methods.

[0299] In some embodiments, the communication device 8100 further includes one or more transceivers 8102. When the communication device 8100 includes the one or more transceivers 8102, the transceiver 8102 performs the communication steps such as transmitting and / or receiving in the above methods, and the processor 8101 performs at least one of the other steps. In an optional embodiment, the transceiver can include a receiver and / or a transmitter, which can be separate or integrated together. Optionally, the terms of transceiver, transceiving unit, transceiver, transceiving circuit, interface circuit, interface, etc. can be replaced by each other, and the terms of transmitter, transmitting unit, transmitter, transmitting circuit, etc. can be replaced by each other, and the terms of receiver, receiving unit, receiver, receiving circuit, etc. can be replaced by each other.

[0300] In some embodiments, the communication device 8100 further includes one or more memories 8103 for storing data. Optionally, all or part of the memory 8103 can also be outside the communication device 8100. In an optional embodiment, the communication device 8100 can include one or more interface circuits 8104. Optionally, the interface circuit 8104 is connected with the memory 8102, and the interface circuit 8104 can be used to receive data from the memory 8102 or other devices, and can be used to send data to the memory 8102 or other devices. For example, the interface circuit 8104 can read the data stored in the memory 8102 and send the data to the processor 8101.

[0301] The communication device 8100 described in the above embodiments can be a network device or a terminal, but the scope of the communication device 8100 described in the present disclosure is not limited thereto, and the structure of the communication device 8100 can not be limited by FIG. 8. The communication device can be a standalone device or can be part of a larger device. For example, the communication device can be: 1) a standalone integrated circuit (IC), or a chip, or a chip system or subsystem; (2) a set of one or more ICs, which can optionally also include storage components for storing data, programs; (3) an ASIC, such as a modem; (4) a module that can be embedded in other devices; (5) a receiver, a terminal device, a smart terminal device, a cellular phone, a wireless device, a handset, a mobile unit, a vehicle-mounted device, a network device, a cloud device, an artificial intelligence device, and the like; (6) other devices, and the like.

[0302] FIG. 9 is a structural schematic diagram of a chip 8200 according to an embodiment of the present disclosure. For the case where the communication device 8100 is a chip or a chip system, the structural schematic diagram of the chip 8200 shown in FIG. 9 can be referred to, but is not limited thereto.

[0303] The chip 8200 includes one or more processors 8201. The chip 8200 is configured to perform any of the above methods.

[0304] In some embodiments, the chip 8200 further includes one or more interface circuits 8202. Optionally, the terms interface circuit, interface, transceiver pin, and the like can be replaced with each other. In some embodiments, the chip 8200 further includes one or more memories 8203 for storing data. Optionally, all or part of the memory 8203 can be outside the chip 8200. Optionally, the interface circuit 8202 is connected to the memory 8203, and the interface circuit 8202 can be configured to receive data from the memory 8203 or other devices, and the interface circuit 8202 can be configured to send data to the memory 8203 or other devices. For example, the interface circuit 8202 can read data stored in the memory 8203 and send the data to the processor 8201.

[0305] In some embodiments, the interface circuit 8202 performs at least one of the communication steps such as sending and / or receiving in the above methods. The interface circuit 8202 performing the communication steps such as sending and / or receiving in the above methods means that the interface circuit 8202 performs data interaction between the processor 8201, the chip 8200, the memory 8203, or a transceiver device. In some embodiments, the processor 8201 performs at least one of the communication method steps described above.

[0306] The modules and / or devices described in various embodiments of the virtual device, the physical device, the chip, etc. can be combined or separated according to circumstances. Alternatively, part or all of the steps can also be performed by multiple modules and / or devices in cooperation, which is not limited here.

[0307] The disclosure further provides a storage medium having instructions stored thereon, which, when executed on the communication device 8100, causes the communication device 8100 to perform any of the above methods. Alternatively, the storage medium is an electronic storage medium. Alternatively, the storage medium is a computer readable storage medium, but is not limited to this, and it can also be a storage medium readable by other devices. Alternatively, the storage medium can be a non-transitory storage medium, but is not limited to this, and it can also be a transitory storage medium.

[0308] The disclosure further provides a program product, which, when executed by the communication device 8100, causes the communication device 8100 to perform any of the above methods. Alternatively, the program product is a computer program product.

[0309] The disclosure further provides a computer program, which, when executed on a computer, causes the computer to perform any of the above methods.

Claims

1. A communication method characterized by comprising: The method is performed by a first network node, and comprises: sending, to a second network node, first information; wherein the first information is used to indicate a first artificial intelligence (AI) function.

2. The method of claim 1, wherein, The first AI function has or does not have an available AI model.

3. The method of claim 2, wherein, The first AI function is determined to not have the available AI model according to at least one of the following: an AI model corresponding to the first AI function is not stored in the first network node; an AI model corresponding to the first AI function stored in the first network node does not satisfy an application condition.

4. The method according to any one of claims 1 to 3, characterized in that, The method further comprises: sending, to the second network node, second information; wherein the second information is used to indicate an application condition corresponding to the first AI function.

5. The method of claim 4, wherein, The application condition indicated by the second information comprises one of the following: an application condition of part of AI models of all AI models corresponding to the first AI function; an application condition of all AI models corresponding to the first AI function.

6. The method according to any one of claims 3 to 5, characterized in that, The application condition comprises at least one of the following: a network condition; a terminal condition.

7. The method of claim 6, wherein, Information used to determine the network condition comprises at least one of the following: a cell type; a network deployment scenario; a wireless channel quality; a frequency where a cell is located; a location of the cell; a distance between network devices; an antenna configuration of a network device; a power at which a network device transmits a signal; numerology.

8. The method of any one of claims 6-7, wherein, Information used to determine the terminal condition comprises at least one of the following: a speed of a terminal; a power of the terminal; a power of the terminal; a computing capability of the terminal; a location of the terminal; a service type of the terminal; an antenna configuration of the terminal; a rotation speed of the terminal; a storage space of the terminal.

9. The method according to any one of claims 1 to 8, characterized in that, The method further comprises: receiving third information sent by the second network node, wherein the third information is used to indicate at least one AI function; determining whether the at least one AI function has an available AI model.

10. The method of claim 9, wherein, The sending, to the second network node, of the first information comprises: sending, to the second network node, the first information according to a result of whether the at least one AI function has the available AI model.

11. The method according to any one of claims 1 to 10, characterized in that, The method further comprises: receiving fourth information sent by the second network node; wherein the fourth information is used to indicate an activated AI function.

12. The method of claim 11, wherein, The method further comprises: determining that the activated AI function does not have an available AI model, and performing one of the following behaviors: not using any AI function; continuing to use an AI function before the fourth information is received.

13. A method of communication, comprising: The method is performed by a second network node, and comprises: receiving first information sent by a first network node; wherein the first information is used to indicate a first artificial intelligence (AI) function.

14. The method of claim 13, wherein, The first AI function has or does not have an available AI model.

15. The method of claim 14, wherein, The first AI function is determined to not have the available AI model according to at least one of the following: an AI model corresponding to the first AI function is not stored in the first network node; an AI model corresponding to the first AI function stored in the first network node does not satisfy an application condition.

16. The method according to any one of claims 13 to 15, characterized in that, The method further comprises: receiving second information sent by the first network node; wherein the second information is used to indicate an application condition corresponding to the first AI function.

17. The method of claim 16, wherein, The application condition indicated by the second information comprises one of the following: An application condition of part of AI models in all AI models corresponding to the first AI function; An application condition of all AI models corresponding to the first AI function.

18. The method of any one of claims 15-17, wherein, The application condition comprises at least one of the following: A network condition; A terminal condition.

19. The method of claim 18, wherein, The information used to determine the network condition comprises at least one of the following: A cell type; A network deployment scenario; A wireless channel quality; A frequency where the cell is located; A location of the cell; A distance between network devices; An antenna configuration of the network device; A power of a signal transmitted by the network device; Numerology.

20. The method of any one of claims 18-19, wherein, The information used to determine the terminal condition comprises at least one of the following: A speed of the terminal; A power of the terminal; A power of the terminal; A computing capability of the terminal; A location of the terminal; A service type of the terminal; An antenna configuration of the terminal; A rotation speed of the terminal; A storage space of the terminal.

21. The method according to any one of claims 13 to 20, characterized in that, The method further comprises: sending third information to the first network node, wherein the third information is used to indicate at least one AI function and make the first network node determine whether the at least one AI function has an available AI model.

22. The method of claim 21, wherein, The first information is sent by the first network node according to a result of whether the at least one AI function has an available AI model.

23. The method of any one of claims 13-22, wherein, The method further comprises: sending fourth information to the first network node; wherein the fourth information is used to indicate an activated AI function.

24. A method of communication, comprising: Comprising: a first network node sending first information to a second network node; the second network node receiving the first information sent by the first network node, wherein the first information is used to indicate a first artificial intelligence (AI) function.

25. A first network node, comprising: Comprising: a transceiver module configured to send first information to a second network node; wherein the first information is used to indicate a first artificial intelligence (AI) function.

26. A second network node, characterized by: Comprising: a transceiver module configured to receive first information sent by a first network node; wherein the first information is used to indicate a first artificial intelligence (AI) function.

27. A communication system, characterized by Comprising: a first network node configured to implement the method of any one of claims 1 to 12; a second network node configured to implement the method of any one of claims 13 to 23.

28. A communications device, characterized by Comprising: one or more processors; wherein the processor is used to execute the method of any one of claims 1 to 23.

29. A computer storage medium, wherein, The computer storage medium stores computer executable instructions; the computer executable instructions are executed by the processor to implement the method of any one of claims 1 to 23.

30. A computer program product comprising a computer program, which, when executed by a processor, can implement the method of any one of claims 1 to 23.

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