Model information transmission method, device, and storage medium

Abstract

Embodiments of the present disclosure relate to a model information transmission method, a device, and a storage medium. The method comprises: a terminal device receives first information sent by a network device, wherein the first information is used for assisting the terminal device to acquire, from a first device, second information corresponding to an artificial intelligence (AI) model, and the second information comprises a model structure and / or a model parameter of the AI model; and the terminal device receives the second information sent by the first device. In this way, the terminal device can acquire related information of the AI model from the first device under the assistance of the network device, so that the AI model can be flexibly managed.

Description

Model information transmission method, device and storage medium Technical Field

[0001] The present disclosure relates to the field of communication technology, and in particular to a model information transmission method, device, and storage medium. Background Art

[0002] With the advancement of communication technology, the 3rd Generation Partnership Project (3GPP) has proposed introducing prediction functions based on artificial intelligence (AI) in communication systems. This prediction function can be implemented based on AI models. Through this prediction function, prediction data for certain scenarios can be obtained, thereby improving network performance.

[0003] Summary of the Invention

[0004] The embodiments of the present disclosure provide a model information transmission method, device, and storage medium.

[0005] According to a first aspect of an embodiment of the present disclosure, a model information transmission method is proposed, which is executed by a terminal device. The method includes:

[0006] Receive first information sent by a network device, where the first information is used to assist the terminal device in obtaining second information corresponding to an artificial intelligence (AI) model from the first device, where the second information includes a model structure and / or model parameters of the AI ​​model;

[0007] Receive the second information sent by the first device.

[0008] According to a second aspect of an embodiment of the present disclosure, a model information transmission method is proposed, which is performed by a network device. The method includes:

[0009] Send first information to the terminal device, where the first information is used to assist the terminal device in obtaining second information corresponding to the artificial intelligence AI model from the first device, where the second information includes the model structure and / or model parameters of the AI ​​model.

[0010] According to a third aspect of an embodiment of the present disclosure, a model information transmission method is provided, which is executed by a first device. The method includes:

[0011] Sending second information to the terminal device, where the second information includes a model structure and / or model parameters of the artificial intelligence AI model.

[0012] According to a fourth aspect of an embodiment of the present disclosure, a terminal device is provided, including:

[0013] The transceiver module is configured to receive first information sent by a network device, where the first information is used to assist the terminal device in obtaining second information corresponding to an artificial intelligence (AI) model from the first device, where the second information includes a model structure and / or model parameters of the AI ​​model; and receive the second information sent by the first device.

[0014] According to a fifth aspect of an embodiment of the present disclosure, a network device is provided, including:

[0015] The transceiver module is configured to send first information to the terminal device, where the first information is used to assist the terminal device in obtaining second information corresponding to the artificial intelligence AI model from the first device, where the second information includes the model structure and / or model parameters of the AI ​​model.

[0016] According to a sixth aspect of an embodiment of the present disclosure, a first device is provided, including:

[0017] The transceiver module is configured to send second information to the terminal device, where the second information includes a model structure and / or model parameters of the artificial intelligence AI model.

[0018] According to a seventh aspect of an embodiment of the present disclosure, a communication device is proposed, comprising: one or more processors; wherein the communication device can be used to execute an optional implementation of the first aspect, the second aspect, or the third aspect.

[0019] According to an eighth aspect of an embodiment of the present disclosure, a storage medium is proposed, 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 aspect, the second aspect or the third aspect.

[0020] According to the ninth aspect of an embodiment of the present disclosure, a computer program product is proposed, which includes a computer program. When the computer program is executed by a communication device, the communication device executes the method described in the optional implementation manner of the first aspect, the second aspect or the third aspect.

[0021] According to the tenth aspect of an embodiment of the present disclosure, a communication system is proposed, which may include: a terminal device, a network device and a first device; wherein, the terminal device is configured to execute the method described in the optional implementation manner of the first aspect, the network device is configured to execute the method described in the optional implementation manner of the second aspect, and the first device is configured to execute the method described in the optional implementation manner of the third aspect.

[0022] The technical solution provided by the embodiments of the present disclosure may have the following beneficial effects: a terminal device receives first information sent by a network device, where the first information is used to assist the terminal device in obtaining second information corresponding to an artificial intelligence (AI) model from the first device, where the second information includes the model structure and / or model parameters of the AI ​​model; and the terminal device receives the second information sent by the first device. In this way, the terminal device can obtain the model structure and / or model parameters of the AI ​​model from the first device with the assistance of the network device, thereby enabling flexible management of the AI ​​model.

[0023] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] 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.

[0025] FIG1A is a schematic diagram showing the architecture of a communication system according to an embodiment of the present disclosure.

[0026] FIG1B is a schematic diagram showing the architecture of a communication system according to an embodiment of the present disclosure.

[0027] FIG2A is an interactive schematic diagram illustrating a model information transmission method according to an embodiment of the present disclosure.

[0028] FIG2B is an interactive schematic diagram illustrating a model information transmission method according to an embodiment of the present disclosure.

[0029] FIG2C is an interactive schematic diagram illustrating a model information transmission method according to an embodiment of the present disclosure.

[0030] FIG2D is an interactive schematic diagram illustrating a model information transmission method according to an embodiment of the present disclosure.

[0031] FIG2E is an interactive schematic diagram illustrating a model information transmission method according to an embodiment of the present disclosure.

[0032] FIG2F is an interactive schematic diagram illustrating a model information transmission method according to an embodiment of the present disclosure.

[0033] FIG3A is a flow chart showing a method for transmitting model information according to an embodiment of the present disclosure.

[0034] FIG3B is a flow chart illustrating a method for transmitting model information according to an embodiment of the present disclosure.

[0035] FIG3C is a flow chart illustrating a method for transmitting model information according to an embodiment of the present disclosure.

[0036] FIG3D is a flow chart illustrating a method for transmitting model information according to an embodiment of the present disclosure.

[0037] FIG4A is a flow chart showing a method for transmitting model information according to an embodiment of the present disclosure.

[0038] FIG4B is a flow chart showing a method for transmitting model information according to an embodiment of the present disclosure.

[0039] FIG4C is a flow chart illustrating a method for transmitting model information according to an embodiment of the present disclosure.

[0040] FIG4D is a flow chart illustrating a method for transmitting model information according to an embodiment of the present disclosure.

[0041] FIG4E is a flow chart showing a method for transmitting model information according to an embodiment of the present disclosure.

[0042] FIG4F is a flow chart of a model information transmission method according to an embodiment of the present disclosure.

[0043] FIG5A is a flow chart showing a method for transmitting model information according to an embodiment of the present disclosure.

[0044] FIG5B is a flow chart illustrating a method for transmitting model information according to an embodiment of the present disclosure.

[0045] FIG5C is a flow chart illustrating a method for transmitting model information according to an embodiment of the present disclosure.

[0046] FIG5D is a flow chart illustrating a method for transmitting model information according to an embodiment of the present disclosure.

[0047] FIG5E is a flow chart of a model information transmission method according to an embodiment of the present disclosure.

[0048] FIG6 is a flow chart showing a method for transmitting model information according to an embodiment of the present disclosure.

[0049] FIG7A is a schematic structural diagram of a terminal device according to an embodiment of the present disclosure.

[0050] FIG7B is a schematic structural diagram of a network device according to an embodiment of the present disclosure.

[0051] FIG7C is a schematic structural diagram of a first device according to an embodiment of the present disclosure.

[0052] FIG8A is a schematic structural diagram of a communication device according to an embodiment of the present disclosure.

[0053] FIG8B is a schematic structural diagram of a chip according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0054] The embodiments of the present disclosure provide a model information transmission method, device, and storage medium.

[0055] In a first aspect, an embodiment of the present disclosure provides a model information transmission method, which is executed by a terminal device. The method includes:

[0056] Receive first information sent by a network device, where the first information is used to assist the terminal device in obtaining second information corresponding to an artificial intelligence (AI) model from the first device, where the second information includes a model structure and / or model parameters of the AI ​​model;

[0057] Receive the second information sent by the first device.

[0058] In the above embodiment, the terminal device can obtain relevant information of the AI ​​model from the first device with the assistance of the network device, so that the AI ​​model can be flexibly managed.

[0059] In conjunction with some embodiments of the first aspect, in some embodiments, the method further includes:

[0060] Establishing a first connection, where the first connection is a connection between the terminal device and the first device;

[0061] And wherein, receiving the second information sent by the first device includes: receiving the second information sent by the first device through the first connection.

[0062] In the above embodiment, the reliability of model information transmission can be improved by transmitting relevant information of the AI ​​model through the first connection.

[0063] In combination with some embodiments of the first aspect, in some embodiments, the first connection is established based on a request of the terminal device and / or the first device.

[0064] In the above embodiment, the first connection can be established flexibly.

[0065] In combination with some embodiments of the first aspect, in some embodiments, the second information is information sent by the first device to the terminal device based on an application layer transmission protocol.

[0066] In the above embodiment, the reliability of model information transmission can be further improved based on the application layer transmission protocol.

[0067] In conjunction with some embodiments of the first aspect, in some embodiments, the first information includes at least one of the following:

[0068] Model description information corresponding to the AI ​​model, wherein the model description information is used to determine the AI ​​model;

[0069] Model transmission information corresponding to the AI ​​model, wherein the model transmission information is used to instruct the terminal device to obtain the model structure and / or model parameters of the AI ​​model;

[0070] Model storage information corresponding to the AI ​​model, wherein the model storage information is used to establish a first connection between the terminal device and the first device.

[0071] In the above embodiment, at least one of the above items in the first information can assist the terminal device in obtaining the AI ​​model from the first device, that is, the first information can facilitate the terminal device to obtain information, parameters or configuration related to the AI ​​model from the first device (for example, the associated server of the network device to which the terminal is connected). Here, assistance can be understood as pre-configuring the AI ​​model for the terminal to obtain from the first device, transferring parameters and establishing a connection. Due to this assistance, subsequent terminal devices can easily obtain the corresponding AI model from the first device, so that the AI ​​model can be flexibly managed.

[0072] In combination with some embodiments of the first aspect, in some embodiments, the model description information includes at least one of the following: model identification; model size; model input information; model output information; model application environment information; and model format information.

[0073] In the above embodiment, the AI ​​model is determined based on the model description information.

[0074] In conjunction with some embodiments of the first aspect, in some embodiments, the method further includes at least one of the following:

[0075] Sending third information to the network device, where the third information is used to request the network device to send the first information;

[0076] In response to receiving the first information sent by the network device, fourth information is sent to the network device, and the fourth information is used to indicate that the terminal device has successfully received the first information and / or the terminal device has started to execute the step of receiving the second information sent by the first device.

[0077] In the above embodiment, the flexibility and reliability of the first information interaction can be improved.

[0078] In combination with some embodiments of the first aspect, in some embodiments, the AI ​​model is a model obtained after training of the first device and / or the network device.

[0079] In the above embodiment, based on the trained AI model, the reliability of model application can be improved.

[0080] In combination with some embodiments of the first aspect, in some embodiments, the AI ​​model is used to perform a first function, wherein the first function includes at least one of the following functions: channel state information CSI enhancement; beam prediction; positioning.

[0081] In combination with some embodiments of the first aspect, in some embodiments, the network device includes at least one of the following: access network equipment; access and mobility management function AMF; positioning management function LMF.

[0082] In combination with some embodiments of the first aspect, in some embodiments, the network device is a network device corresponding to the first function.

[0083] In the above embodiment, the network device is flexibly determined according to the function performed by the AI ​​model, so that it can adapt to various scenarios, further improving the flexibility of model management.

[0084] In a second aspect, an embodiment of the present disclosure provides a model information transmission method, which is executed by a network device. The method includes:

[0085] Send first information to the terminal device, where the first information is used to assist the terminal device in obtaining second information corresponding to the artificial intelligence AI model from the first device, where the second information includes the model structure and / or model parameters of the AI ​​model.

[0086] In the above embodiment, the network device can assist the terminal device in obtaining relevant information of the AI ​​model from the first device through the first information, so that the AI ​​model can be flexibly managed.

[0087] In conjunction with some embodiments of the second aspect, in some embodiments, the first information includes at least one of the following:

[0088] Model description information corresponding to the AI ​​model, wherein the model description information is used to determine the AI ​​model;

[0089] Model transmission information corresponding to the AI ​​model, wherein the model transmission information is used to instruct the terminal device to obtain the model structure and / or model parameters of the AI ​​model;

[0090] Model storage information corresponding to the AI ​​model, wherein the model storage information is used to establish a first connection between the terminal device and the first device.

[0091] In combination with some embodiments of the second aspect, in some embodiments, the model description information includes at least one of the following: model identification; model size; model input information; model output information; model application environment information; and model format information.

[0092] In conjunction with some embodiments of the second aspect, in some embodiments, the method further includes at least one of the following:

[0093] receiving third information sent by the terminal device, where the third information is used to request the network device to send the first information;

[0094] Receive fourth information sent by the terminal device, where the fourth information is used to indicate that the terminal device has successfully received the first information and / or that the terminal device has started to execute the step of receiving the second information sent by the first device.

[0095] In combination with some embodiments of the second aspect, in some embodiments, the AI ​​model is a model obtained after training of the first device and / or the network device.

[0096] In conjunction with some embodiments of the second aspect, in some embodiments, the method further includes at least one of the following:

[0097] Sending fifth information to the first device, where the fifth information is used by the first device to train the AI ​​model;

[0098] receiving seventh information sent by the first device, where the seventh information includes information for assisting the terminal device in acquiring the AI ​​model;

[0099] sending sixth information to the first device, where the sixth information is used to request the first device to send the seventh information;

[0100] Send eighth information to the first device, where the eighth information includes the AI ​​model generated by the network device.

[0101] In combination with some embodiments of the second aspect, in some embodiments, the AI ​​model is used to perform a first function, wherein the first function includes at least one of the following functions: channel state information CSI enhancement; beam prediction; positioning.

[0102] In combination with some embodiments of the second aspect, in some embodiments, the network device includes at least one of the following: access network equipment; access and mobility management function AMF; positioning management function LMF.

[0103] In combination with some embodiments of the second aspect, in some embodiments, the network device is a network device corresponding to the first function.

[0104] In a third aspect, an embodiment of the present disclosure provides a model information transmission method, which is executed by a first device. The method includes:

[0105] Sending second information to the terminal device, where the second information includes a model structure and / or model parameters of the artificial intelligence AI model.

[0106] In the above embodiment, the first device can transmit relevant information of the AI ​​model to the terminal device, so that the AI ​​model can be flexibly managed.

[0107] In conjunction with some embodiments of the third aspect, in some embodiments, the method further includes:

[0108] Establishing a first connection, where the first connection is a connection between the terminal device and the first device;

[0109] The sending the second information to the terminal device includes: sending the second information to the terminal device through the first connection.

[0110] In combination with some embodiments of the third aspect, in some embodiments, the first connection is established based on a request of the terminal device and / or the first device.

[0111] In combination with some embodiments of the third aspect, in some embodiments, the second information is information sent by the first device to the terminal device based on an application layer transmission protocol.

[0112] In combination with some embodiments of the third aspect, in some embodiments, the AI ​​model is a model obtained after training of the first device and / or network device.

[0113] In conjunction with some embodiments of the third aspect, in some embodiments, the method further includes at least one of the following:

[0114] receiving fifth information sent by the network device, where the fifth information is used by the first device to train the AI ​​model;

[0115] Sending seventh information to the network device, where the seventh information includes information that assists the terminal device in acquiring the AI ​​model;

[0116] receiving sixth information sent by the network device, where the sixth information is used to request the first device to send the seventh information;

[0117] Receive eighth information sent by the network device, where the eighth information includes an AI model generated by the network device.

[0118] In combination with some embodiments of the third aspect, in some embodiments, the AI ​​model is used to perform a first function, wherein the first function includes at least one of the following functions: channel state information CSI enhancement; beam prediction; positioning.

[0119] In combination with some embodiments of the third aspect, in some embodiments, the network device includes at least one of the following: access network equipment; access and mobility management function AMF; positioning management function LMF.

[0120] In combination with some embodiments of the third aspect, in some embodiments, the network device is a network device corresponding to the first function.

[0121] In a fourth aspect, an embodiment of the present disclosure proposes a terminal device, which may include at least one of a transceiver module and a processing module; wherein the terminal device can be used to execute the optional implementation method of the first aspect.

[0122] In a fifth aspect, an embodiment of the present disclosure proposes a network device, which may include at least one of a transceiver module and a processing module; wherein the network device can be used to execute the optional implementation method of the second aspect.

[0123] In a sixth aspect, an embodiment of the present disclosure proposes a first device, which may include at least one of a transceiver module and a processing module; wherein the first device may be used to execute the optional implementation method of the third aspect.

[0124] In a seventh aspect, an embodiment of the present disclosure proposes a communication device, which may include: one or more processors; wherein the communication device can be used to execute an optional implementation of the first aspect, the second aspect or the third aspect.

[0125] In an eighth aspect, an embodiment of the present disclosure proposes a storage medium storing instructions, which, when executed on a communication device, enables the communication device to execute the method described in the optional implementation of the first aspect, the second aspect, or the third aspect.

[0126] In the ninth aspect, an embodiment of the present disclosure proposes a computer program product, which includes a computer program. When the computer program is executed by a communication device, the communication device executes the method described in the optional implementation of the first aspect, the second aspect or the third aspect.

[0127] In the tenth aspect, an embodiment of the present disclosure proposes a communication system, which may include: a terminal device, a network device and a first device; wherein, the terminal device is configured to execute the method described in the optional implementation manner of the first aspect, the network device is configured to execute the method described in the optional implementation manner of the second aspect, and the first device is configured to execute the method described in the optional implementation manner of the third aspect.

[0128] 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 described in the optional implementation of the first aspect, the second aspect, or the third aspect.

[0129] In a twelfth aspect, an embodiment of the present disclosure provides a chip or a chip system, wherein the chip or chip system includes a processing circuit configured to execute the method described in the optional implementation of the first aspect, the second aspect, or the third aspect.

[0130] It is understandable that the above-mentioned terminal device, network device, first device, communication device, communication system, storage medium, program product, computer program, chip or chip system can be used to perform the method proposed in the embodiment of the present disclosure. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects of the corresponding method and will not be repeated here.

[0131] The present disclosure provides a model information transmission method, device, and storage medium. In some embodiments, the terms "model information transmission method" and "information processing method" and "communication method" are interchangeable; "model information transmission device" and "information processing device" and "communication device" are interchangeable; and "information processing system" and "communication system" are interchangeable.

[0132] 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 certain 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 certain embodiment can also be implemented as an independent embodiment, and the order of the steps in a certain embodiment can be arbitrarily exchanged. In addition, the optional implementation methods in a certain embodiment can be arbitrarily combined; in addition, the embodiments can be arbitrarily combined. For example, some or all steps of different embodiments can be arbitrarily combined, and a certain embodiment can be arbitrarily combined with the optional implementation methods of other embodiments.

[0133] 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.

[0134] 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.

[0135] 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.

[0136] In some embodiments, "plurality" may refer to two or more.

[0137] In some embodiments, the terms "at least one," "one or more," "a plurality of," "multiple," etc. may be used interchangeably.

[0138] 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.

[0139] 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.

[0140] 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.

[0141] 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.

[0142] 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.

[0143] 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.

[0144] In some embodiments, devices and the like can be interpreted as physical or virtual, and their names are not limited to those described 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.

[0145] In some embodiments, "network" can be interpreted as devices included in the network (eg, network equipment, access network equipment, core network equipment, etc.).

[0146] In some embodiments, the network device may include at least one of an access network device and a core network device.

[0147] In some embodiments, the terms "Access Network Device (AN Device)", "Radio Access Network Device (RAN Device)", "Base Station (BS)", "Radio Base Station (Radio Base Station)", "Fixed Station (Fixed Station)", "Node (Node)", "Access Point (Access Point)", "Transmission Point (TP)", "Reception Point (RP)", "Transmission and / or Reception Point (TRP))", "Panel (Panel)", "Antenna Panel (Antenna Panel)", "Antenna Array (Antenna Array)" "Cell (Cell)", "Macro Cell (Macro Cell)", "Small Cell (Small Cell)", "Femto Cell (Femto Cell)", "Pico Cell (Pico Cell)" "Sector (Sector)", "Cell Group (Cell Group)", "Serving Cell (Cell)", "Carrier (Carrier)", "Component Carrier (Component Carrier)", "Bandwidth Part (BWP)" and the like may be used interchangeably.

[0148] In some embodiments, the terms "terminal", "terminal device", "terminal side device", "user equipment (UE)", "user terminal" "mobile station (MS)", "mobile terminal (MT)", subscriber station (Subscriber Station), mobile unit (Mobile Unit), subscriber unit (Subscriber Unit), wireless unit (Wireless Unit), remote unit (Remote Unit), mobile device (Mobile Device), wireless device (Wireless Device), wireless communication device (Wireless Communication Device), remote device (Remote Device), mobile subscriber station (Mobile Subscriber Station), access terminal (Access Terminal), mobile terminal (Mobile Terminal), wireless terminal (Wireless Terminal), remote terminal (Remote Terminal), handset (Handset), user agent (User Agent), mobile client (Mobile Client), client (Client) and the like can be used interchangeably.

[0149] In some embodiments, the access network device, the core network device, or the network device can be replaced by a terminal device. 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 device is replaced by the communication between multiple terminal devices (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 device 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 terminal devices (for example, "side"). For example, uplink channels, downlink channels, etc. can be replaced by side channels or direct channels, and uplinks, downlinks, etc. can be replaced by side links or direct links.

[0150] In some embodiments, the terminal device 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 device.

[0151] In some embodiments, obtaining data, information, etc. may comply with the laws and regulations of the country where the data is obtained.

[0152] In some embodiments, data, information, etc. may be obtained with the user's consent.

[0153] 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.

[0154] FIG1A is a schematic diagram illustrating an architecture of a communication system according to an embodiment of the present disclosure. As shown in FIG1A , the communication system 100 may include a terminal device 101 , a network device 102 , and a first device 103 .

[0155] In some embodiments, the terminal device 101 may include at least one of a mobile phone, a wearable device, an Internet of Things device, a car with communication function, a smart car, a vehicle-mounted terminal, a tablet computer, a computer with wireless transceiver function, a road side unit (RSU), 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 smart grid, a wireless terminal device in transportation safety, a wireless terminal device in smart city, and a wireless terminal device in smart home, but is not limited thereto.

[0156] In some embodiments, the network device 102 may include at least one of an access network device and a core network device.

[0157] In some embodiments, the access network device may be a node or device that accesses the terminal device 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 Wi-Fi system, but is not limited thereto.

[0158] 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.

[0159] 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 (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.

[0160] In some embodiments, the core network device may be a single device, or may be multiple devices or a group of devices. The core network may include at least one of an Evolved Packet Core (EPC), a 5G Core Network (5GCN), a 6G Core Network (6GCN), and a Next Generation Core (NGC).

[0161] In some embodiments, the first device 103 may be a server or a device with storage and processing capabilities. For example, the first device may be a server or device associated with a network device. Alternatively, the first device may be a server or device included in the network device, or a server or device independent of the network device and within the communication system. Alternatively, the server may be a server included in the communication system, or a server deployed independently of the communication system.

[0162] In some embodiments, the terminal device and the first device can communicate through a network device, or through other networks (such as WIFI or the Internet), etc., which is not limited in this disclosure.

[0163] Figure 1B is a schematic diagram illustrating an architecture of a communication system according to an embodiment of the present disclosure. As shown in Figure 1B, the communication system 100 may include a terminal device 101, a network device 102, and a first device 103. The first device 103 may be one or more.

[0164] The network device 102 may include at least one of the following: an access network device 1021 , an access and mobility management function (AMF) 10221 , and a location management function (LMF) 10222 .

[0165] Optionally, the above-mentioned AMF and LMF can be network elements of the core network equipment, and the core network equipment can also include but is not limited to: user plane function (UPF), session management function (SMF) and other network elements.

[0166] 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.

[0167] The following embodiments of the present disclosure may be applied to the communication system 100 shown in FIG1A or FIG1B , or a portion thereof, but are not limited thereto. The entities shown in FIG1A are examples. The communication system may include all or part of the entities shown in FIG1A , or may include other entities other than those shown in FIG1A . The number and form of the entities are arbitrary. The entities may be physical or virtual. The connection relationship between the entities is an example. The entities may be connected or disconnected. The connection may be in any manner, directly or indirectly, and wired or wireless.

[0168] The embodiments of the present disclosure may 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 802.17 (WiMAX (registered trademark)), IEEE 802.18 (WiMAX (registered trademark)), IEEE 802.19 (WiMAX (registered trademark)), IEEE 802.20 (WiMAX (registered trademark)), IEEE 802.21 (WiMAX (registered trademark)), IEEE 802.22 (WiMAX (registered trademark)), IEEE 802.23 (WiMAX (registered trademark)), IEEE 802.24 (WiMAX (registered trademark)), IEEE 802.25 (WiMAX (registered trademark)), IEEE 802.26 (WiMAX (registered trademark)), IEEE 802.27 (WiMAX (registered trademark)), IEEE 802.28 (WiMAX (registered trademark)), IEEE 802.29 (WiMAX (registered trademark)), IEEE 802.30 (WiMAX (registered trademark)), IEEE 802.31 (WiMAX (registered trademark)), IEEE 802.32 (WiMAX (registered trademark)), IEEE 802.33 (WiMAX (registered trademark)), 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).

[0169] In some embodiments of the present disclosure, an artificial intelligence (AI) model may be deployed in the communication system. For example, the AI ​​model may be deployed in at least one of a terminal device, a network device (such as an access network device, an AMF or LMF device), and a first device. The AI ​​model may be used to predict events and obtain relatively accurate prediction results. It should be noted that the name of the AI ​​model in the embodiments of the present disclosure is not limited. For example, it may be a machine learning (ML) model, or any model or function obtained through training.

[0170] The AI ​​model deployed in the communication system can be used to perform at least one of the following functions:

[0171] Channel State Information (CSI) enhancement. For example, this AI function can be used to perform enhanced CSI prediction, obtain accurate CSI prediction, and improve CSI management performance.

[0172] Beam prediction: For example, beam prediction (or beam management) can be performed based on this AI function to improve beam management performance.

[0173] Positioning, for example, can be performed based on this AI function to improve positioning accuracy.

[0174] In some embodiments, the AI ​​model can be stored on a first device (e.g., a server). When the terminal device needs to obtain the AI ​​model (e.g., when the network device needs to transmit the AI ​​model to the terminal device), the AI ​​model stored on the first device can be transmitted to the terminal device.

[0175] In one implementation, a network device may collect data and then transmit the data to a first device for model training. The first device may store the trained model. The first device may be a server associated with the network device. The data collected by the network device may be data used to train the AI ​​model.

[0176] In another implementation, the network device may train the AI ​​model and send the trained AI model to the first device, and the first device may store the AI ​​model.

[0177] In another implementation, the network device can pre-train the AI ​​model and send the pre-trained AI model to the first device. The network device can also send the data used for model training to the first device, and the first device can re-train the AI ​​model based on the data to obtain and store the trained AI model. Optionally, the first device can periodically obtain data from the network device and train the AI ​​model to improve the reliability of the AI ​​model.

[0178] In some embodiments, the first device may include one device (eg, a server), or may include multiple devices or a device group.

[0179] For example, the first device may include a server, which can be used for at least one of the following: training an AI model, storing an AI model, and transmitting the AI ​​model to a terminal device.

[0180] For another example, the first device may include multiple servers, each of which has the same function and can be used for at least one of the following: training an AI model, storing the AI ​​model, and transmitting the AI ​​model to a terminal device. Optionally, different servers can store different AI models, and different AI models can be distinguished by model identifiers.

[0181] For another example, the first device may include multiple servers, and the functions of different servers may be different. For example, some servers may be used to train and / or store AI models, and other servers may be used to store AI models and / or transmit the AI ​​models to terminal devices.

[0182] The embodiment of the present disclosure does not limit the deployment method of the first device.

[0183] In some embodiments, the trained AI model is stored in the first device, and how the terminal device obtains the trained AI model from the first device becomes an urgent problem to be solved.

[0184] FIG2A is an interactive diagram illustrating a method for transmitting model information according to an embodiment of the present disclosure. The method may be executed by the above-mentioned communication system. As shown in FIG2A , the method may include:

[0185] Step S2101: The network device sends eighth information to the first device.

[0186] In some embodiments, the first device may receive the eighth information. For example, the first device may receive the eighth information sent by the network device.

[0187] In some embodiments, the eighth information may include an AI model generated by the network device. Optionally, the AI ​​model may be an untrained model, a pre-trained model, or a trained model.

[0188] In some embodiments, the name of the eighth information is not limited, for example, it can be "model information", "model data", "AI model information", "AI model data", etc.

[0189] In some embodiments, the first device may obtain an AI model based on the eighth information.

[0190] In some embodiments, step S2101 can be omitted, and the first device can obtain the AI ​​model by itself. For example, the AI ​​model can be deployed directly on the first device without obtaining the AI ​​model from the network device.

[0191] In some embodiments, the AI ​​model obtained by the first device based on the eighth information or obtained by itself may be a trained model, and the first device may directly store the AI ​​model without training.

[0192] In other embodiments, the AI ​​model obtained by the first device based on the eighth information or obtained by itself may be an untrained or incompletely trained model (for example, only pre-trained), and the first device may train the AI ​​model based on subsequent steps S2102 and S2103.

[0193] Step S2102: The network device sends fifth information to the first device.

[0194] In some embodiments, the first device may receive the fifth information. For example, the first device may receive the fifth information sent by the network device.

[0195] In some embodiments, the fifth information can be used by the first device to train the AI ​​model.

[0196] In some embodiments, the fifth information may include data collected by the network device, which may be used to train the AI ​​model. For example, the fifth information may include beam measurement results, positioning results, CSI measurement results, etc. The first device may train the AI ​​function based on the fifth information.

[0197] In some embodiments, the name of the fifth information is not limited, for example, it can be "model training data", "model training information", "collected data", etc.

[0198] In some embodiments, the first device may train the AI ​​model based on the fifth information.

[0199] In some embodiments, the eighth information and the fifth information may be sent independently or in parallel.

[0200] In some embodiments, the network device may send the fifth information to the first device based on a request from the first device so that the first device performs model training.

[0201] In some embodiments, the network device may also send the fifth information to the first device based on the request of the terminal device so that the first device performs model training.

[0202] Step S2103: The first device performs model training.

[0203] In some embodiments, the first device may perform model training on the AI ​​model based on the fifth information, and determine the model structure and model parameters of the AI ​​model after training.

[0204] In some embodiments, the first device may perform model training on the AI ​​model in response to the fifth information.

[0205] In some embodiments, the first device may periodically perform model training on the AI ​​model.

[0206] In some embodiments, if the AI ​​model obtained by the first device based on the eighth information or obtained by itself is a trained model, steps S2102 and S2103 can be omitted.

[0207] It should be noted that the specific method of model training can refer to the description in the relevant technology, and the embodiments of the present disclosure are not limited to this.

[0208] Step S2104: The network device sends sixth information to the first device.

[0209] In some embodiments, the first device may receive the sixth information. For example, the first device may receive the sixth information sent by the network device.

[0210] In some embodiments, the sixth information may be used to request the first device to send the seventh information. Optionally, the seventh information may include information that assists the terminal device in obtaining the AI ​​model.

[0211] In some embodiments, the name of the sixth information is not limited, for example, it can be "model download auxiliary information request", "model information request", "model related information request", etc.

[0212] Step S2105: The first device sends seventh information to the network device.

[0213] In some embodiments, the network device may receive the seventh information. For example, the network device may receive the seventh information sent by the first device.

[0214] In some embodiments, the seventh information may include information that assists the terminal device in obtaining the AI ​​model.

[0215] In some embodiments, the name of the seventh information is not limited, and may be, for example, "model download auxiliary information", "model transmission configuration", "model information", "model related information", etc.

[0216] In some embodiments, the first device may send the seventh information based on a request from the network device. For example, the first device sends the seventh information in response to the sixth information.

[0217] In some embodiments, the first device may also actively send the seventh information to the network device, so that the above step S2104 may be omitted.

[0218] In some embodiments, the seventh information may include at least one of the following:

[0219] Model description information corresponding to the AI ​​model, where the model description information is used to determine the AI ​​model;

[0220] Model transmission information corresponding to the AI ​​model, where the model transmission information is used to instruct the terminal device to obtain the model structure and / or model parameters of the AI ​​model. For example, the model transmission information may be used to indicate that the model to be transmitted is a completely new model structure and model parameters. For another example, the model transmission information may be used to indicate that the model to be transmitted is the model parameters of an AI model that has already been deployed on the terminal device.

[0221] The model storage information corresponding to the AI ​​model is used to establish a first connection between the terminal device and the first device. For example, it may include address information corresponding to the first device storing the AI ​​model and / or connection auxiliary information for establishing a connection with the first device.

[0222] In one implementation, the model description information includes at least one of the following:

[0223] Model ID, which can be used to identify the AI ​​model;

[0224] Model size, which can be used to indicate the amount of data an AI model uses;

[0225] Model input information, which can be used to indicate relevant information (such as type and quantity) of the input data of the AI ​​model;

[0226] Model output information, which can be used to indicate relevant information (such as type and quantity) of the output data of the AI ​​model;

[0227] Model application environment information, which can be used to indicate the usage environment of the AI ​​model;

[0228] Model format information, which can be used to indicate the format of the AI ​​model.

[0229] Step S2106: The terminal device sends third information to the network device.

[0230] In some embodiments, the network device may receive the third information. For example, the network device may receive the third information sent by the terminal device.

[0231] In some embodiments, the third information may be used to request the network device to send the first information.

[0232] In some embodiments, the third information may be used to request the network device to send information for assisting in model transmission.

[0233] In some embodiments, the name of the third information is not limited, and may be, for example, "model download request", "model request", "model information request", etc.

[0234] In some embodiments, the third information can be carried in at least one of physical layer information, radio resource control (RRC) message, medium access control control element (MAC CE), uplink control information (UCI), non-access stratum (NAS) message or other messages sent by the terminal device to the network device.

[0235] Step S2107: The network device sends first information to the terminal device.

[0236] In some embodiments, the terminal device may receive the first information. For example, the terminal device may receive the first information sent by the network device.

[0237] In some embodiments, the first information can be used to assist the terminal device in obtaining second information corresponding to the artificial intelligence (AI) model from the first device. Optionally, the second information may include the model structure and / or model parameters of the AI ​​model.

[0238] Optionally, the first device may be used to store the AI ​​model and / or transmit the AI ​​model to the terminal device. For example, the first device may be a server that stores the AI ​​model. For another example, the first device may transmit the AI ​​model to the terminal device. The first device may obtain the AI ​​model from other devices (such as network devices or other servers) and transmit it to the terminal device.

[0239] In some embodiments, the name of the first information is not limited, and may be, for example, "model download indication information", "model download auxiliary information", "model transmission configuration information", "model information", etc.

[0240] In some embodiments, the first information may be carried in at least one of an RRC message, a MAC CE, downlink control information DCI (Downlink Control Information), a NAS message, or other messages sent by a network device to a terminal device.

[0241] In some embodiments, the first information may include at least one of the following:

[0242] Model description information corresponding to the AI ​​model, where the model description information is used to determine the AI ​​model;

[0243] Model transmission information corresponding to the AI ​​model, where the model transmission information is used to instruct the terminal device to obtain the model structure and / or model parameters of the AI ​​model; for example, the model transmission information may be used to indicate that the model to be transmitted is a completely new model structure and model parameters; for another example, the model transmission information may be used to indicate that the model to be transmitted is the model parameters of an AI model already deployed on the terminal device; optionally, the model transmission information may also be referred to as the type of the model to be transmitted;

[0244] The model storage information corresponding to the AI ​​model is used to establish a first connection between the terminal device and the first device. For example, it may include address information corresponding to the first device storing the AI ​​model and / or connection auxiliary information for establishing a connection with the first device.

[0245] In one implementation, the model description information includes at least one of the following:

[0246] Model ID, which can be used to identify the AI ​​model. Different AI models correspond to different model IDs.

[0247] Model size, which can be used to indicate the amount of data for the AI ​​model;

[0248] Model input information, which can be used to indicate relevant information (such as type and quantity) of the input data of the AI ​​model;

[0249] Model output information, which can be used to indicate relevant information (such as type and quantity) of the output data of the AI ​​model;

[0250] Model application environment information, which can be used to indicate the applicable environment of the AI ​​model. For example, it can indicate whether the AI ​​model is applicable to terminal devices and / or network devices;

[0251] Model format information, which can be used to indicate the format for storage and / or transmission of the AI ​​model. For example, the format may include the Open Neural Network Exchange (ONNX) format, a binary serialization format, etc. This embodiment does not limit the model format.

[0252] In some embodiments, the first information may also include indication information, which is used to instruct the terminal device to download the AI ​​model.

[0253] In some embodiments, the first information may be information sent by the network device to the terminal device in response to the third information. For example, the first information may be a response to the third information, and the network device may send the first information to the terminal device in response to receiving the third information.

[0254] In other embodiments, the first information may be proactively sent by the network device to the terminal device. In this case, the above step S2106 may be omitted.

[0255] In some embodiments, the network device may determine the first information based on the seventh information. For example, the first information may be the same as the seventh information. For another example, the first information may include part or all of the seventh information.

[0256] Step S2108: The terminal device sends fourth information to the network device.

[0257] In some embodiments, the terminal device may send the fourth information to the network device in response to receiving the first information.

[0258] In some embodiments, the network device may receive the fourth information. For example, the network device may receive the fourth information sent by the terminal device.

[0259] In some embodiments, the fourth information may be used in response to the first information.

[0260] In some embodiments, the fourth information can be used to instruct the terminal device to start downloading the AI ​​model.

[0261] In some embodiments, the fourth information can be used to indicate that the terminal device has successfully received the first information and / or the terminal device has started to execute the step of receiving the second information sent by the first device.

[0262] For example, the fourth information may be used to indicate that the terminal device has successfully received the first information (ie, responded to the first information).

[0263] For another example, the fourth information may be used to instruct the terminal device to begin receiving the second information. Optionally, the terminal device may begin receiving the second information by directly receiving the second information sent by the first device, or by first establishing a first connection with the first device and then receiving the second information.

[0264] For another example, the fourth information may be used to indicate that the terminal device has successfully received the first information, and also to instruct the terminal device to start executing the step of receiving the second information.

[0265] In some embodiments, step S2108 can be omitted, and the terminal device can start the step of receiving the second information directly based on the above-mentioned first information without sending the fourth information to the network device (it can directly receive the second information or establish a connection with the first device before receiving the second information).

[0266] In some embodiments, the name of the fourth information is not limited, for example, it can be "model transmission response", "model download response", "model download confirmation", etc.

[0267] In some embodiments, the fourth information may be carried in at least one of physical layer information, RRC message, MAC CE, UCI, NAS message, or other messages sent by the terminal device to the network device.

[0268] Step S2109: The terminal device establishes a first connection with the first device.

[0269] In some embodiments, the terminal device can determine the first device storing the AI ​​model based on the above-mentioned first information and establish a first connection with the first device.

[0270] Optionally, the first information may include model storage information (such as the first device storing the AI ​​model and / or connection auxiliary information), and the terminal device may establish a connection with the first device based on the model storage information.

[0271] In one implementation, the connection auxiliary information may include application layer transport protocol, IP address, port and other information. The application layer transport protocol may include any one of the following: Transmission Control Protocol (TCP), User Datagram Protocol (UDP), Stream Control Transmission Protocol (SCTP), File Transfer Protocol (FTP), Hypertext Transfer Protocol (HTTP), Session Initiation Protocol (SIP), etc.

[0272] In some embodiments, the first connection may be established based on a request from the terminal device and / or the first device.

[0273] In one implementation, the terminal device may initiate establishment of the first connection. For example, the terminal device may send a connection establishment request to the first device, and the first device may send a connection establishment response to the terminal device, thereby establishing the first connection.

[0274] In another implementation, the first device may initiate establishment of the first connection. For example, the first device may send a connection establishment request to the terminal device, and the terminal device may send a connection establishment response to the first device, thereby establishing the first connection.

[0275] In another implementation manner, the first device and the terminal device may also initiate establishment of the first connection in parallel.

[0276] In some embodiments, the terminal device may establish the first connection with the first device after receiving the first information sent by the network device.

[0277] In other embodiments, the first connection between the terminal device and the first device can also be established in advance, and the connection establishment step can be omitted during the process of downloading the AI ​​model.

[0278] In some other embodiments, the first device may also send the second information to the terminal device in a connectionless manner, and similarly, the terminal device may also receive the second information sent by the first device in a connectionless manner. In this case, the terminal device and the first device do not need to establish a first connection, and step S2109 may be omitted.

[0279] Step S2110: The first device sends second information to the terminal device.

[0280] In some embodiments, the terminal device may receive the second information. For example, the terminal device may receive the second information sent by the first device.

[0281] In some embodiments, the second information may include a model structure and / or model parameters of the AI ​​model.

[0282] In some embodiments, the second information can be used by the terminal device to obtain the model structure and / or model parameters of the AI ​​model.

[0283] In some embodiments, the name of the second information is not limited, and may be, for example, "model download information", "model information", "model data", etc.

[0284] In some embodiments, the second information may be information sent by the first device to the terminal device based on an application layer transmission protocol.

[0285] For example, the terminal device may obtain the second information from the first device based on any one of the above-mentioned application layer transmission protocols. For example, the terminal device may download the second information, i.e., download the AI ​​model, from the first device based on the TCP protocol or the FTP protocol.

[0286] In some embodiments, after successfully completing the transmission of the second information, the terminal device and / or the first device may actively release the first connection to improve network security.

[0287] In some embodiments, after successfully completing the transmission of the second information, if there is no new data transmission on the first connection within a specific time, the terminal device and / or the first device may proactively release the first connection. The specific time may be a configured time or a time specified by the protocol, such as 2 seconds, 5 seconds, or 10 seconds.

[0288] In some embodiments, after establishing the first connection, the terminal device can obtain second information corresponding to one or more AI models to improve the efficiency of information transmission.

[0289] Step S2111: The terminal device determines the model structure and / or model parameters of the AI ​​model.

[0290] In some embodiments, the terminal device can determine the model structure and / or model parameters of the AI ​​model based on the second information.

[0291] Optionally, the terminal device can perform specific functions based on the AI ​​model, such as at least one of CSI enhancement, beam prediction, positioning, etc.

[0292] In some embodiments, the AI ​​model determined by the terminal device may be a model obtained after training by the first device and / or the network device.

[0293] For example, the network device may generate an initial AI model and send the AI ​​model to the first device based on step S2101 above, and the first device may train the AI ​​model based on steps S2102 and S2103 above. In this way, the AI ​​model may be a model obtained after training by the first device.

[0294] For another example, the first device may directly deploy an initial AI model and perform training based on the above steps S2102 to S2103. In this way, the AI ​​model may be a model obtained after training by the first device.

[0295] For another example, the network device may pre-train the AI ​​model and send the pre-trained AI model to the first device based on step S2101. The first device may then re-train the pre-trained AI model based on steps S2102 and S2103. In this way, the AI ​​model may be the model obtained after training by the first device and the network device.

[0296] For another example, the network device can send the trained AI model generated in step S2101 to the first device, and the first device can directly store or use the AI ​​model. In this way, the AI ​​model can be a model obtained after training by the network device. Optionally, the first device can also retrain the AI ​​model to obtain a more optimized model structure and / or model parameters.

[0297] In some embodiments, the AI ​​model may perform a first function, wherein the first function may include at least one of the following functions:

[0298] Channel state information CSI enhancement;

[0299] Beam prediction;

[0300] position.

[0301] Optionally, the first function (i.e., the function performed by the AI ​​model) can also be referred to as an AI use case, an AI application case, etc., which is not limited in this disclosure.

[0302] In some embodiments, the network device may include at least one of the following:

[0303] Access network equipment;

[0304] Access and mobility management function AMF;

[0305] Location Management Function LMF.

[0306] In some embodiments, different network devices may perform different first functions based on the AI ​​model. For example, the AMF may be configured to perform one or more of the aforementioned functions based on the AI ​​model. For another example, the access network device and / or the AMF may perform beam prediction based on the AI ​​model. For another example, the AMF and / or the LMF may perform positioning based on the AI ​​model.

[0307] In some embodiments, the network device is the network device corresponding to the first function. The network devices corresponding to different first functions may be the same or different. When the first function executed by the AI ​​model is determined, the network device is the network device corresponding to the first function.

[0308] For example, the network device corresponding to the CSI enhancement function is AMF. That is to say, if the first function performed by the AI ​​model is CSI enhancement, the network device can be AMF.

[0309] For another example, the network device corresponding to the beam prediction function is AMF and / or access network device. That is to say, if the first function performed by the AI ​​model is beam prediction, the network device can be AMF and / or access network device.

[0310] For another example, the network device corresponding to the positioning function is AMF and / or LMF. That is to say, if the first function performed by the AI ​​model is positioning, the network device can be AMF and / or LMF.

[0311] The method involved in the embodiment of the present disclosure may include at least one of the above steps S2101 to S2111. For example, step S2110 can be implemented as an independent embodiment, steps S2107+S2110 can be implemented as an independent embodiment, steps S2109+S2110 can be implemented as an independent embodiment, steps S2107+S2109+S2110 can be implemented as an independent embodiment, steps S2107+S2110+S2111 can be implemented as an independent embodiment, steps S2107+S2109+S2110+S2111 can be implemented as an independent embodiment, steps S2106+S2107+S2109+S2110 can be implemented as an independent embodiment, steps S2107+S2108+S2109+S2110 can be implemented as an independent embodiment, Steps S2106+S2107+S2108+S2109+S2110 can be implemented as independent embodiments, step S2102+S2103 can be implemented as an independent embodiment, step S2101+S2102+S2103 can be implemented as an independent embodiment, step S2102+S2103+S2105 can be implemented as an independent embodiment, step S2104+S2105 can be implemented as an independent embodiment, step S2102+S2103+S2104+S2105 can be implemented as an independent embodiment, step S2104+S2105+S2107+S2108+S2109+S2110 can be implemented as an independent embodiment, but are not limited thereto.

[0312] In some embodiments, the above steps S2101 to S21011 can be executed in a swapped order or simultaneously.

[0313] In some embodiments, the above steps S2101 to S21011 are all optional steps.

[0314] In some embodiments, reference may be made to other optional implementations described before or after the description corresponding to FIG. 2A .

[0315] FIG2B is an interactive diagram illustrating a method for transmitting model information according to an embodiment of the present disclosure. As shown in FIG2B , the embodiment of the present disclosure relates to a method for transmitting model information, which can be executed by a communication system and can include:

[0316] Step S2201: The terminal device sends third information to the network device.

[0317] The optional implementation of step S2201 can refer to the optional implementation of step S2106 in FIG2A and other related parts in the embodiment involved in FIG2A , which will not be described in detail here.

[0318] Step S2202: The network device sends first information to the terminal device.

[0319] The optional implementation of step S2202 can refer to the optional implementation of step S2107 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0320] Step S2203: The terminal device establishes a first connection with the first device.

[0321] The optional implementation of step S2203 can refer to the optional implementation of step S2109 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0322] In some embodiments, the first connection may be established based on a request from the terminal device. For example, the terminal device may send a connection establishment request to the first device, and the first device may send a connection establishment response to the terminal device, thereby establishing the first connection.

[0323] Step S2204: The first device sends second information to the terminal device.

[0324] The optional implementation of step S2204 can refer to the optional implementation of step S2110 in FIG. 2A and other related parts in the embodiment involved in FIG. 2A , which will not be described in detail here.

[0325] In some embodiments, the above steps are all optional steps.

[0326] In some embodiments, the embodiment shown in FIG. 2B may also be combined with any one or more steps in the embodiment shown in FIG. 2A to form a new embodiment.

[0327] FIG2C is an interactive diagram illustrating a method for transmitting model information according to an embodiment of the present disclosure. As shown in FIG2C , an embodiment of the present disclosure relates to a method for transmitting model information, which can be executed by a communication system and can include:

[0328] Step S2301: The network device sends first information to the terminal device.

[0329] The optional implementation of step S2301 can refer to the optional implementation of step S2107 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0330] Step S2302: The terminal device sends fourth information to the network device.

[0331] The optional implementation of step S2302 can refer to the optional implementation of step S2108 in FIG2A and other related parts in the embodiment involved in FIG2A , which will not be described in detail here.

[0332] Step S2303: The terminal device establishes a first connection with the first device.

[0333] The optional implementation of step S2303 can refer to the optional implementation of step S2109 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0334] In some embodiments, the first connection may be established based on a request from the first device. For example, the first device may send a connection establishment request to the terminal device, and the terminal device may send a connection establishment response to the first device, thereby establishing the first connection.

[0335] Step S2304: The first device sends second information to the terminal device.

[0336] The optional implementation of step S2304 can refer to the optional implementation of step S2110 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0337] In some embodiments, the above steps are all optional steps.

[0338] In some embodiments, the embodiment shown in FIG. 2C may also be combined with any one or more steps in the embodiment shown in FIG. 2A to form a new embodiment.

[0339] FIG2D is an interactive diagram illustrating a method for transmitting model information according to an embodiment of the present disclosure. As shown in FIG2D , an embodiment of the present disclosure relates to a method for transmitting model information, which can be executed by a communication system and can include:

[0340] Step S2401: The network device sends fifth information to the first device.

[0341] The optional implementation of step S2401 can refer to the optional implementation of step S2102 in FIG. 2A and other related parts in the embodiment involved in FIG. 2A , which will not be described in detail here.

[0342] Step S2402: The first device performs model training.

[0343] The optional implementation of step S2402 can refer to the optional implementation of step S2103 in FIG. 2A and other related parts in the embodiment involved in FIG. 2A , which will not be described in detail here.

[0344] Step S2403: The first device sends seventh information to the network device.

[0345] The optional implementation of step S2403 can refer to the optional implementation of step S2105 in FIG2A and other related parts in the embodiment involved in FIG2A , which will not be described in detail here.

[0346] Step S2404: The network device sends the first message to the terminal device.

[0347] The optional implementation of step S2404 can refer to the optional implementation of step S2107 in FIG. 2A and other related parts in the embodiment involved in FIG. 2A , which will not be described in detail here.

[0348] Step S2405: The terminal device sends fourth information to the network device.

[0349] The optional implementation of step S2405 can refer to the optional implementation of step S2108 in FIG2A and other related parts in the embodiment involved in FIG2A , which will not be described in detail here.

[0350] Step S2406: The terminal device establishes a first connection with the first device.

[0351] The optional implementation of step S2406 can refer to the optional implementation of step S2109 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0352] In some embodiments, the first connection may be established based on a request from the first device. For example, the first device may send a connection establishment request to the terminal device, and the terminal device may send a connection establishment response to the first device, thereby establishing the first connection.

[0353] Step S2407: The first device sends second information to the terminal device.

[0354] The optional implementation of step S2407 can refer to the optional implementation of step S2110 in FIG. 2A and other related parts in the embodiment involved in FIG. 2A , which will not be described in detail here.

[0355] In some embodiments, the above steps are all optional steps.

[0356] In some embodiments, the embodiment shown in FIG. 2D may also be combined with any one or more steps in the embodiment shown in FIG. 2A to form a new embodiment.

[0357] Figure 2E is an interactive diagram illustrating a model information transmission method according to an embodiment of the present disclosure. As shown in Figure 2E, the embodiment of the present disclosure relates to a model information transmission method, which can be executed by a communication system and may include:

[0358] Step S2501: The terminal device sends third information to the network device.

[0359] The optional implementation of step S2501 can refer to the optional implementation of step S2106 in FIG2A and other related parts in the embodiment involved in FIG2A , which will not be described in detail here.

[0360] Step S2502: The network device sends sixth information to the first device.

[0361] The optional implementation of step S2502 can refer to the optional implementation of step S2104 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0362] Step S2503: The first device sends seventh information to the network device.

[0363] The optional implementation of step S2503 can refer to the optional implementation of step S2105 in FIG. 2A and other related parts in the embodiment involved in FIG. 2A , which will not be described in detail here.

[0364] Step S2504: The network device sends first information to the terminal device.

[0365] The optional implementation of step S2504 can refer to the optional implementation of step S2107 in FIG2A and other related parts in the embodiment involved in FIG2A , which will not be described in detail here.

[0366] Step S2505: The terminal device establishes a first connection with the first device.

[0367] The optional implementation of step S2505 can refer to the optional implementation of step S2109 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0368] In some embodiments, the first connection may be established based on a request from the terminal device. For example, the terminal device may send a connection establishment request to the first device, and the first device may send a connection establishment response to the terminal device, thereby establishing the first connection.

[0369] Step S2506: The first device sends second information to the terminal device.

[0370] The optional implementation of step S2506 can refer to the optional implementation of step S2110 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0371] In some embodiments, the above steps are all optional steps.

[0372] In some embodiments, the embodiment shown in FIG. 2E may also be combined with any one or more steps in the embodiment shown in FIG. 2A to form a new embodiment.

[0373] Figure 2F is an interactive diagram illustrating a model information transmission method according to an embodiment of the present disclosure. As shown in Figure 2F, the embodiment of the present disclosure relates to a model information transmission method, which can be executed by a communication system and may include:

[0374] Step S2601: The network device sends a first message to the terminal device.

[0375] The optional implementation of step S2601 can refer to the optional implementation of step S2107 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0376] Step S2602: The first device sends the second information to the terminal device.

[0377] The optional implementation of step S2602 can refer to the optional implementation of step S2110 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0378] In some embodiments, the above steps are all optional steps.

[0379] In some embodiments, the embodiment shown in FIG. 2F may also be combined with any one or more steps in the embodiment shown in FIG. 2A to form a new embodiment.

[0380] FIG3A is a flow chart of a method for transmitting model information according to an embodiment of the present disclosure. As shown in FIG3A , the embodiment of the present disclosure relates to a method for transmitting model information, which can be executed by a terminal device. The method may include:

[0381] Step S3101: Send the third information.

[0382] The optional implementation of step S3101 can refer to the optional implementation of step S2106 in FIG2A and other related parts in the embodiment involved in FIG2A , which will not be described in detail here.

[0383] In some embodiments, the terminal device may send the third information to the network device, but is not limited thereto. The terminal device may also send the third information to other entities.

[0384] Step S3102: Obtain first information.

[0385] The optional implementation of step S3102 can refer to the optional implementation of step S2107 in FIG2A and other related parts in the embodiment involved in FIG2A , which will not be described in detail here.

[0386] In some embodiments, the terminal device may receive the first information sent by the network device, but is not limited thereto. The terminal device may also receive the first information sent by other entities.

[0387] In some embodiments, the terminal device may obtain first information specified by the protocol.

[0388] In some embodiments, the terminal device may obtain the first information from an upper layer(s).

[0389] In some embodiments, the terminal device may perform processing to obtain the first information.

[0390] In some embodiments, step S3102 may be omitted, and the terminal device may autonomously implement the function indicated by the first information, or the above function may be default or by default.

[0391] Step S3103: Send the fourth information.

[0392] The optional implementation of step S3103 can refer to the optional implementation of step S2108 in FIG2A and other related parts in the embodiment involved in FIG2A , which will not be described in detail here.

[0393] In some embodiments, the terminal device may send the fourth information to the network device, but is not limited thereto. The terminal device may also send the fourth information to other entities.

[0394] Step S3104: The terminal device establishes a first connection with the first device.

[0395] The optional implementation of step S3104 can refer to the optional implementation of step S2109 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0396] Step S3105: Obtain second information.

[0397] The optional implementation of step S3105 can refer to the optional implementation of step S2110 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0398] In some embodiments, the terminal device may receive the second information sent by the first device, but is not limited thereto. The terminal device may also receive the second information sent by other entities.

[0399] In some embodiments, the terminal device may perform processing to obtain the second information.

[0400] Step S3106: Determine the model structure and / or model parameters of the AI ​​model.

[0401] The optional implementation of step S3106 can refer to the optional implementation of step S2111 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0402] The method involved in the embodiments of the present disclosure may include at least one of the above steps S3101 to S3106. For example, step S3105 can be implemented as an independent embodiment, steps S3102+S3105 can be implemented as an independent embodiment, steps S3104+S3105 can be implemented as an independent embodiment, steps S3102+S3104+S3105 can be implemented as an independent embodiment, steps S3101+S3102+S3104+S3105 can be implemented as an independent embodiment, steps S3102+S3103+S3104+S3105 can be implemented as an independent embodiment, steps S3101+S3102+S3105 can be implemented as an independent embodiment, and steps S3102+S3103+S3105 can be implemented as an independent embodiment, but the present invention is not limited thereto.

[0403] In some embodiments, the above steps S3101 to S3106 can be executed in a swapped order or simultaneously.

[0404] In some embodiments, the above steps S3101 to S3106 are all optional steps.

[0405] FIG3B is a flow chart of a method for transmitting model information according to an embodiment of the present disclosure. As shown in FIG3B , the embodiment of the present disclosure relates to a method for transmitting model information, which can be executed by a terminal device. The method may include:

[0406] Step S3201: Send the third information.

[0407] The optional implementation of step S3201 can be found in step S2106 of FIG. 2A , the optional implementation of step S3101 of FIG. 3A , and other related parts in the embodiments involved in FIG. 2A and FIG. 3A , which will not be described in detail here.

[0408] Step S3202: Obtain first information.

[0409] The optional implementation of step S3202 can be found in step S2107 of FIG. 2A , the optional implementation of step S3102 of FIG. 3A , and other related parts in the embodiments involved in FIG. 2A and FIG. 3A , which will not be described in detail here.

[0410] Step S3203: The terminal device establishes a first connection with the first device.

[0411] The optional implementation of step S3203 can be found in step S2109 of FIG. 2A , the optional implementation of step S3104 of FIG. 3A , and other related parts in the embodiments involved in FIG. 2A and FIG. 3A , which will not be described in detail here.

[0412] Step S3204: Obtain second information.

[0413] The optional implementation of step S3204 can be found in step S2110 of FIG. 2A , the optional implementation of step S3105 of FIG. 3A , and other related parts in the embodiments involved in FIG. 2A and FIG. 3A , which will not be described in detail here.

[0414] In some embodiments, the above steps are all optional steps.

[0415] In some embodiments, the embodiment shown in FIG. 3B may also be combined with any one or more steps in the embodiment shown in FIG. 3A to form a new embodiment.

[0416] FIG3C is a flow chart of a method for transmitting model information according to an embodiment of the present disclosure. As shown in FIG3C , an embodiment of the present disclosure relates to a method for transmitting model information, which can be executed by a terminal device. The method may include:

[0417] Step S3301: Obtain first information.

[0418] The optional implementation of step S3301 can be found in step S2107 of FIG. 2A , the optional implementation of step S3102 of FIG. 3A , and other related parts in the embodiments involved in FIG. 2A and FIG. 3A , which will not be described in detail here.

[0419] Step S3302: Send the fourth information.

[0420] The optional implementation of step S3302 can be found in step S2108 of FIG. 2A , the optional implementation of step S3103 of FIG. 3A , and other related parts in the embodiments involved in FIG. 2A and FIG. 3A , which will not be described in detail here.

[0421] Step S3303: The terminal device establishes a first connection with the first device.

[0422] The optional implementation of step S3303 can be found in step S2109 of FIG. 2A , the optional implementation of step S3104 of FIG. 3A , and other related parts in the embodiments involved in FIG. 2A and FIG. 3A , which will not be described in detail here.

[0423] Step S3304: Obtain the second information.

[0424] The optional implementation of step S3304 can be found in step S2110 of FIG. 2A , the optional implementation of step S3105 of FIG. 3A , and other related parts in the embodiments involved in FIG. 2A and FIG. 3A , which will not be repeated here.

[0425] In some embodiments, the above steps are all optional steps.

[0426] In some embodiments, the embodiment shown in FIG. 3C may also be combined with any one or more steps in the embodiment shown in FIG. 3A to form a new embodiment.

[0427] FIG3D is a flow chart of a method for transmitting model information according to an embodiment of the present disclosure. As shown in FIG3D , the embodiment of the present disclosure relates to a method for transmitting model information, which can be executed by a terminal device. The method may include:

[0428] Step S3401: Obtain first information.

[0429] The optional implementation of step S3401 can be found in step S2107 of FIG. 2A , the optional implementation of step S3102 of FIG. 3A , and other related parts in the embodiments involved in FIG. 2A and FIG. 3A , which will not be described in detail here.

[0430] Step S3402: Obtain second information.

[0431] The optional implementation of step S3402 can be found in step S2110 of FIG. 2A , the optional implementation of step S3105 of FIG. 3A , and other related parts in the embodiments involved in FIG. 2A and FIG. 3A , which will not be described in detail here.

[0432] In some embodiments, the above steps are all optional steps.

[0433] In some embodiments, the embodiment shown in FIG. 3D may also be combined with any one or more steps in the embodiment shown in FIG. 3A to form a new embodiment.

[0434] In some embodiments, the first information is used to assist the terminal device in obtaining second information corresponding to the artificial intelligence AI model from the first device, where the second information includes the model structure and / or model parameters of the AI ​​model.

[0435] In some embodiments, the method further comprises:

[0436] Establishing a first connection, where the first connection is a connection between the terminal device and the first device;

[0437] And wherein, receiving the second information sent by the first device includes: receiving the second information sent by the first device through the first connection.

[0438] In some embodiments, the first connection is established based on a request from the terminal device and / or the first device.

[0439] In some embodiments, the second information is information sent by the first device to the terminal device based on an application layer transmission protocol.

[0440] In some embodiments, the first information includes at least one of the following:

[0441] Model description information corresponding to the AI ​​model, wherein the model description information is used to determine the AI ​​model;

[0442] Model transmission information corresponding to the AI ​​model, wherein the model transmission information is used to instruct the terminal device to obtain the model structure and / or model parameters of the AI ​​model;

[0443] Model storage information corresponding to the AI ​​model, wherein the model storage information is used to establish a first connection between the terminal device and the first device.

[0444] In some embodiments, the model description information includes at least one of the following: model identification; model size; model input information; model output information; model application environment information; and model format information.

[0445] In some embodiments, the method further comprises at least one of the following:

[0446] Sending third information to the network device, where the third information is used to request the network device to send the first information;

[0447] In response to receiving the first information sent by the network device, fourth information is sent to the network device, and the fourth information is used to indicate that the terminal device has successfully received the first information and / or the terminal device has started to execute the step of receiving the second information sent by the first device.

[0448] In some embodiments, the AI ​​model is a model obtained after training the first device and / or the network device.

[0449] In some embodiments, the AI ​​model is used to perform a first function, wherein the first function includes at least one of the following functions: channel state information CSI enhancement; beam prediction; positioning.

[0450] In some embodiments, the network device includes at least one of the following: access network equipment; access and mobility management function AMF; positioning management function LMF.

[0451] In some embodiments, the network device is a network device corresponding to the first function.

[0452] FIG4A is a flow chart of a model information transmission method according to an embodiment of the present disclosure. As shown in FIG4A , the embodiment of the present disclosure relates to a model information transmission method, which can be executed by a network device, and the method includes:

[0453] Step S4101: Send the eighth information.

[0454] The optional implementation of step S4101 can refer to the optional implementation of step S2101 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0455] In some embodiments, the network device may send the eighth information to the first device, but is not limited thereto. The network device may also send the eighth information to other entities.

[0456] Step S4102: Send the fifth information.

[0457] The optional implementation of step S4102 can refer to the optional implementation of step S2102 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0458] In some embodiments, the network device may send the fifth information to the first device, but is not limited thereto. The network device may also send the fifth information to other entities.

[0459] Step S4103: Send the sixth information.

[0460] The optional implementation of step S4103 can refer to the optional implementation of step S2104 in FIG2A and other related parts in the embodiment involved in FIG2A , which will not be described in detail here.

[0461] In some embodiments, the network device may send the sixth information to the first device, but is not limited thereto. The network device may also send the sixth information to other entities.

[0462] Step S4104: Obtain the seventh information.

[0463] The optional implementation of step S4104 can refer to the optional implementation of step S2105 in FIG2A and other related parts in the embodiment involved in FIG2A , which will not be described in detail here.

[0464] In some embodiments, the network device may receive the seventh information sent by the first device, but is not limited thereto. The network device may also receive the seventh information sent by other entities.

[0465] In some embodiments, the network device may perform processing to obtain the seventh information.

[0466] Step S4105: Obtain third information.

[0467] The optional implementation of step S4105 can refer to the optional implementation of step S2106 in FIG2A and other related parts in the embodiment involved in FIG2A , which will not be described in detail here.

[0468] In some embodiments, the network device may receive the third information sent by the terminal device, but is not limited thereto. The network device may also receive the third information sent by other entities.

[0469] In some embodiments, the network device may perform processing to obtain the third information.

[0470] Step S4106: Send the first information.

[0471] The optional implementation of step S4106 can refer to the optional implementation of step S2107 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0472] In some embodiments, the network device may send the first information to the terminal device, but is not limited thereto. The network device may also send the first information to other entities.

[0473] Step S4107: Obtain fourth information.

[0474] The optional implementation of step S4107 can refer to the optional implementation of step S2108 in FIG2A and other related parts in the embodiment involved in FIG2A , which will not be described in detail here.

[0475] In some embodiments, the network device may receive the fourth information sent by the terminal device, but is not limited thereto. The network device may also receive the fourth information sent by other entities.

[0476] In some embodiments, the network device may perform processing to obtain the fourth information.

[0477] The method involved in the embodiment of the present disclosure may include at least one of the above steps S4101 to S4107. For example, step S4106 can be implemented as an independent embodiment, step S4101 can be implemented as an independent embodiment, step S4102 can be implemented as an independent embodiment, step S4105 can be implemented as an independent embodiment, steps S4105+S4106 can be implemented as an independent embodiment, steps S4106+S4107 can be implemented as an independent embodiment, steps S4105+S4106+S4107 can be implemented as an independent embodiment, and step S4106 can be implemented as an independent embodiment. 2+S4104 can be implemented as an independent embodiment, step S4103+S4104 can be implemented as an independent embodiment, step S4101+S4104 can be implemented as an independent embodiment, step S4102+S4104+S4106 can be implemented as an independent embodiment, step S4103+S4104+S4106 can be implemented as an independent embodiment, step S4101+S4104+S4106 can be implemented as an independent embodiment, but is not limited to this.

[0478] In some embodiments, the above steps S4101 to S4107 can be executed in a swapped order or simultaneously.

[0479] In some embodiments, the above steps S4101 to S4107 are all optional steps.

[0480] FIG4B is a flow chart of a method for transmitting model information according to an embodiment of the present disclosure. As shown in FIG4B , the embodiment of the present disclosure relates to a method for transmitting model information, which can be executed by a network device. The method may include:

[0481] Step S4201: Obtain third information.

[0482] The optional implementation of step S4201 can be found in step S2106 of FIG. 2A , the optional implementation of step S4105 of FIG. 4A , and other related parts in the embodiments involved in FIG. 2A and FIG. 4A , which will not be described in detail here.

[0483] Step S4202: Send the first information.

[0484] The optional implementation of step S4202 can be found in step S2107 of FIG. 2A , the optional implementation of step S4106 of FIG. 4A , and other related parts in the embodiments involved in FIG. 2A and FIG. 4A , which will not be described in detail here.

[0485] In some embodiments, the above steps are all optional steps.

[0486] In some embodiments, the embodiment shown in FIG. 4B may also be combined with any one or more steps in the embodiment shown in FIG. 4A to form a new embodiment.

[0487] FIG4C is a flow chart of a method for transmitting model information according to an embodiment of the present disclosure. As shown in FIG4C , the embodiment of the present disclosure relates to a method for transmitting model information, which can be executed by a network device. The method may include:

[0488] Step S4301: Send the first information.

[0489] The optional implementation of step S4301 can be found in step S2107 of FIG. 2A , the optional implementation of step S4106 of FIG. 4A , and other related parts in the embodiments involved in FIG. 2A and FIG. 4A , which will not be described in detail here.

[0490] Step S4302: Obtain fourth information.

[0491] The optional implementation of step S4302 can be found in step S2108 of FIG. 2A , the optional implementation of step S4107 of FIG. 4A , and other related parts in the embodiments involved in FIG. 2A and FIG. 4A , which will not be described in detail here.

[0492] In some embodiments, the above steps are all optional steps.

[0493] In some embodiments, the embodiment shown in FIG. 4C may also be combined with any one or more steps in the embodiment shown in FIG. 4A to form a new embodiment.

[0494] FIG4D is a flow chart of a method for transmitting model information according to an embodiment of the present disclosure. As shown in FIG4D , an embodiment of the present disclosure relates to a method for transmitting model information, which can be executed by a network device. The method may include:

[0495] Step S4401: Send the fifth information.

[0496] Optional implementations of step S4401 may refer to step S2102 in FIG. 2A , optional implementations of step S4102 in FIG. 4A , and other related parts in the embodiments involved in FIG. 2A and FIG. 4A , which will not be described in detail here.

[0497] Step S4402: Obtain the seventh information.

[0498] The optional implementation of step S4402 can be found in step S2105 of FIG. 2A , the optional implementation of step S4104 of FIG. 4A , and other related parts in the embodiments involved in FIG. 2A and FIG. 4A , which will not be described in detail here.

[0499] Step S4403: Send the first information.

[0500] Optional implementations of step S4403 may refer to step S2107 in FIG. 2A , optional implementations of step S4106 in FIG. 4A , and other related parts in the embodiments involved in FIG. 2A and FIG. 4A , which will not be described in detail here.

[0501] Step S4404: Obtain fourth information.

[0502] The optional implementation of step S4404 can be found in step S2108 of FIG. 2A , the optional implementation of step S4107 of FIG. 4A , and other related parts in the embodiments involved in FIG. 2A and FIG. 4A , which will not be described in detail here.

[0503] In some embodiments, the above steps are all optional steps.

[0504] In some embodiments, the embodiment shown in FIG. 4D may also be combined with any one or more steps in the embodiment shown in FIG. 4A to form a new embodiment.

[0505] FIG4E is a flow chart of a measurement method according to an embodiment of the present disclosure. As shown in FIG4E , an embodiment of the present disclosure relates to a measurement method, which can be performed by a network device. The method may include:

[0506] Step S4501: Obtain third information.

[0507] Optional implementations of step S4501 may refer to step S2106 in FIG. 2A , optional implementations of step S4105 in FIG. 4A , and other related parts in the embodiments involved in FIG. 2A and FIG. 4A , which will not be described in detail here.

[0508] Step S4502: Send the sixth information.

[0509] The optional implementation of step S4502 can be found in step S2104 of FIG. 2A , the optional implementation of step S4103 of FIG. 4A , and other related parts in the embodiments involved in FIG. 2A and FIG. 4A , which will not be described in detail here.

[0510] Step S4503: Obtain the seventh information.

[0511] The optional implementation of step S4503 can be found in step S2105 of FIG. 2A , the optional implementation of step S4104 of FIG. 4A , and other related parts in the embodiments involved in FIG. 2A and FIG. 4A , which will not be described in detail here.

[0512] Step S4504: Send the first information.

[0513] The optional implementation of step S4504 can be found in step S2107 of FIG. 2A , the optional implementation of step S4106 of FIG. 4A , and other related parts in the embodiments involved in FIG. 2A and FIG. 4A , which will not be described in detail here.

[0514] In some embodiments, the above steps are all optional steps.

[0515] In some embodiments, the embodiment shown in FIG. 4E may also be combined with any one or more steps in the embodiment shown in FIG. 4A to form a new embodiment.

[0516] FIG4F is a flow chart of a measurement method according to an embodiment of the present disclosure. As shown in FIG4F , an embodiment of the present disclosure relates to a measurement method, which can be performed by a network device. The method may include:

[0517] Step S4601: Send the first information.

[0518] The optional implementation of step S4601 can be found in step S2107 of FIG. 2A , the optional implementation of step S4106 of FIG. 4A , and other related parts in the embodiments involved in FIG. 2A and FIG. 4A , which will not be repeated here.

[0519] In some embodiments, the above steps are all optional steps.

[0520] In some embodiments, the embodiment shown in FIG. 4F may also be combined with any one or more steps in the embodiment shown in FIG. 4A to form a new embodiment.

[0521] In some embodiments, the first information is used to assist the terminal device in obtaining second information corresponding to the artificial intelligence AI model from the first device, where the second information includes the model structure and / or model parameters of the AI ​​model.

[0522] In some embodiments, the first information includes at least one of the following:

[0523] Model description information corresponding to the AI ​​model, wherein the model description information is used to determine the AI ​​model;

[0524] Model transmission information corresponding to the AI ​​model, wherein the model transmission information is used to instruct the terminal device to obtain the model structure and / or model parameters of the AI ​​model;

[0525] Model storage information corresponding to the AI ​​model, wherein the model storage information is used to establish a first connection between the terminal device and the first device.

[0526] In some embodiments, the model description information includes at least one of the following: model identification; model size; model input information; model output information; model application environment information; and model format information.

[0527] In some embodiments, the method further comprises at least one of the following:

[0528] receiving third information sent by the terminal device, where the third information is used to request the network device to send the first information;

[0529] Receive fourth information sent by the terminal device, where the fourth information is used to indicate that the terminal device has successfully received the first information and / or that the terminal device has started to execute the step of receiving the second information sent by the first device.

[0530] In some embodiments, the AI ​​model is a model obtained after training the first device and / or the network device.

[0531] In some embodiments, the method further comprises at least one of the following:

[0532] Sending fifth information to the first device, where the fifth information is used by the first device to train the AI ​​model;

[0533] receiving seventh information sent by the first device, where the seventh information includes information for assisting the terminal device in acquiring the AI ​​model;

[0534] sending sixth information to the first device, where the sixth information is used to request the first device to send the seventh information;

[0535] Send eighth information to the first device, where the eighth information includes the AI ​​model generated by the network device.

[0536] In some embodiments, the AI ​​model is used to perform a first function, wherein the first function includes at least one of the following functions: channel state information CSI enhancement; beam prediction; positioning.

[0537] In some embodiments, the network device includes at least one of the following: access network equipment; access and mobility management function AMF; positioning management function LMF.

[0538] In some embodiments, the network device is a network device corresponding to the first function.

[0539] FIG5A is a flow chart of a method for transmitting model information according to an embodiment of the present disclosure. As shown in FIG5A , the embodiment of the present disclosure relates to a method for transmitting model information, which can be executed by a first device. The method includes:

[0540] Step S5101: Obtain the eighth information.

[0541] The optional implementation of step S5101 can refer to the optional implementation of step S2101 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0542] In some embodiments, the first device may receive the eighth information sent by the network device, but is not limited thereto. The first device may also receive the eighth information sent by other entities.

[0543] In some embodiments, the first device may perform processing to obtain the eighth information.

[0544] Step S5102: Obtain the fifth information.

[0545] The optional implementation of step S5102 can refer to the optional implementation of step S2102 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0546] In some embodiments, the first device may receive the fifth information sent by the network device, but is not limited thereto. The first device may also receive the fifth information sent by other entities.

[0547] In some embodiments, the first device may perform processing to obtain the fifth information.

[0548] Step S5103: Execute model training.

[0549] The optional implementation of step S5103 can refer to the optional implementation of step S2103 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0550] Step S5104: Obtain sixth information.

[0551] The optional implementation of step S5104 can refer to the optional implementation of step S2104 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0552] In some embodiments, the first device may receive the sixth information sent by the network device, but is not limited thereto. The first device may also receive the sixth information sent by other entities.

[0553] In some embodiments, the first device may perform processing to obtain the sixth information.

[0554] Step S5105: Send the seventh information.

[0555] The optional implementation of step S5105 can refer to the optional implementation of step S2105 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0556] In some embodiments, the first device may send the seventh information to the network device, but is not limited thereto. The first device may also send the seventh information to other entities.

[0557] Step S5106: The first device establishes a first connection with the terminal device.

[0558] The optional implementation of step S5106 can refer to the optional implementation of step S2109 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0559] Step S5107: Send the second information.

[0560] The optional implementation of step S5107 can refer to the optional implementation of step S2110 in Figure 2A and other related parts in the embodiment involved in Figure 2A, which will not be repeated here.

[0561] In some embodiments, the first device may send the second information to the terminal device, but is not limited thereto. The first device may also send the second information to other entities.

[0562] The method involved in the embodiments of the present disclosure may include at least one of the above steps S5101 to S5107. For example, step S5107 can be implemented as an independent embodiment, step S5105 can be implemented as an independent embodiment, steps S5106 + S5107 can be implemented as an independent embodiment, steps S5104 + S5105 can be implemented as an independent embodiment, steps S5102 + S5103 + S5105 can be implemented as an independent embodiment, steps S5104 + S5105 + S5106 + S5107 can be implemented as an independent embodiment, steps S5102 + S5103 + S5105 + S5106 + S5107 can be implemented as an independent embodiment, and steps S5101 + S5104 + S5105 + S5106 + S5107 can be implemented as an independent embodiment, but are not limited thereto.

[0563] In some embodiments, the above steps S5101 to S5107 can be executed in a swapped order or simultaneously.

[0564] In some embodiments, the above steps S5101 to S5107 are all optional steps.

[0565] FIG5B is a flow chart of a method for transmitting model information according to an embodiment of the present disclosure. As shown in FIG5B , the embodiment of the present disclosure relates to a method for transmitting model information, which can be performed by a first device. The method may include:

[0566] Step S5201: The first device establishes a first connection with the terminal device.

[0567] The optional implementation of step S5201 can be found in step S2109 of FIG. 2A , the optional implementation of step S5106 of FIG. 5A , and other related parts in the embodiments involved in FIG. 2A and FIG. 5A , which will not be described in detail here.

[0568] Step S5202: Send the second information.

[0569] The optional implementation of step S5202 can be found in step S2110 of FIG. 2A , the optional implementation of step S5107 of FIG. 5A , and other related parts in the embodiments involved in FIG. 2A and FIG. 5A , which will not be repeated here.

[0570] In some embodiments, the above steps are all optional steps.

[0571] In some embodiments, the embodiment shown in FIG. 5B may also be combined with any one or more steps in the embodiment shown in FIG. 5A to form a new embodiment.

[0572] FIG5C is a flow chart of a method for transmitting model information according to an embodiment of the present disclosure. As shown in FIG5C , an embodiment of the present disclosure relates to a method for transmitting model information, which can be performed by a first device. The method may include:

[0573] Step S5301: Obtain the fifth information.

[0574] The optional implementation of step S5301 can be found in step S2102 of FIG. 2A , the optional implementation of step S5102 of FIG. 5A , and other related parts in the embodiments involved in FIG. 2A and FIG. 5A , which will not be repeated here.

[0575] Step S5302: Execute model training.

[0576] The optional implementation of step S5302 can be found in step S2103 of FIG. 2A , the optional implementation of step S5103 of FIG. 5A , and other related parts in the embodiments involved in FIG. 2A and FIG. 5A , which will not be repeated here.

[0577] Step S5303: Send the seventh information.

[0578] The optional implementation of step S5303 can be found in step S2105 of FIG. 2A , the optional implementation of step S5105 of FIG. 5A , and other related parts in the embodiments involved in FIG. 2A and FIG. 5A , which will not be described in detail here.

[0579] Step S5304: The first device establishes a first connection with the terminal device.

[0580] The optional implementation of step S5304 can be found in step S2109 of FIG. 2A , the optional implementation of step S5106 of FIG. 5A , and other related parts in the embodiments involved in FIG. 2A and FIG. 5A , which will not be described in detail here.

[0581] Step S5305: Send the second information.

[0582] The optional implementation of step S5305 can be found in step S2110 of FIG. 2A , the optional implementation of step S5107 of FIG. 5A , and other related parts in the embodiments involved in FIG. 2A and FIG. 5A , which will not be described in detail here.

[0583] In some embodiments, the above steps are all optional steps.

[0584] In some embodiments, the embodiment shown in FIG. 5C may also be combined with any one or more steps in the embodiment shown in FIG. 5A to form a new embodiment.

[0585] FIG5D is a flow chart of a method for transmitting model information according to an embodiment of the present disclosure. As shown in FIG5D , an embodiment of the present disclosure relates to a method for transmitting model information, which can be performed by a first device. The method may include:

[0586] Step S5401: Obtain sixth information.

[0587] Optional implementations of step S5401 may refer to step S2104 in FIG. 2A , optional implementations of step S5104 in FIG. 5A , and other related parts in the embodiments involved in FIG. 2A and FIG. 5A , which will not be described in detail here.

[0588] Step S5402: Send the seventh information.

[0589] The optional implementation of step S5402 can be found in step S2105 of FIG. 2A , the optional implementation of step S5105 of FIG. 5A , and other related parts in the embodiments involved in FIG. 2A and FIG. 5A , which will not be repeated here.

[0590] Step S5403: The first device establishes a first connection with the terminal device.

[0591] The optional implementation of step S5403 can be found in step S2109 of FIG. 2A , the optional implementation of step S5106 of FIG. 5A , and other related parts in the embodiments involved in FIG. 2A and FIG. 5A , which will not be described in detail here.

[0592] Step S5404: Send the second information.

[0593] The optional implementation of step S5404 can be found in step S2110 of FIG. 2A , the optional implementation of step S5107 of FIG. 5A , and other related parts in the embodiments involved in FIG. 2A and FIG. 5A , which will not be repeated here.

[0594] In some embodiments, the above steps are all optional steps.

[0595] In some embodiments, the embodiment shown in FIG. 5D may also be combined with any one or more steps in the embodiment shown in FIG. 5A to form a new embodiment.

[0596] FIG5E is a flow chart of a measurement method according to an embodiment of the present disclosure. As shown in FIG5E , an embodiment of the present disclosure relates to a measurement method, which can be performed by a first device. The method may include:

[0597] Step S5501: Send the second information.

[0598] The optional implementation of step S5501 can be found in step S2110 of FIG. 2A , the optional implementation of step S5107 of FIG. 5A , and other related parts in the embodiments involved in FIG. 2A and FIG. 5A , which will not be described in detail here.

[0599] In some embodiments, the above steps are all optional steps.

[0600] In some embodiments, the embodiment shown in FIG. 5E may also be combined with any one or more steps in the embodiment shown in FIG. 5A to form a new embodiment.

[0601] In some embodiments, the second information includes a model structure and / or model parameters of an artificial intelligence (AI) model.

[0602] In some embodiments, the method further comprises:

[0603] Establishing a first connection, where the first connection is a connection between the terminal device and the first device;

[0604] The sending the second information to the terminal device includes: sending the second information to the terminal device through the first connection.

[0605] In some embodiments, the first connection is established based on a request from the terminal device and / or the first device.

[0606] In some embodiments, the second information is information sent by the first device to the terminal device based on an application layer transmission protocol.

[0607] In some embodiments, the AI ​​model is a model obtained after training of the first device and / or network device.

[0608] In some embodiments, the method further comprises at least one of the following:

[0609] receiving fifth information sent by the network device, where the fifth information is used by the first device to train the AI ​​model;

[0610] Sending seventh information to the network device, where the seventh information includes information that assists the terminal device in acquiring the AI ​​model;

[0611] receiving sixth information sent by the network device, where the sixth information is used to request the first device to send the seventh information;

[0612] Receive eighth information sent by the network device, where the eighth information includes an AI model generated by the network device.

[0613] In some embodiments, the AI ​​model is used to perform a first function, wherein the first function includes at least one of the following functions: channel state information CSI enhancement; beam prediction; positioning.

[0614] In some embodiments, the network device includes at least one of the following: access network equipment; access and mobility management function AMF; positioning management function LMF.

[0615] In some embodiments, the network device is a network device corresponding to the first function.

[0616] Figure 6 is a flow chart of a method for transmitting model information according to an embodiment of the present disclosure. As shown in Figure 6, the embodiment of the present disclosure relates to a method for transmitting model information, which can be executed by a communication system and may include:

[0617] Step S6101: The terminal device obtains the AI ​​model.

[0618] In some embodiments, a terminal device may obtain an AI model through a first process and a second process. Optionally, the interaction subjects of the first process may include a network device (e.g., a network node) and a terminal device; the interaction subjects of the second process may include a network-associated server and a terminal device, where the server may be referred to as the first device.

[0619] Alternatively, the server may be a node outside the network and the AI ​​model may be stored on the server.

[0620] In some embodiments, the second process may include at least one of the following steps:

[0621] Step 1: The terminal device establishes a connection with the server. Optionally, the connection can be established through the interaction of a connection establishment request and a connection establishment response, and the connection establishment request can be initiated by the terminal device or by the server;

[0622] Step 2: The server transmits the AI ​​model to the terminal device.

[0623] Optionally, the server may transmit the AI ​​model to the terminal device based on an application layer transmission protocol.

[0624] In some embodiments, the first process may include information that assists in performing the second process. For example, the second process may include at least one of the following information:

[0625] Instruction information from the network device to the terminal device to download the AI ​​model;

[0626] Request information from the terminal device requesting the network device to transmit the model;

[0627] Model description information of the model to be transmitted, including at least one of the following: model size, model ID, model input information, model output information, model applicable environment, model format, etc.;

[0628] Type of model to be transmitted: For example, the model to be transmitted is a brand new model structure and model parameters, or the model parameters of a model structure deployed on the terminal device;

[0629] The storage information of the AI ​​model may include, for example, the server address where the AI ​​model is stored, auxiliary information for establishing a connection between the terminal device and the server, etc.

[0630] Optionally, the information in the first process may be physical layer information, RRC information or NAS information.

[0631] In some embodiments, the network devices (network nodes) participating in the first process may be the same or different in different AI use cases.

[0632] For example, in all AI use cases, the network device can be AMF, that is, the AMF node and the terminal device perform the first process.

[0633] For another example, in AI-based beam management, the network device that executes the first process may be an access network device (base station) and / or AMF.

[0634] For another example, in AI-based positioning, the network device that executes the first process may be LMF and / or AMF.

[0635] In some embodiments, the method further includes a third process, and an execution subject of the third process includes a network device and a server associated with the network.

[0636] For example, the third process may include at least one of the following steps:

[0637] The network device uploads the collected data to the server, which trains the AI ​​model based on the data;

[0638] The network device requests information about the AI ​​model from the server, and the server sends the information about the AI ​​model to the network device.

[0639] The network device uploads the trained AI model to the server.

[0640] In some embodiments, the third process may be located before the first process and the second process, or may be performed during the first process and the second process.

[0641] In some embodiments of the present disclosure, a communication system is provided, which may include a terminal device, a network device and a first device, wherein the terminal device can execute the model information transmission method executed by the terminal device in the aforementioned embodiment of the present disclosure; the network device can execute the model information transmission method executed by the network device in the aforementioned embodiment of the present disclosure; and the first device can execute the model information transmission method executed by the first device in the aforementioned embodiment of the present disclosure.

[0642] 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 device 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.

[0643] 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), and the functions of some or all of the above units or modules are realized 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.

[0644] 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 a 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 to implement 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 ASIC, such as a neural network processing unit (NPU), a tensor processing unit (TPU), a deep learning processing unit (DPU), etc.

[0645] Figure 7A is a schematic diagram of the structure of a terminal device proposed in an embodiment of the present disclosure. As shown in Figure 7A, the terminal device 101 may include: at least one of a transceiver module 7101, a processing module 7102, etc. In some embodiments, the transceiver module 7101 is configured to receive a first message sent by a network device, wherein the first message is used to assist the terminal device in obtaining second information corresponding to an artificial intelligence (AI) model from a first device, wherein the second information includes a model structure and / or model parameters of the AI ​​model; and receive the second information sent by the first device. Optionally, the transceiver module 7101 can be used to execute at least one of the communication steps such as sending and / or receiving performed by the terminal device 101 in any of the above methods (for example, step S2101, step S2102, step S2104, step S2105, step S2106, step S2107, step S2108, step S2109, step S2110, but not limited thereto), which will not be repeated here. Optionally, the processing module 7102 can be used to execute at least one of the other steps (such as step S2103, step S2111, but not limited to these) performed by the terminal device 101 in any of the above methods, which will not be repeated here.

[0646] Figure 7B is a structural diagram of a network device proposed in an embodiment of the present disclosure. As shown in Figure 7B, the network device 102 may include: at least one of a transceiver module 7201, a processing module 7202, etc. In some embodiments, the transceiver module 7201 is configured to send a first message to a terminal device, wherein the first message is used to assist the terminal device in obtaining second information corresponding to an artificial intelligence AI model from the first device, and the second information includes a model structure and / or model parameters of the AI ​​model. Optionally, the transceiver module 7201 can be used to execute at least one of the communication steps such as sending and / or receiving performed by the network device 102 in any of the above methods (for example, step S2101, step S2102, step S2104, step S2105, step S2106, step S2107, step S2108, step S2109, step S2110, but not limited to this), which will not be repeated here. Optionally, the processing module 7202 can be used to execute at least one of the other steps (such as step S2103 and step S2111, but not limited thereto) performed by the network device 102 in any of the above methods, which will not be repeated here.

[0647] Figure 7C is a structural diagram of a first device proposed in an embodiment of the present disclosure. As shown in Figure 7C, the first device 103 may include: at least one of a transceiver module 7301, a processing module 7302, etc. In some embodiments, the transceiver module 7301 is configured to send second information to the terminal device, and the second information includes the model structure and / or model parameters of the artificial intelligence AI model. Optionally, the transceiver module 7301 can be used to execute at least one of the communication steps such as sending and / or receiving performed by the first device 103 in any of the above methods (for example, step S2101, step S2102, step S2104, step S2105, step S2106, step S2107, step S2108, step S2109, step S2110, but not limited to this), which will not be repeated here. Optionally, the processing module 7302 can be used to execute at least one of the other steps (such as step S2103 and step S2111, but not limited thereto) performed by the first device 103 in any of the above methods, which will not be repeated here.

[0648] In some embodiments, the transceiver 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 transceiver module may be interchangeable with the transceiver.

[0649] 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.

[0650] Figure 8A is a schematic diagram of the structure of a communication device 8100 proposed in an embodiment of the present disclosure. Communication device 8100 can be a network device (e.g., an access network device, a core network device, a network device, a first device, etc.), or a terminal device (e.g., a user device, etc.). It can also be 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 device to implement any of the above methods. Communication device 8100 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.

[0651] As shown in Figure 8A, the communication device 8100 includes one or more processors 8101. The processor 8101 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 the communication protocol and communication data, and the central processing unit can be used to control the communication device (such as a base station, a baseband chip, a terminal device, a terminal device chip, a DU or a CU, etc.), execute programs, and process program data. Optionally, the communication device 8100 can be used to perform any of the above methods. Optionally, one or more processors 8101 are used to call instructions to enable the communication device 8100 to perform any of the above methods.

[0652] In some embodiments, the communication device 8100 may further include one or more transceivers 8102. When the communication device 8100 includes one or more transceivers 8102, the transceiver 8102 may perform 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, step S2106, step S2107, step S2108, step S2109, and step S2110, but not limited thereto), and the processor 8101 may perform at least one of the other steps (for example, step S2103 and step S2111, but not limited thereto).

[0653] 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, transceiver circuit, interface circuit, and interface 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.

[0654] In some embodiments, the communication device 8100 further includes one or more memories 8103 for storing data. Alternatively, all or part of the memories 8103 may be located outside the communication device 8100. In alternative embodiments, the communication device 8100 may include one or more interface circuits 8104. Optionally, the interface circuits 8104 are connected to the memories 8103 and may be configured to receive data from the memories 8103 or other devices, or to send data to the memories 8103 or other devices. For example, the interface circuits 8104 may read data stored in the memories 8103 and send the data to the processor 8101.

[0655] The communication device 8100 described in the above embodiment may be a network device or a terminal device, 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 may not be limited by FIG. 8A. 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.

[0656] FIG8B is a schematic diagram of the structure of a chip 8200 according to an embodiment of the present disclosure. If the communication device 8100 can be a chip or a chip system, please refer to the schematic diagram of the structure of the chip 8200 shown in FIG8B , but the present disclosure is not limited thereto.

[0657] The chip 8200 includes one or more processors 8201 , and the chip 8200 is configured to execute any of the above methods.

[0658] In some embodiments, chip 8200 further includes one or more interface circuits 8204. Alternatively, the terms interface circuit, interface, and transceiver pins may be used interchangeably. In some embodiments, chip 8200 further includes one or more memories 8203 for storing data. Alternatively, all or part of memories 8203 may be located external to chip 8200.

[0659] Optionally, the interface circuit 8204 is connected to the memory 8203. The interface circuit 8204 can be used to receive data from the memory 8203 or other devices, and the interface circuit 8204 can be used to send data to the memory 8203 or other devices. For example, the interface circuit 8204 can read data stored in the memory 8203 and send the data to the processor 8201.

[0660] In some embodiments, the interface circuit 8204 performs at least one of the communication steps (e.g., steps S2101, S2102, S2104, S2105, S2106, S2107, S2108, S2109, and S2110) of the aforementioned method. The interface circuit 8204 performing the communication steps (e.g., steps S2101, S2102, S2104, S2105, S2106, S2107, S2108, S2109, and S2110) of the aforementioned method, for example, means that the interface circuit 8204 performs data exchange between the processor 8201, the chip 8200, the memory 8203, or the transceiver device. In some embodiments, the processor 8201 may perform at least one of the other steps (e.g., steps S2103 and S2111, but not limited thereto).

[0661] The modules and / or devices described in various embodiments, such as virtual devices, physical devices, and chips, can be arbitrarily combined or separated according to circumstances. Optionally, some or all steps can also be performed collaboratively by multiple modules and / or devices, which is not limited here.

[0662] The embodiments of the present disclosure further provide a storage medium having instructions stored thereon. When the instructions are executed on the communication device 8100, the communication device 8100 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.

[0663] The present disclosure also provides a program product. When executed by the communication device 8100, the program product causes the communication device 8100 to perform any of the above methods. Optionally, the program product may be a computer program product. Optionally, the computer program product may include a computer program that, when executed by the communication device, implements any of the above optional methods.

[0664] The embodiments of the present disclosure also provide a computer program, which, when executed on a computer, enables the computer to execute any one of the above methods.

Claims

1. A model information transmission method, characterized in that: Executed by a terminal device, the method includes: Receive first information sent by a network device, where the first information is used to assist the terminal device in obtaining second information corresponding to an artificial intelligence (AI) model from the first device, where the second information includes a model structure and / or model parameters of the AI model; Receive the second information sent by the first device.

2. The method according to claim 1, characterized in that The method further comprises: Establishing a first connection, where the first connection is a connection between the terminal device and the first device; And wherein, receiving the second information sent by the first device includes: receiving the second information sent by the first device through the first connection.

3. The method according to claim 2, characterized in that The first connection is established based on a request from the terminal device and / or the first device.

4. The method according to claim 2, characterized in that The second information is information sent by the first device to the terminal device based on an application layer transmission protocol.

5. The method according to any one of claims 1 to 4, characterized in that The first information includes at least one of the following: Model description information corresponding to the AI model, wherein the model description information is used to determine the AI model; Model transmission information corresponding to the AI model, wherein the model transmission information is used to instruct the terminal device to obtain the model structure and / or model parameters of the AI model; Model storage information corresponding to the AI model, wherein the model storage information is used to establish a first connection between the terminal device and the first device.

6. The method according to claim 5, characterized in that The model description information includes at least one of the following: Model identification; Model size; Model input information; Model output information; Model application environment information; Model format information.

7. The method according to claim 5, characterized in that The method further comprises at least one of the following: Sending third information to the network device, where the third information is used to request the network device to send the first information; In response to receiving the first information sent by the network device, fourth information is sent to the network device, and the fourth information is used to indicate that the terminal device has successfully received the first information and / or the terminal device has started to execute the step of receiving the second information sent by the first device.

8. The method according to claim 1, characterized in that The AI model is a model obtained after training the first device and / or the network device.

9. The method according to any one of claims 1 to 8, characterized in that The AI model is configured to perform a first function, wherein the first function includes at least one of the following functions: Channel state information CSI enhancement; Beam prediction; position.

10. The method according to claim 9, characterized in that The network device includes at least one of the following: Access network equipment; Access and mobility management function AMF; Location Management Function LMF.

11. The method according to claim 10, characterized in that The network device is a network device corresponding to the first function.

12. A model information transmission method, characterized in that: Executed by a network device, the method includes: Send first information to the terminal device, where the first information is used to assist the terminal device in receiving second information corresponding to an artificial intelligence (AI) model from the first device, where the second information includes a model structure and / or model parameters of the AI model.

13. The method according to claim 12, characterized in that The first information includes at least one of the following: Model description information corresponding to the AI model, wherein the model description information is used to determine the AI model; Model transmission information corresponding to the AI model, wherein the model transmission information is used to instruct the terminal device to obtain the model structure and / or model parameters of the AI model; Model storage information corresponding to the AI model, wherein the model storage information is used to establish a first connection between the terminal device and the first device.

14. The method according to claim 13, characterized in that The model description information includes at least one of the following: Model identification; Model size; Model input information; Model output information; Model application environment information; Model format information.

15. The method according to claim 13, characterized in that The method further comprises at least one of the following: receiving third information sent by the terminal device, where the third information is used to request the network device to send the first information; Receive fourth information sent by the terminal device, where the fourth information is used to indicate that the terminal device has successfully received the first information and / or that the terminal device has started to execute the step of receiving the second information sent by the first device.

16. The method according to any one of claims 12 to 15, characterized in that The AI model is a model obtained after training the first device and / or the network device.

17. The method according to claim 16, characterized in that The method further comprises at least one of the following: Sending fifth information to the first device, where the fifth information is used by the first device to train the AI model; receiving seventh information sent by the first device, where the seventh information includes information for assisting the terminal device in acquiring the AI model; sending sixth information to the first device, where the sixth information is used to request the first device to send the seventh information; Send eighth information to the first device, where the eighth information includes the AI model generated by the network device.

18. The method according to any one of claims 12 to 17, characterized in that The AI model is configured to perform a first function, wherein the first function includes at least one of the following functions: Channel state information CSI enhancement; Beam prediction; position.

19. The method according to claim 18, characterized in that The network device includes at least one of the following: Access network equipment; Access and mobility management function AMF; Location Management Function LMF.

20. The method according to claim 19, characterized in that The network device is a network device corresponding to the first function.

21. A model information transmission method, characterized in that: Executed by a first device, the method includes: Sending second information to the terminal device, where the second information includes a model structure and / or model parameters of the artificial intelligence AI model.

22. The method according to claim 21, characterized in that The method further comprises: Establishing a first connection, where the first connection is a connection between the terminal device and the first device; The sending the second information to the terminal device includes: sending the second information to the terminal device through the first connection.

23. The method according to claim 22, characterized in that The first connection is established based on a request from the terminal device and / or the first device.

24. The method according to claim 22, characterized in that The second information is information sent by the first device to the terminal device based on an application layer transmission protocol.

25. The method according to any one of claims 21 to 24, characterized in that The AI model is a model obtained after training the first device and / or network device.

26. The method according to claim 25, characterized in that The method further comprises at least one of the following: receiving fifth information sent by the network device, where the fifth information is used by the first device to train the AI model; Sending seventh information to the network device, where the seventh information includes information that assists the terminal device in acquiring the AI model; receiving sixth information sent by the network device, where the sixth information is used to request the first device to send the seventh information; Receive eighth information sent by the network device, where the eighth information includes an AI model generated by the network device.

27. The method according to any one of claims 25 to 26, characterized in that The AI model is configured to perform a first function, wherein the first function includes at least one of the following functions: Channel state information CSI enhancement; Beam prediction; position.

28. The method according to claim 27, characterized in that The network device includes at least one of the following: Access network equipment; Access and mobility management function AMF; Location Management Function LMF.

29. The method according to claim 28, characterized in that The network device is a network device corresponding to the first function.

30. A terminal device, characterized in that: include: The transceiver module is configured to receive first information sent by a network device, where the first information is used to assist the terminal device in obtaining second information corresponding to an artificial intelligence (AI) model from the first device, where the second information includes a model structure and / or model parameters of the AI model; and receive the second information sent by the first device.

31. A network device, characterized in that: include: The transceiver module is configured to send first information to the terminal device, where the first information is used to assist the terminal device in obtaining second information corresponding to the artificial intelligence AI model from the first device, where the second information includes the model structure and / or model parameters of the AI model.

32. A first device, characterized in that: include: The transceiver module is configured to send second information to the terminal device, where the second information includes a model structure and / or model parameters of the artificial intelligence AI model.

33. A communication device, characterized in that: include: one or more processors; The communication device is used to execute the model information transmission method according to any one of claims 1 to 11, claims 12 to 20, or claims 21 to 29.

34. 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 model information transmission method according to any one of claims 1 to 11, claims 12 to 20, or claims 21 to 29.

35. A computer program product comprising a computer program, characterized in that When the computer program is executed by a communication device, the model information transmission method according to any one of claims 1 to 11, claims 12 to 20, or claims 21 to 29 is implemented.

36. A communication system, characterized in that: The communication system includes a terminal device, a network device and a first device, wherein the terminal device is configured to implement the model information transmission method described in any one of claims 1 to 11, the network device is configured to implement the model information transmission method described in any one of claims 12 to 20, and the first device is configured to implement the model information transmission method described in any one of claims 21 to 29.

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