Wireless communication method and apparatus, terminal device, and network device

Abstract

A wireless communication method and apparatus, a terminal device, and a network device. The method comprises: a terminal device determines, on the basis of model application time reported to a network device, or on the basis of model application time configured by the network device, a moment when a first AI model starts to be applied; and after the moment, the terminal device uses the first AI model to communicate with the network device.

Description

Wireless communication method and device, terminal equipment, and network equipment Technical Field

[0001] The embodiments of the present application relate to the field of mobile communication technology, and specifically to a wireless communication method and apparatus, terminal equipment, and network equipment. Background Art

[0002] Given the tremendous success of artificial intelligence (AI) technology in computer vision, natural language processing, and other fields, the communications field has begun to try to use AI technology to seek new technical ideas to solve technical problems that are limited by traditional methods.

[0003] When AI models are used for wireless communications, they can be divided into single-end models and dual-end models. The dual-end model needs to be deployed in pairs on the terminal device and network device sides. For example, the AI ​​model used for channel state information (CSI) feedback is a typical dual-end model, in which the terminal device can use the obtained channel information (such as eigenvectors, beam information, delay information, etc.) as the input of the AI ​​model, and the AI ​​model can infer the corresponding CSI quantization bits. Correspondingly, the corresponding AI model on the network device side can use the CSI quantization bits as input and reversely infer to obtain the corresponding channel information.

[0004] For a dual-end model, if the performance of the AI ​​model on the current terminal device side is poor, the network device can instruct the terminal device to update the model through signaling (for example, replace an AI model or adjust model parameters). At this time, the network device also needs to perform a corresponding model update so that the AI ​​models on both sides still match each other. If the updates of the AI ​​models on both sides are not completely synchronized, the output of the receiving AI model will be incorrect, thereby affecting the information transmission between the terminal device and the network device. How to ensure that the model updates between the network device and the terminal device are synchronized is a problem that needs to be solved.

[0005] Summary of the Invention

[0006] The embodiments of the present application provide an information transmission method and apparatus, a terminal device, and a network device.

[0007] In a first aspect, an embodiment of the present application provides a wireless communication method, including:

[0008] The terminal device determines the time to start applying the first AI model based on the model application time reported to the network device, or based on the model application time configured by the network device;

[0009] After the moment, the terminal device uses the first AI model to communicate with the network device.

[0010] In a second aspect, the wireless communication method provided by the embodiments of the present application includes:

[0011] The network device determines, based on the model application time reported by the terminal device or the model application time configured for the terminal device, a time at which the first AI model starts to be applied;

[0012] After the moment, the network device uses the second AI model corresponding to the first AI model to communicate with the terminal device.

[0013] In a third aspect, an embodiment of the present application provides a wireless communication device, which is applied to a terminal device. The device includes:

[0014] A first determining unit is configured to determine a time to start applying the first AI model based on a model application time reported to the network device, or based on a model application time configured by the network device;

[0015] The first communication unit is configured to communicate with the network device using the first AI model after the moment.

[0016] In a fourth aspect, an embodiment of the present application provides a wireless communication device, which is applied to a network device, and includes:

[0017] a second determining unit, configured to determine a time point for starting application of the first AI model based on a model application time reported by a terminal device, or based on a model application time configured for the terminal device;

[0018] The second communication unit is configured to communicate with the terminal device using a second AI model corresponding to the first AI model after the moment.

[0019] In a fifth aspect, an embodiment of the present application provides a terminal device, the terminal device including a processor and a memory. The memory is used to store a computer program, and the processor is used to call and run the computer program stored in the memory to perform the above-mentioned wireless communication method.

[0020] In a sixth aspect, an embodiment of the present application provides a network device, the network device comprising a processor and a memory. The memory is used to store a computer program, and the processor is used to call and run the computer program stored in the memory to perform the above-mentioned wireless communication method.

[0021] The chip provided in the embodiment of the present application is used to implement the above-mentioned wireless communication method.

[0022] Specifically, the chip includes: a processor, which is used to call and run a computer program from a memory, so that a device equipped with the chip executes the above-mentioned wireless communication method.

[0023] The computer-readable storage medium provided in an embodiment of the present application is used to store a computer program, which enables a computer to execute the above-mentioned wireless communication method.

[0024] The computer program product provided in the embodiments of the present application includes computer program instructions, which enable a computer to execute the above-mentioned wireless communication method.

[0025] The computer program provided in the embodiment of the present application, when executed on a computer, enables the computer to execute the above-mentioned wireless communication method.

[0026] In the wireless communication method provided in the embodiments of the present application, when corresponding dual-end AI models are used on the terminal device side and the network device side, if the AI ​​model on the terminal device side is updated or reconfigured, the terminal device can determine the time when the updated or reconfigured AI model starts to be applied based on the model application time reported to the network device, or based on the model application time configured by the network device. In this way, the time when the models on both sides start to be applied can be ensured to be the same, thereby ensuring that the output of the AI ​​model is usable and improving the performance of the communication system. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0028] FIG1 is a schematic diagram of a communication architecture provided in an embodiment of the present application;

[0029] FIG2 is a schematic diagram of a neuron structure provided in an embodiment of the present application;

[0030] FIG3 is a schematic diagram of a neural network structure provided in an embodiment of the present application;

[0031] FIG4 is a schematic diagram of a neural network for CSI feedback provided in an embodiment of the present application;

[0032] FIG5 is a schematic flow chart of a wireless communication method provided in an embodiment of the present application;

[0033] FIG6A is a schematic diagram of a time slot structure provided in an embodiment of the present application;

[0034] FIG6B is a second schematic diagram of a time slot structure provided in an embodiment of the present application;

[0035] FIG7A is a third schematic diagram of a time slot structure provided in an embodiment of the present application;

[0036] FIG7B is a fourth schematic diagram of a time slot structure provided in an embodiment of the present application;

[0037] FIG8 is a fifth schematic diagram of a time slot structure provided in an embodiment of the present application;

[0038] FIG9A is a sixth schematic diagram of a time slot structure provided in an embodiment of the present application;

[0039] FIG9B is a seventh schematic diagram of a time slot structure provided in an embodiment of the present application;

[0040] FIG9C is a schematic diagram of a time slot structure provided in an embodiment of the present application;

[0041] FIG10 is a schematic structural diagram of a wireless communication device 1000 provided in an embodiment of the present application;

[0042] FIG11 is a schematic structural diagram of a wireless communication device 1100 provided in an embodiment of the present application;

[0043] FIG12 is a schematic structural diagram of a communication device provided in an embodiment of the present application;

[0044] FIG13 is a schematic structural diagram of a chip according to an embodiment of the present application;

[0045] FIG14 is a schematic block diagram of a communication system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0046] The following will describe the technical solutions in the embodiments of this application in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0047] FIG1 is a schematic diagram of an application scenario of an embodiment of the present application.

[0048] As shown in Figure 1, a communication system 100 may include a terminal device 110 and a network device 120. The network device 120 may communicate with the terminal device 110 via an air interface. The terminal device 110 and the network device 120 support multi-service transmission.

[0049] It should be understood that the embodiments of the present application are only illustrative of the communication system 100, but the embodiments of the present application are not limited thereto. That is, the technical solutions of the embodiments of the present application can be applied to various communication systems, such as: Long Term Evolution (LTE) system, LTE Time Division Duplex (TDD), Universal Mobile Telecommunication System (UMTS), Internet of Things (IoT) system, Narrow Band Internet of Things (NB-IoT) system, enhanced Machine-Type Communications (eMTC) system, 5G communication system (also known as New Radio (NR) communication system), or future communication systems.

[0050] In the communication system 100 shown in Figure 1, the network device 120 may be an access network device that communicates with the terminal device 110. The access network device may provide communication coverage for a specific geographical area and may communicate with the terminal device 110 (eg, UE) located within the coverage area.

[0051] The network device 120 may be an evolved Node B (eNB or eNodeB) in a Long Term Evolution (LTE) system, or a Next Generation Radio Access Network (NG RAN) device, or a base station (gNB) in an NR system, or a wireless controller in a Cloud Radio Access Network (CRAN), or the network device 120 may be a relay station, an access point, an in-vehicle device, a wearable device, a hub, a switch, a bridge, a router, or a network device in a future evolved Public Land Mobile Network (PLMN), etc.

[0052] The terminal device 110 may be any terminal device, including but not limited to a terminal device connected to the network device 120 or other terminal devices by wire or wireless connection.

[0053] For example, the terminal device 110 may refer to an access terminal, user equipment (UE), a subscriber unit, a subscriber station, a mobile station, a mobile station, a remote station, a remote terminal, a mobile device, a user terminal, a terminal, a wireless communication device, a user agent, or a user apparatus. An access terminal may be a cellular phone, a cordless phone, a Session Initiation Protocol (SIP) phone, an IoT device, a satellite handheld terminal, a Wireless Local Loop (WLL) station, a Personal Digital Assistant (PDA), a handheld device with wireless communication capabilities, a computing device or other processing device connected to a wireless modem, an in-vehicle device, a wearable device, a terminal device in a 5G network, or a terminal device in a future evolution network, etc.

[0054] The terminal device 110 can be used for device-to-device (D2D) communication.

[0055] The wireless communication system 100 may further include a core network device 130 that communicates with the network device 120. The core network device 130 may be a 5G core network (5G Core, 5GC) device, such as an Access and Mobility Management Function (AMF), an Authentication Server Function (AUSF), a User Plane Function (UPF), or a Session Management Function (SMF). Optionally, the core network device 130 may also be an Evolved Packet Core (EPC) device of an LTE network, such as a Session Management Function + Core Packet Gateway (SMF+PGW-C) device. It should be understood that SMF+PGW-C can simultaneously implement the functions that can be implemented by SMF and PGW-C. During the network evolution process, the above-mentioned core network device may also be called other names, or a new network entity may be formed by dividing the functions of the core network, which is not limited in the embodiments of the present application.

[0056] The functional units in the communication system 100 may also establish connections and implement communication via next generation (NG) network interfaces.

[0057] For example, the terminal device establishes an air interface connection with the access network device through the NR interface for transmitting user plane data and control plane signaling; the terminal device can establish a control plane signaling connection with the AMF through the NG interface 1 (referred to as N1); the access network device, such as the next generation wireless access base station (gNB), can establish a user plane data connection with the UPF through the NG interface 3 (referred to as N3); the access network device can establish a control plane signaling connection with the AMF through the NG interface 2 (referred to as N2); the UPF can establish a control plane signaling connection with the SMF through the NG interface 4 (referred to as N4); the UPF can exchange user plane data with the data network through the NG interface 6 (referred to as N6); the AMF can establish a control plane signaling connection with the SMF through the NG interface 11 (referred to as N11); the SMF can establish a control plane signaling connection with the PCF through the NG interface 7 (referred to as N7).

[0058] Figure 1 exemplarily shows a network device, a core network device and two terminal devices. Optionally, the wireless communication system 100 may include multiple network devices and each network device may include other numbers of terminal devices within its coverage area, which is not limited in this embodiment of the present application.

[0059] It should be noted that Figure 1 is merely an example of a system applicable to this application. Of course, the methods described in the embodiments of this application can also be applied to other systems. Furthermore, the terms "system" and "network" are often used interchangeably herein. The term "and / or" herein simply describes an association relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, or B exists alone. Furthermore, the character " / " generally indicates that the associated objects are in an "or" relationship. It should also be understood that the "indication" mentioned in the embodiments of this application can be a direct indication, an indirect indication, or an indication of an association relationship. For example, "A indicates B" can mean that A directly indicates B, for example, B can obtain information through A; it can also mean that A indirectly indicates B, for example, A indicates C, and B can obtain information through C; or it can mean that A and B have an association relationship. It should also be understood that the "correspondence" mentioned in the embodiments of this application can mean that there is a direct or indirect correspondence between two objects, or that there is an association relationship between the two objects, or a relationship between an indicator and the indicated, a configuration and the configured, and so on. It should also be understood that the “predefined” or “predefined rules” mentioned in the embodiments of the present application can be implemented by pre-saving corresponding codes, tables or other methods that can be used to indicate relevant information in a device (for example, including a terminal device and a network device), and the present application does not limit its specific implementation method. For example, predefined can refer to a definition in a protocol. It should also be understood that in the embodiments of the present application, the “protocol” may refer to a standard protocol in the field of communications, such as an LTE protocol, a NR protocol, and related protocols used in future communication systems, and the present application does not limit this.

[0060] To facilitate understanding of the technical solutions of the embodiments of the present application, the relevant technologies of the embodiments of the present application are described below. The following relevant technologies can be arbitrarily combined with the technical solutions of the embodiments of the present application as optional solutions, and they all fall within the protection scope of the embodiments of the present application.

[0061] AI models are capable of handling a variety of tasks. They possess the ability to self-learn and adapt, dynamically adjusting and making decisions based on environmental changes. AI models can also be referred to as machine learning (ML) models; the two are equivalent or interchangeable.

[0062] In practical applications, AI models can be constructed using neural networks. A neural network is a computational model consisting of multiple interconnected neuron nodes. The connections between nodes represent weighted values ​​from input signals to output signals, called weights. Each node performs a weighted summation of different input signals and outputs the result through a specific activation function. Refer to the neuron structure diagram shown in Figure 2, where a1, a2, ..., an, and 1 are neuron inputs, w1, w2, ..., wn, and b represent weights, Sum represents the summation function, f represents the activation function, and t represents the output result.

[0063] A simple neural network, shown in Figure 3, consists of an input layer, hidden layers, and an output layer. Different connections, weights, and activation functions between multiple neurons produce different outputs, thereby fitting the mapping from input to output. Each node in the previous level is connected to all nodes in the next level. This fully connected model is also called a DNN, or deep neural network.

[0064] An AI model can be trained and obtained through the process of dataset construction, training, verification, and testing. Training can be divided into offline and online training. Offline training of a dataset can produce a static training result, which is referred to as offline training. As network devices or terminal devices use the AI ​​model, as the terminal devices further measure and / or report, the network devices can continue to collect more data and conduct real-time online training to optimize the AI ​​model parameters and achieve better inference and prediction results. After the AI ​​model is obtained, the current information is input into the AI ​​model to infer the corresponding model output.

[0065] When AI is used in wireless communications, it can be divided into single-ended and dual-ended models. Single-ended models are deployed on only one side of the terminal device or network equipment, and AI model training can be performed on only one side. Dual-ended models require paired deployment on both the terminal device and the network equipment, and the models on both sides must be trained together. This means the models deployed on both sides correspond to each other and cannot be used or updated independently.

[0066] For example, the AI ​​model used for channel state information (CSI) feedback is a typical dual-end model. Refer to Figure 4 for a schematic diagram of the dual-end AI model structure for CSI feedback. Among them, an AI model for encoding (encoder) is deployed on the terminal side, and a corresponding AI model for decoding (decoder) is deployed on the network side. The terminal device outputs CSI quantization bits based on the encoder model, typically PMI bits, and then feeds back to the network device through the uplink channel (PUSCH / PUCCH). The network device uses the CSI quantization bits (PMI) fed back by the terminal as the input of the decoder model, thereby outputting channel information corresponding to the terminal side input, such as the eigenvectors of each subband, etc., for downlink precoding. At the same time, the terminal device also needs to monitor the model performance and report to the network device when the model performance is poor, so that the network device can update the model (for example, update the model structure or update the model parameters). Since the AI ​​models on both sides are matched, if the network device updates the model, it needs to notify the terminal device through signaling so that the terminal device can also update to the corresponding AI model. Otherwise, the output result of the network device will be unusable.

[0067] It should be noted that the above-mentioned AI model based on dual-end deployment can not only be used for CSI feedback, but also for other processing methods with corresponding operations / structures on the terminal device and network device sides, such as channel coding-channel decoding, modulation-demodulation, pilot generation-channel estimation, transceiver RF signal processing, etc. It is only necessary to train a set of AI models on the corresponding terminal device side and network device side.

[0068] It is understandable that for the dual-end model, if the model performance on the current terminal device side is poor, the network device can instruct the terminal device to update the model through signaling (for example, replace an AI model or adjust model parameters). At this time, the network device also needs to perform a corresponding model update so that the AI ​​models on both sides are still matched with each other. If the updates of the AI ​​models on both sides are not completely synchronized, the output of the receiving end AI model will be incorrect, thereby affecting the information transmission between the terminal device and the network device.

[0069] In addition, due to the different processing capabilities of different terminal devices, the time required to deploy AI models is also different. How to ensure that model updates can be performed synchronously between network devices and different terminal devices is a problem that needs to be solved.

[0070] Based on this, an embodiment of the present application provides a wireless communication method, wherein, when corresponding dual-end AI models are used on the terminal device side and the network device side, if the AI ​​model on the terminal device side is updated or reconfigured, the terminal device can determine the time when the AI ​​model configured by the network device starts to be applied based on the model application time reported to the network device, or based on the model application time configured by the network device. In this way, the model application time on both sides can be ensured to be the same, thereby ensuring that the output of the AI ​​model is usable, and improving the performance of the communication system.

[0071] To facilitate understanding of the technical solutions of the embodiments of the present application, the technical solutions of the present application are described in detail below through specific embodiments. The above related technologies can be combined arbitrarily with the technical solutions of the embodiments of the present application as optional solutions, and all of them fall within the scope of protection of the embodiments of the present application. The embodiments of the present application include at least part of the following contents.

[0072] FIG5 shows a wireless communication method provided in an embodiment of the present application, which may include step S110 and step S120.

[0073] S110. The terminal device determines a time to start applying the first AI model based on the model application time reported to the network device, or based on the model application time configured by the network device.

[0074] S120. After the time, the terminal device uses the first AI model to communicate with the network device.

[0075] Accordingly, the network device can determine the time when the first AI model starts to be applied based on the model application time reported by the terminal device, or based on the model application time configured for the terminal device; and after the time, the network device uses the second AI model corresponding to the first AI model to communicate with the terminal device.

[0076] It should be noted that the terminal device and the network device use corresponding two-end AI models for communication. Among them, the first AI model is a neural network model deployed on the terminal device side, and the second AI model is a neural network model deployed on the network device side.

[0077] Exemplarily, the first AI model can be used in any of the following processes:

[0078] Downlink CSI feedback; or,

[0079] Downlink beam feedback; or,

[0080] Channel decoding of downlink data; or,

[0081] Demodulation of downlink signals; or,

[0082] Downlink channel estimation; or,

[0083] Downlink RF signal processing; or,

[0084] Channel coding of uplink data; or,

[0085] Modulation of uplink data; or,

[0086] Uplink pilot generation; or,

[0087] Uplink RF signal processing.

[0088] Among them, the first AI model is used for downlink CSI feedback. The terminal device can use the obtained channel information (such as eigenvectors, beam information, delay information, etc.) as the input of the first AI model, and infer the corresponding CSI quantization bits through the first AI model.

[0089] The first AI model is used for channel decoding of downlink data. The terminal device may use the received encoded data as input of the first AI model and output the decoded information bits.

[0090] The first AI model is used for demodulating the downlink signal. The terminal device may use the received downlink modulated signal as the input of the first AI model and output the demodulated information bits.

[0091] The first AI model is used for downlink channel estimation. The terminal device may use the received downlink channel and pilot signal as input of the first AI model and output the channel estimation result.

[0092] The first AI model is used for downlink RF signal processing. The terminal device may use the received downlink RF signal as the input of the first AI model and output the downlink RF signal processing result.

[0093] The first AI model is used for channel coding of uplink data, and the terminal device may use the information bits to be sent as the input of the first AI model and output the encoded data.

[0094] The first AI model is used for modulation of uplink data. The terminal device may use the information bits of the uplink data to be sent as the input of the first AI model and output an uplink modulated signal.

[0095] The first AI model is used for uplink pilot generation, and the terminal device may use the signal to be sent as the input of the first AI model and output a pilot signal.

[0096] The first AI model is used for uplink RF signal processing. The terminal device may use the signal to be sent as the input of the first AI model and output an uplink RF signal.

[0097] It can be understood that the first AI model can be trained through the processes of data set construction, training, verification and testing.

[0098] It is understandable that the first AI model can be trained in advance through offline training and / or online training.

[0099] Exemplarily, the second AI model can be used in any of the following processes:

[0100] Decoding of downlink CSI feedback information; or,

[0101] Decoding of downlink beam feedback information; or,

[0102] Channel decoding of uplink data; or,

[0103] Demodulation of uplink signals; or,

[0104] Uplink channel estimation; or,

[0105] Uplink RF signal processing; or,

[0106] Channel coding of downlink data; or,

[0107] Modulation of downlink data; or,

[0108] Downlink pilot generation; or,

[0109] Downlink RF signal processing.

[0110] It should be noted that the correspondence between the first AI model and the second AI model may refer to a one-to-one correspondence between the operations implemented by the first AI model and the second AI model. For example, if the first AI model is used for downlink CSI feedback, the second AI model may be used for decoding the downlink CSI feedback information; or if the first AI model is used for downlink beam information generation, the second AI model may be used for decoding the downlink beam feedback information; or if the first AI model is used for uplink data channel coding, the second AI model may be used for uplink data channel decoding, etc.

[0111] It can be understood that the second AI model can be trained through the processes of data set construction, training, verification and testing.

[0112] It is understandable that the second AI model can be trained in advance through offline training and / or online training.

[0113] In some embodiments, the first AI model deployed on the terminal device side can be configured for the terminal device by the network device. It should be noted that the network device can configure the first AI model for the terminal device when it initially connects to the network device; or the network device can configure the first AI model for the terminal device when the terminal device detects that the original AI model has poor performance, thereby instructing the terminal device to update the model.

[0114] In some embodiments, the network device may send first information to the terminal device, and the terminal device may receive the first information sent by the network device. The first information is used to configure the first AI model. In other words, the first information is downlink information used to configure the first AI model.

[0115] In some embodiments, the first information may be sent to the terminal device via broadcast signaling. For example, the first information may be carried via a physical broadcast channel (PBCH), system information (SIB), group common downlink control information (Group Common DCI), etc., and the embodiments of the present application are not limited to this. It should be noted that Group Common DCI is DCI sent to a group of terminal devices via a common search space (CSS). Among them, Group Common DCI is scrambled using a public radio network temporary identifier (RNTI). In some embodiments, the first information may be high-layer information, sent via high-layer signaling. For example, the first information may be sent via radio resource control (RRC) signaling, or via media access control (MAC) signaling, such as a MAC control unit (MAC Control Element, MAC CE). In some embodiments, the first information may also be physical layer information, sent via physical layer signaling. For example, the first information may be carried by DCI.

[0116] In one embodiment, the first information may be model recovery information sent by the network device, wherein the model recovery information includes configuration information of the first AI model. After receiving the model failure reporting information sent by the terminal device, the network device may send corresponding model recovery information for updating the terminal-side model.

[0117] In some embodiments, the first information may include one or more of the following:

[0118] Identification information of the first AI model;

[0119] First, the AI ​​model's functionality;

[0120] The model structure of the first AI model; and

[0121] Model parameters of the first AI model.

[0122] In some embodiments, the first information may carry identification information of the first AI model. It should be understood that the terminal device may pre-configure or pre-define one or more AI models. The terminal device may determine the first AI model to be applied / updated from one or more AI models based on the identification information of the first AI model carried in the first information. Each AI model may have a one-to-one corresponding identification information. The corresponding relationship may be pre-agreed between the network device and the terminal device, or configured by the network device to the terminal device.

[0123] In some embodiments, the first information may indicate a model function of the first AI model. The model function is the function implemented by the AI / ML model. Different models have different model functions, such as: PMI reporting, RI / PMI / CQI reporting, beam information reporting, RSRP reporting, CSI compression, channel coding and decoding, modulation and demodulation, CSI prediction, CSI prediction and compression, etc. After receiving the first information, the terminal device can determine the first AI model to be used based on the model function to be implemented by the AI ​​model.

[0124] It should be noted that the model structure of the first AI model carried in the first information may be at least a portion of the model structure of the first AI model, or in other words, the first information may carry all or part of the model structure of the first AI model. Similarly, the model parameters of the first AI model carried in the first information may be at least a portion of the model parameters of the first AI model, or in other words, the first information may carry all or part of the model parameters of the first AI model. It is understandable that the network device does not necessarily need to configure the entire AI model; it may only configure or update part of the structure or part of the model parameters of the first AI model.

[0125] In other embodiments, the first AI model deployed on the terminal device side may also be a model selected and used by the terminal device from a plurality of preconfigured or predefined AI models. It should be noted that the terminal device may report the first AI model it uses to the network device upon initial access; in addition, the terminal device may also update the model (such as through online training) when it detects that the performance of the original AI model is poor, use the first AI model for communication, and indicate the first AI model to the network device at the same time, so that the network device can update the corresponding model currently deployed on the network device side.

[0126] Among them, the terminal device can send the second information to the network device, and accordingly, the network device receives the second information sent by the terminal device, and the second information is used to indicate to the network device the first AI model used by the terminal device. At this time, the second information can be sent to the network device through a physical layer channel, typically reported to the network device through PUSCH or PUCCH. If the second information is physical layer information, it can be reported to the network device through PUSCH or PUCCH, for example, as part of the CSI report; if the second information is high-layer information, it can be reported to the network device through PUSCH, such as MAC signaling.

[0127] After receiving the second information, the network device may send response information corresponding to the second information to inform the terminal device that the network device has correctly received the second information. For example, if the second information is carried via the PRACH, the response information to the second information may be the corresponding RAR (Random Access Response); if the second information is carried via the PUSCH, the second information may be the HARQ-ACK information of the PUSCH.

[0128] In some embodiments, the second information may include one or more of the following:

[0129] Identification information of the first AI model;

[0130] First, the AI ​​model's functionality;

[0131] The model structure of the first AI model; and

[0132] Model parameters of the first AI model.

[0133] In some embodiments, the second information may carry identification information of the first AI model. It should be understood that the network device can, based on the identification information of the first AI model carried in the second information, determine the first AI model to be applied / updated by the terminal device from one or more AI models, thereby determining the second AI model corresponding to the first AI model. Each AI model may have a one-to-one corresponding identification information, and the corresponding relationship may be pre-agreed between the network device and the terminal device, or configured by the network device for the terminal device.

[0134] In some embodiments, the second information may indicate the model function of the first AI model. The model function is the function implemented by the AI / ML model. Different models have different model functions, such as: PMI reporting, RI / PMI / CQI reporting, beam information reporting, RSRP reporting, CSI compression, channel coding and decoding, modulation and demodulation, CSI prediction, CSI prediction and compression, etc. After receiving the second information, the network device can determine the first AI model to be used / updated by the terminal device based on the model function to be implemented by the AI ​​model, thereby determining the second model corresponding to the first AI model.

[0135] It should be noted that the model structure of the first AI model carried in the second information may be at least a portion of the model structure of the first AI model, or in other words, the second information may carry all or part of the model structure of the first AI model. Similarly, the model parameters of the first AI model carried in the second information may be at least a portion of the model parameters of the first AI model, or in other words, the second information may carry all or part of the model parameters of the first AI model. It is understandable that the terminal device does not necessarily need to indicate the entire first AI model and may only configure or update part of the structure or part of the model parameters of the first AI model.

[0136] It can be understood that after the terminal device receives the first information for configuring the first AI model, or the terminal device sends the second information indicating the first AI model to the network device, both the terminal device and the network device need to determine the time when the first AI model starts to be applied, so as to start enabling the first AI model to communicate with the network device at this time, ensuring that the application time of the corresponding models on the terminal device side and the network device side are synchronized, and avoiding the problem of mismatch between the models on both sides.

[0137] In one possible implementation, the terminal device may determine the time when the first AI model configured by the network device / indicated by the terminal device begins to be applied based on the model application time reported by the terminal device; accordingly, the network device may determine the time when the first AI model configured by the network device for the terminal device / indicated by the terminal device begins to be applied based on the model application time reported by the terminal device. In another possible implementation, the terminal device may determine the time when the first AI model configured by the network device / indicated by the terminal device begins to be applied based on the model application time configured by the network device; accordingly, the network device may determine the time when the first AI model configured by the network device / indicated by the terminal device begins to be applied based on the model application time configured by the network device.

[0138] The following describes the detailed process of how the terminal device determines the moment when the first AI model starts to be applied through Method #A and Method #B.

[0139] Method #A: The terminal device determines the time when the first AI model configured by the network device / indicated by the terminal device starts to be applied based on the model application time reported to the network device; correspondingly, the network device can determine the time when the first AI model configured for the terminal device / indicated by the terminal device starts to be applied based on the model application time reported by the terminal device.

[0140] It should be noted that before determining the time when the first AI model starts to be applied, the terminal device can report the application time of the model it supports to the network device.

[0141] Exemplarily, the terminal device reports the model application time to the network device through UE capability information (eg, UECapabilityInformation).

[0142] In some embodiments, the terminal device may report the model application time to the network device before receiving the first information for configuring the first AI model sent by the network device. Correspondingly, the network device may receive the model application time reported by the terminal device before sending the first information.

[0143] In some embodiments, the terminal device may report the model application time to the network device before sending the second information indicating the first AI model; accordingly, the network device may receive the model application time reported by the terminal device before receiving the second information. Alternatively, the terminal device may include the model application time in the second information indicating the first AI model, and report the first AI model used and the model application time together to the network device. In this way, the network device can also determine the model application time at the same time after receiving the second information, and can apply the model more quickly.

[0144] In some embodiments, for a scenario in which a network device configures a first AI model for a terminal device through first information, the model application time may be any one of the following:

[0145] The time interval between the terminal device receiving the first information and the moment when the first AI model is applied;

[0146] The time interval between the terminal device sending the HARQ-ACK information of the first information and the moment when the first AI model is applied;

[0147] The time interval between when the terminal device receives the first information and when the terminal device sends feedback information obtained based on the first AI model;

[0148] The time interval between the moment when the terminal device sends the HARQ-ACK information of the first information and the moment when the terminal device sends the feedback information obtained based on the first AI model.

[0149] In one possible implementation, the output information of the model does not need to be reported to the first AI model of the network device, such as the first AI model used for operations such as channel decoding of downlink data, demodulation of downlink channels, downlink channel estimation, downlink RF signal processing, channel coding of uplink data, modulation of uplink data, uplink pilot generation, and uplink RF signal processing. The model application time can be the time interval between the terminal device receiving the first information and the moment of applying the first AI model, or the time interval between the terminal device sending the HARQ-ACK information of the first information and the moment of applying the first AI model.

[0150] In one possible implementation, for the first AI model whose output information of the model needs to be reported to the network device, for example, the first AI model used for downlink CSI feedback or downlink beam information feedback, the model application time can be the time interval between the time when the terminal device receives the first information and the time when the terminal device sends feedback information obtained based on the first AI model, or the time interval between the time when the terminal device sends the HARQ-ACK information of the first information and the time when the terminal device sends the feedback information obtained based on the first AI model.

[0151] In some embodiments, for a scenario in which the terminal device indicates the first AI model to the network device through the second information, the model application time may be any one of the following:

[0152] The time interval between the time when the terminal device sends the second information and the time when the first AI model is applied;

[0153] The time interval between the time when the terminal device sends the second information and the time when the terminal device sends the feedback information obtained based on the first AI model;

[0154] The time interval between the terminal device receiving the response information of the second information and the time when the first AI model is applied;

[0155] The time interval between the moment when the terminal device receives the response information of the second information and the moment when the terminal device sends the feedback information obtained based on the first AI model.

[0156] Among them, for the first AI model of the network device, the output information of the model does not need to be reported, such as the first AI model used for channel decoding of downlink data, demodulation of downlink channels, downlink channel estimation, downlink RF signal processing, channel coding of uplink data, modulation of uplink data, uplink pilot generation, and uplink RF signal processing. The model application time can be the time interval between the terminal device sending the second information and the moment of applying the first AI model, or the time interval between the terminal device receiving the response information of the second information and the moment of applying the first AI model.

[0157] In addition, for the first AI model whose output information of the model needs to be reported to the network device, for example, the first AI model used for downlink CSI feedback or downlink beam information feedback, the model application time can be the time interval between the time when the terminal device sends the second information and the time when the terminal device sends feedback information obtained based on the first AI model, or the time interval between the time when the terminal device receives the response information of the second information and the time when the terminal device sends feedback information obtained based on the first AI model.

[0158] It should be noted that the model application time in the above two scenarios involves the moment when the terminal device sends feedback information obtained based on the first AI model, which may refer to the moment when the terminal device sends feedback information obtained based on the first AI model for the first time.

[0159] For example, for the first AI model used for downlink CSI feedback, the model application time may be: the time interval between the time the terminal device receives the first information and the time the terminal device sends CSI feedback information obtained based on the first AI model (for the first time), or the time interval between the time the terminal device sends HARQ-ACK information for the first information and the time the terminal device sends CSI feedback information obtained based on the first AI model (for the first time). The model application time may also be: the time interval between the time the terminal device sends the second information and the time the terminal device sends CSI feedback information obtained based on the first AI model (for the first time), or the time interval between the time the terminal device receives a response to the second information and the time the terminal device sends CSI feedback information obtained based on the first AI model (for the first time).

[0160] Exemplarily, for the first AI model used for downlink beam information feedback, the model application time may be: the time interval between the time the terminal device receives the first information and the time the terminal device sends the downlink beam information obtained based on the first AI model (for the first time), or the time interval between the time the terminal device sends the HARQ-ACK information of the first information and the time the terminal device sends the downlink beam information obtained based on the first AI model (for the first time). In addition, the model application time may also be the time interval between the time the terminal device sends the second information and the time the terminal device sends the downlink beam information obtained based on the first AI model (for the first time), or the time interval between the time the terminal device receives the response information for the second information and the time the terminal device sends the downlink beam information obtained based on the first AI model (for the first time).

[0161] It should also be noted that the above time intervals can be in units of time slots or OFDM symbols. In addition, the above time intervals can also be in units of mini-time slots, OFDM symbol sets, or absolute time (e.g., N milliseconds, N seconds, N>0), which is not limited in the embodiments of the present application.

[0162] In some embodiments, the model application time reported by the terminal device to the network device may include one or more of the following:

[0163] model application time corresponding to one or more AI models supported by the terminal device; wherein the one or more AI models supported by the terminal device include the first AI model;

[0164] the model application time corresponding to each of the one or more model update methods supported by the terminal device; wherein the one or more model update methods supported by the terminal device include an update method for the first AI model;

[0165] the model application time corresponding to one or more AI model functions supported by the terminal device; wherein the one or more model functions supported by the terminal device include the function of the first AI model;

[0166] The model application time corresponding to one or more model types supported by the terminal device; wherein, the one or more model types supported by the terminal device include the type of the first AI model.

[0167] In one possible implementation, a terminal device may support one or more AI models, which may be preconfigured or predefined. It is understood that different AI models have different model structures and model parameters, and therefore different AI models have different model application times. The terminal device may report the model application time for each of the one or more AI models it supports. It is understood that the terminal device may report different model application times for different models.

[0168] In a possible implementation, the terminal device may support one or more model updating modes. Exemplarily, the model updating modes include: updating model parameters and / or updating model structure.

[0169] Among them, the terminal device can report the corresponding model application time for one or more AI model update methods it supports. It is understandable that the terminal device can report different model application times for different model update methods. For example, the application time required to update only the model parameters is t1, the application time required to update the model structure and model parameters is t2, and t1 <t2。

[0170] It should be noted that updating the model structure and model parameters at the same time can be considered as updating the entire AI model.

[0171] In a possible implementation, the terminal device may support one or more model types. For example, the model types supported by the terminal device may include high-precision models and low-precision models; or known models and unknown models.

[0172] High-precision models are more complex than low-precision models, so they take longer to apply. Compared to low-precision models, high-precision models can have more output bits, more neural network layers, or a more complex neural network structure.

[0173] In addition, a known model may be a model that has been deployed on a terminal device, and an unknown model may be a model that has not been deployed on a terminal device. The application time required for a known model is shorter than that required for an unknown model.

[0174] It should be noted that the model application time reported by the terminal device can be determined based on the processing power or hardware configuration of the terminal device, as well as the time required for inference of different AI models / different AI model types. For example, the model application time of an AI model using a CPU on a terminal device can be longer than the model application time of an AI model using a GPU.

[0175] It is understandable that the terminal device and the network device determine the time when the first AI model (the first AI model may be configured by the network device through the first information or indicated by the terminal device through the second information) starts to be applied based on the reported model application time, which can be achieved by one or more of the following:

[0176] Determining a time to start applying the first AI model based on the first AI model configured by the network device / indicated by the terminal device and the model application times corresponding to one or more AI models reported by the terminal device;

[0177] Determining a time to start applying the first AI model based on a function of the first AI model configured by the network device / indicated by the terminal device, and model application times corresponding to one or more model functions reported by the terminal device;

[0178] Determining a start time for applying the first AI model based on a model update method of the first AI model configured by the network device / indicated by the terminal device, and model application times corresponding to one or more model update methods reported by the terminal device;

[0179] Determine the time when the first AI model starts to be applied based on the model type of the first AI model configured by the network device / indicated by the terminal device, and the model application time corresponding to one or more model types reported by the terminal device.

[0180] For example, the terminal device may report the model application time corresponding to AI model 1 as T1, and the model application time corresponding to AI model 2 as T2. If the network device configures model 1 for the terminal device through first information, the terminal device and the network device may determine the time when AI model 1 configured in the first information starts to be applied based on the model application time T1 corresponding to AI model 1. Alternatively, if the terminal device indicates model 2 through second information, the terminal device and the network device may determine the time when AI model 2 starts to be applied based on the model application time T2 corresponding to AI model 2.

[0181] Exemplarily, the terminal device may report that the model application time corresponding to model function 1 (e.g., CSI compression function) is T3, and the model application time corresponding to model function 2 (e.g., channel coding and decoding function) is T4. If the network device configures model function 1 for the terminal device through the first information, the terminal device and the network device may determine the moment when the AI ​​model configured by the first information starts to be applied based on the model application time T3 corresponding to model function 1. Alternatively, if the terminal device indicates model function 2 through the second information, the terminal device and the network device may determine the moment when the AI ​​model indicated by the second information starts to be applied based on the model application time T4 corresponding to model function 2.

[0182] For example, the terminal device may report the model application time T5 corresponding to the high-precision model and the model application time T6 corresponding to the low-precision model. If the AI ​​model configured for the terminal device by the network device through the first information is a low-precision model, the terminal device and the network device may determine the time when the AI ​​model configured by the first information starts to be applied based on the model application time T6 of the low-precision model. If the terminal device indicates that the type of AI model is a high-precision model through the second information, the terminal device and the network device may determine the time when the AI ​​model indicated by the second information starts to be applied based on the application time T5 of the high-precision model.

[0183] Exemplarily, the terminal device reports the model application time T7 corresponding to the known model and the model application time T8 corresponding to the unknown model. If the AI ​​model 1 configured for the terminal device by the network device through the first information is an unknown model (for example, the AI ​​model 1 is a model other than the preconfigured or predefined candidate model of the terminal device), the terminal device and the network device can determine the time when the AI ​​model 1 configured by the first information starts to be applied based on the model application time T8 of the unknown model.

[0184] It should be noted that, when two or more of the model application time corresponding to the first AI model reported by the terminal device, the model application time corresponding to the model function of the first AI model, the model application time corresponding to the model type of the first AI model, and the model application time corresponding to the model update method of the first AI model are different, the terminal device can determine the start time of application of the first AI model based on the longest (or shortest) model application time.

[0185] Method #B: The terminal device determines the moment when the first AI model configured by the network device / indicated by the terminal device starts to be applied based on the model application time configured by the network device; correspondingly, the network device can determine the moment when the first AI model configured by the network device / indicated by the terminal device starts to be applied based on the model application time configured for the terminal device.

[0186] It should be noted that, for the relevant explanation of the model application time, reference can be made to the description in the above embodiment, which will not be repeated here for the sake of brevity.

[0187] In some embodiments, a network device can directly configure the model application time for a terminal device. The network device can send third information to the terminal device, and the terminal device can receive the third information sent by the network device. The third information is used to configure the model application time. In other words, the network device configures the model application time for the terminal device using the third information.

[0188] In some embodiments, the third information may be sent to the terminal device via broadcast signaling. For example, the third information may be carried via PBCH, SIB, Group Common DCI, etc., which is not limited in the embodiments of the present application. In some embodiments, the third information may be high-layer information, sent via high-layer signaling. For example, the third information may be sent via RRC signaling or MAC CE signaling. In some embodiments, the third information may also be physical layer information, sent via physical layer signaling. For example, the third information may be carried via DCI signaling.

[0189] For the scenario where the network device configures the first AI model for the terminal device through the first information, the third information may include the model application time of the first AI model configured in the first information.

[0190] It should be noted that the third information can be indicated to the terminal device together with the first information, so that the terminal device can also determine the application time of the model after receiving the configuration information of the model, and can apply the model more quickly.

[0191] In one possible implementation, the network device may configure the model application time of the first AI model for the terminal device according to a preset rule or a preset mapping relationship.

[0192] Exemplarily, the network device may configure the application time of the first AI model for the terminal device based on factors such as the type of the first AI model configured for the terminal device and the update method of the first AI model.

[0193] Exemplarily, the network device may pre-store the model application time corresponding to each AI model (a mapping relationship between AI models and model application time). When the network device configures a first AI model for a terminal device, the model application time corresponding to the first AI model may be configured for the terminal device based on the mapping relationship.

[0194] In another possible implementation, the network device may receive the model application time reported by the terminal device, and configure the actual model application time for the terminal device according to the model application time reported by the terminal device.

[0195] It should be noted that the network device can determine the model application time configured for the terminal device based on the model application time reported by multiple terminal devices within the coverage area.

[0196] In some embodiments, the network device may use the maximum value of the model application time reported by multiple terminal devices as the model application time actually used by each terminal device within the coverage area, and configure the model application time for these terminal devices. In other words, the duration of the model application time configured by the network device for the terminal device is greater than or equal to the duration of the model application time reported by the terminal device.

[0197] It can be seen from this that the network device can configure the model application time for multiple different terminal devices within its coverage range at the same time. In this way, the network device and different terminal devices can update the model synchronously, thereby ensuring that the model output at the receiving end is available and improving communication performance.

[0198] In a scenario where the terminal device indicates the first AI model via the second information, in one possible implementation, the network device may, after receiving the second information, determine the model application time of the first AI model indicated by the second information, and indicate the model application time to the terminal device via third information. In other words, after receiving the second information, the network device may send the third information to the terminal device to configure the model application time of the first AI model indicated in the second information for the terminal device.

[0199] It should be noted that the network device can configure the model application time of the first AI model for the terminal device according to a preset rule or a preset mapping relationship. Alternatively, the network device can configure the actual model application time for the terminal device based on the model application time reported by the terminal device. For example, the network device can use the maximum value of the model application time reported by multiple terminal devices as the model application time actually used by each terminal device within the coverage area, and configure the model application time to these terminal devices.

[0200] For the scenario where the terminal device indicates the first AI model through the second information, in another possible implementation, the network device may also send third information to the terminal device before the second information. In this implementation, the third information may include one or more of the following:

[0201] Model application time corresponding to one or more AI models, respectively; wherein the one or more AI models include the first AI model;

[0202] Model application time corresponding to one or more model functions, respectively; wherein the one or more model functions include the function of the first AI model;

[0203] Model application time corresponding to one or more model update methods; wherein the one or more model update methods include an update method for the first AI model;

[0204] Model application time corresponding to one or more model types respectively; wherein the one or more model types include the type of the first AI model.

[0205] It can be understood that after the terminal device receives the third information, it can determine the actual model application time of the first AI model indicated by the second information based on the first AI model indicated by the second information, and the model application time corresponding to each AI model, each model function, each model update method, or each model type configured by the third information.

[0206] It should be noted that the model application time configured in the third information can be determined by the network device based on the model application time reported by the terminal device. It is understandable that the network device can determine the model application time configured for the terminal device based on the model application time reported by multiple terminal devices within the coverage area. In some embodiments, the network device can use the maximum value of the model application time reported by multiple terminal devices as the model application time actually used by each terminal device within the coverage area, and configure the model application time for these terminal devices.

[0207] Exemplarily, the third information may configure the model application time corresponding to AI model 1 (or model function 1 / model update mode 1 / model type 1) and AI model 2 (or model function 2 / model update mode 2 / model type 2), respectively. The model application time of AI model 1 (or model function 1 / model update mode 1 / model type 1) configured in the third information may be the maximum value of the model application times corresponding to AI model 1 (or model function 1 / model update mode 1 / model type 1) reported by multiple terminal devices, and the model application time of AI model 2 (or model function 2 / model update mode 2 / model type 2) configured in the third information may be the maximum value of the model application times corresponding to AI model 2 (or model function 2 / model update mode 2 / model type 2) reported by multiple terminal devices.

[0208] In this way, the network device can configure the model application time for multiple different terminal devices within its coverage area at the same time. In this way, the network device and different terminal devices can synchronize model updates, thereby ensuring that the model output at the receiving end is available and improving communication performance.

[0209] In an embodiment of the present application, after the terminal device determines the time to start applying the first AI model based on the above method, the terminal device can further use the first AI model to transmit information between the terminal device and the network device after this time. Correspondingly, the network device can use the second model corresponding to the first AI model to transmit information between the terminal device and the network device after this time.

[0210] In some embodiments, before the terminal device applies the first AI model, the terminal device may use a third AI model to transmit information with the network device, or the terminal device may not use an AI model to transmit information with the network device. Accordingly, before the terminal device applies the first AI model, the network device may use a fourth AI model corresponding to the third AI model to transmit information with the terminal device, or the network device may not use an AI model to transmit information with the terminal device. For example, the network device may receive information transmitted by the terminal device using a traditional non-AI method.

[0211] It should be noted that the third AI model can be a predefined AI model or a historical AI model. The predefined AI model is an AI model agreed upon in advance by the terminal device and the network device. The historical AI model can be an AI model configured by the network device for the terminal device before the first AI model starts to be applied, or an AI model indicated by the terminal device. The historical AI model here can be an AI model with a model structure and model parameters that are completely different from those of the first AI model, or an AI model with the same model structure but different model parameters, or an AI model with different model functions. This embodiment of the present application does not impose any restrictions on this. In addition, the fourth AI model can be an AI model deployed on the network device side corresponding to the third AI model.

[0212] Exemplarily, if the first AI model configured by the network device through the first information / the first AI model indicated by the terminal device through the second information is a new model (i.e., the model ID of the first AI model is different from the model ID of the third AI model), then before the first AI model starts to be applied, the terminal device can use the previously used third AI model to transmit information with the network device.

[0213] For example, if the network device configures a new model function through the first information / the terminal device indicates a new model function through the second information (i.e., the functionality of the first AI model is different from the functionality of the third AI model), then before the first AI model begins to be applied, the terminal device can use the third model corresponding to the previous functionality to transmit information to and from the network device. The function here can also be a function ID.

[0214] For example, if the network device updates the model structure and model parameters through the first information / the terminal device updates the model structure and model parameters through the second information, before the moment when the first AI model determined by the terminal device starts to be applied, the terminal device can use the previously adopted model structure and model parameters to transmit information between the network device.

[0215] For example, if the network device only updates the model parameters through the first information / the terminal device only updates the model parameters through the second information, before the moment when the first AI model determined by the terminal device starts to be applied, the terminal device can use the previously adopted model parameters to transmit information between the network device.

[0216] It should also be noted that the terminal device does not transmit information with the network device based on the AI ​​model, which means that the terminal device uses traditional non-AI methods to transmit information with the network device.

[0217] In summary, in the embodiments of the present application, when corresponding dual-end AI models are used on the terminal device side and the network device side, if the AI ​​model on the terminal device side is updated or reconfigured, the terminal device can determine the time when the AI ​​model configured by the network device starts to be applied based on the model application time reported to the network device, or based on the model application time configured by the network device. In this way, the model application time on both sides can be ensured to be the same, thereby ensuring that the output of the AI ​​model is usable and improving the performance of the communication system.

[0218] In scenarios where a network device configures a first AI model for a terminal device using first information, the time at which the terminal device and the network device determine that the first AI model begins to be applied is related to the first information. The following describes, using Methods #1 to #3, the time at which the first AI model begins to be applied in scenarios where the network device configures the first AI model for a terminal device using first information.

[0219] Method #1: The first AI model can be applied at:

[0220] The first time slot or the first OFDM symbol after the last OFDM symbol of the uplink channel carrying the HARQ-ACK information of the first information starts k OFDM symbols; or

[0221] The first time slot or the first OFDM symbol after the last OFDM symbol of the downlink channel carrying the first information starts k OFDM symbols; wherein k is the model application time.

[0222] It should be noted that the time interval represented by the model application time in method #1 can be in units of OFDM symbols. The model application time can be k OFDM symbols, or in other words, the time interval represented by the model application time is k OFDM symbols, where k is an integer greater than or equal to 1.

[0223] It can be understood that, as described above, k can be reported by the terminal device to the network device, or can be configured by the network device.

[0224] In one possible implementation, the terminal device may use the first time slot or the first OFDM symbol k OFDM symbols after the last OFDM symbol of the downlink channel carrying the first information as the time when the first AI model starts to be applied. In other words, the terminal device may use the first time slot or the first OFDM symbol k OFDM symbols after the last OFDM symbol of the downlink channel carrying the first information as the time when the first AI model starts to be applied.

[0225] It should be noted that the downlink channel here can be PBCH, PDSCH, PDCCH, etc. For example, when the first information is broadcast information, the downlink channel can be PBCH; when the first information is high-layer information, the downlink channel can be PDSCH; when the first information is physical layer information, the downlink channel can be PDCCH.

[0226] It should also be noted that the k OFDM symbols in the embodiment of the present application can also be k-1 or k+1 OFDM symbols, and the embodiment of the present application does not limit this.

[0227] Exemplarily, referring to FIG6A , assuming that the last OFDM symbol of the downlink channel carrying the first information is symbol m, the terminal device can determine that the moment when the first AI model starts to be applied is the first time slot after the symbol where symbol m+k is located.

[0228] For example, referring to FIG6B , assuming that the last OFDM symbol of the downlink channel carrying the first information is symbol m, the terminal device can determine that the moment when the first AI model starts to apply is the first OFDM symbol after the symbol m+k, that is, the symbol m+k+1 shown in FIG6B .

[0229] In another possible implementation, the terminal device may use the first time slot or the first OFDM symbol after the last OFDM symbol of the uplink channel carrying the HARQ-ACK information of the first information k OFDM symbols later than the last OFDM symbol of the uplink channel carrying the HARQ-ACK information of the first information as the time when the first AI model starts to be applied. In other words, the terminal device may use the first time slot or the first OFDM symbol after the last OFDM symbol of the uplink channel carrying the HARQ-ACK information of the first information k OFDM symbols later than the last OFDM symbol of the uplink channel carrying the HARQ-ACK information of the first information as the time when the first AI model starts to be applied.

[0230] It is understandable that after receiving the first information, the terminal device can send HARQ-ACK information of the first information to the network device. Exemplarily, when the first information is high-layer information or physical layer information, after receiving the first information, the terminal device can feedback HARQ-ACK information of the first information to the network device.

[0231] It should be noted that the uplink channel carrying the HARQ-ACK information of the first information may be a PUCCH.

[0232] It should also be noted that the k OFDM symbols in the embodiment of the present application can also be k-1 or k+1 OFDM symbols, and the embodiment of the present application does not limit this.

[0233] Exemplarily, referring to Figure 7A, assuming that the last OFDM symbol of the uplink channel carrying the HARQ-ACK information of the first information is symbol m, the terminal device can determine that the moment when the first AI model starts to apply is the first time slot after the symbol where symbol m+k is located.

[0234] For example, referring to FIG7B , assuming that the last OFDM symbol of the uplink channel carrying the HARQ-ACK information of the first information is symbol m, the terminal device can determine that the moment when the first AI model starts to apply is the first OFDM symbol after the symbol m+k, that is, the symbol m+k+1 shown in FIG7B .

[0235] It can be understood that using the first OFDM symbol after k OFDM symbols as the moment to start applying the first AI model can shorten the time interval for applying the first AI model, compared to using the first time slot after k OFDM symbols as the moment to start applying the first AI model, and at the same time improve the accuracy of the model application time.

[0236] Method #2: The first AI model can be applied at:

[0237] The first time slot after k time slots starts from the time slot in which the terminal device receives the first information, where k is the model application time.

[0238] It should be noted that the time interval represented by the model application time in method #2 can be in time slots. The model application time can be k time slots, or in other words, the time interval represented by the model application time is k time slots, where k is an integer greater than or equal to 1.

[0239] It can be understood that, as described above, k can be reported by the terminal device to the network device, or can be configured by the network device.

[0240] In this method #2, the terminal device may use the first time slot after k time slots from the time slot in which the first information is received as the time point at which the first AI model starts to be applied. Alternatively, the terminal device may use the first time slot after k time slots from the time slot in which the first information is received as the time point at which the first AI model starts to be applied.

[0241] It should be noted that the k time slots in the embodiment of the present application can also be k-1 or k+1 time slots, and the embodiment of the present application does not limit this.

[0242] Exemplarily, as shown in reference Figure 8, assuming that the terminal device receives the first information in time slot n, the terminal device can determine that the moment when the first AI model starts to be applied is the first time slot after time slot n+k, that is, time slot n+k+1.

[0243] Method #3: The first AI model can be applied at:

[0244] The first time slot after k time slots, (k+3N) time slots, or max(k,3N) time slots from the time slot where the uplink channel of the HARQ-ACK information carrying the first information is located, where k is the application time of the model and N is the number of time slots contained in 1ms.

[0245] It should be noted that the time interval represented by the model application time in method #3 can be in time slots. The model application time can be k time slots, or in other words, the time interval represented by the model application time is k time slots, where k is an integer greater than or equal to 1.

[0246] It can be understood that, as described above, k can be reported by the terminal device to the network device, or can be configured by the network device.

[0247] In one embodiment, the terminal device may use the first time slot after k time slots from the time slot in which the uplink channel carrying the HARQ-ACK information of the first information is located as the time point when the first AI model starts to be applied. Alternatively, the terminal device may use the first time slot after k time slots from the time slot in which the uplink channel carrying the HARQ-ACK information of the first information is located as the time point when the first AI model starts to be applied.

[0248] It should be noted that, in this implementation, the first information is high-layer information. Typically, the first information is sent via RRC signaling.

[0249] It should also be noted that the k time slots in the embodiment of the present application can also be k-1 or k+1 time slots, and the embodiment of the present application does not limit this.

[0250] For example, referring to FIG9A , assuming that the terminal device sends HARQ-ACK information of the PDSCH carrying the first information in time slot n, the time when the first AI model starts to be applied is the first time slot after time slot n+k, that is, time slot n+k+1.

[0251] In one embodiment, the terminal device may use the first time slot after (k+3N) time slots from the time slot in which the uplink channel carrying the HARQ-ACK information of the first information is located as the time point when the first AI model starts to be applied. In other words, the terminal device may use the first time slot after (k+3N) time slots from the time slot in which the uplink channel carrying the HARQ-ACK information of the first information is located as the time point when the first AI model starts to be applied.

[0252] It should be noted that, in this embodiment, the first information is high-layer information. Typically, the first information is sent via MAC layer signaling, such as the signaling defined in 3GPP TS38.321.

[0253] It can be understood that 3N time slots (ie, 3 ms) is the minimum time required for MAC layer signaling to take effect, and the MAC layer signaling is ensured to have sufficient time to take effect by spacing k+3N time slots.

[0254] It should also be noted that the k time slots in the embodiment of the present application can also be k-1 or k+1 time slots, and the embodiment of the present application does not limit this.

[0255] For example, referring to FIG9B , assuming that the terminal device sends HARQ-ACK information of the PDSCH carrying the first information in time slot n, the time when the first AI model starts to be applied is the first time slot after time slot n+k+3N, that is, time slot n+k+3N+1.

[0256] In one embodiment, the terminal device may use the first time slot after the time slot containing the uplink channel carrying the HARQ-ACK information of the first information and the interval of max(k,3N) time slots as the time point when the first AI model starts to be applied. Alternatively, the terminal device may use the first time slot after the time slot containing the uplink channel carrying the HARQ-ACK information of the first information and the interval of max(k,3N) time slots as the time point when the first AI model starts to be applied.

[0257] It should be noted that, in this embodiment, the first information is high-layer information. Typically, the first information is transmitted via MAC layer signaling, such as signaling defined in 3GPP TS38.321.

[0258] It can be understood that 3N time slots (ie, 3 ms) is the minimum time required for MAC layer signaling to take effect. By taking the larger value of k and 3N, it is ensured that the MAC layer signaling has sufficient time to take effect.

[0259] It should also be noted that the k time slots in the embodiment of the present application can also be k-1 or k+1 time slots, and the embodiment of the present application does not limit this.

[0260] For example, referring to Figure 9C, assuming that the terminal device sends HARQ-ACK information of the PDSCH carrying the first information in time slot n and k<3N, the time when the first AI model starts to be applied is the first time slot after time slot n+3N, that is, time slot n+3N+1.

[0261] It should be noted that the terminal device and the network device can agree on one of the methods #1 to #3, or the network device can specify one of the methods #1 to #3 for the terminal device to determine the time when the first AI model starts to be applied, thereby ensuring that the time when the corresponding AI models on both sides start to be applied is the same.

[0262] Furthermore, for scenarios where the terminal device indicates the first AI model to the network device via second information, the time at which the terminal device and the network device determine to begin applying the first AI model can be related to the second information. The following describes, using Methods #1' to #3', the time at which the first AI model begins applying in scenarios where the terminal device indicates the first AI model to the network device via second information.

[0263] Method #1', the time when the first AI model starts to be applied is:

[0264] The first time slot or the first OFDM symbol after the last OFDM symbol of the uplink channel carrying the second information starts k OFDM symbols; or,

[0265] The first time slot or the first OFDM symbol after the last OFDM symbol of the response information of the uplink channel carrying the second information starts k OFDM symbols; wherein k is the model application time.

[0266] It should be noted that the time interval represented by the model application time in method #1' can be in units of OFDM symbols. The model application time can be k OFDM symbols, or in other words, the time interval represented by the model application time is k OFDM symbols, where k is an integer greater than or equal to 1.

[0267] In one possible implementation, the terminal device may use the first time slot or the first OFDM symbol k OFDM symbols after the last OFDM symbol of the uplink channel carrying the second information as the time when the first AI model starts to be applied. In other words, the terminal device may use the first time slot or the first OFDM symbol k OFDM symbols after the last OFDM symbol of the uplink channel carrying the second information as the time when the first AI model starts to be applied.

[0268] It should be noted that the uplink channel here may be PUSCH or PUCCH. For example, if the second information is high-layer information, the uplink channel may be PUSCH; if the second information is physical layer information, the uplink channel may be PUCCH.

[0269] It should also be noted that the k OFDM symbols in the embodiment of the present application can also be k-1 or k+1 OFDM symbols, and the embodiment of the present application does not limit this.

[0270] In another possible implementation, the terminal device may use the first time slot or the first OFDM symbol after the last OFDM symbol of the downlink channel carrying the response information of the second information k OFDM symbols later than the last OFDM symbol of the downlink channel carrying the response information as the time when the first AI model starts to be applied. In other words, the terminal device may use the first time slot or the first OFDM symbol after the last OFDM symbol of the downlink channel carrying the response information of the second information k OFDM symbols later than the last OFDM symbol of the downlink channel carrying the response information of the second information as the time when the first AI model starts to be applied.

[0271] It is understandable that after receiving the second information, the network device can send a response message corresponding to the second information to let the terminal device know that the network device has correctly received the second information. For example, if the second information is carried by PRACH, the response message of the second information can be the corresponding RAR; if the second information is carried by PUSCH, the second information can be the HARQ-ACK information of the PUSCH.

[0272] It should be noted that the above-mentioned k OFDM symbols can also be k-1 or k+1 OFDM symbols, and the embodiment of the present application does not limit this.

[0273] Method #2', the time when the first AI model starts to be applied is:

[0274] The first time slot that is k time slots after the time slot in which the terminal device sends the second information starts; the second information is uplink information used to indicate the first AI model, and k is the model application time.

[0275] It should be noted that the time interval represented by the model application time in method #2' can be in time slots. The model application time can be k time slots, or in other words, the time interval represented by the model application time is k time slots, where k is an integer greater than or equal to 1.

[0276] It can be understood that, as described above, k can be reported by the terminal device to the network device, or can be configured by the network device.

[0277] In this approach #2', the terminal device may use the first time slot k time slots after the time slot in which the second information is sent as the time point at which the first AI model starts to be applied. Alternatively, the terminal device may use the first time slot k time slots after the time slot in which the second information is sent as the time point at which the first AI model starts to be applied.

[0278] It should be noted that the k time slots in the embodiment of the present application can also be k-1 or k+1 time slots, and the embodiment of the present application does not limit this.

[0279] Method #3', the moment when the first AI model starts to be applied is:

[0280] The first time slot after k time slots, (k+3N) time slots, or max(k,3N) time slots from the time slot where the downlink channel of the response information carrying the second information is located, wherein the second information is the uplink information used to indicate the first AI model, k is the model application time, and N is the number of time slots contained in 1ms.

[0281] It should be noted that the time interval represented by the model application time in method #3' can be in time slots. The model application time can be k time slots, or in other words, the time interval represented by the model application time is k time slots, where k is an integer greater than or equal to 1.

[0282] It can be understood that, as described above, k can be reported by the terminal device to the network device, or can be configured by the network device.

[0283] In one embodiment, the terminal device may use the first time slot that is k time slots after the time slot in which the downlink channel carrying the response information of the second information is located as the time point at which the first AI model starts to be applied. Alternatively, the terminal device may use the first time slot that is k time slots after the time slot in which the downlink channel carrying the response information of the second information is located as the time point at which the first AI model starts to be applied.

[0284] It should be noted that, in this implementation, the second information is high-layer information. Typically, the second information is sent via RRC signaling.

[0285] It should also be noted that the k time slots in the embodiment of the present application can also be k-1 or k+1 time slots, and the embodiment of the present application does not limit this.

[0286] In one embodiment, the terminal device may use the first time slot after (k+3N) time slots from the time slot in which the downlink channel carrying the response information of the second information is located as the time point at which the first AI model starts to be applied. Alternatively, the terminal device may use the first time slot after (k+3N) time slots from the time slot in which the downlink channel carrying the response information of the second information is located as the time point at which the first AI model starts to be applied.

[0287] It should be noted that, in this embodiment, the second information is high-layer information. Typically, the second information is sent via MAC layer signaling, such as the signaling defined in 3GPP TS38.321.

[0288] It can be understood that 3N time slots (ie, 3 ms) is the minimum time required for MAC layer signaling to take effect, and the MAC layer signaling is ensured to have sufficient time to take effect by spacing k+3N time slots.

[0289] It should also be noted that the k time slots in the embodiment of the present application can also be k-1 or k+1 time slots, and the embodiment of the present application does not limit this.

[0290] In one embodiment, the terminal device may use the first time slot after the time slot containing the downlink channel of the response information carrying the second information and the interval of max(k,3N) time slots as the time point at which the first AI model starts to be applied. Alternatively, the terminal device may use the first time slot after the time slot containing the downlink channel of the response information carrying the second information and the interval of max(k,3N) time slots as the time point at which the first AI model starts to be applied.

[0291] It should be noted that, in this embodiment, the second information is high-layer information. Typically, the second information is sent via MAC layer signaling, such as the signaling defined in 3GPP TS38.321.

[0292] It can be understood that 3N time slots (ie, 3 ms) is the minimum time required for MAC layer signaling to take effect. By taking the larger value of k and 3N, it is ensured that the MAC layer signaling has sufficient time to take effect.

[0293] It should also be noted that the k time slots in the embodiment of the present application can also be k-1 or k+1 time slots, and the embodiment of the present application does not limit this.

[0294] It should be noted that the terminal device and the network device can agree on one of the methods #1' to #3', or the network device can specify one of the methods #1' to #3' for the terminal device to determine the time when the first AI model starts to be applied, thereby ensuring that the time when the corresponding AI models on both sides start to be applied is the same.

[0295] In some embodiments, the moment when the first AI model starts to be applied and / or the model application time can be determined according to any one of the following:

[0296] a subcarrier spacing of a downlink channel carrying the first information;

[0297] a subcarrier spacing of an uplink channel carrying HARQ-ACK information carrying the first information;

[0298] a subcarrier spacing of an uplink channel carrying second information;

[0299] a subcarrier spacing of a downlink channel carrying response information of the second information;

[0300] The subcarrier spacing of the activated BWP on the carrier to which the first AI model is applied.

[0301] It should be noted that the time when the first AI model starts to be applied and the model application time are parameters in time slots or OFDM symbols. The actual corresponding time length / time (or absolute time length / time slot) needs to be determined based on the subcarrier spacing. Different subcarrier spacings correspond to different time lengths.

[0302] For example, refer to Table 1 for the relationship between the subcarrier spacing, the number of time slots, and the time slot length.

[0303] Table 1

[0304] As shown in Table 1, the subcarrier spacing is 30 kHz, corresponding to a time slot length of 0.5 ms. If the model is applied for k time slots, the length of k time slots is 0.5 k ms. Similarly, if the subcarrier spacing is 60 kHz, the length of each time slot is 0.25 ms. If the model is applied for k time slots, the length of k time slots is 0.25 k ms.

[0305] It can be understood that the moment when the first AI model starts to be applied and / or the model application time can be determined according to the subcarrier spacing related to the first AI model.

[0306] In some embodiments, for a scenario in which a network device configures a first AI model for a terminal device using first information, the moment when the first AI model starts to be applied and / or the model application time can be determined according to any one of the following:

[0307] a subcarrier spacing of a downlink channel carrying the first information;

[0308] a subcarrier spacing of an uplink channel carrying HARQ-ACK information of the first information;

[0309] The subcarrier spacing of the BWP activated on the carrier to which the first AI model is applied.

[0310] In one possible implementation, the moment when the first AI model starts to be applied and / or the model application time can be determined according to the subcarrier spacing of the downlink channel carrying the first information.

[0311] Exemplarily, if the first information is carried via the PBCH, the time at which the first AI model starts to be applied and / or the model application time are determined based on the subcarrier spacing of the PBCH. If the first information is carried via the Group Common DCI, the time at which the first AI model starts to be applied and / or the model application time are determined based on the subcarrier spacing of the PDCCH carrying the DCI.

[0312] For example, in combination with the time slot structure diagram shown in Figure 8, the time when the model starts to be applied is time slot n+k+1. The terminal device can obtain the time length between time slot n+k+1 and time slot n based on the subcarrier spacing carrying the first information, thereby determining the time when the model is applied.

[0313] In another possible implementation, the moment when the first AI model starts to be applied and / or the model application time can be determined according to the subcarrier spacing of the uplink channel of the HARQ-ACK information carrying the first information.

[0314] Exemplarily, if the first information is carried through high-layer signaling, the time when the first AI model starts to be applied and / or the model application time can be determined based on the subcarrier spacing of the uplink channel where the HARQ-ACK information of the PDSCH carrying the high-layer signaling is located.

[0315] For example, in combination with the time slot structure diagram shown in Figure 9B, if the time when the model starts to be applied is time slot n+k+3N+1, the terminal device can obtain the time length between time slot n+k+3N+1 and time slot n based on the determined subcarrier spacing, thereby determining the time when the model is applied.

[0316] In another possible implementation, the moment when the first AI model starts to be applied and / or the model application time may be based on the subcarrier spacing of the BWP activated on the carrier to which the first AI model is applied.

[0317] In some embodiments, when there are multiple carriers to which the first AI model is applied, the time at which the first AI model starts to be applied and / or the model application time can be determined based on the first subcarrier spacing. The first subcarrier spacing is any subcarrier spacing of the BWPs activated on the multiple carriers to which the first AI model is applied. The first subcarrier spacing can be agreed upon by the network device and the terminal device.

[0318] Exemplarily, the first subcarrier spacing may be the minimum subcarrier spacing among the BWPs activated on multiple carriers to which the first AI model is applied. For example, the carriers to which the first AI model is applied are CC1, CC2, and CC3 respectively, the BWPs activated on the three CCs are BWP1, BWP2, and BWP3 respectively, and the subcarrier spacing configured for BWP1 < the subcarrier spacing configured for BWP2 < the subcarrier spacing configured for BWP3. At this time, the start time and / or the model application time of the first AI model may be determined according to the subcarrier spacing configured for BWP1.

[0319] In some other embodiments, for the scenario where the terminal device indicates the first AI model to the network device through the second information, the start time and / or the model application time of the first AI model may be determined according to any one of the following:

[0320] The subcarrier spacing of the uplink channel carrying the second information;

[0321] The subcarrier spacing of the downlink channel carrying the response information of the second information;

[0322] The subcarrier spacing of the BWP activated on the carrier to which the first AI model is applied.

[0323] In a possible implementation, the start time and / or the model application time of the first AI model may be determined according to the subcarrier spacing of the uplink channel carrying the second information.

[0324] Exemplarily, if the second information is carried by UCI, the start time and / or the model application time of the first AI model are determined according to the subcarrier spacing of the PUCCH of the UCI. If the second information is carried by high-layer signaling, the start time and / or the model application time of the first AI model are determined according to the subcarrier spacing of the PUSCH carrying the high-layer signaling. If the second information is carried by PRACH, the start time and / or the model application time of the first AI model are determined according to the subcarrier spacing of the PRACH.

[0325] In another possible implementation, the start time and / or the model application time of the first AI model may be determined according to the subcarrier spacing of the downlink channel carrying the response information of the second information.

[0326] Exemplarily, if the second information is carried by high-layer signaling, the start time and / or the model application time of the first AI model may be determined according to the subcarrier spacing of the downlink channel where the HARQ-ACK information of the PUSCH carrying the high-layer signaling is located. If the second information is carried by PRACH, the start time and / or the model application time of the first AI model may be determined according to the subcarrier spacing of the downlink channel where the corresponding RAR is located.

[0327] In another possible implementation, the moment when the first AI model starts to be applied and / or the model application time can be determined according to the subcarrier spacing of the BWP activated on the carrier for applying the first AI model.

[0328] In some embodiments, when the number of carriers for applying the first AI model is multiple, the moment when the first AI model starts to be applied and / or the model application time can be determined according to the first subcarrier spacing. Here, the first subcarrier spacing is any one of the subcarrier spacings of the BWPs respectively activated on the multiple carriers for applying the first AI model. The first subcarrier spacing can be agreed upon by the network device and the terminal device.

[0329] Exemplarily, the first subcarrier spacing can be the smallest subcarrier spacing of the BWPs respectively activated on the multiple carriers for applying the first AI model. For example, the carriers for applying the first AI model are CC1, CC2, and CC3 respectively, and the BWPs activated on the three CCs are BWP1, BWP2, and BWP3 respectively, and the subcarrier spacing configured by BWP1 < the subcarrier spacing configured by BWP2 < the subcarrier spacing configured by BWP3. At this time, the moment when the first AI model starts to be applied and / or the model application time can be determined according to the subcarrier spacing configured by BWP1.

[0330] It can be seen that by agreeing on the same subcarrier spacing between the terminal device and the network device to determine the moment when the first AI model starts to be applied and / or the model application time, it can ensure that the model application time determined by the terminal device and the network, and the moment when the first AI model starts to be applied are the same, thus achieving the effect of synchronously updating the model. On the contrary, when the subcarrier spacing of the channel carrying the first information / second information is different from the subcarrier spacing used for the carrier applying the first AI model, if it is not agreed which subcarrier spacing is used to determine the moment when the first AI model starts to be applied and / or the model application time, the terminal device and the network device cannot determine the actual time length, which may lead to different time lengths determined on both sides.

[0331] The method provided by the embodiments of the present application will be elaborated in detail below in combination with specific application scenarios.

[0332] Embodiment 1:

[0333] In this Embodiment 1, the network device can configure an AI model for the terminal devices within its coverage area through broadcast signaling (that is, the first information is carried by broadcast signaling). This embodiment may include the following steps:

[0334] S1. The terminal device reports the supported model application time through UE capability information.

[0335] It should be noted that the model application time is the time interval between the terminal device receiving the broadcast signaling for configuring the AI ​​model and applying the AI ​​model. The time interval is in time slots.

[0336] In some embodiments, the model application time reported by the terminal device may include:

[0337] The model application time corresponding to one or more AI models supported by the terminal device;

[0338] Model application time corresponding to one or more model update methods supported by the terminal device;

[0339] The model application time corresponding to one or more model types supported by the terminal device.

[0340] S2. The network device indicates the model application time to the terminal device based on the UE capabilities reported by the terminal device.

[0341] It should be noted that the network device needs to consider the model application time reported by multiple terminal devices within the coverage area to determine the indicated model application time. For example, the network device can use the maximum value of the model application time reported by multiple terminal devices as the model application time used by each terminal within the coverage area and indicate it to these terminal devices.

[0342] In some embodiments, the model application time may be indicated by broadcast signaling. Exemplarily, the broadcast signaling may be PBCH, SIB, or Group Common DCI. The broadcast signaling indicating the model application time may be the same as or different from the broadcast signaling indicating the AI ​​model, and this is not limited in this embodiment of the present application.

[0343] In some embodiments, the model application time may also be indicated by higher layer signaling or physical layer signaling. For example, the higher layer signaling may be a MAC layer signaling indication for a model failure recovery response, or a MAC layer signaling for a model update.

[0344] S3. The terminal device receives the broadcast signaling sent by the network device for configuring the AI ​​model.

[0345] In some embodiments, the terminal device can receive at least one of the model ID, functionality, model structure, and model parameters of the AI ​​model configured by the network device through broadcast signaling.

[0346] It is understandable that the network device does not have to configure the entire AI model, but can only configure or update part of the structure or part of the model parameters in the AI ​​model.

[0347] In some embodiments, if a network device configures a new model ID via broadcast signaling, the time at which the AI ​​model begins to be applied is the time at which the updated model begins to be applied. Prior to this time, the terminal device may use the previously used model to transmit information to and from the network device.

[0348] In some embodiments, if a network device configures a new model functionality via broadcast signaling, the moment the AI ​​model begins to be applied is the moment the updated model begins to be applied. Before this moment, the terminal device can use the model corresponding to the previous functionality to transmit information to and from the network device. The functionality here can also be a functionality ID.

[0349] In some embodiments, if the network device updates the model structure and model parameters via broadcast signaling, the time when the AI ​​model begins to be applied is the time when the updated model structure and model parameters begin to be applied. Before this time, the terminal device can use the previously used model structure and model parameters to transmit information between the network device.

[0350] In some embodiments, if the network device only updates the model parameters via broadcast signaling, the time when the AI ​​model begins to be applied is the time when the updated model parameters begin to be applied. Before this time, the terminal device can use the previously used model parameters to transmit information between the network device and the terminal device.

[0351] It should be noted that all terminal devices that receive broadcast signaling for configuring an AI model must apply the AI ​​model configured in the broadcast signaling. For example, a network device can indicate the AI ​​model to a group of terminal devices using Group Common DCI, which is transmitted via the common search space (CSS) and scrambled using a common RNTI.

[0352] In some embodiments, while the network device configures the AI ​​model through broadcast signaling, it can also indicate the corresponding model application time through the same signaling.

[0353] It is understandable that a network device can deploy the same AI model to a group of terminal devices and indicate the same model application time, so that the group of terminal devices can apply the AI ​​model simultaneously. In this way, only one AI model needs to be deployed on the network side as the corresponding encoder / decoder model, and there is no need to deploy a corresponding model for each terminal device, which significantly reduces the implementation complexity of the network device and also reduces the overhead of downlink signaling.

[0354] S4. The terminal device determines the time to start applying the AI ​​model based on the model application time configured by the network device.

[0355] Among them, the moment when the AI ​​model starts to be applied is: the first time slot after k time slots from the time slot when the terminal device receives the broadcast signaling used to configure the AI ​​model; k is the model application time indicated by the network device (in time slots).

[0356] For example, referring to Figure 8, assuming that the terminal device receives the broadcast signaling for configuring the AI ​​model in time slot n, the time when the AI ​​model starts to be applied is the first time slot after time slot n+k, that is, it starts to be applied in time slot n+k+1.

[0357] It should be noted that in this embodiment, the time when the AI ​​model starts to be applied and / or the model application time are parameters in time slots, and the corresponding time length / time needs to be determined according to the subcarrier spacing, where different subcarrier spacings correspond to different time lengths.

[0358] In an embodiment of the present application, the time when the AI ​​model configured by the network device starts to be applied and / or the model application time can be determined according to the subcarrier spacing of the channel carrying the broadcast signaling.

[0359] It can be understood that by agreeing on the same subcarrier spacing between the terminal device and the network device to determine the moment when the AI ​​model starts to be applied and the model application time, it can be ensured that the model application time and the moment when the model starts to be applied determined by the terminal device and the network device are the same, thereby achieving the effect of synchronously updating the model. Conversely, when the subcarrier spacing of the channel carrying the broadcast signaling used to configure the AI ​​model is different from the subcarrier spacing used by the carrier to which the AI ​​model is applied, if it is not determined based on which subcarrier spacing to determine the moment when the AI ​​model starts to be applied and / or the model application time, then the terminal device and the network device cannot determine the length of k time slots.

[0360] S5. After the AI ​​model starts to be applied, the terminal device uses the AI ​​model configured by broadcast signaling to transmit information with the network device.

[0361] In some embodiments, before the terminal device applies the AI ​​model, the terminal device may use a predefined AI model to transmit information with the network device, or the terminal device may transmit information with the network device without using an AI model. A predefined AI model is an AI model agreed upon in advance by the terminal device and the network device. The terminal device may transmit information with the network device without using an AI model, i.e., the terminal device may transmit information with the network device using a traditional non-AI method.

[0362] In some embodiments, after the AI ​​model configured by the broadcast signaling begins to be applied, the terminal device may use the AI ​​model for any of the following processes:

[0363] Downlink CSI feedback; or,

[0364] Channel decoding of downlink data; or,

[0365] Demodulation of downlink signals; or,

[0366] Downlink channel estimation; or,

[0367] Downlink RF signal processing; or,

[0368] Channel coding of uplink data; or,

[0369] Modulation of uplink data; or,

[0370] Uplink pilot generation; or,

[0371] Uplink RF signal processing.

[0372] S6. After the AI ​​model starts to be applied, the network device uses the network-side model corresponding to the AI ​​model configured by the above-mentioned broadcast signaling to transmit information between the terminal device.

[0373] In some embodiments, after the AI ​​model configured by broadcast signaling begins to be applied, the network device may use the network-side model corresponding to the configured AI model for any of the following processes:

[0374] Decoding of downlink CSI feedback information; or,

[0375] Channel decoding of uplink data; or,

[0376] Demodulation of uplink signals; or,

[0377] Uplink channel estimation; or,

[0378] Uplink RF signal processing; or,

[0379] Channel coding of downlink data; or,

[0380] Modulation of downlink data; or,

[0381] Downlink pilot generation; or,

[0382] Downlink RF signal processing.

[0383] It should be noted that the modules of the network equipment application model correspond one-to-one to the modules of the AI ​​model applied on the terminal side, such as channel coding-channel decoding, modulation-demodulation, pilot generation-channel estimation, transmitting end RF signal processing-receiving end RF signal processing, etc.

[0384] Example 2

[0385] In the second embodiment, the network device may configure the AI ​​model for the terminal device through high-layer signaling (i.e., the first information is carried through high-layer signaling). This embodiment may include the following steps:

[0386] S1. The terminal device reports the supported model application time through UE capabilities.

[0387] It should be noted that the model application time is the time interval between the terminal device feeding back the HARQ-ACK information of the high-layer signaling used to configure the AI ​​model and the application of the AI ​​model. The time interval is in time slots or OFDM symbols.

[0388] In some embodiments, the above-mentioned high-layer signaling may be RRC signaling or MAC layer signaling (MAC CE).

[0389] In some embodiments, the HARQ-ACK information of the above-mentioned higher-layer signaling is the HARQ-ACK information of the PDSCH carrying the first information.

[0390] S2. The terminal device receives the AI ​​model configured by the network device through high-level signaling.

[0391] S3. The terminal device determines the time to start applying the AI ​​model configured on the network device based on the model application time reported in S1.

[0392] In one embodiment, the time when the AI ​​model configured by the high-layer signaling starts to be applied may be: the first time slot after the time slot where the HARQ-ACK information of the PDSCH carrying the high-layer signaling is located, which is k time slots away.

[0393] Among them, k is the model application time, which can be determined by the model application time supported by the terminal device through UE capability reporting.

[0394] It should be noted that the typical high-layer signaling in this embodiment is RRC signaling.

[0395] In one embodiment, the time when the AI ​​model configured by the high-layer signaling starts to be applied can be: the first time slot after the time slot where the HARQ-ACK information of the PDSCH carrying the high-layer signaling is located (k+3N) time slots.

[0396] Here, k is the application time of the model, and N is the number of time slots contained in 1 ms, that is, 3N time slots are 3 ms.

[0397] It should be noted that typical high-layer signaling may be MAC layer signaling. 3N time slots (ie, 3 ms) is the minimum time required for MAC layer signaling to take effect. By spacing k+3N time slots, sufficient time is ensured for MAC layer signaling to take effect.

[0398] In one embodiment, the time when the AI ​​model configured by the high-layer signaling starts to be applied may be: the first time slot after the time slot where the HARQ-ACK information of the PDSCH carrying the high-layer signaling is located, which is p time slots away.

[0399] Here, p is the larger value of k and 3N, k is the model application time (in time slots), and N is the number of time slots contained in 1ms, that is, 3N time slots are 3ms.

[0400] It should be noted that typical high-layer signaling may be MAC layer signaling, and 3N time slots (ie, 3ms) is the minimum time required for the MAC layer signaling to take effect. By taking the larger value of k and 3N, sufficient time is ensured for the MAC layer signaling to take effect.

[0401] It should also be noted that in this embodiment, the time when the AI ​​model starts to be applied and / or the model application time are parameters in time slots, and the corresponding time length / time needs to be determined according to the subcarrier spacing, where different subcarrier spacings correspond to different time lengths.

[0402] In one embodiment, the time when the AI ​​model configured by the network device starts to be applied and / or the model application time can be determined according to the subcarrier spacing of the uplink channel where the HARQ-ACK information of the PDSCH carrying the high-layer signaling is located.

[0403] In another embodiment, the time when the AI ​​model configured by the network device starts to be applied and / or the model application time can be determined according to the subcarrier spacing of the BWP activated on the carrier of the AI ​​model.

[0404] If the AI ​​model is applied to multiple carriers and BWPs are activated on all of them, the AI ​​model application start time and / or model application time are determined based on the smallest subcarrier spacing among the BWPs activated on the multiple carriers. This allows network devices and terminal devices to determine a single application start time even in multi-carrier scenarios.

[0405] It can be understood that by agreeing on the same subcarrier spacing between the terminal device and the network device to determine the moment when the AI ​​model starts to be applied and the model application time, it can be ensured that the model application time and the moment when the model starts to be applied determined by the terminal device and the network device are the same, thereby achieving the effect of synchronously updating the model. Conversely, when the subcarrier spacing of the channel carrying the broadcast signaling used to configure the AI ​​model is different from the subcarrier spacing used by the carrier to which the AI ​​model is applied, if it is not determined based on which subcarrier spacing to determine the moment when the AI ​​model starts to be applied and / or the model application time, then the terminal device and the network device cannot determine the length of k time slots.

[0406] S4. After the AI ​​model starts to be applied, the terminal device uses the AI ​​model configured by the above-mentioned high-level signaling to transmit information between the terminal device and the network device.

[0407] S5. After the AI ​​model starts to be applied, the network device uses the network-side model corresponding to the AI ​​model configured by the above-mentioned high-level signaling to transmit information between the terminal device.

[0408] Example 3

[0409] In this first embodiment, the network device may configure the AI ​​model for the terminal device via DCI (i.e., the first information is carried via DCI). This embodiment may include the following steps:

[0410] S1. The terminal device reports the supported model application time through UE capabilities.

[0411] It should be noted that the model application time is the time interval between the terminal device feeding back the HARQ-ACK information of the DCI signaling used to configure the AI ​​model and the application of the AI ​​model. The time interval is in time slots or OFDM symbols.

[0412] S2. The terminal device receives the AI ​​model configured by the network device through DCI signaling.

[0413] It should be noted that the network device can configure the AI ​​model for the terminal device through DCI signaling transmitted in the UE-specific search space. For example, the DCI signaling can be a DCI sent by the network device for model failure recovery response, or a DCI for scheduling PDSCH or PUSCH. Among them, the transmission of PDSCH or PUSCH can be based on the AI ​​model (not necessarily the configured AI model).

[0414] S3. The terminal device determines the time to start applying the AI ​​model configured on the network device based on the model application time reported in S1.

[0415] In one embodiment, the AI ​​model configured by the DCI signaling may be applied at the first time slot at least k OFDM symbols after the last OFDM symbol of the uplink channel carrying the HARQ-ACK information of the DCI, where k is the model application time (in units of OFDM symbols).

[0416] For example, referring to FIG6A , assuming that the last OFDM symbol of the uplink channel carrying the HARQ-ACK information of the DCI signaling is symbol m, the time when the AI ​​model starts to be applied is the first time slot after the time slot where symbol m+k is located.

[0417] In another embodiment, the AI ​​model configured by the DCI signaling may be applied at the first OFDM symbol at least k OFDM symbols after the last OFDM symbol of the uplink channel carrying the HARQ-ACK information of the DCI, where k is the model application time (in units of OFDM symbols).

[0418] For example, referring to FIG6N , assuming that the last OFDM symbol of the uplink channel carrying the HARQ-ACK information of the DCI is symbol m, the moment when the AI ​​model starts to be applied is the first symbol after symbol m+k, that is, symbol m+k+1.

[0419] It should also be noted that, in this embodiment, the moment when the AI ​​model starts to be applied and / or the model application time are parameters in time slots / OFDM units, and the corresponding time length / moment needs to be determined based on the subcarrier spacing, where different subcarrier spacings correspond to different time lengths.

[0420] Among them, the time when the AI ​​model configured by the network device starts to be applied and / or the model application time can be determined according to the subcarrier spacing of the BWP activated on the carrier of the AI ​​model.

[0421] If the AI ​​model is applied to multiple carriers and BWPs are activated on all of them, the AI ​​model application start time and / or model application time are determined based on the smallest subcarrier spacing among the BWPs activated on the multiple carriers. This allows network devices and terminal devices to determine a single application start time even in multi-carrier scenarios.

[0422] S4. After the AI ​​model starts to be applied, the terminal device uses the AI ​​model configured by the above DCI signaling to transmit information between the terminal device and the network device.

[0423] S5. After the AI ​​model starts to be applied, the network device uses the network side model corresponding to the AI ​​model configured by the above DCI signaling to transmit information between the terminal device.

[0424] To sum up, when corresponding dual-end AI models are used on the terminal device side and the network device side, if the model on the terminal device side is updated or reconfigured, the wireless communication method provided in the embodiment of the present application can ensure that the model application time on both sides is the same, and the network device and different terminals can synchronize model updates, thereby ensuring that the model output of the other end is available.

[0425] The preferred embodiments of the present application are described in detail above in conjunction with the accompanying drawings. However, the present application is not limited to the specific details in the above embodiments. Within the technical concept of the present application, the technical solution of the present application can be subjected to a variety of simple modifications, and these simple modifications all fall within the scope of protection of the present application. For example, the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the present application will no longer describe the various possible combinations separately. For another example, the various different embodiments of the present application can also be arbitrarily combined, as long as they do not violate the idea of ​​the present application, they should also be regarded as the contents disclosed in the present application. For another example, under the premise of no conflict, the various embodiments and / or the technical features in each embodiment described in the present application can be arbitrarily combined with the prior art, and the technical solution obtained after the combination should also fall within the scope of protection of the present application.

[0426] It should also be understood that in the various method embodiments of the present application, the sequence numbers of the above-mentioned processes do not imply a precedence in the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application. In addition, in the embodiments of the present application, the terms "downlink," "uplink," and "sidelink" are used to indicate the transmission direction of signals or data, where "downlink" is used to indicate the first direction of transmission of signals or data from a site to a user equipment in a cell, "uplink" is used to indicate the second direction of transmission of signals or data from a user equipment in a cell to a site, and "sidelink" is used to indicate the third direction of transmission of signals or data from user equipment 1 to user equipment 2. For example, "downlink signal" indicates that the transmission direction of the signal is the first direction. In addition, in the embodiments of the present application, the term "and / or" is merely a description of the association relationship between associated objects, indicating that three relationships can exist. Specifically, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this document generally indicates that the associated objects are in an "or" relationship.

[0427] FIG10 is a schematic diagram of the structure of a wireless communication device 1000 provided in an embodiment of the present application, which is applied to a terminal device. As shown in FIG10 , the wireless communication device 1000 includes:

[0428] A first determining unit 1001 is configured to determine a time to start applying the first AI model based on a model application time reported to the network device, or based on a model application time configured by the network device;

[0429] The first communication unit 1002 is configured to communicate with the network device using the first AI model after the moment.

[0430] In some embodiments, the model application time is any one of the following:

[0431] the time interval between the terminal device receiving the first information and the moment when the first AI model is applied;

[0432] The time interval between the terminal device sending the HARQ-ACK information of the first information and the moment when the first AI model is applied;

[0433] The time interval between when the terminal device receives the first information and when the terminal device sends feedback information obtained based on the first AI model;

[0434] The time interval between when the terminal device sends HARQ-ACK information of the first information and when the terminal device sends feedback information obtained based on the first AI model;

[0435] The first information is downlink information used to configure the first AI model, and the time interval is in units of time slots or OFDM symbols.

[0436] In some embodiments, the time when the first AI model starts to be applied is any one of the following:

[0437] The first time slot or the first OFDM symbol after the last OFDM symbol of the uplink channel carrying the HARQ-ACK information of the first information is k OFDM symbols;

[0438] The first time slot or the first OFDM symbol after the last OFDM symbol of the downlink channel carrying the first information is k OFDM symbols;

[0439] The first time slot after k time slots from the time slot in which the terminal device receives the first information;

[0440] The first time slot after k time slots, (k+3N) time slots, or max(k,3N) time slots from the time slot where the uplink channel of the HARQ-ACK information carrying the first information is located;

[0441] The first information is downlink information used to configure the first AI model, k is the model application time, and N is the number of time slots contained in 1ms.

[0442] In some embodiments, the wireless communication device 1000 further includes a receiving unit configured to receive first information, where the first information is downlink information for configuring the first AI model, wherein the first information includes one or more of the following:

[0443] identification information of the first AI model;

[0444] Functions of the first AI model;

[0445] The model structure of the first AI model; and

[0446] Model parameters of the first AI model.

[0447] In some embodiments, the model application time is any one of the following:

[0448] The time interval between the time when the terminal device sends the second information and the time when the first AI model is applied;

[0449] The time interval between the time when the terminal device sends the second information and the time when the terminal device sends the feedback information obtained based on the first AI model;

[0450] The time interval between the time when the terminal device receives the response information of the second information and the time when the first AI model is applied;

[0451] The time interval between when the terminal device receives the response information of the second information and when the terminal device sends the feedback information obtained based on the first AI model;

[0452] The second information is uplink information used to indicate the first AI model, and the time interval is in units of time slots or OFDM symbols.

[0453] In some embodiments, the time when the first AI model starts to be applied is any one of the following:

[0454] The first time slot or the first OFDM symbol after the last OFDM symbol of the uplink channel carrying the second information is k OFDM symbols;

[0455] The first time slot or the first OFDM symbol after the last OFDM symbol of the response information of the uplink channel carrying the second information starts k OFDM symbols;

[0456] The first time slot that is k time slots after the time slot in which the terminal device sends the second information;

[0457] The first time slot after k time slots, (k+3N) time slots, or max(k,3N) time slots from the time slot where the downlink channel carrying the response information of the second information is located;

[0458] The second information is uplink information used to indicate the first AI model, k is the model application time, and N is the number of time slots contained in 1ms.

[0459] In some embodiments, the wireless communication device 1000 further includes a sending unit configured to send second information, where the second information is uplink information indicating the first AI model;

[0460] The second information includes one or more of the following:

[0461] identification information of the first AI model;

[0462] a model function of the first AI model;

[0463] The model structure of the first AI model; and

[0464] Model parameters of the first AI model.

[0465] In some embodiments, the model application time reported to the network device includes one or more of the following:

[0466] model application time corresponding to each of the one or more AI models supported by the terminal device; wherein the one or more AI models supported by the terminal device include the first AI model;

[0467] The model application time corresponding to the one or more model functions supported by the terminal device; wherein the one or more model functions supported by the terminal device include the function of the first AI model;

[0468] The model application time corresponding to each of the one or more model update modes supported by the terminal device; wherein the one or more model update modes supported by the terminal device include the update mode of the first AI model;

[0469] The model application time corresponding to the one or more model types supported by the terminal device; wherein, the one or more model types supported by the terminal device include the type of the first AI model.

[0470] In some embodiments, the model updating method includes: updating model parameters and / or updating model structure.

[0471] In some embodiments, the model types include:

[0472] High-precision models and low-precision models; or, known models and unknown models.

[0473] In some embodiments, the moment when the first AI model starts to be applied and / or the model application time are determined according to any one of the following:

[0474] a subcarrier spacing of a downlink channel carrying the first information;

[0475] a subcarrier spacing of an uplink channel carrying second information;

[0476] a subcarrier spacing of an uplink channel carrying HARQ-ACK information of the first information;

[0477] a subcarrier spacing of a downlink channel carrying response information of the second information;

[0478] the subcarrier spacing of the BWP activated on the carrier to which the first AI model is applied;

[0479] The first information is downlink information used to configure the first AI model, and the second information is uplink information used to indicate the first AI model.

[0480] In some embodiments, the number of carriers to which the first AI model is applied is multiple,

[0481] The moment when the first AI model starts to be applied and / or the model application time is determined according to a first subcarrier spacing, where the first subcarrier spacing is the minimum subcarrier spacing among the BWPs respectively activated on multiple carriers to which the first AI model is applied.

[0482] In some embodiments, before the terminal device applies the first AI model, the terminal device transmits information with the network device based on a third AI model, or the terminal device transmits information with the network device not based on the AI ​​model;

[0483] The third AI model is a predefined AI model or a historical AI model.

[0484] FIG11 is a schematic diagram of the structure of a wireless communication device 1100 provided in an embodiment of the present application, which is applied to a network device. As shown in FIG11 , the wireless communication device 1100 includes:

[0485] The second determining unit 1101 is configured to determine a time point for starting application of the first AI model based on the model application time reported by the terminal device, or based on the model application time configured for the terminal device;

[0486] The second communication unit 1102 is configured to communicate with the terminal device using a second AI model corresponding to the first AI model after the moment.

[0487] In some embodiments, the model application time is any one of the following:

[0488] The time interval between the time when the terminal device receives the first information and the time when the first AI model is applied;

[0489] The time interval between the time when the terminal device sends HARQ-ACK information of the first information and the time when the first AI model is applied;

[0490] The time interval between when the terminal device receives the first information and when the terminal device sends feedback information obtained based on the first AI model;

[0491] The time interval between when the terminal device sends HARQ-ACK information of the first information and when the terminal device sends feedback information obtained based on the first AI model;

[0492] The first information is downlink information used to configure the first AI model, and the time interval is in units of time slots or OFDM symbols.

[0493] In some embodiments, the time when the first AI model starts to be applied is any one of the following:

[0494] The first time slot or the first OFDM symbol after the last OFDM symbol of the uplink channel carrying the HARQ-ACK information of the first information is k OFDM symbols;

[0495] The first time slot or the first OFDM symbol after the last OFDM symbol of the downlink channel carrying the first information is k OFDM symbols;

[0496] The first time slot after k time slots from the time slot in which the terminal device receives the first information;

[0497] The first time slot after k time slots, (k+3N) time slots, or max(k,3N) time slots from the time slot where the uplink channel of the HARQ-ACK information carrying the first information is located;

[0498] The first information is downlink information used to configure the first AI model, k is the model application time, and N is the number of time slots contained in 1ms.

[0499] In some embodiments, the wireless communication apparatus 1100 further includes a sending unit configured to send first information to the terminal device, where the first information is a downlink for configuring the first AI model, wherein the first information includes one or more of the following:

[0500] identification information of the first AI model;

[0501] Functions of the first AI model;

[0502] The model structure of the first AI model; and

[0503] Model parameters of the first AI model.

[0504] In some embodiments, the model application time is any one of the following:

[0505] The time interval between the time when the terminal device sends the second information and the time when the first AI model is applied;

[0506] The time interval between the time when the terminal device sends the second information and the time when the terminal device sends the feedback information obtained based on the first AI model;

[0507] The time interval between the time when the terminal device receives the response information of the second information and the time when the first AI model is applied;

[0508] The time interval between when the terminal device receives the response information of the second information and when the terminal device sends the feedback information obtained based on the first AI model;

[0509] The second information is uplink information used to indicate the first AI model, and the time interval is in units of time slots or OFDM symbols.

[0510] In some embodiments, the time when the first AI model starts to be applied is any one of the following:

[0511] The first time slot or the first OFDM symbol after the last OFDM symbol of the uplink channel carrying the second information is k OFDM symbols;

[0512] The first time slot or the first OFDM symbol after the last OFDM symbol of the response information of the uplink channel carrying the second information starts k OFDM symbols;

[0513] The first time slot that is k time slots after the time slot in which the terminal device sends the second information;

[0514] The first time slot after k time slots, (k+3N) time slots, or max(k,3N) time slots from the time slot where the downlink channel carrying the response information of the second information is located;

[0515] The second information is uplink information for indicating the first AI model, k is the model application time, and N is the number of time slots contained in 1ms.

[0516] In some embodiments, the wireless communication device 1100 further includes a receiving unit configured to receive second information sent by the terminal device, where the second information is uplink information indicating the first AI model;

[0517] The second information includes one or more of the following:

[0518] identification information of the first AI model;

[0519] a model function of the first AI model;

[0520] The model structure of the first AI model; and

[0521] Model parameters of the first AI model.

[0522] In some embodiments, the model application time reported by the terminal device includes one or more of the following:

[0523] model application time corresponding to each of the one or more AI models supported by the terminal device; wherein the one or more AI models supported by the terminal device include the first AI model;

[0524] The model application time corresponding to the one or more model functions supported by the terminal device; wherein the one or more model functions supported by the terminal device include the function of the first AI model;

[0525] The model application time corresponding to each of the one or more model update modes supported by the terminal device; wherein the one or more model update modes supported by the terminal device include the update mode of the first AI model;

[0526] The model application time corresponding to the one or more model types supported by the terminal device; wherein, the one or more model types supported by the terminal device include the type of the first AI model.

[0527] In some embodiments, the model updating method includes: updating model parameters and / or updating model structure.

[0528] In some embodiments, the model types include:

[0529] High-precision models and low-precision models; or, known models and unknown models.

[0530] In some embodiments, the model application time configured by the network device for the terminal device is determined based on the model application time reported by the terminal device.

[0531] In some embodiments, the duration of the model application time configured by the network device for the terminal device is greater than or equal to the duration of the model application time reported by the terminal device.

[0532] In some embodiments, the moment when the first AI model starts to be applied and / or the model application time are determined according to any one of the following:

[0533] a subcarrier spacing of a downlink channel carrying the first information;

[0534] a subcarrier spacing of an uplink channel carrying second information;

[0535] a subcarrier spacing of an uplink channel carrying HARQ-ACK information of the first information;

[0536] a subcarrier spacing of a downlink channel carrying response information of the second information;

[0537] the subcarrier spacing of the BWP activated on the carrier to which the first AI model is applied;

[0538] The first information is downlink information used to configure the first AI model, and the second information is uplink information used to indicate the first AI model.

[0539] In some embodiments, the number of carriers to which the first AI model is applied is multiple;

[0540] The moment when the first AI model starts to be applied and / or the model application time is determined according to a first subcarrier spacing, where the first subcarrier spacing is the minimum subcarrier spacing among the BWPs respectively activated on multiple carriers to which the first AI model is applied.

[0541] In some embodiments, before the network device applies the first AI model, the network device transmits information with the terminal device based on a fourth AI model corresponding to the third AI model, or the network device transmits information with the terminal device not based on the AI ​​model;

[0542] The third AI model is a predefined model or a historical AI model.

[0543] Those skilled in the art should understand that the relevant description of the above-mentioned wireless communication device in the embodiment of the present application can be understood with reference to the relevant description of the wireless communication method in the embodiment of the present application.

[0544] Figure 12 is a schematic diagram of a communication device 1200 provided in an embodiment of the present application. The communication device can be a terminal device or a network device. The communication device 1200 shown in Figure 12 includes a processor 1210, which can call and execute a computer program from a memory to implement the method in the embodiment of the present application.

[0545] Optionally, as shown in FIG12 , the communication device 1200 may further include a memory 1220. The processor 1210 may call and execute a computer program from the memory 1220 to implement the method in the embodiment of the present application.

[0546] The memory 1220 may be a separate device independent of the processor 1210 , or may be integrated into the processor 1210 .

[0547] Optionally, as shown in FIG12 , the communication device 1200 may further include a transceiver 1230 , and the processor 1210 may control the transceiver 1230 to communicate with other devices, specifically, to send information or data to other devices, or to receive information or data sent by other devices.

[0548] The transceiver 1230 may include a transmitter and a receiver. The transceiver 1230 may further include an antenna, and the number of antennas may be one or more.

[0549] Optionally, the communication device 1200 may specifically be a network device in an embodiment of the present application, and the communication device 1800 may implement the corresponding processes implemented by the network device in each method in the embodiment of the present application. For the sake of brevity, they will not be repeated here.

[0550] Optionally, the communication device 1200 may specifically be a mobile terminal / terminal device of an embodiment of the present application, and the communication device 1200 may implement the corresponding processes implemented by the mobile terminal / terminal device in each method of the embodiment of the present application. For the sake of brevity, they will not be repeated here.

[0551] Figure 13 is a schematic structural diagram of a chip according to an embodiment of the present application. The chip 1300 shown in Figure 13 includes a processor 1910, which can call and run a computer program from a memory to implement the method according to the embodiment of the present application.

[0552] Optionally, as shown in FIG13 , the chip 1300 may further include a memory 1320 , wherein the processor 1310 may call and execute a computer program from the memory 1320 to implement the method in the embodiment of the present application.

[0553] The memory 1320 may be a separate device independent of the processor 1310 , or may be integrated into the processor 1310 .

[0554] Optionally, the chip 1300 may further include an input interface 1330. The processor 1310 may control the input interface 1330 to communicate with other devices or chips, and specifically, may obtain information or data sent by other devices or chips.

[0555] Optionally, the chip 1300 may further include an output interface 1340. The processor 1310 may control the output interface 1340 to communicate with other devices or chips, and specifically, may output information or data to other devices or chips.

[0556] Optionally, the chip can be applied to the network device in the embodiments of the present application, and the chip can implement the corresponding processes implemented by the network device in each method of the embodiments of the present application. For the sake of brevity, they will not be repeated here.

[0557] Optionally, the chip can be applied to the mobile terminal / terminal device in the embodiments of the present application, and the chip can implement the corresponding processes implemented by the mobile terminal / terminal device in the various methods of the embodiments of the present application. For the sake of brevity, they will not be repeated here.

[0558] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0559] An embodiment of the present application further provides a computer storage medium, which stores one or more programs. The one or more programs can be executed by one or more processors to implement the method in the embodiment of the present application.

[0560] FIG14 is a schematic block diagram of a communication system 1400 provided in an embodiment of the present application. As shown in FIG14 , the communication system 1400 includes a terminal device 1410 and a network device 1420 .

[0561] Among them, the terminal device 1410 can be used to implement the corresponding functions implemented by the terminal device in the above method, and the network device 1420 can be used to implement the corresponding functions implemented by the network device in the above method. For the sake of brevity, they are not repeated here.

[0562] It should be understood that the processor of the embodiments of the present application may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method embodiment can be completed by hardware integrated logic circuits in the processor or software instructions. The above processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. The various methods, steps, and logic block diagrams disclosed in the embodiments of the present application can be implemented or executed. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in the embodiments of the present application can be directly embodied as being executed by a hardware decoding processor, or can be executed by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium mature in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The storage medium is located in the memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware.

[0563] It is understood that the memory in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct RAM bus random access memory (DR RAM). It should be noted that the memory of the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0564] It should be understood that the above-mentioned memories are exemplary but not restrictive. For example, the memories in the embodiments of the present application may also be static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct RAM RAM (DR RAM), etc. In other words, the memories in the embodiments of the present application are intended to include, but are not limited to, these and any other suitable types of memories.

[0565] An embodiment of the present application also provides a computer-readable storage medium for storing a computer program.

[0566] Optionally, the computer-readable storage medium can be applied to the network device in the embodiments of the present application, and the computer program enables the computer to execute the corresponding processes implemented by the network device in the various methods of the embodiments of the present application. For the sake of brevity, they are not repeated here.

[0567] Optionally, the computer-readable storage medium can be applied to the mobile terminal / terminal device in the embodiments of the present application, and the computer program enables the computer to execute the corresponding processes implemented by the mobile terminal / terminal device in the various methods of the embodiments of the present application. For the sake of brevity, they will not be repeated here.

[0568] An embodiment of the present application also provides a computer program product, including computer program instructions.

[0569] Optionally, the computer program product can be applied to the network device in the embodiments of the present application, and the computer program instructions enable the computer to execute the corresponding processes implemented by the network device in the various methods of the embodiments of the present application. For the sake of brevity, they are not repeated here.

[0570] Optionally, the computer program product can be applied to the mobile terminal / terminal device in the embodiments of the present application, and the computer program instructions enable the computer to execute the corresponding processes implemented by the mobile terminal / terminal device in the various methods of the embodiments of the present application. For the sake of brevity, they will not be repeated here.

[0571] The embodiment of the present application also provides a computer program.

[0572] Optionally, the computer program can be applied to the network device in the embodiments of the present application. When the computer program runs on a computer, the computer executes the corresponding processes implemented by the network device in the various methods of the embodiments of the present application. For the sake of brevity, they are not described here.

[0573] Optionally, the computer program can be applied to the mobile terminal / terminal device in the embodiments of the present application. When the computer program runs on the computer, the computer executes the corresponding processes implemented by the mobile terminal / terminal device in the various methods of the embodiments of the present application. For the sake of brevity, they will not be repeated here.

[0574] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0575] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0576] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0577] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0578] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0579] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0580] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A wireless communication method, the method comprising: The terminal device determines the time when the first AI model starts to be applied according to the model application time reported to the network device, or according to the model application time configured by the network device; After the moment, the terminal device uses the first AI model to communicate with the network device.

2. The method according to claim 1, wherein: The model application time is any one of the following: The time interval between when the terminal device receives the first information and when the first AI model is applied; The time interval between when the terminal device sends HARQ-ACK information of the first information and when the first AI model is applied; The time interval between when the terminal device receives the first information and when the terminal device sends feedback information obtained based on the first AI model; The time interval between when the terminal device sends HARQ-ACK information of the first information and when the terminal device sends feedback information obtained based on the first AI model; The first information is downlink information used to configure the first AI model, and the time interval is in units of time slots or OFDM symbols.

3. The method according to claim 1 or 2, wherein: The time when the first AI model starts to be applied is any one of the following: The first time slot or the first OFDM symbol after the last OFDM symbol of the uplink channel of the HARQ-ACK information carrying the first information starts k OFDM symbols; The first time slot or the first OFDM symbol after the last OFDM symbol of the downlink channel carrying the first information starts k OFDM symbols; The first time slot after the time slot where the terminal device receives the first information starts with k time slots; The first time slot after k time slots, (k+3N) time slots, or max(k,3N) time slots from the time slot where the uplink channel of the HARQ-ACK information carrying the first information is located; Among them, the first information is downlink information used to configure the first AI model, k is the model application time, and N is the number of time slots contained in 1ms.

4. The method according to claim 2 or 3, wherein: The method further comprises: The terminal device receives first information, where the first information is downlink information for configuring the first AI model. The first information includes one or more of the following: identification information of the first AI model; a model function of the first AI model; the model structure of the first AI model; and Model parameters of the first AI model.

5. The method according to claim 1, wherein: The model application time is any one of the following: The time interval between when the terminal device sends the second information and when the first AI model is applied; The time interval between when the terminal device sends the second information and when the terminal device sends the feedback information obtained based on the first AI model; The time interval between when the terminal device receives the response information of the second information and when the first AI model is applied; The time interval between when the terminal device receives the response information of the second information and when the terminal device sends the feedback information obtained based on the first AI model; The second information is uplink information used to indicate the first AI model, and the time interval is in units of time slots or OFDM symbols.

6. The method according to claim 1 or 5, wherein: The time when the first AI model starts to be applied is any one of the following: The first time slot or the first OFDM symbol after the last OFDM symbol of the uplink channel carrying the second information starts k OFDM symbols; The first time slot or the first OFDM symbol after the last OFDM symbol of the response information of the uplink channel carrying the second information starts k OFDM symbols; The first time slot after k time slots from the time slot where the terminal device sends the second information; The first time slot after k time slots, (k+3N) time slots, or max(k,3N) time slots from the time slot where the downlink channel carrying the response information of the second information is located; The second information is uplink information used to indicate the first AI model, k is the model application time, and N is the number of time slots contained in 1ms.

7. The method according to claim 5 or 6, wherein: The method further comprises: The terminal device sends second information, where the second information is uplink information used to indicate the first AI model; The second information includes one or more of the following: identification information of the first AI model; a model function of the first AI model; the model structure of the first AI model; and Model parameters of the first AI model.

8. The method according to any one of claims 1 to 7, wherein: The model application time reported to the network device includes one or more of the following: model application time corresponding to one or more AI models supported by the terminal device; wherein the one or more AI models supported by the terminal device include the first AI model; the model application time corresponding to the one or more model functions supported by the terminal device; wherein the one or more model functions supported by the terminal device include the function of the first AI model; the model application time corresponding to the one or more model update modes supported by the terminal device; wherein the one or more model update modes supported by the terminal device include the update mode of the first AI model; The model application time corresponding to the one or more model types supported by the terminal device; wherein, the one or more model types supported by the terminal device include the type of the first AI model.

9. The method according to claim 8, wherein: The model updating method includes: updating model parameters and / or updating model structure.

10. The method according to claim 8 or 9, wherein: The model types include: High-precision models and low-precision models; or, known models and unknown models.

11. The method according to any one of claims 1 to 10, wherein: The moment when the first AI model starts to be applied and / or the model application time are determined according to any one of the following: a subcarrier spacing of a downlink channel carrying the first information; a subcarrier spacing of an uplink channel carrying second information; a subcarrier spacing of an uplink channel carrying HARQ-ACK information of the first information; The subcarrier spacing of the downlink channel carrying the response information of the second information; The subcarrier spacing of the BWP activated on the carrier to which the first AI model is applied; The first information is downlink information used to configure the first AI model, and the second information is uplink information used to indicate the first AI model.

12. The method according to claim 11, wherein: The number of carriers to which the first AI model is applied is multiple, The moment when the first AI model starts to be applied and / or the model application time is determined according to a first subcarrier spacing, where the first subcarrier spacing is the smallest subcarrier spacing among the BWPs respectively activated on multiple carriers to which the first AI model is applied.

13. The method according to any one of claims 1 to 12, wherein: Before the terminal device applies the first AI model, the terminal device transmits information with the network device based on a third AI model, or the terminal device transmits information with the network device not based on the AI ​​model; The third AI model is a predefined AI model or a historical AI model.

14. A wireless communication method, the method comprising: The network device determines the time when the first AI model starts to be applied according to the model application time reported by the terminal device, or according to the model application time configured for the terminal device; After the moment, the network device uses the second AI model corresponding to the first AI model to communicate with the terminal device.

15. The method according to claim 14, wherein: The model application time is any one of the following: The time interval between when the terminal device receives the first information and when the first AI model is applied; The time between when the terminal device sends the HARQ-ACK information of the first information and when the first AI model is applied interval; The time interval between when the terminal device receives the first information and when the terminal device sends feedback information obtained based on the first AI model; The time interval between when the terminal device sends HARQ-ACK information of the first information and when the terminal device sends feedback information obtained based on the first AI model; The first information is downlink information used to configure the first AI model, and the time interval is in units of time slots or OFDM symbols.

16. The method according to claim 14 or 15, wherein: The time when the first AI model starts to be applied is any one of the following: The first time slot or the first OFDM symbol after the last OFDM symbol of the uplink channel of the HARQ-ACK information carrying the first information starts k OFDM symbols; The first time slot or the first OFDM symbol after the last OFDM symbol of the downlink channel carrying the first information starts k OFDM symbols; The first time slot after the time slot where the terminal device receives the first information starts with k time slots; The first time slot after k time slots, (k+3N) time slots, or max(k,3N) time slots from the time slot where the uplink channel of the HARQ-ACK information carrying the first information is located; Among them, the first information is downlink information used to configure the first AI model, k is the model application time, and N is the number of time slots contained in 1ms.

17. The method according to claim 15 or 16, wherein: The method further comprises: The network device sends first information to the terminal device, where the first information is a downlink for configuring the first AI model, wherein the first information includes one or more of the following: identification information of the first AI model; Functions of the first AI model; the model structure of the first AI model; and Model parameters of the first AI model.

18. The method according to claim 14, wherein: The model application time is any one of the following: The time interval between when the terminal device sends the second information and when the first AI model is applied; The time interval between when the terminal device sends the second information and when the terminal device sends the feedback information obtained based on the first AI model; The time interval between when the terminal device receives the response information of the second information and when the first AI model is applied; The time interval between when the terminal device receives the response information of the second information and when the terminal device sends the feedback information obtained based on the first AI model; The second information is uplink information used to indicate the first AI model, and the time interval is in units of time slots or OFDM symbols.

19. The method according to claim 14 or 18, wherein: The time when the first AI model starts to be applied is any one of the following: The first time slot or the first OFDM symbol after the last OFDM symbol of the uplink channel carrying the second information starts k OFDM symbols; The first time slot or the first OFDM symbol after the last OFDM symbol of the response information of the uplink channel carrying the second information starts k OFDM symbols; The first time slot after k time slots from the time slot where the terminal device sends the second information; The first time slot after k time slots, (k+3N) time slots, or max(k,3N) time slots from the time slot where the downlink channel carrying the response information of the second information is located; The second information is uplink information used to indicate the first AI model, k is the model application time, and N is the number of time slots contained in 1ms.

20. The method according to claim 18 or 19, wherein: The method further comprises: The network device receives second information sent by the terminal device, where the second information is uplink information for indicating the first AI model; The second information includes one or more of the following: identification information of the first AI model; a model function of the first AI model; the model structure of the first AI model; and Model parameters of the first AI model.

21. The method according to any one of claims 14 to 20, wherein: The model application time reported by the terminal device includes one or more of the following: model application time corresponding to one or more AI models supported by the terminal device; wherein the one or more AI models supported by the terminal device include the first AI model; the model application time corresponding to the one or more model functions supported by the terminal device; wherein the one or more model functions supported by the terminal device include the function of the first AI model; the model application time corresponding to the one or more model update modes supported by the terminal device; wherein the one or more model update modes supported by the terminal device include the update mode of the first AI model; The model application time corresponding to the one or more model types supported by the terminal device; wherein, the one or more model types supported by the terminal device include the type of the first AI model.

22. The method according to claim 21, wherein: The model updating method includes: updating model parameters and / or updating model structure.

23. The method according to claim 21 or 22, wherein: The model types include: High-precision models and low-precision models; or, known models and unknown models.

24. The method according to any one of claims 14 to 23, wherein: The model application time configured by the network device for the terminal device is determined based on the model application time reported by the terminal device.

25. The method according to any one of claims 14 to 24, wherein: The duration of the model application time configured by the network device for the terminal device is greater than or equal to the duration of the model application time reported by the terminal device.

26. The method according to any one of claims 14 to 25, wherein: The moment when the first AI model starts to be applied and / or the model application time are determined according to any one of the following: a subcarrier spacing of a downlink channel carrying the first information; a subcarrier spacing of an uplink channel carrying second information; a subcarrier spacing of an uplink channel carrying HARQ-ACK information of the first information; The subcarrier spacing of the downlink channel carrying the response information of the second information; The subcarrier spacing of the BWP activated on the carrier to which the first AI model is applied; The first information is downlink information used to configure the first AI model, and the second information is uplink information used to indicate the first AI model.

27. The method according to claim 26, wherein: The number of carriers to which the first AI model is applied is multiple; The moment when the first AI model starts to be applied and / or the model application time is determined according to a first subcarrier spacing, where the first subcarrier spacing is the smallest subcarrier spacing among the BWPs respectively activated on multiple carriers to which the first AI model is applied.

28. The method according to any one of claims 14 to 27, wherein: Before the network device applies the first AI model, the network device transmits information with the terminal device based on a fourth AI model corresponding to the third AI model, or the network device transmits information with the terminal device not based on the AI ​​model; The third AI model is a predefined model or a historical AI model.

29. A wireless communication device, applied to a terminal device, the device comprising: A first determining unit is configured to determine a time when the first AI model starts to be applied according to the model application time reported to the network device, or according to the model application time configured by the network device; The first communication unit is configured to communicate with the network device using the first AI model after the moment.

30. A wireless communication device, applied to a network device, comprising: A second determining unit is configured to determine a time when the first AI model starts to be applied according to the model application time reported by the terminal device, or according to the model application time configured for the terminal device; The second communication unit is configured to communicate with the terminal device using a second AI model corresponding to the first AI model after the moment.

31. A terminal device, comprising: A memory for storing computer executable instructions; A processor, connected to the memory, configured to implement the method according to any one of claims 1 to 13 by executing the computer executable instructions.

32. A network device comprising: A memory for storing computer executable instructions; A processor, connected to the memory, configured to implement the method of any one of claims 14 to 28 by executing the computer executable instructions.

33. A chip, comprising: A processor, configured to call and run a computer program from a memory, so that a device equipped with the chip executes a method as claimed in any one of claims 1 to 13, or executes a method as claimed in any one of claims 14 to 28.

34. A computer-readable storage medium storing a computer program, wherein the computer program, when executed by at least one processor, implements the method according to any one of claims 1 to 13, or implements the method according to any one of claims 14 to 28.

35. A computer program product, comprising a computer storage medium storing a computer program, wherein the computer program comprises instructions executable by at least one processor, and when the instructions are executed by the at least one processor, the method according to any one of claims 1 to 13 is implemented, or the method according to any one of claims 14 to 28 is implemented.

36. A computer program, the computer program causing a computer to execute the method according to any one of claims 1 to 13, or to implement the method according to any one of claims 14 to 28.

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