Terminal, wireless communication method, and base station

Abstract

A terminal according to an aspect of the present disclosure comprises: a transmission / reception unit that performs transmission of information related to a period related to offline engineering and reception of an instruction related to execution of the offline engineering; and a control unit that executes activation of a model on the basis of at least one of the information and the instruction. According to the aspect of the present disclosure, it is possible to achieve favorable overhead reduction / channel estimation / resource utilization.

Description

Terminal, wireless communication method and base station

[0001] The present disclosure relates to a terminal, a wireless communication method, and a base station in a next-generation mobile communication system.

[0002] Long Term Evolution (LTE) has been specified for the Universal Mobile Telecommunications System (UMTS) network with the aim of achieving higher data rates and lower latency (Non-Patent Document 1). Also, LTE-Advanced (3GPP Rel. 10-14) has been specified with the aim of achieving higher capacity and more advanced features than LTE (Third Generation Partnership Project (3GPP (registered trademark)) Release (Rel.) 8, 9).

[0003] Successor systems to LTE (e.g., 5th generation mobile communication system (5G), 5G+ (plus), 6th generation mobile communication system (6G), New Radio (NR), 3GPP Rel. 15 or later, etc.) are also being considered.

[0004] 3GPP TS 36.300 V8.12.0 “Evolved Universal Terrestrial Radio Access (E-UTRA) and Evolved Universal Terrestrial Radio Access Network (E-UTRAN); Overall description; Stage 2 (Release 8)”, April 2010

[0005] Regarding future wireless communication technologies, the use of artificial intelligence (AI) technologies such as machine learning (ML) for network / device control and management is being considered.

[0006] When utilizing an AI model, a scenario is envisioned in which, when a corresponding (paired) model between the UE and the NW is used, information about the model is shared from the NW to the UE.

[0007] In this scenario, when the UE receives information about the model, it may require a certain amount of time for processing (e.g., offline engineering) before the model can be applied / used.

[0008] However, the processing time and the use of the model have not been sufficiently considered, and if this consideration is insufficient, it may not be possible to achieve suitable overhead reduction / channel estimation / resource utilization by utilizing AI / ML, which may hinder improvements in communication throughput / communication quality.

[0009] Therefore, one of the objects of the present disclosure is to provide a terminal, a wireless communication method, and a base station that can achieve suitable overhead reduction / channel estimation / resource utilization.

[0010] A terminal according to one aspect of the present disclosure has a transceiver unit that transmits information regarding a period related to offline engineering and receives instructions regarding the execution of offline engineering, and a control unit that activates a model based on at least one of the information and the instructions.

[0011] According to one aspect of the present disclosure, it is possible to achieve favorable overhead reduction / channel estimation / resource utilization.

[0012] FIG. 1 illustrates an example of a framework for managing AI models. FIG. 2 illustrates an example of specifying an AI model. FIG. 3 illustrates an example of an ORAN architecture. FIG. 4 illustrates an example of AI-based CSI feedback. FIG. 5 illustrates an example of processing when a UE has a decoder. FIG. 6 illustrates an example of CSI reconstruction using a proxy model. FIG. 7A illustrates an example of generating an existing NR codebook. FIG. 7B illustrates an example of signal generation according to Option 1. FIG. 7C illustrates an example of signal reconstruction according to Option 1. FIG. 8 illustrates an example of signal generation / signal reconstruction according to Option 3a-1. FIG. 9 illustrates an example of signal generation / signal reconstruction according to Option 3a-2. FIG. 10 illustrates an example of signal generation / signal reconstruction according to Option 3a-3. FIG. 11 illustrates an example of signal generation / signal reconstruction according to Option 3b. FIG. 12 illustrates an example of signal generation / signal reconstruction according to Option 5a-1. FIG. 13 illustrates an example of signal generation / signal reconstruction according to Option 5a-2. FIG. 14 is a diagram showing an example of signal generation / signal reconfiguration according to option 5a-3. FIG. 15 is a diagram showing an example of signal generation / signal reconfiguration according to option 5b. FIG. 16 is a diagram showing an example of a schematic configuration of a wireless communication system according to an embodiment. FIG. 17 is a diagram showing an example of a configuration of a base station according to an embodiment. FIG. 18 is a diagram showing an example of a configuration of a user terminal according to an embodiment. FIG. 19 is a diagram showing an example of hardware configurations of a base station and a user terminal according to an embodiment. FIG. 20 is a diagram showing an example of a vehicle according to an embodiment.

[0013] (Application of Artificial Intelligence (AI) Technology to Wireless Communications) With regard to future wireless communications technologies, the use of AI technology such as machine learning (ML) for network / device control and management is being considered.

[0014] For example, it is being considered that terminals (user terminals, user equipment (UE)) / base stations (BSs) will utilize AI technology to improve Channel State Information (CSI) feedback (e.g., reduced overhead, improved accuracy, prediction), improve beam management (e.g., improved accuracy, prediction in the time / space domain), and improve position measurement (e.g., improved position estimation / prediction).

[0015] Based on the input information, the AI ​​model may output at least one information such as an estimate, a prediction, a selected action, a classification, etc. The UE / BS may input channel state information, reference signal measurements, etc. to the AI ​​model and output highly accurate channel state information / measurements / beam selection / location, future channel state information / radio link quality, etc.

[0016] In the present disclosure, AI may be interpreted as an object (also called a subject, object, data, function, program, etc.) that has (performs) at least one of the following characteristics: - Estimation based on observed or collected information; - Selection based on observed or collected information; - Prediction based on observed or collected information.

[0017] In the present disclosure, estimation, prediction, and inference may be used interchangeably. Also, in the present disclosure, estimate, predict, and infer may be used interchangeably.

[0018] In the present disclosure, an object may be, for example, an apparatus, device, etc., such as a UE or a BS. Also, in the present disclosure, an object may correspond to a program / model / entity that operates in the apparatus.

[0019] Also, in the present disclosure, an AI model may be interpreted as an object that has (performs) at least one of the following characteristics: - Generates an estimate by feeding information; - Predicts an estimate by feeding information; - Discovers features by feeding information; - Selects an action by feeding information.

[0020] Additionally, in this disclosure, an AI model may refer to a data-driven algorithm that applies AI techniques to generate a set of outputs based on a set of inputs.

[0021] In addition, in the present disclosure, the terms AI model, model, ML model, predictive analytics, predictive analysis model, tool, autoencoder, encoder, decoder, neural network model, AI algorithm, scheme, etc. may be interchangeable. The AI ​​model may be derived using at least one of regression analysis (e.g., linear regression analysis, multiple regression analysis, logistic regression analysis), support vector machine, random forest, neural network, deep learning, etc.

[0022] In this disclosure, the term "autoencoder" may be interchangeably referred to as any autoencoder, such as a stacked autoencoder, a convolutional autoencoder, etc. The encoder / decoder of this disclosure may employ a model such as a Residual Network (ResNet), a DenseNet, or a RefineNet.

[0023] Furthermore, in the present disclosure, the terms encoder, encoding, encode / encoded, modification / alteration / control by an encoder, compressing, compress / compressed, generating, generate / generated, etc. may be read interchangeably.

[0024] In addition, in the present disclosure, decoder, decoding, decode / decoded, modification / alteration / control by decoder, decompressing, decompress / decompressed, reconstructing, reconstruct / reconstructed, etc. may be read interchangeably.

[0025] In the present disclosure, a layer (of an AI model) may be interchangeably read as a layer (such as an input layer or an intermediate layer) used in the AI ​​model. The layer in the present disclosure may correspond to at least one of an input layer, an intermediate layer, an output layer, a batch normalization layer, a convolutional layer, an activation layer, a dense layer, a normalization layer, a pooling layer, an attention layer, a dropout layer, a fully connected layer, etc.

[0026] In this disclosure, methods for training an AI model may include supervised learning, unsupervised learning, reinforcement learning, federated learning, etc. Supervised learning may refer to the process of training a model from inputs and corresponding labels. Unsupervised learning may refer to the process of training a model without labeled data. Reinforcement learning may refer to the process of training a model from inputs (i.e., states) and feedback signals (i.e., rewards) resulting from the model's outputs (i.e., actions) in an environment with which the model interacts.

[0027] In the present disclosure, terms such as generate, calculate, derive, etc. may be interchangeable. In the present disclosure, terms such as implement, operate, operate, execute, etc. may be interchangeable. In the present disclosure, terms such as train, learn, update, retrain, etc. may be interchangeable. In the present disclosure, terms such as infer, after-training, live use, actual use, etc. may be interchangeable. In the present disclosure, signal may be interchangeable with signal / channel.

[0028] FIG. 1 is a diagram illustrating an example of a framework for managing AI models. In this example, each stage related to an AI model is shown as a block. This example is also referred to as AI model life cycle management (LCM).

[0029] The data collection stage corresponds to a stage of collecting data for generating / updating an AI model. The data collection stage may include data organization (e.g., determining which data to transfer for model training / model inference), data transfer (e.g., transferring data to an entity (e.g., UE, gNB) that performs model training / model inference), etc.

[0030] Note that data collection may refer to a process in which data is collected by a network node, a management entity, or a UE for the purpose of AI model training / data analysis / inference. In this disclosure, the terms "process" and "procedure" may be interchangeable. Also, in this disclosure, collection may refer to obtaining a data set (e.g., usable as input / output) for AI model training / inference based on measurements (e.g., channel measurements, beam measurements, radio link quality measurements, position estimation, etc.).

[0031] In the present disclosure, offline field data may be data collected from the field (real world) and used for offline training of an AI model. Also, in the present disclosure, online field data may be data collected from the field (real world) and used for online training of an AI model.

[0032] In the model training stage, model training is performed based on the data (training data) transferred from the collection stage. This stage may include data preparation (e.g., performing data preprocessing, cleaning, formatting, transformation, etc.), model training / validation, model testing (e.g., verifying whether the trained model meets a performance threshold), model exchange (e.g., transferring the model for distributed learning), and model deployment / update (deploying / updating the model to the entity that will perform model inference).

[0033] It should be noted that AI model training may refer to a process for training an AI model in a data-driven manner and obtaining a trained AI model for inference.

[0034] AI model validation may also refer to a sub-process of training that evaluates the quality of an AI model using a dataset different from the dataset used to train the model, which helps select model parameters that generalize beyond the dataset used to train the model.

[0035] AI model testing may also refer to a sub-process of training for evaluating the performance of the final AI model using a dataset different from that used for model training / validation. Note that, unlike validation, testing does not necessarily require subsequent model tuning.

[0036] In the model inference stage, model inference is performed based on the data (inference data) transferred from the collection stage. This stage may include data preparation (e.g., performing data preprocessing, cleaning, formatting, transformation, etc.), model inference, model monitoring (e.g., monitoring the performance of model inference), model performance feedback (feeding back model performance to the entity training the model), and output (providing model output to the actor).

[0037] Additionally, AI model inference may refer to the process of using a trained AI model to produce a set of outputs from a set of inputs.

[0038] Also, a UE side model may refer to an AI model whose inference is performed entirely in the UE, and a network side model may refer to an AI model whose inference is performed entirely in the network (e.g., gNB).

[0039] Also, a one-sided model may refer to a UE-side model or a network-side model. A two-sided model may refer to a pair of AI models in which joint inference is performed. Here, joint inference may include AI inference in which the inference is performed jointly across the UE and the network, e.g., a first part of the inference may be performed first by the UE and the remaining part by the gNB (or vice versa).

[0040] In addition, AI model monitoring may refer to a process for monitoring the inference performance of an AI model, and may be interchangeably read as model performance monitoring, performance monitoring, etc.

[0041] Note that model registration may refer to assigning a version identifier to a model and making the model executable (registering) the model by compiling it into the specific hardware used in the inference stage. Also, model deployment may refer to distributing (or activating in) a runtime image (or an image of an execution environment) of a fully developed and tested model to (or enabling in) a target (e.g., UE / gNB) where inference will be performed.

[0042] An actor stage may include action triggers (e.g., deciding whether to trigger an action on another entity), feedback (e.g., feeding back information needed for training data / inference data / performance feedback), etc.

[0043] For example, training of a model for mobility optimization may be performed in, for example, Operation, Administration and Maintenance (Management) (OAM) / gNodeB (gNB) in a network (NW). In the former case, interoperability, large-capacity storage, operator manageability, and model flexibility (feature engineering, etc.) are advantageous. In the latter case, the latency of model updates and the need for data exchange for model deployment are advantageous. Inference of the above model may be performed in, for example, a gNB.

[0044] The entity that performs training / inference may vary depending on the use case (i.e., the functionality of the AI ​​model), which may include beam management, beam prediction, autoencoder (or information compression), CSI feedback, positioning, etc.

[0045] For example, for AI-assisted beam management based on measurement reports, the OAM / gNB may perform model training and the gNB may perform model inference.

[0046] For AI-assisted UE-assisted positioning, a Location Management Function (LMF) may perform model training and the LMF may perform model inference.

[0047] For CSI feedback / channel estimation using an autoencoder, the OAM / gNB / UE may perform model training and the gNB / UE may perform model inference (jointly).

[0048] For AI-assisted beam management or AI-assisted UE-based positioning based on beam measurements, the OAM / gNB / UE may perform model training and the UE may perform model inference.

[0049] Note that model activation may refer to activating an AI model for a specific functionality, model deactivation may refer to disabling an AI model for a specific functionality, and model switching may refer to deactivating a currently active AI model for a specific functionality and activating a different AI model.

[0050] Model transfer may also refer to distributing an AI model over the air interface. This distribution may include distributing parameters of a model structure already known at the receiving end, or a new model with parameters, or both. This distribution may include a complete model or a partial model. Model download may refer to transferring a model from the network to the UE. Model upload may refer to transferring a model from the UE to the network.

[0051] 2 is a diagram showing an example of specifying an AI model. In this example, a UE and a NW (e.g., a base station (BS)) can recognize models #1 and #2 (although they do not need to fully understand the details of the models). The UE may report, for example, the capabilities of model #1 and model #2 to the NW, and the NW may instruct the UE on the AI ​​model to use.

[0052] (Open RAN (ORAN)) The ORAN architecture will be described below with reference to FIG.

[0053] In 5G NR, standardization of Open RAN (ORAN) is being considered to reduce the burden on operators in building and operating RAN and to introduce automation using AI / ML models.

[0054] In conventional closed networks, the radio units (RU) that make up a base station and the distributed units (DU) / central units (CU) cannot be connected to each other if they are from the same vendor.

[0055] On the other hand, ORAN allows interconnection of equipment from multiple vendors (e.g., RUs and CUs / DUs), enabling a more scalable and flexible RAN configuration, which can support new services / industries, diversifying requirements, etc.

[0056] In the ORAN architecture, in order to realize network operation utilizing the AI / ML model, a RAN Intelligent Controller (RIC) may be defined as a logical node that automates and optimizes the parameter design / configuration / operation of base stations.

[0057] As shown in the figure, the RIC may include a non-real-time RIC and a near real-time RIC (which may simply be called a real-time RIC).

[0058] The non-real-time RIC may be controlled in seconds and may be located within Service Management and Orchestration (SMO), which monitors, maintains, and orchestrates the RAN.

[0059] The non-real-time RIC may be connected to the near real-time RIC via an A1 interface.

[0060] The near real-time RIC may be controlled in milliseconds and may be connected to E2 nodes such as an O-eNB (ORAN base station), an O-CU (Open Central Unit), and an O-DU (Open Distributed Unit) via an E2 interface. The SMO may be connected to the O-eNB, the O-CU, and the O-DU via an O1 interface.

[0061] The non-real-time RIC may cooperate with a functional unit that provides OAM services within the SMO to collect data accumulated within the E2 node, such as performance management counters, fault management data, and trace management data.

[0062] The near real-time RIC may collect information about the E2 node from the E2 node using the E2 interface, and may control the E2 node according to a policy notified by the non-real-time RIC.

[0063] The ORAN architecture shown in the figure is merely an example and is not limited to this example.

[0064] (AI-based CSI feedback) As a representative sub-use case, space-frequency domain CSI compression using a two-sided AI model is being considered.

[0065] 4 is a diagram showing an example of AI-based CSI feedback. The UE performs pre-processing, AI / ML-based CSI generation, and post-processing on CSI measurement results, etc., and transmits encoded bits (CSI feedback information) to the NW (base station). The NW (base station) performs pre-processing, AI / ML-based CSI reconstruction, and post-processing on the received bits to obtain CSI (channel / precoding matrix).

[0066] <CSI Reconstruction in UE> Figure 5 is a diagram showing an example of processing when the UE has a decoder. If the UE has the same decoder as the base station, it can use reconstructed CSI in pre-processing. Note that the pre-processing may use, for example, svd+IDFT transform. The UE can monitor the accuracy of the model by comparing the target CSI (CSI (W, H) without error due to CSI compression) with the reconstructed CSI (W', H') as shown in Figure 5. The UE can report rank information and channel quality indication information based on the reconstructed CSI.

[0067] However, CSI reconstruction in the UE has two issues: (1) UE processing for CSI reconstruction is added, and model storage of the reconstruction model (decoder) in addition to the generation model (encoder) is required; and (2) intellectual property rights issues. Base station (gNB) vendors may consider model information to be their own intellectual property and may not want to disclose generation model information to UE vendors.

[0068] The UE can use a proxy model to calculate the expected reconstructed CSI instead of the reconstruction model actually used by the base station. The proxy model is a model that mimics the reconstruction model used by the base station. The proxy model can be a simple model. This can alleviate the UE processing and storage problem ((1) above). The proxy model can be different from the actual reconstruction model at the base station. This can avoid the uniqueness problem ((2) above).

[0069] FIG. 6 is a diagram showing an example of CSI reconstruction (pseudo-reconstruction) using a proxy model. The UE receives a proxy model for decoding from a NW (base station). The UE uses the proxy model to reconstruct encoded CSI and outputs it as an estimated CSI. The UE maps the estimated result to actual CSI and calculates a Key Performance Indicator (KPI) (e.g., squared generalized cosine similarity (SGCS)). There is a significant correlation between the KPI (SGCS) when an actual decoder such as the example of FIG. 5 is used and the KPI (SGCS) when a proxy model such as the example of FIG. 6 is used.

[0070] (Analysis) In future wireless communication systems (e.g., Rel. 19 and later), the introduction of at least one of the following options 1 to 5 is being considered as a scheme for inter-vendor collaboration: Option 1: Fully standardized model. Option 2: Standardized dataset. Option 3: Standardized reference model structure + parameter exchange between NW-side and UE-side. Option 4: Standardized data / dataset format + dataset exchange between NW-side and UE-side. Option 5: Standardized data / dataset format + reference model exchange between NW-side and UE-side.

[0071] Of these, option 1 may mean that the structure and parameters of the models used are standardized / specified.

[0072] Standardizing and specifying the models used, as in Option 1, is believed to contribute to reducing the complexity of collaboration between vendors.

[0073] These options can be suitably used when operating a two-sided model, regardless of whether they are applied in a vendor collaboration. In a two-sided model, model pairing is performed on the network side and the user equipment side, but by specifying at least one of the models, the pairing operation can be facilitated. Each embodiment of the present disclosure can also be applied regardless of whether it is applied in a vendor collaboration.

[0074] For example, in option 1, the structure / parameters of the model are specified, which not only eliminates the need for a model determination / pairing procedure between the UE and the NW, but also makes it easier to test the model.

[0075] 7A is a diagram illustrating an example of generating an existing NR codebook. As shown in FIG. 7A, in the existing NR, the feedback content (i １ , i ２ ) from which a precoding matrix is ​​generated according to the specification.

[0076] 7B is a diagram illustrating an example of signal generation according to Option 1. As shown in FIG. 7B, in Option 1, feedback content (i ｘ ) may be generated.

[0077] 7C is a diagram illustrating an example of signal reconstruction according to Option 1. As shown in FIG. 7C, in Option 1, the feedback content (i ｘ ), the precoding / channel matrices may be reconstructed according to the model specifications.

[0078] Also, for example, in option 3, the structure of the model is specified, so that only the procedure of determining / pairing parameters related to the model can be performed between the UE and the NW.

[0079] Option 3 is broadly divided into Option 3a-1, Option 3a-2, Option 3a-3, and Option 3b depending on the part that performs parameter exchange and whether or not offline engineering is performed on the UE side.

[0080] Option 3a-1 is an option in which parameters of the signal generation part are exchanged and offline engineering is performed.

[0081] 8 is a diagram showing an example of signal generation / signal reconstruction according to Option 3a-1. In the example shown in FIG. 8, CSI is used as an example of a signal, and the same applies to the subsequent figures. Therefore, in the present disclosure, a CSI generation / reconstruction part may be read as an arbitrary signal generation / reconstruction part.

[0082] As shown in Figure 8, in Option 3a-1, a model structure is specified for the signal (CSI) generation part. The UE receives information (e.g., model parameters / weights) related to the model required for the CSI generation part from the NW. The UE then performs UE-side offline engineering, generates CSI from the precoding / channel matrix (target CSI) using the derived model, and provides CSI feedback to the NW. The NW reconstructs the target CSI through the CSI reconstruction part.

[0083] Option 3a-2 is an option in which parameter exchange of the signal reconstruction part is performed and offline engineering (with a long delay) is performed.

[0084] FIG. 9 is a diagram showing an example of signal generation / signal reconstruction according to Option 3a-2. As shown in FIG. 9, in Option 3a-2, a model structure is specified for the signal (CSI) reconstruction part (the CSI generation part may depend on the UE implementation). The UE receives information (e.g., model parameters / weights) related to the model required for the CSI reconstruction part from the NW. The UE then performs UE-side offline engineering, generates CSI from the precoding / channel matrix (target CSI) using the derived model, and provides CSI feedback to the NW. The NW reconstructs the target CSI using the CSI reconstruction part.

[0085] Option 3a-3 is an option in which parameters of both the signal generation part and the signal reconstruction part are exchanged and offline engineering is performed.

[0086] FIG. 10 is a diagram showing an example of signal generation / signal reconstruction according to Option 3a-3. As shown in FIG. 10, in Option 3a-3, model structures are specified for both the signal (CSI) generation part and the signal (CSI) reconstruction part. The UE receives information (e.g., model parameters / weights) related to the model required for the CSI generation part and information (e.g., model parameters / weights) related to the model required for the CSI reconstruction part from the NW. The UE then performs UE-side offline engineering, generates CSI from the precoding / channel matrix (target CSI) using the derived model, and provides CSI feedback to the NW. The NW reconstructs the target CSI using the CSI reconstruction part.

[0087] Option 3b is an option in which parameter exchange of the signal generation part is performed, but offline engineering is not performed.

[0088] Figure 11 is a diagram showing an example of signal generation / signal reconstruction according to Option 3b. As shown in Figure 11, in Option 3b, a model structure is specified for the signal (CSI) generation part. The UE receives information (e.g., model parameters / weights) related to the model required for the CSI generation part from the NW. The UE then uses the specified model to generate CSI from the precoding / channel matrix (target CSI) based on the received information related to the model, and provides CSI feedback to the NW. The NW reconstructs the target CSI using the CSI reconstruction part.

[0089] Also, for example, in option 5, a model format (for delivery / transfer) is specified, so that determination / pairing regarding the reference model can be performed between the UE and the NW.

[0090] Option 5 is broadly divided into Option 5a-1, Option 5a-2, Option 5a-3, and Option 5b depending on the part that performs model (model format) exchange and whether or not offline engineering is performed on the UE side.

[0091] Option 5a-1 is an option in which model exchange of the signal generation part is performed and offline engineering is carried out.

[0092] FIG. 12 is a diagram illustrating an example of signal generation / signal reconstruction according to Option 5a-1. As shown in FIG. 12, in Option 5a-1, a model for the signal (CSI) generation part may be based on the UE's implementation. The UE receives a model (model format) for the CSI generation part and information about the model (e.g., model parameters / weights) from the NW. The UE then performs UE-side offline engineering, generates CSI from the precoding / channel matrix (target CSI) using the derived model, and provides CSI feedback to the NW. The NW reconstructs the target CSI using the CSI reconstruction part.

[0093] Option 5a-2 is an option in which model exchange of the signal reconstruction part is performed and offline engineering (with a long delay) is performed.

[0094] FIG. 13 is a diagram illustrating an example of signal generation / signal reconstruction according to Option 5a-2. As shown in FIG. 13, in Option 5a-2, the model for the signal (CSI) generation part may be based on the UE's implementation. The UE receives a model (model format) for the CSI reconstruction part and information about the model (e.g., model parameters / weights) from the NW. The UE then performs UE-side offline engineering, generates CSI from the precoding / channel matrix (target CSI) using the derived model, and provides CSI feedback to the NW. The NW reconstructs the target CSI using the CSI reconstruction part.

[0095] Option 5a-3 is an option in which models of both the signal generation part and the signal reconstruction part are exchanged and offline engineering is performed.

[0096] FIG. 14 is a diagram illustrating an example of signal generation / signal reconstruction according to Option 5a-3. As shown in FIG. 14, in Option 5a-3, the model for the signal (CSI) generation part may be based on the UE's implementation. The UE receives from the NW a model (model format) for the CSI generation part, a model (model format) for the CSI reconstruction part, information about the model for the CSI generation part (e.g., model parameters / weights), and information about the model for the CSI reconstruction part (e.g., model parameters / weights). The UE then performs UE-side offline engineering, generates CSI from the precoding / channel matrix (target CSI) using the derived model, and provides CSI feedback to the NW. The NW reconstructs the target CSI using the CSI reconstruction part.

[0097] Option 5b is an option in which model exchange of the signal generation part is performed, but offline engineering is not performed.

[0098] Figure 15 is a diagram showing an example of signal generation / signal reconstruction according to option 5b. As shown in Figure 15, in option 5b, the model for the signal (CSI) generation part may be based on the UE's implementation. The UE receives a model (model format) for the CSI generation part and information about the model for the CSI generation part (e.g., model parameters / weights) from the NW. Then, the UE generates CSI from the precoding / channel matrix (target CSI) based on / using the received model and information about the model, and provides CSI feedback to the NW. The NW reconstructs the target CSI using the CSI reconstruction part.

[0099] However, the latency of offline engineering is important for practical deployment of models (e.g., localized models), so it is preferable for the network to be able to control the latency so that the distributed / transferred models are ready when needed.

[0100] However, the delay time and the use of the model have not been sufficiently considered. If this consideration is insufficient, it may be impossible to properly utilize the AI / ML model in future wireless communication systems, which may hinder improvement of communication throughput.

[0101] Therefore, the present inventors came up with a solution to this problem.

[0102] Hereinafter, embodiments according to the present disclosure will be described in detail with reference to the drawings. Wireless communication methods according to the embodiments may be applied independently or in combination.

[0103] (Various Reinterpretations) In the present disclosure, a word enclosed in "( )" in a sentence may indicate an explanation of the word immediately preceding it (for example, an explanation of spelling), a paraphrase, a specific example, a supplementary explanation, etc. Furthermore, in the present disclosure, a word enclosed in "[ ]" in a sentence may be interpreted including the word in the meaning of the entire sentence, or may be interpreted excluding (ignoring) the word in the meaning of the entire sentence. Note that "( )" and "[ ]" may also be used for purposes / meanings other than those mentioned above.

[0104] In the present disclosure, "A / B" and "at least one of A and B" may be interpreted interchangeably. Also, in the present disclosure, "A / B / C" may mean "at least one of A, B, and C."

[0105] In the present disclosure, terms such as notify, activate, deactivate, indicate (or indicate), select, configure, update, and determine may be read interchangeably. In the present disclosure, terms such as support, control, controllable, operate, and operate may be read interchangeably.

[0106] In the present disclosure, Radio Resource Control (RRC), RRC parameters, RRC messages, higher layer parameters, fields, information elements (IEs), settings, etc. may be interchangeable. In the present disclosure, Medium Access Control (MAC) control elements (CEs), update commands, activation / deactivation commands, etc. may be interchangeable.

[0107] In the present disclosure, the higher layer signaling may be, for example, any one of Radio Resource Control (RRC) signaling, Medium Access Control (MAC) signaling, broadcast information, other messages (e.g., messages from the core network such as positioning protocol (e.g., NR Positioning Protocol A (NRPPa) / LTE Positioning Protocol (LPP)) messages), or a combination thereof.

[0108] In the present disclosure, MAC signaling may use, for example, a MAC Control Element (MAC CE), a MAC Protocol Data Unit (PDU), etc. Broadcast information may be, for example, a Master Information Block (MIB), a System Information Block (SIB), Remaining Minimum System Information (RMSI), Other System Information (OSI), etc.

[0109] In the present disclosure, physical layer signaling may be, for example, Downlink Control Information (DCI), Uplink Control Information (UCI), and the like.

[0110] In the present disclosure, the network function (NF) may include, for example, at least one of the following: - Application Function (AF) (e.g., a function that realizes an application server outside the 5G Core Network (5GC)); - Access and Mobility management Function (AMF) (e.g., a function that manages UE registration, location, etc.); - Data Network (DN) (e.g., a function that realizes a data network outside 5GC); - Location Management Function (LMF) (e.g., a communication control function related to location-based services); - Non-3GPP Inter-Working Function (N3IWF) (e.g., a function that connects 5GC with an untrusted non-3GPP access network); - Network Exposure Function (NEF) (e.g., a function that provides an application interface for 5GC NF services to the outside); - Network Slice Selection Function (NSSF) (e.g., a function that selects a network slice); - Network Data Analytics Function (NWDAF) (e.g., a function that analyzes network data). Operation, Administration and Maintenance (Management) (OAM) (e.g., a function that provides means for operation, maintenance and management). Policy Control Function (PCF) (e.g., a function that controls the quality, policy, etc. of data transfer paths). Session Management Function (SMF) (e.g., a function that manages sessions). Trusted Non-3GPP Gateway Function (TNGF) (e.g., a function that connects trusted non-3GPP access networks with 5GC).- Trusted WLAN Interworking Function (TWIF) (e.g., a function that connects a trusted non-3GPP access network with 5GC for a non-5G capable UE via a Wireless Local Area Network (LAN)). - (Radio) Access Network ((R)AN) (e.g., a function that provides a radio access network). - User Equipment (UE) (e.g., a function that provides user access to network services via the radio interface). - Unified Data Management (UDM) (e.g., a function that stores / manages subscriber information, UE authentication information, etc.). - Unified Data Repository (UDR) (e.g., a function that manages authentication / authorization based on subscriber information). - User Plane Function (UPF) (e.g., a function that transports user data packets). - Over The Top (OTT) (e.g., content / services / functions provided by an independent provider / vendor bypassing the carrier's network).

[0111] Each embodiment of the present disclosure can also be applied to an ORAN network (e.g., a base station that complies with the ORAN specifications) as appropriate.

[0112] In the present disclosure, the terms "model to be specified," "specification of a model," and "model specification" may be read interchangeably.

[0113] In the present disclosure, an entity (e.g., a UE / NW entity) may generate an output from an input in a particular format according to a model specification.

[0114] The model specification may be defined for at least one of the following: - Information / description(s) about a series of layers / functions (e.g., type of computation (e.g., n-dimensional convolution, linear function, attention, sigmoid function, or ReLU function, etc.)) and information / description(s) about the parameters / weights required for the computations being defined; - Information / description(s) about a series of computations and information / description(s) about the parameters / weights required for the computations being defined; - Information / description(s) about the computation order across the layers / functions / computations being defined; - Information / description(s) about inputs / outputs / data types / formats for each computation step; - Information about the specified (model) name / functionality and corresponding ID / version / timestamp / release number; - Information about applicable conditions / additional conditions.

[0115] In this disclosure, a specified model may refer to a model / entity / module / functionality / behavior that is defined by a model specification.

[0116] In the present disclosure, a portion (e.g., a layer) of information / description about a model may be specified, in which case the model of which a portion is specified may be referred to as a specified layer / parameter, a specified model part(s), etc.

[0117] In this disclosure, Signal Generation Part (SGP) may mean a model / functionality / entity / module that generates a signal to be transmitted based on an input signal.

[0118] For example, the SGP may include a CSI generation part, a waveform generation part, and so on.

[0119] In this disclosure, the terms "implemented SGP" and "SGP implementation" may be interchangeable. In this disclosure, the terms "specified SGP," "SGP specification," and "model-specific SGP" may be interchangeable.

[0120] In this disclosure, Signal Reconstruction Part (SRP) may refer to a model / functionality / entity / module that outputs (reconstructs) a signal based on a received signal.

[0121] In this disclosure, terms such as reconstruct, configure, represent, display, describe, restore, process, etc. may be read interchangeably.

[0122] For example, the SRP may include a CSI reconstruction part, a waveform reconstruction part, etc.

[0123] In the present disclosure, the terms "implemented SRP" and "SRP implementation" may be interchangeable. In the present disclosure, the terms "specified SRP," "SRP specification," and "model-specific SRP" may be interchangeable.

[0124] The SGP / SRP may be specified by the model specification or may be included as part of the specification by the model specification.

[0125] In this disclosure, input signal / output signal may refer to at least a portion of the model / data set being specified.

[0126] In this disclosure, the names and types of model specifications / parts of model specifications / SGP / SRP / input signals / output signals are merely examples, and are not limited to the examples described, and may be changed as appropriate depending on the use case to be applied.

[0127] Each embodiment in the present disclosure may be applied to at least one of the above options requiring offline engineering (on the UE side).

[0128] In the present disclosure, information about a model and model information may be read interchangeably.

[0129] In the present disclosure, offline engineering, offline operation, internal operation, processing, internal processing, model, and operation for activating / using / deploying / configuring at least one of corresponding functionality / module / option (e.g., corresponding codebook), etc. may be read interchangeably.

[0130] (Wireless Communication Method) First Embodiment The first embodiment relates to the period of offline engineering.

[0131] The UE may report information regarding the duration of the offline engineering.

[0132] The UE may send the report before receiving at least one of the model and information about the model (e.g., model parameters / weights), or after receiving at least one of the model and information about the model (e.g., model parameters / weights).

[0133] The information about the duration of the offline engineering may include, for example, information about at least one of the following: - Information about the duration from the time / point in time when the UE receives information about the model (e.g., model parameters / weights) [group] to the time / point in time when the model or corresponding functionality / module / option (e.g., corresponding codebook) can be activated / used / deployed / configured (first information). - Information about the duration from the time / point in time when the UE receives the model (e.g., which may include information about the model (e.g., model parameters / weights)) to the time / point in time when the model or corresponding functionality / module / option (e.g., corresponding codebook) can be activated / used / deployed / configured (second information).

[0134] For example, in the case of Option 3 above, the first information may be included in information regarding offline engineering.

[0135] For example, in the case of option 5, the second information may be included in information regarding offline engineering.

[0136] For option 3 / 5, the information about the period may include information about at least one of the following: - Information about the length of the period (e.g., absolute time unit / slot unit / symbol unit / subframe unit / radio frame unit); - Information about periods at different levels; - Information about periods for different target performance.

[0137] Two or more levels may be defined for different levels, for example, a first level may be a level that takes necessary actions to ensure that the model in the UE is viable for benchmark performance, and a second level (or higher) may be a level that takes optional actions for higher performance targets.

[0138] The target performance may be, for example, a KPI of a functionality / model. For example, the UE may report that any target performance within the reported period was not achieved.

[0139] The level / target performance may be set / instructed / specified to the UE.

[0140] The UE may report a capability type, which is defined as a combination of period length / type / target performance.

[0141] The definition of the capability type may be configured / indicated / specified to the UE.

[0142] The UE may report information about the period per functionality / per model (received / specified) / per group of information about the model (received) (e.g., model parameters / weights).

[0143] The UE may report information about the period before receiving at least one of the model and the information about the model. In this case, for example, the UE may report the information about the period using the report of UE capability information.

[0144] The UE may report information about the period after receiving the model and / or information about the model, e.g., for each (group of) information about the model or for each received model.

[0145] According to the first embodiment described above, the NW can appropriately grasp the period of offline engineering on the UE side.

[0146] Second Embodiment The second embodiment relates to control of offline engineering.

[0147] The NW may control the UE to perform configured / instructed offline engineering. The UE may receive a configuration / instruction regarding the execution of offline engineering.

[0148] The NW may configure / instruct the UE to perform offline engineering and complete preparation of the model within a specific period (or after a specific period has elapsed).

[0149] The UE may perform / control the preparation / activation of the model to be applied based on at least one of the settings / instructions from the NW and at least one piece of information (report) described in the first embodiment above.

[0150] The UE may be configured / instructed with information regarding a time period for at least one of the functionality, the model, and / or the group of information regarding the model.

[0151] The information about the period may be information about at least one of the following: - Information about the level; - Information about the target performance; - Information about requirements for the period from when the UE receives the model / [group of] information about the model to when / at what point in time the model (corresponding to the model information) and corresponding functionality / module / option (e.g., corresponding codebook) can be activated / used / deployed / configured (third information).

[0152] With regard to the information about the level, the UE may take action corresponding to the indicated / set level.

[0153] With this information about the target performance, the UE may take action to achieve the indicated / set target performance.

[0154] For example, the UE may not assume / expect to be configured / instructed for the third information to have a period shorter / smaller than (the period corresponding to) the reported UE capability.

[0155] For example, the UE may compare the reported UE capability (a period corresponding to the third information) with the set / instructed period and determine to take a specific action.

[0156] For example, the set / indicated period may be shorter / smaller than (the period corresponding to) the reported UE capability.

[0157] In this case, the UE may perform (a subset of) the operations that it is able to perform / complete within the set / instructed time period.

[0158] For example, the UE may perform an action that is selected based on the action level, e.g., the UE may select / perform an action in order from highest priority level to lowest priority level.

[0159] For example, the UE may perform an action that is selected based on a target performance, e.g., the UE may select / perform an action in order from an action that achieves the lowest target performance to an action that achieves the highest target performance.

[0160] For example, the UE may not expect / hope to be configured / instructed to have a period shorter / smaller than the reported period for the highest priority level / lowest target performance.

[0161] Also, for example, the set / indicated period may be longer / larger than (the period corresponding to) the reported UE capabilities.

[0162] In this case, the UE may perform the reported action (eg, the action corresponding to the reported time period) and / or additionally selected action.

[0163] For example, the UE may perform additional actions that are selected based on activity level / priority / target performance.

[0164] For example, the UE may report (e.g., report on the execution / completion of an action, report on whether requirements regarding delay time / level / target performance can be achieved) at a specific time after completing the action being reported (e.g., the action corresponding to the period being reported) and starting to perform additional actions.

[0165] The UE may report whether it can achieve the requirements regarding delay time / level / target performance.

[0166] The UE may report the status of at least one of the functionality / model / entity corresponding to the information about the received model and the received model (at a configured / instructed point / time, or at a specific timing after the model / received model corresponding to the information about the received model is activated).

[0167] The status may indicate, for example, ready to be activated, under processing, under processing but ready with Level X, or under processing but ready with target performance value Y.

[0168] According to the second embodiment, the NW performs settings / instructions / controls on the offline engineering operations on the UE, thereby enabling appropriate preparation / activation of a model.

[0169] <Modification> In the present disclosure, functionality may be a set of parameters (e.g., a set of parameters for CSI prediction / beam prediction / CSI compression) that are supported based on conditions indicated by UE capabilities.

[0170] In the present disclosure, the UE may report parameter values ​​related to a function or a model as a condition to the NW using at least one of the methods described in the supplemental section below. For example, the UE may report the condition using a UE capability report or a UE feature / feature group report.

[0171] The UE may report parameter values ​​related to a function or model as additional conditions using at least one of the methods described in the supplementary section below or a method other than signaling via the air interface of the network (e.g., a radio section (e.g., between the UE and the network)).

[0172] The UE may be instructed as an additional condition on parameter values ​​related to a function or model using at least one of the methods described in the supplementary section below or a method other than signaling via the air interface of the network.

[0173] The UE may report specific information (e.g., parameter names) in the present disclosure as information / instructions regarding additional conditions using at least one of the methods described in the supplementary section below or a method other than signaling via the air interface of the network.

[0174] The UE may be instructed, as information / instructions regarding additional conditions, specific information (e.g., parameter names) in the present disclosure using at least one of the methods described in the supplementary section below or a method other than signaling via the air interface of the network.

[0175] For example, the UE may report a device ID / device vendor ID as an additional condition, or may be instructed to report a cell ID as an additional condition.

[0176] For example, the UE may report / indicate information on a parameter name (for example, a cell ID / UE ID instead of an ID value) as information / indication of an additional condition.

[0177] In the present disclosure, a method other than signaling via the air interface of the network may be at least one of pre-configuration of the UE (e.g., by the UE vendor) and operator configuration provided by the network operator.

[0178] In the present disclosure, a model / function for CSI may refer to a CSI report associated with a model ID or a particular function (e.g., at least one of predicted CSI, compressed CSI, advanced CSI, and CSI of a particular type (e.g., type x)).

[0179] In the present disclosure, AI / ML functions, CSI-oriented AI / ML functions, and CSI-oriented functions may refer to functions instructed by the NW or reported by the UE (e.g., at least one of predicted CSI, compressed CSI, advanced CSI, and CSI of a particular type (e.g., type x)).

[0180] In this disclosure, the AI / ML model, the AI / ML model for CSI, and the model for CSI may be identified by an ID or function and may refer to a model / entity that performs the specific function described above.

[0181] <Supplementary Information> <<Model Information>> In the present disclosure, AI model information (or simply "model") may refer to information including at least one of the following: - Input / output information of the AI ​​model. - Pre-processing / post-processing information for the input / output of the AI ​​model. - Parameter information of the AI ​​model. - Training information for the AI ​​model. - Inference information for the AI ​​model. - Performance information regarding the AI ​​model.

[0182] Here, the input / output information of the AI ​​model may include information on at least one of the following: - Contents of the input / output data (e.g., RSRP, SINR, amplitude / phase information in the channel matrix (or precoding matrix), information on the angle of arrival (Angle of Arrival (AoA)), information on the angle of departure (Angle of Departure (AoD)), location information); - Auxiliary information of the data (which may be called meta-information); - Type of the input / output data (e.g., immutable value, floating-point number); - Bit width of the input / output data (e.g., 64 bits for each input value); - Quantization interval (quantization step size) of the input / output data (e.g., 1 dBm for L1-RSRP); - Range that the input / output data can take (e.g., [0, 1]).

[0183] In the present disclosure, the information on AoA may include information on at least one of an azimuth angle of arrival and a zenith angle of arrival (ZoA). The information on AoD may include information on at least one of an azimuth angle of departure and a zenith angle of departure (ZoD).

[0184] In the present disclosure, location information may be location information related to a UE / NW. The location information may include at least one of information (e.g., latitude, longitude, altitude) obtained using a positioning system (e.g., a satellite positioning system (Global Navigation Satellite System (GNSS), Global Positioning System (GPS), etc.)), information about a BS neighboring (or serving) the UE (e.g., a BS / cell identifier (ID), a BS-UE distance, a direction / angle of the BS (UE) as seen from the UE (BS), coordinates of the BS (UE) as seen from the UE (BS) (e.g., X / Y / Z axis coordinates), etc.), a specific address of the UE (e.g., an Internet Protocol (IP) address), etc. The location information of the UE is not limited to information based on the position of the BS, and may be information based on a specific point.

[0185] The location information may include information about its implementation (e.g., location / position / orientation of antennas, location / orientation of antenna panels, number of antennas, number of antenna panels, etc.).

[0186] The location information may include mobility information, which may include information indicating at least one of information indicating a mobility type, a moving speed of the UE, an acceleration of the UE, and a moving direction of the UE.

[0187] Here, the mobility type may correspond to at least one of a fixed location UE, a movable / moving UE, a no mobility UE, a low mobility UE, a middle mobility UE, a high mobility UE, a cell-edge UE, a not-cell-edge UE, etc.

[0188] In the present disclosure, environmental information (for data) may be information about the environment in which the data is acquired / used, and may correspond to, for example, frequency information (such as a band ID), environmental type information (information indicating at least one of indoor, outdoor, Urban Macro (UMa), Urban Micro (Umi), etc.), information indicating Line Of Site (LOS) / Non-Line Of Site (NLOS), etc.

[0189] Here, LOS may mean that the UE and the BS are in an environment where they can see each other (or there is no obstruction), and NLOS may mean that the UE and the BS are not in an environment where they can see each other (or there is an obstruction). The information indicating LOS / NLOS may indicate a soft value (e.g., the probability of LOS / NLOS) or a hard value (e.g., either LOS or NLOS).

[0190] In the present disclosure, meta-information may mean, for example, information regarding input / output information suitable for an AI model, information regarding acquired / acquirable data, etc. Specifically, meta-information may include information regarding beams of RS (e.g., CSI-RS / SRS / SSB, etc.) (e.g., the pointing angle of each beam, the 3 dB beam width, the shape of the pointed beam, the number of beams), layout information of the gNB / UE antenna, frequency information, environmental information, meta-information ID, etc. Note that meta-information may be used as input / output of the AI ​​model.

[0191] The pre-processing / post-processing information for the input / output of the AI ​​model may include information on at least one of the following: Whether to apply normalization (e.g., Z-score normalization (standardization), min-max normalization); Parameters for normalization (e.g., mean / variance for Z-score normalization, min / max for min-max normalization); Whether to apply a specific numerical conversion method (e.g., one hot encoding, label encoding, etc.); Selection rules for whether to use as training data.

[0192] For example, Z-score normalization (x) is performed as a preprocessing step for input information x. ｎｅｗ = (x - μ) / σ, where μ is the mean of x and σ is the standard deviation) ｎｅｗ may be input to the AI ​​model, and the output y ｏｕｔ may be subjected to post-processing to obtain the final output y.

[0193] The information on the parameters of the AI ​​model may include information on at least one of the following: - Information on weights in the AI ​​model (e.g., neuron coefficients (connection coefficients)); - Structure of the AI ​​model; - Type of the AI ​​model as a model component (e.g., Residual Network (ResNet), DenseNet, RefineNet, Transformer model, CRBlock, Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU)); - Function of the AI ​​model as a model component (e.g., decoder, encoder).

[0194] Note that the weight information in the AI ​​model may include information on at least one of the following: - Bit width (size) of the weight information; - Quantization interval of the weight information; - Granularity of the weight information; - Range that the weight information can take; - Weight parameters in the AI ​​model; - Information on the difference from the AI ​​model before update (if updating); - Weight initialization method (e.g., zero initialization, random initialization (based on normal distribution / uniform distribution / truncated normal distribution), Xavier initialization (for sigmoid function), He initialization (for rectified linear units (ReLU))).

[0195] The structure of the AI ​​model may also include information about at least one of the following: the number of layers, the type of layer (e.g., convolutional layer, activation layer, dense layer, normalization layer, pooling layer, attention layer), layer information, time series specific parameters (e.g., bidirectionality, time step), parameters for training (e.g., type of function (e.g., L2 regularization, dropout function, etc.), where (e.g., after which layer) to place this function).

[0196] The layer information may include information about at least one of the following: Number of neurons in each layer; Kernel size; Stride for pooling / convolutional layers; Pooling method (MaxPooling, AveragePooling, etc.); Residual block information; Number of heads; Normalization method (Batch normalization, instance normalization, layer normalization, etc.); Activation function (Sigmoid, tanh function, ReLU, leaky ReLU information, Maxout, Softmax).

[0197] An AI model may be included as a component of another AI model, for example, an AI model that includes model component #1, ResNet, model component #2, a Transformer model, a dense layer, and a normalization layer in that order.

[0198] The training information for the AI ​​model may include information about at least one of the following: - Information for the optimization algorithm (e.g., type of optimization (Stochastic Gradient Descent (SGD)), AdaGrad, Adam, etc.), parameters of the optimization (learning rate, momentum information, etc.); - Information on the loss function (e.g., information on metrics of the loss function (Mean Absolute Error (MAE)), Mean Square Error (MSE), Cross Entropy Loss, NLL Loss, Kullback-Leibler (KL) Divergence, etc.)); - Parameters to be frozen for training (e.g., layers, weights); - Parameters to be updated (e.g., layers, weights); - Parameters to be (used as) initial parameters for training (e.g., layers, weights); - Method of training / updating the AI ​​model (e.g., (recommended) number of epochs, batch size, number of data to use for training).

[0199] The inference information for the AI ​​model may include information regarding decision tree branch pruning, parameter quantization, and functions of the AI ​​model, etc. Here, the functions of the AI ​​model may correspond to at least one of, for example, time domain beam prediction, spatial domain beam prediction, an autoencoder for CSI feedback, and an autoencoder for beam management.

[0200] An autoencoder for CSI feedback may be used as follows: The UE inputs the CSI / channel matrix / precoding matrix into the AI ​​model of the encoder and transmits the encoded bits as CSI feedback (CSI report). The BS inputs the received encoded bits into the AI ​​model of the decoder to reconstruct the CSI / channel matrix / precoding matrix, which is the output.

[0201] In spatial domain beam prediction, the UE / BS may input measurement results (beam quality, e.g., RSRP) based on sparse (or thick) beams into an AI model and output dense (or thin) beam quality.

[0202] In time domain beam prediction, the UE / BS may input time series (past, present, etc.) measurement results (beam quality, e.g., RSRP) into an AI model and output future beam quality.

[0203] The performance information regarding the AI ​​model may include information regarding the expected value of a loss function defined for the AI ​​model.

[0204] The AI ​​model information in the present disclosure may include information regarding the application range (applicable range) of the AI ​​model. The application range may be indicated by a physical cell ID, a serving cell index, etc. The information regarding the application range may be included in the above-mentioned environment information.

[0205] AI model information regarding a specific AI model may be predetermined in a standard or may be notified to a UE from a network (NW). An AI model defined in a standard may be referred to as a reference AI model. AI model information regarding a reference AI model may be referred to as reference AI model information.

[0206] Note that the AI ​​model information in the present disclosure may include an index for identifying the AI ​​model (which may be referred to as, for example, an AI model index, an AI model ID, a model ID, etc.). The AI ​​model information in the present disclosure may include an AI model index in addition to / instead of the input / output information of the AI ​​model described above. The association between the AI ​​model index and the AI ​​model information (for example, input / output information of the AI ​​model) may be predetermined in a standard, or may be notified to the UE from the NW.

[0207] The AI ​​model information in the present disclosure may be associated with an AI model and may be referred to as AI model relevant information, simply relevant information, etc. The AI ​​model relevant information does not need to explicitly include information for identifying the AI ​​model. The AI ​​model relevant information may be information that includes only meta information, for example.

[0208] In the present disclosure, the ML model file information may be at least one of the format / size / encoding of the ML model file, the runtime context (eg, runtime environment / libraries), and the required computational resources.

[0209] <<Notification of Information to UE>> In the above-described embodiments, notification of any information to the UE [from a Network (NW) (e.g., a Base Station (BS))] (in other words, reception of any information from the BS by the UE) may be performed using physical layer signaling (e.g., DCI), higher layer signaling (e.g., RRC signaling, MAC CE), a specific signal / channel (e.g., PDCCH, PDSCH, reference signal), or a combination thereof.

[0210] When the notification is performed by a MAC CE, the MAC CE may be identified by including a new Logical Channel ID (LCID) in the MAC subheader, which is not defined in existing standards.

[0211] When the notification is made by DCI, the notification may be made by a specific field of the DCI, a Radio Network Temporary Identifier (RNTI) used to scramble Cyclic Redundancy Check (CRC) bits assigned to the DCI, the format of the DCI, etc.

[0212] Furthermore, notification of any information to the UE in the above embodiments may be performed periodically, semi-persistently, or aperiodically.

[0213] <<Notification of Information from UE>> In the above-described embodiments, notification of any information from the UE [to the NW] (in other words, transmission / report of any information from the UE to the BS) may be performed using physical layer signaling (e.g., UCI), higher layer signaling (e.g., RRC signaling, MAC CE), a specific signal / channel (e.g., PUCCH, PUSCH, PRACH, reference signal), or a combination thereof.

[0214] When the notification is performed by a MAC CE, the MAC CE may be identified by including a new LCID, which is not defined in existing standards, in the MAC subheader.

[0215] If the notification is made by UCI, the notification may be transmitted using PUCCH or PUSCH.

[0216] Furthermore, any information in the above-described embodiments may be notified from the UE periodically, semi-persistently, or aperiodically.

[0217] <<Application of Each Embodiment>> In a UE / BS, specific (one or more) processes / operations / controls / assumptions / information for at least one of the above-described embodiments may be applied (used) when one or more of the following conditions are met: - A higher layer parameter indicating the specific processes / operations / controls / assumptions / information is configured. - The specific processes / operations / controls / assumptions / information is determined based on related higher layer parameters. - The specific processes / operations / controls / assumptions / information is specified / activated / triggered by a MAC CE / DCI / UCI / resource / channel / RS. - A specific UE capability indicating (or related to) the specific processes / operations / controls / assumptions / information is reported or supported. - The application of the specific processes / operations / controls / assumptions / information is determined based on specific conditions.

[0218] The particular UE capability may indicate, for example, at least one of: a minimum duration for offline engineering and support for the particular process / operation / control / assumption / information.

[0219] The length of the period may be based / dependent, for example, on a target performance / level.

[0220] Furthermore, the above-mentioned specific UE capability may be a capability that is applied across all frequencies (commonly regardless of frequency), or may be a capability for each frequency (e.g., one or a combination of a cell, a band, a band combination, a BWP, a component carrier, etc.), or may be a capability for each frequency range (e.g., Frequency Range 1 (FR1), FR2, FR3, FR4, FR5, FR2-1, FR2-2), or may be a capability for each subcarrier spacing (SubCarrier Spacing (SCS)), or may be a capability for each Feature Set (FS) or Feature Set Per Component-carrier (FSPC).

[0221] Furthermore, the specific UE capability may be a capability that is applied to all duplexing methods (commonly regardless of the duplexing method), or may be a capability for each duplexing method (e.g., Time Division Duplex (TDD) or Frequency Division Duplex (FDD)).

[0222] If the above conditions are not met, the UE / BS may follow the behavior specified in existing 3GPP releases.

[0223] (Supplementary Notes) The following inventions are supplemented with respect to one embodiment of the present disclosure. [Supplementary Note 1] A terminal having a transceiver unit that transmits information regarding a period related to offline engineering and receives instructions regarding the execution of offline engineering, and a control unit that activates a model based on at least one of the information and the instructions. [Supplementary Note 2] The terminal described in Supplementary Note 1, wherein the information includes information regarding a period from a time when at least one of a model and information related to the model is received to a time when the model or a corresponding function can be activated. [Supplementary Note 3] The terminal described in Supplementary Note 1 or Supplementary Note 2, wherein the instruction includes information regarding a requirement regarding a period from a time when at least one of a model and information related to the model is received to a time when the model or a corresponding function can be activated. [Supplementary Note 4] The terminal described in any of Supplements 1 to 3, wherein the control unit does not assume that the instruction will specify a period shorter than the period corresponding to the information.

[0224] (Wireless Communication System) The configuration of a wireless communication system according to an embodiment of the present disclosure will be described below. In this wireless communication system, communication is performed using any one of the wireless communication methods according to the above embodiments of the present disclosure or a combination thereof.

[0225] 16 is a diagram illustrating an example of a schematic configuration of a wireless communication system according to an embodiment. The wireless communication system 1 (which may be simply referred to as system 1) may be a system that realizes communication using Long Term Evolution (LTE) or 5th generation mobile communication system New Radio (5G NR) specified by the Third Generation Partnership Project (3GPP).

[0226] The wireless communication system 1 may also support dual connectivity between multiple Radio Access Technologies (RATs) (Multi-RAT Dual Connectivity (MR-DC)). MR-DC may include dual connectivity between LTE (Evolved Universal Terrestrial Radio Access (E-UTRA)) and NR (E-UTRA-NR Dual Connectivity (EN-DC)), dual connectivity between NR and LTE (NR-E-UTRA Dual Connectivity (NE-DC)), etc.

[0227] In EN-DC, the LTE (E-UTRA) base station (eNB) is the master node (Master Node (MN)), and the NR base station (gNB) is the secondary node (Secondary Node (SN)). In NE-DC, the NR base station (gNB) is the MN, and the LTE (E-UTRA) base station (eNB) is the SN.

[0228] The wireless communication system 1 may support dual connectivity between multiple base stations within the same RAT (for example, dual connectivity in which both the MN and SN are NR base stations (gNBs) (NR-NR Dual Connectivity (NN-DC))).

[0229] The wireless communication system 1 may include a base station 11 that forms a macrocell C1 with a relatively wide coverage, and base stations 12 (12a-12c) that are located within the macrocell C1 and form small cells C2 that are smaller than the macrocell C1. A user terminal 20 may be located within at least one of the cells. The location, number, shape, size, etc. of each cell and user terminal 20 are not limited to the embodiment shown in the figure. Hereinafter, when there is no need to distinguish between the base stations 11 and 12, they will be collectively referred to as the base station 10.

[0230] The wireless communication system 1 may utilize multi-input multi-output (MIMO). For example, one cell may be formed by one antenna / base station 10, or may be formed by multiple antennas / base stations 10. One [virtual] cell (which may be called, for example, a supercell) may be composed of multiple [virtual] cells (which may be called, for example, subcells). A supercell may correspond to a cell with a fixed physical range, and a subcell may correspond to a cell with a quasi-static / dynamically variable physical range. In this case, the wireless communication system 1 may be called a cell-free system.

[0231] The user terminal 20 may be connected to at least one of the multiple base stations 10. The user terminal 20 may utilize at least one of carrier aggregation (CA) using multiple component carriers (CCs) and dual connectivity (DC).

[0232] Each CC may be included in at least one of a first frequency band (Frequency Range 1 (FR1)) and a second frequency band (Frequency Range 2 (FR2)). The macro cell C1 may be included in FR1, and the small cell C2 may be included in FR2. For example, FR1 may be a frequency band of 6 GHz or less (sub-6 GHz), and FR2 may be a frequency band higher than 24 GHz (above-24 GHz). Note that the frequency bands and definitions of FR1 and FR2 are not limited to these, and for example, FR1 may correspond to a higher frequency band than FR2.

[0233] Furthermore, the user terminal 20 may perform communication using at least one of time division duplex (TDD) and frequency division duplex (FDD) in each CC.

[0234] The multiple base stations 10 may be connected by wire (e.g., optical fiber compliant with the Common Public Radio Interface (CPRI), an X2 / Xn interface, etc.) or wirelessly (e.g., NR communication). For example, when NR communication is used as a backhaul between the base stations 11 and 12, the base station 11 corresponding to the upper station may be called an Integrated Access Backhaul (IAB) donor, and the base station 12 corresponding to the relay station (relay) may be called an IAB node.

[0235] The base station 10 may be connected to the core network 30 directly or via another base station 10. The core network 30 may include, for example, at least one of an Evolved Packet Core (EPC), a 5G Core Network (5GCN), a Next Generation Core (NGC), and the like.

[0236] The core network 30 may include network functions (Network Functions (NF)) such as a User Plane Function (UPF), an Access and Mobility management Function (AMF), a Session Management Function (SMF), a Unified Data Management (UDM), an Application Function (AF), a Data Network (DN), a Location Management Function (LMF), and Operation, Administration and Maintenance (Management) (OAM). A single network node may provide multiple functions. Communication with an external network (e.g., the Internet) may also be performed via the DN.

[0237] The user terminal 20 may be a terminal that supports at least one of communication methods such as LTE, LTE-A, and 5G.

[0238] An Orthogonal Frequency Division Multiplexing (OFDM)-based radio access scheme may be used in the wireless communication system 1. For example, Cyclic Prefix OFDM (CP-OFDM), Discrete Fourier Transform Spread OFDM (DFT-s-OFDM), Orthogonal Frequency Division Multiple Access (OFDMA), Single Carrier Frequency Division Multiple Access (SC-FDMA), or the like may be used in at least one of the downlink (DL) and uplink (UL).

[0239] The radio access scheme may also be called a waveform. Note that in the wireless communication system 1, other radio access schemes (e.g., other single-carrier transmission schemes, other multi-carrier transmission schemes) may be used as the UL and DL radio access schemes.

[0240] In the wireless communication system 1, a downlink shared channel (Physical Downlink Shared Channel (PDSCH)) shared by each user terminal 20, a broadcast channel (Physical Broadcast Channel (PBCH)), a downlink control channel (Physical Downlink Control Channel (PDCCH)), etc. may be used as the downlink channel.

[0241] Furthermore, in the wireless communication system 1, an uplink shared channel (Physical Uplink Shared Channel (PUSCH)) shared by each user terminal 20, an uplink control channel (Physical Uplink Control Channel (PUCCH)), a random access channel (Physical Random Access Channel (PRACH)), or the like may be used as an uplink channel.

[0242] The PDSCH transmits user data, higher layer control information, a System Information Block (SIB), etc. The PUSCH may transmit user data, higher layer control information, etc. Furthermore, the PBCH may transmit a Master Information Block (MIB).

[0243] Lower layer control information may be transmitted by the PDCCH. The lower layer control information may include, for example, Downlink Control Information (DCI) including scheduling information for at least one of the PDSCH and the PUSCH.

[0244] Note that the DCI for scheduling the PDSCH may be referred to as a DL assignment, a DL DCI, etc., and the DCI for scheduling the PUSCH may be referred to as a UL grant, a UL DCI, etc. Note that the PDSCH may be replaced with DL data, and the PUSCH may be replaced with UL data.

[0245] A control resource set (CORESET) and a search space may be used to detect the PDCCH. The CORESET corresponds to resources for searching for DCI. The search space corresponds to a search region and a search method for PDCCH candidates. One CORESET may be associated with one or more search spaces. The UE may monitor the CORESET associated with a certain search space based on the search space configuration.

[0246] One search space may correspond to PDCCH candidates corresponding to one or more aggregation levels. One or more search spaces may be referred to as a search space set. Note that the terms "search space," "search space set," "search space configuration," "search space set configuration," "CORESET," "CORESET configuration," and the like in the present disclosure may be read interchangeably.

[0247] The PUCCH may transmit uplink control information (UCI) including at least one of channel state information (CSI), delivery confirmation information (which may be called, for example, Hybrid Automatic Repeat reQuest ACKnowledgement (HARQ-ACK), ACK / NACK, etc.), and scheduling request (SR). The PRACH may transmit a random access preamble for establishing a connection with a cell.

[0248] In the present disclosure, downlink, uplink, etc. may be expressed without adding "link." Also, various channels may be expressed without adding "Physical" to the beginning.

[0249] In the wireless communication system 1, a synchronization signal (SS), a downlink reference signal (DL-RS), etc. may be transmitted. In the wireless communication system 1, as the DL-RS, a cell-specific reference signal (CRS), a channel state information reference signal (CSI-RS), a demodulation reference signal (DMRS), a positioning reference signal (PRS), a phase tracking reference signal (PTRS), etc. may be transmitted.

[0250] The synchronization signal may be, for example, at least one of a Primary Synchronization Signal (PSS) and a Secondary Synchronization Signal (SSS). A signal block including an SS (PSS, SSS) and a PBCH (and a DMRS for the PBCH) may be referred to as an SS / PBCH block, an SS Block (SSB), or the like. Note that the SS, SSB, and the like may also be referred to as a reference signal.

[0251] Furthermore, in the wireless communication system 1, a sounding reference signal (SRS), a demodulation reference signal (DMRS), or the like may be transmitted as an uplink reference signal (UL-RS). Note that the DMRS may also be called a user equipment-specific reference signal (UE-specific reference signal).

[0252] (Base Station) Fig. 17 is a diagram showing an example of the configuration of a base station according to an embodiment. The base station 10 includes a control unit 110, a transceiver unit 120, a transceiver antenna 130, and a transmission line interface 140. Note that the base station may include one or more of each of the control unit 110, the transceiver unit 120, the transceiver antenna 130, and the transmission line interface 140.

[0253] In this example, the functional blocks of the characteristic parts of the present embodiment are mainly shown, and it may be assumed that the base station 10 also has other functional blocks necessary for wireless communication. Some of the processing of each unit described below may be omitted.

[0254] The control unit 110 performs overall control of the base station 10. The control unit 110 can be configured from a controller, a control circuit, and the like that are explained based on common understanding in the technical field to which the present disclosure relates.

[0255] The control unit 110 may control signal generation, scheduling (e.g., resource allocation, mapping), etc. The control unit 110 may control transmission and reception using the transceiver unit 120, the transceiver antenna 130, and the transmission path interface 140, measurement, etc. The control unit 110 may generate data, control information, sequences, etc. to be transmitted as signals, and transfer them to the transceiver unit 120. The control unit 110 may perform call processing (setting up, releasing, etc.) of communication channels, status management of the base station 10, management of radio resources, etc.

[0256] The transceiver unit 120 may include a baseband unit 121, a radio frequency (RF) unit 122, and a measurement unit 123. The baseband unit 121 may include a transmission processing unit 1211 and a reception processing unit 1212. The transceiver unit 120 may be configured with a transmitter / receiver, an RF circuit, a baseband circuit, a filter, a phase shifter, a measurement circuit, a transceiver circuit, etc., which are described based on common understanding in the technical field related to the present disclosure.

[0257] The transmitting / receiving unit 120 may be configured as an integrated transmitting / receiving unit, or may be configured from a transmitting unit and a receiving unit. The transmitting unit may be configured from a transmission processing unit 1211 and an RF unit 122. The receiving unit may be configured from a reception processing unit 1212, the RF unit 122, and a measurement unit 123.

[0258] The transmitting and receiving antenna 130 can be configured from an antenna described based on common understanding in the technical field to which the present disclosure relates, such as an array antenna.

[0259] The transceiver 120 may transmit the above-mentioned downlink channel, synchronization signal, downlink reference signal, etc. The transceiver 120 may receive the above-mentioned uplink channel, uplink reference signal, etc.

[0260] The transceiver 120 may form at least one of the transmit beam and the receive beam using digital beamforming (e.g., precoding), analog beamforming (e.g., phase rotation), or the like.

[0261] The transmitter / receiver unit 120 (transmission processing unit 1211) may perform Packet Data Convergence Protocol (PDCP) layer processing, Radio Link Control (RLC) layer processing (e.g., RLC retransmission control), Medium Access Control (MAC) layer processing (e.g., HARQ retransmission control), etc. on data, control information, etc. obtained from the control unit 110, and generate a bit string to be transmitted.

[0262] The transmitter / receiver unit 120 (transmission processing unit 1211) may perform transmission processing such as channel coding (which may include error correction coding), modulation, mapping, filtering, Discrete Fourier Transform (DFT) processing (if necessary), Inverse Fast Fourier Transform (IFFT) processing, precoding, and digital-to-analog conversion on the bit string to be transmitted, and output a baseband signal.

[0263] The transceiver unit 120 (RF unit 122) may perform modulation, filtering, amplification, etc. on the baseband signal to a radio frequency band, and transmit the radio frequency band signal via the transceiver antenna 130.

[0264] On the other hand, the transceiver unit 120 (RF unit 122) may perform amplification, filtering, demodulation to a baseband signal, etc. on the radio frequency band signal received by the transceiver antenna 130.

[0265] The transceiver 120 (reception processing unit 1212) may apply reception processing such as analog-to-digital conversion, Fast Fourier Transform (FFT) processing, Inverse Discrete Fourier Transform (IDFT) processing (if necessary), filtering, demapping, demodulation, decoding (which may include error correction decoding), MAC layer processing, RLC layer processing, and PDCP layer processing to the acquired baseband signal, thereby acquiring user data, etc.

[0266] The transceiver 120 (measurement unit 123) may perform measurements on the received signal. For example, the measurement unit 123 may perform Radio Resource Management (RRM) measurements, Channel State Information (CSI) measurements, etc. based on the received signal. The measurement unit 123 may measure received power (e.g., Reference Signal Received Power (RSRP)), received quality (e.g., Reference Signal Received Quality (RSRQ), Signal to Interference plus Noise Ratio (SINR), Signal to Noise Ratio (SNR)), signal strength (e.g., Received Signal Strength Indicator (RSSI)), propagation path information (e.g., CSI), etc. The measurement results may be output to the control unit 110.

[0267] The transmission path interface 140 may transmit and receive signals (backhaul signaling) between devices included in the core network 30 (e.g., network nodes that provide NF), other base stations 10, etc., and may acquire and transmit user data (user plane data), control plane data, etc. for the user terminal 20.

[0268] The transmitting section and receiving section of the base station 10 in the present disclosure may be configured by at least one of the transmitting / receiving section 120, the transmitting / receiving antenna 130, and the transmission path interface 140.

[0269] The base station 10 may be separated into three elements: a radio unit (RU), a distributed unit (DU), and a central unit (CU). For example, the RU may implement RF processing (digital beamforming, digital-to-analog conversion, analog beamforming, etc.) and lower-level functions of the physical layer (precoding, IFFT, FFT, etc.). The DU may implement higher-level functions of the physical layer (coding to resource element mapping, etc.), MAC layer functions, and RLC layer functions. The CU may implement the functions of the PDCP layer, Service Data Adaptation Protocol (SDAP) layer, and RRC layer.

[0270] In the present disclosure, the base station 10 may include a single device that realizes all of the functions of the RU, DU, and CU, or may include multiple devices that each realize some of the functions of the RU, DU, and CU and are connected to each other. In the present disclosure, the base station 10 may be interchangeably read as RU / DU / CU.

[0271] The transceiver 120 may receive information about a period related to offline engineering and transmit instructions related to the execution of offline engineering. The controller 110 may use at least one of the information and the instructions to instruct the execution of model activation.

[0272] (User Terminal) Fig. 18 is a diagram showing an example of the configuration of a user terminal according to one embodiment. The user terminal 20 includes a control unit 210, a transceiver unit 220, and a transceiver antenna 230. Note that the user terminal 20 may include one or more of each of the control unit 210, the transceiver unit 220, and the transceiver antenna 230.

[0273] In this example, the functional blocks of the characteristic parts of the present embodiment are mainly shown, and it may be assumed that the user terminal 20 also has other functional blocks necessary for wireless communication. Some of the processing of each unit described below may be omitted.

[0274] The control unit 210 performs overall control of the user terminal 20. The control unit 210 can be configured from a controller, a control circuit, etc., which are described based on common understanding in the technical field to which the present disclosure relates.

[0275] The control unit 210 may control signal generation, mapping, etc. The control unit 210 may control transmission and reception, measurement, etc. using the transceiver unit 220 and the transceiver antenna 230. The control unit 210 may generate data, control information, sequences, etc. to be transmitted as signals and transfer them to the transceiver unit 220.

[0276] The transceiver unit 220 may include a baseband unit 221, an RF unit 222, and a measurement unit 223. The baseband unit 221 may include a transmission processing unit 2211 and a reception processing unit 2212. The transceiver unit 220 may be configured with a transmitter / receiver, an RF circuit, a baseband circuit, a filter, a phase shifter, a measurement circuit, a transceiver circuit, etc., which are described based on common understanding in the technical field related to the present disclosure.

[0277] The transmitting / receiving unit 220 may be configured as an integrated transmitting / receiving unit, or may be composed of a transmitting unit and a receiving unit. The transmitting unit may be composed of a transmission processing unit 2211 and an RF unit 222. The receiving unit may be composed of a reception processing unit 2212, an RF unit 222, and a measurement unit 223.

[0278] The transmitting / receiving antenna 230 can be configured from an antenna described based on common understanding in the technical field to which the present disclosure relates, such as an array antenna.

[0279] The transceiver 220 may receive the above-mentioned downlink channel, synchronization signal, downlink reference signal, etc. The transceiver 220 may transmit the above-mentioned uplink channel, uplink reference signal, etc.

[0280] The transceiver unit 220 may form at least one of the transmit beam and the receive beam using digital beamforming (e.g., precoding), analog beamforming (e.g., phase rotation), or the like.

[0281] The transceiver unit 220 (transmission processing unit 2211) may perform PDCP layer processing, RLC layer processing (e.g., RLC retransmission control), MAC layer processing (e.g., HARQ retransmission control), etc. on data, control information, etc. obtained from the control unit 210, and generate a bit string to be transmitted.

[0282] The transmitter / receiver unit 220 (transmission processing unit 2211) may perform transmission processing such as channel coding (which may include error correction coding), modulation, mapping, filtering, DFT processing (if necessary), IFFT processing, precoding, and digital-to-analog conversion on the bit string to be transmitted, and output a baseband signal.

[0283] Whether or not to apply DFT processing may be based on the setting of transform precoding. When transform precoding is enabled for a certain channel (e.g., PUSCH), the transceiver unit 220 (transmission processing unit 2211) may perform DFT processing as the transmission processing to transmit the channel using a DFT-s-OFDM waveform, and if not, it may not be necessary to perform DFT processing as the transmission processing.

[0284] The transceiver unit 220 (RF unit 222) may perform modulation, filtering, amplification, etc. on the baseband signal to a radio frequency band, and transmit the radio frequency band signal via the transceiver antenna 230.

[0285] On the other hand, the transceiver unit 220 (RF unit 222) may perform amplification, filtering, demodulation to a baseband signal, etc. on the radio frequency band signal received by the transceiver antenna 230.

[0286] The transceiver unit 220 (reception processing unit 2212) may apply reception processing such as analog-to-digital conversion, FFT processing, IDFT processing (if necessary), filtering, demapping, demodulation, decoding (which may include error correction decoding), MAC layer processing, RLC layer processing, and PDCP layer processing to the acquired baseband signal, and acquire user data, etc.

[0287] The transceiver 220 (measurement unit 223) may perform measurements on the received signal. For example, the measurement unit 223 may perform RRM measurements, CSI measurements, etc. based on the received signal. The measurement unit 223 may measure received power (e.g., RSRP), received quality (e.g., RSRQ, SINR, SNR), signal strength (e.g., RSSI), propagation path information (e.g., CSI), etc. The measurement results may be output to the control unit 210.

[0288] The measurement unit 223 may derive channel measurements for CSI calculation based on the channel measurement resources. The channel measurement resources may be, for example, non-zero power (NZP) CSI-RS resources. The measurement unit 223 may also derive interference measurements for CSI calculation based on the interference measurement resources. The interference measurement resources may be at least one of an NZP CSI-RS resource for interference measurement, a CSI-Interference Measurement (IM) resource, etc. Note that CSI-IM may be referred to as CSI-Interference Management (IM) or may be interchangeably read as Zero Power (ZP) CSI-RS. Note that in the present disclosure, CSI-RS, NZP CSI-RS, ZP CSI-RS, CSI-IM, CSI-SSB, etc. may be interchangeably read as interchangeable.

[0289] The transmitting unit and receiving unit of the user terminal 20 in the present disclosure may be configured by at least one of the transmitting / receiving unit 220 and the transmitting / receiving antenna 230.

[0290] The receiving unit 220 may transmit information about a period related to offline engineering and receive instructions about performing offline engineering. The control unit 210 may activate a model based on at least one of the information and the instructions.

[0291] The information may include information regarding a period of time between the time the model and / or information about the model is received and the time at which the model or corresponding functionality can be activated.

[0292] The instructions may include information regarding requirements for a time period from the time the model and / or information about the model is received until the time the model or corresponding functionality can be activated.

[0293] The control unit 210 does not need to assume that the instruction specifies a period shorter than the period corresponding to the information.

[0294] (Hardware Configuration) Note that the block diagrams used to explain the above embodiments show functional blocks. These functional blocks (components) are realized by any combination of at least one of hardware and software. Furthermore, the method for realizing each functional block is not particularly limited. That is, each functional block may be realized using a single device that is physically or logically coupled, or may be realized using two or more physically or logically separated devices that are directly or indirectly connected (for example, using wires, wirelessly, etc.) and these multiple devices. The functional block may be realized by combining software with the single device or the multiple devices.

[0295] Here, the functions include, but are not limited to, judgment, determination, judgment, calculation, computation, processing, derivation, investigation, search, confirmation, reception, transmission, output, access, resolution, selection, election, establishment, comparison, assumption, expectation, deeming, broadcasting, notifying, communicating, forwarding, configuring, reconfiguring, allocating, mapping, and assignment. For example, a functional block (component) that performs transmission may be called a transmitting unit, transmitter, etc. As described above, the implementation method of each is not particularly limited.

[0296] For example, a base station, a user terminal, etc. according to an embodiment of the present disclosure may function as a computer that performs processing of the wireless communication method of the present disclosure. Fig. 19 is a diagram illustrating an example of the hardware configuration of a base station and a user terminal according to an embodiment. The above-described base station 10 and user terminal 20 may be physically configured as a computer device including a processor 1001, a memory 1002, a storage 1003, a communication device 1004, an input device 1005, an output device 1006, a bus 1007, etc.

[0297] In the present disclosure, the terms apparatus, circuit, device, section, unit, etc. may be used interchangeably. The hardware configurations of the base station 10 and the user terminal 20 may be configured to include one or more of the devices shown in the drawings, or may be configured to exclude some of the devices.

[0298] For example, although only one processor 1001 is shown, there may be multiple processors. Furthermore, processing may be performed by one processor, or processing may be performed by two or more processors simultaneously, serially, or in other ways. Furthermore, processor 1001 may be implemented by one or more chips.

[0299] Each function in the base station 10 and the user terminal 20 is realized, for example, by loading specified software (programs) onto hardware such as a processor 1001 and a memory 1002, causing the processor 1001 to perform calculations, control communication via the communication device 1004, and control at least one of reading and writing data in the memory 1002 and the storage 1003.

[0300] The processor 1001, for example, runs an operating system to control the entire computer. The processor 1001 may be configured as a central processing unit (CPU) including an interface with peripheral devices, a control device, an arithmetic unit, a register, etc. For example, at least a part of the above-mentioned control unit 110 (210), transceiver unit 120 (220), etc. may be realized by the processor 1001.

[0301] The processor 1001 also reads programs (program codes), software modules, data, etc. from at least one of the storage 1003 and the communication device 1004 into the memory 1002 and executes various processes in accordance with these. The programs used are those that cause a computer to execute at least some of the operations described in the above-described embodiments. For example, the control unit 110 (210) may be implemented by a control program stored in the memory 1002 and running on the processor 1001, and the other functional blocks may be implemented in a similar manner.

[0302] The memory 1002 is a computer-readable recording medium and may be configured by at least one of, for example, Read Only Memory (ROM), Erasable Programmable ROM (EPROM), Electrically EEPROM (EEPROM), Random Access Memory (RAM), or other suitable storage medium. The memory 1002 may also be referred to as a register, cache, main memory, etc. The memory 1002 may store executable programs (program codes), software modules, etc. for implementing a wireless communication method according to an embodiment of the present disclosure.

[0303] Storage 1003 is a computer-readable recording medium and may be composed of at least one of, for example, a flexible disk, a floppy disk, a magneto-optical disk (e.g., a compact disc (e.g., a Compact Disc ROM (CD-ROM)), a digital versatile disc, a Blu-ray disc), a removable disk, a hard disk drive, a smart card, a flash memory device (e.g., a card, a stick, a key drive), a magnetic stripe, a database, a server, or other suitable storage medium. Storage 1003 may also be referred to as an auxiliary storage device.

[0304] The communication device 1004 is hardware (transmission / reception device) for communicating between computers via at least one of a wired network and a wireless network, and is also referred to as, for example, a network device, a network controller, a network card, or a communication module. The communication device 1004 may be configured to include a high-frequency switch, a duplexer, a filter, a frequency synthesizer, etc. to realize at least one of frequency division duplex (FDD) and time division duplex (TDD). For example, the above-mentioned transmission / reception unit 120 (220), transmission / reception antenna 130 (230), etc. may be realized by the communication device 1004. The transmission / reception unit 120 (220) may be implemented as a transmission unit 120a (220a) and a reception unit 120b (220b) that are physically or logically separated.

[0305] The input device 1005 is an input device (e.g., a keyboard, a mouse, a microphone, a switch, a button, a sensor, etc.) that accepts input from the outside. The output device 1006 is an output device (e.g., a display, a speaker, a light emitting diode (LED) lamp, etc.) that outputs to the outside. Note that the input device 1005 and the output device 1006 may be integrated into one device (e.g., a touch panel).

[0306] Furthermore, each device, such as the processor 1001 and the memory 1002, is connected by a bus 1007 for communicating information. The bus 1007 may be configured using a single bus, or may be configured using different buses between each device.

[0307] Furthermore, the base station 10 and the user terminal 20 may be configured to include hardware such as a microprocessor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a programmable logic device (PLD), or a field programmable gate array (FPGA), and some or all of the functional blocks may be realized using this hardware. For example, the processor 1001 may be implemented using at least one of these pieces of hardware.

[0308] In addition, the devices included in the core network 30 (for example, network nodes that provide NF) may also be realized by the above-mentioned functional block / hardware configuration.

[0309] (Modifications) Note that terms described in the present disclosure and terms necessary for understanding the present disclosure may be replaced with terms having the same or similar meanings. For example, a channel, a symbol, and a signal (signal or signaling) may be interchangeable. A signal may also be a message. A reference signal may be abbreviated as RS, and may also be called a pilot, pilot signal, etc. depending on the applicable standard. A component carrier (CC) may also be called a cell, frequency carrier, carrier frequency, etc.

[0310] A radio frame may be composed of one or more periods (frames) in the time domain. Each of the one or more periods (frames) constituting a radio frame may be called a subframe. Furthermore, a subframe may be composed of one or more slots in the time domain. A subframe may have a fixed time length (e.g., 1 ms) that is independent of numerology.

[0311] Here, the numerology may be a communication parameter applied to at least one of transmission and reception of a signal or channel, and may indicate at least one of, for example, Subcarrier Spacing (SCS), bandwidth, symbol length, cyclic prefix length, Transmission Time Interval (TTI), number of symbols per TTI, radio frame structure, specific filtering performed by a transceiver in the frequency domain, and specific windowing performed by a transceiver in the time domain.

[0312] A slot may be composed of one or more symbols (such as an Orthogonal Frequency Division Multiplexing (OFDM) symbol or a Single Carrier Frequency Division Multiple Access (SC-FDMA) symbol) in the time domain. A slot may also be a time unit based on numerology.

[0313] A slot may include multiple minislots. Each minislot may consist of one or multiple symbols in the time domain. A minislot may also be called a subslot. A minislot may consist of fewer symbols than a slot. A PDSCH (or PUSCH) transmitted in a time unit larger than a minislot may be called PDSCH (PUSCH) mapping type A. A PDSCH (or PUSCH) transmitted using a minislot may be called PDSCH (PUSCH) mapping type B.

[0314] A radio frame, a subframe, a slot, a minislot, and a symbol all represent time units for transmitting signals. The radio frame, the subframe, the slot, the minislot, and the symbol may be referred to by other names corresponding to the radio frame, the subframe, the slot, the minislot, and the symbol. Note that the time units such as a frame, a subframe, a slot, a minislot, and a symbol in the present disclosure may be interchangeable.

[0315] For example, one subframe may be referred to as a TTI, or multiple consecutive subframes may be referred to as a TTI, or one slot or one minislot may be referred to as a TTI. That is, at least one of the subframe and the TTI may be a subframe (1 ms) in existing LTE, a period shorter than 1 ms (for example, 1-13 symbols), or a period longer than 1 ms. Note that the unit representing the TTI may be called a slot, minislot, etc. instead of a subframe.

[0316] Here, TTI refers to, for example, the smallest time unit for scheduling in wireless communication. For example, in an LTE system, a base station performs scheduling to allocate radio resources (such as frequency bandwidth and transmission power that can be used by each user terminal) to each user terminal in TTI units. Note that the definition of TTI is not limited to this.

[0317] The TTI may be a transmission time unit for a channel-encoded data packet (transport block), a code block, a code word, etc., or may be a processing unit for scheduling, link adaptation, etc. When a TTI is given, the time interval (e.g., the number of symbols) to which a transport block, a code block, a code word, etc. is actually mapped may be shorter than the TTI.

[0318] When one slot or one minislot is called a TTI, one or more TTIs (i.e., one or more slots or one or more minislots) may be the minimum time unit for scheduling. Also, the number of slots (minislots) constituting the minimum time unit for scheduling may be controlled.

[0319] A TTI having a time length of 1 ms may be called a regular TTI (TTI in 3GPP Rel. 8-12), normal TTI, long TTI, regular subframe, normal subframe, long subframe, slot, etc. A TTI shorter than a regular TTI may be called a shortened TTI, short TTI, partial or fractional TTI, shortened subframe, short subframe, minislot, subslot, slot, etc.

[0320] In addition, a long TTI (e.g., a normal TTI, a subframe, etc.) may be interpreted as a TTI having a time length of more than 1 ms, and a short TTI (e.g., a shortened TTI, etc.) may be interpreted as a TTI having a TTI length shorter than the TTI length of a long TTI and greater than or equal to 1 ms.

[0321] A resource block (RB) is a resource allocation unit in the time domain and the frequency domain, and may include one or more consecutive subcarriers in the frequency domain. The number of subcarriers included in an RB may be the same regardless of numerology, for example, 12. The number of subcarriers included in an RB may be determined based on numerology.

[0322] In addition, an RB may include one or more symbols in the time domain and may have a length of one slot, one minislot, one subframe, or one TTI, each of which may be composed of one or more resource blocks.

[0323] In addition, one or more RBs may be referred to as a physical resource block (PRB), a sub-carrier group (SCG), a resource element group (REG), a PRB pair, an RB pair, etc.

[0324] Furthermore, a resource block may be composed of one or more resource elements (REs). For example, one RE may be a radio resource region of one subcarrier and one symbol.

[0325] A Bandwidth Part (BWP), which may also be referred to as a partial bandwidth, may represent a subset of contiguous common resource blocks (RBs) for a given numerology on a given carrier, where the common RBs may be identified by their index relative to a Common Reference Point of the carrier. PRBs may be defined in a BWP and numbered within the BWP.

[0326] The BWP may include a UL BWP (BWP for UL) and a DL BWP (BWP for DL). One or more BWPs may be configured for a UE within one carrier.

[0327] At least one of the configured BWPs may be active, and the UE may not expect to transmit or receive a given signal / channel outside the active BWP. Note that the terms "cell," "carrier," etc. in this disclosure may be read as "BWP."

[0328] The above-described structures of radio frames, subframes, slots, minislots, symbols, etc. are merely examples. For example, the number of subframes included in a radio frame, the number of slots per subframe or radio frame, the number of minislots included in a slot, the number of symbols and RBs included in a slot or minislot, the number of subcarriers included in an RB, the number of symbols in a TTI, the symbol length, the cyclic prefix (CP) length, etc. may be changed in various ways.

[0329] Furthermore, the information, parameters, etc. described in the present disclosure may be expressed using absolute values, may be expressed using relative values ​​from a predetermined value, or may be expressed using other corresponding information. For example, a radio resource may be indicated by a predetermined index.

[0330] The names used for parameters and the like in this disclosure are not intended to be limiting in any way. Furthermore, the mathematical expressions and the like using these parameters may differ from those explicitly disclosed in this disclosure. The various channels (PUCCH, PDCCH, etc.) and information elements may be identified by any suitable names, and therefore the various names assigned to these various channels and information elements are not intended to be limiting in any way.

[0331] The information, signals, etc. described in this disclosure may be represented using any of a variety of different technologies. For example, data, instructions, commands, information, signals, bits, symbols, chips, etc. that may be referred to throughout the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields or magnetic particles, optical fields or photons, or any combination thereof.

[0332] Furthermore, information, signals, etc. may be output from a higher layer to a lower layer and / or from a lower layer to a higher layer. Information, signals, etc. may be input / output via multiple network nodes.

[0333] Input and output information, signals, etc. may be stored in a specific location (for example, memory) or may be managed using a management table. Input and output information, signals, etc. may be overwritten, updated, or added. Output information, signals, etc. may be deleted. Input information, signals, etc. may be transmitted to another device.

[0334] With respect to any information (e.g., variables, constants, parameters) described in the present disclosure, even if not specifically stated in the above embodiments, any first device (e.g., UE / base station) may notify any second device (e.g., base station / UE) of information indicating / specifying (or relating to) the value of the any information.

[0335] The notification of information is not limited to the aspects / embodiments described in the present disclosure, and may be performed using other methods. For example, the notification of information in the present disclosure may be performed by physical layer signaling (e.g., Downlink Control Information (DCI) and Uplink Control Information (UCI)), higher layer signaling (e.g., Radio Resource Control (RRC) signaling, broadcast information (Master Information Block (MIB) and System Information Block (SIB)), Medium Access Control (MAC) signaling), other signals, or a combination thereof.

[0336] Note that the physical layer signaling may be referred to as Layer 1 / Layer 2 (L1 / L2) control information (L1 / L2 control signal), L1 control information (L1 control signal), etc. Furthermore, the RRC signaling may be referred to as an RRC message, such as an RRC Connection Setup message or an RRC Connection Reconfiguration message. Furthermore, the MAC signaling may be notified using, for example, a MAC Control Element (CE).

[0337] Furthermore, notification of specified information (e.g., notification that "it is X") is not limited to explicit notification, but may be made implicitly (e.g., by not notifying the specified information or by notifying other information).

[0338] The determination may be made by a value represented by one bit (0 or 1), by a Boolean value represented by true or false, or by a comparison of numerical values ​​(e.g., comparison with a predetermined value).

[0339] Software shall be construed broadly to mean instructions, instruction sets, code, code segments, program code, programs, subprograms, software modules, applications, software applications, software packages, routines, subroutines, objects, executable files, threads of execution, procedures, functions, etc., whether referred to as software, firmware, middleware, microcode, hardware description language, or otherwise.

[0340] Software, instructions, information, etc. may also be transmitted or received over a transmission medium. For example, if software is transmitted from a website, server, or other remote source using wired technologies (such as coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL)), and / or wireless technologies (such as infrared, microwave), these wired and / or wireless technologies are included within the definition of transmission media.

[0341] As used in this disclosure, the terms "system" and "network" may be used interchangeably. A "network" may refer to devices included in the network (e.g., base stations).

[0342] In this disclosure, terms such as "precoding," "precoder," "weight (precoding weight)," "Quasi-Co-Location (QCL)," "Transmission Configuration Indication state (TCI state)," "spatial relation," "spatial domain filter," "transmit power," "phase rotation," "antenna port," "layer," "number of layers," "rank," "resource," "resource set," "beam," "beam width," "beam angle," "antenna," "antenna element," "panel," "UE panel," "transmitting entity," "receiving entity," etc. may be used interchangeably.

[0343] In the present disclosure, the term "antenna port" may be interchangeably read as an antenna port for any signal / channel (e.g., a demodulation reference signal (DMRS) port). In the present disclosure, the term "resource" may be interchangeably read as a resource for any signal / channel (e.g., a reference signal resource, an SRS resource, etc.). The resource may include time / frequency / code / space / power resources. The spatial domain transmission filter may include at least one of a spatial domain transmission filter and a spatial domain reception filter.

[0344] The group may include, for example, at least one of a spatial relationship group, a Code Division Multiplexing (CDM) group, a Reference Signal (RS) group, a Control Resource Set (CORESET) group, a PUCCH group, an antenna port group (e.g., a DMRS port group), a layer group, a resource group, a beam group, an antenna group, a panel group, and the like.

[0345] In addition, in the present disclosure, beam, SRS Resource Indicator (SRI), CORESET, CORESET pool, PDSCH, PUSCH, codeword (CW), transport block (TB), RS, etc. may be read as interchangeable terms.

[0346] In addition, in the present disclosure, the terms TCI state, downlink TCI state (DL TCI state), uplink TCI state (UL TCI state), unified TCI state, common TCI state, joint TCI state, etc. may be read interchangeably.

[0347] Furthermore, in the present disclosure, terms such as "QCL," "QCL assumption," "QCL relationship," "QCL type information," "QCL property / properties," "specific QCL type (e.g., Type A, Type D) property," and "specific QCL type (e.g., Type A, Type D)" may be interchangeable.

[0348] In the present disclosure, terms such as index, identifier (ID), indicator, indication, and resource ID may be interchangeable. In the present disclosure, terms such as sequence, list, set, group, cluster, and subset may be interchangeable.

[0349] Furthermore, the spatial relationship information identifier (ID) (TCI state ID) and the spatial relationship information (TCI state) may be interchangeable. The "spatial relationship information (TCI state)" may be interchangeable with "set of spatial relationship information (TCI state)", "one or more pieces of spatial relationship information", etc. The TCI state and the TCI may be interchangeable. The spatial relationship information and the spatial relationship may be interchangeable.

[0350] In the present disclosure, terms such as "base station (BS)," "radio base station," "fixed station," "NodeB," "eNB (eNodeB)," "gNB (gNodeB)," "access point," "transmission point (TP)," "reception point (RP)," "transmission / reception point (TRP)," "panel," "cell," "sector," "cell group," "carrier," "component carrier," etc. may be used interchangeably. Base stations may also be referred to by terms such as macrocell, small cell, femtocell, picocell, etc.

[0351] A base station can accommodate one or more (e.g., three) cells. When a base station accommodates multiple cells, the overall coverage area of ​​the base station can be partitioned into multiple smaller areas, and each smaller area can be provided with communication service by a base station subsystem (e.g., a small indoor base station (Remote Radio Head (RRH))). The terms "cell" or "sector" refer to part or all of the coverage area of ​​a base station and / or base station subsystem that provides communication service within that coverage.

[0352] In the present disclosure, a base station transmitting information to a terminal may be interpreted as the base station instructing the terminal to control / operate based on the information.

[0353] In this disclosure, the terms "Mobile Station (MS)," "user terminal," "User Equipment (UE)," "terminal," etc. may be used interchangeably.

[0354] A mobile station may also be referred to as a subscriber station, mobile unit, subscriber unit, wireless unit, remote unit, mobile device, wireless device, wireless communication device, remote device, mobile subscriber station, access terminal, mobile terminal, wireless terminal, remote terminal, handset, user agent, mobile client, client, or some other suitable terminology.

[0355] At least one of the base station and the mobile station may be called a transmitting device, a receiving device, a wireless communication device, etc. Note that at least one of the base station and the mobile station may be a device mounted on a moving object, the moving object itself, etc.

[0356] The mobile body is a movable object that can move at any speed and naturally includes cases where the mobile body is stationary. Examples of the mobile body include, but are not limited to, vehicles, transport vehicles, automobiles, motorcycles, bicycles, connected cars, excavators, bulldozers, wheel loaders, dump trucks, forklifts, trains, buses, handcars, rickshaws, ships and other watercraft, airplanes, rockets, satellites, drones, multicopters, quadcopters, balloons, and objects mounted thereon. The mobile body may also be a mobile body that moves autonomously based on an operation command.

[0357] The mobile object may be a vehicle (e.g., a car, an airplane, etc.), an unmanned mobile object (e.g., a drone, an autonomous vehicle, etc.), or a robot (manned or unmanned). Note that at least one of the base station and the mobile station may also include devices that do not necessarily move during communication operations. For example, at least one of the base station and the mobile station may be an Internet of Things (IoT) device such as a sensor.

[0358] 20 is a diagram showing an example of a vehicle according to an embodiment. The vehicle 40 includes a drive unit 41, a steering unit 42, an accelerator pedal 43, a brake pedal 44, a shift lever 45, left and right front wheels 46, left and right rear wheels 47, axles 48, an electronic control unit 49, various sensors (including a current sensor 50, an RPM sensor 51, an air pressure sensor 52, a vehicle speed sensor 53, an acceleration sensor 54, an accelerator pedal sensor 55, a brake pedal sensor 56, a shift lever sensor 57, and an object detection sensor 58), an information service unit 59, and a communication module 60.

[0359] The drive unit 41 is configured with at least one of an engine, a motor, and a hybrid of an engine and a motor, for example. The steering unit 42 includes at least a steering wheel (also called a handle) and is configured to steer at least one of the front wheels 46 and the rear wheels 47 based on the operation of the steering wheel operated by a user.

[0360] The electronic control unit 49 is composed of a microprocessor 61, memory (ROM, RAM) 62, and a communication port (for example, an input / output (IO) port) 63. Signals are input to the electronic control unit 49 from various sensors 50-58 provided in the vehicle. The electronic control unit 49 may also be called an Electronic Control Unit (ECU).

[0361] The signals from the various sensors 50-58 include a current signal from a current sensor 50 that senses the current of the motor, a rotation speed signal of the front wheels 46 / rear wheels 47 obtained by a rotation speed sensor 51, an air pressure signal of the front wheels 46 / rear wheels 47 obtained by an air pressure sensor 52, a vehicle speed signal obtained by a vehicle speed sensor 53, an acceleration signal obtained by an acceleration sensor 54, a depression amount signal of the accelerator pedal 43 obtained by an accelerator pedal sensor 55, a depression amount signal of the brake pedal 44 obtained by a brake pedal sensor 56, an operation signal of the shift lever 45 obtained by a shift lever sensor 57, and a detection signal for detecting obstacles, vehicles, pedestrians, etc. obtained by an object detection sensor 58.

[0362] The information service unit 59 is composed of various devices, such as a car navigation system, an audio system, speakers, a display, a television, and a radio, for providing (outputting) various information such as driving information, traffic information, and entertainment information, and one or more ECUs for controlling these devices. The information service unit 59 uses information acquired from external devices via the communication module 60 or the like to provide various information / services (e.g., multimedia information / multimedia services) to the occupants of the vehicle 40.

[0363] The information service unit 59 may include input devices (e.g., keyboards, mice, microphones, switches, buttons, sensors, touch panels, etc.) that accept input from the outside, and may also include output devices (e.g., displays, speakers, LED lamps, touch panels, etc.) that output to the outside.

[0364] The driving assistance system unit 64 includes various devices for providing functions to prevent accidents and reduce the driver's driving burden, such as millimeter-wave radar, Light Detection and Ranging (LiDAR), cameras, positioning locators (e.g., Global Navigation Satellite System (GNSS)), map information (e.g., High Definition (HD) maps, Autonomous Vehicle (AV) maps), gyro systems (e.g., Inertial Measurement Units (IMUs), Inertial Navigation Systems (INSs)), artificial intelligence (AI) chips, and AI processors, as well as one or more ECUs that control these devices. The driving assistance system unit 64 also transmits and receives various information via the communication module 60 to realize driving assistance functions or autonomous driving functions.

[0365] The communication module 60 can communicate with the microprocessor 61 and components of the vehicle 40 via the communication port 63. For example, the communication module 60 transmits and receives data (information) via the communication port 63 to and from the drive unit 41, steering unit 42, accelerator pedal 43, brake pedal 44, shift lever 45, left and right front wheels 46, left and right rear wheels 47, axles 48, the microprocessor 61 and memory (ROM, RAM) 62 in the electronic control unit 49, and the various sensors 50-58, which are provided in the vehicle 40.

[0366] The communication module 60 is a communication device that can be controlled by the microprocessor 61 of the electronic control unit 49 and can communicate with an external device. For example, it transmits and receives various information to and from the external device via wireless communication. The communication module 60 may be located either inside or outside the electronic control unit 49. The external device may be, for example, the base station 10 or the user terminal 20 described above. Furthermore, the communication module 60 may be, for example, at least one of the base station 10 and the user terminal 20 described above (or may function as at least one of the base station 10 and the user terminal 20).

[0367] The communication module 60 may transmit at least one of signals from the above-mentioned various sensors 50-58 input to the electronic control unit 49, information obtained based on the signals, and information based on input from the outside (user) obtained via the information service unit 59 to an external device via wireless communication. The electronic control unit 49, the various sensors 50-58, the information service unit 59, etc. may be referred to as input units that accept input. For example, the PUSCH transmitted by the communication module 60 may include information based on the above-mentioned input.

[0368] The communication module 60 receives various information (traffic information, traffic signal information, vehicle distance information, etc.) transmitted from an external device and displays it on an information service unit 59 provided in the vehicle. The information service unit 59 may also be called an output unit that outputs information (for example, outputs information to a device such as a display or speaker based on the PDSCH received by the communication module 60 (or data / information decoded from the PDSCH)).

[0369] Furthermore, the communication module 60 stores various information received from external devices in a memory 62 that can be used by the microprocessor 61. Based on the information stored in the memory 62, the microprocessor 61 may control the drive unit 41, steering unit 42, accelerator pedal 43, brake pedal 44, shift lever 45, left and right front wheels 46, left and right rear wheels 47, axles 48, various sensors 50-58, and the like provided in the vehicle 40.

[0370] Furthermore, a base station in the present disclosure may be read as a user terminal. For example, the aspects / embodiments of the present disclosure may be applied to a configuration in which communication between a base station and a user terminal is replaced with communication between multiple user terminals (which may be called, for example, Device-to-Device (D2D) or Vehicle-to-Everything (V2X)). In this case, the user terminal 20 may be configured to have the functions of the base station 10 described above. Furthermore, terms such as "uplink" and "downlink" may be read as terms corresponding to terminal-to-terminal communication (for example, "sidelink"). For example, terms such as an uplink channel and a downlink channel may be read as a sidelink channel.

[0371] Similarly, the user terminal in the present disclosure may be read as a base station, in which case the base station 10 may be configured to have the functions of the user terminal 20 described above.

[0372] In the present disclosure, an operation described as being performed by a base station may be performed by its upper node in some cases. It is apparent that in a network including one or more network nodes having a base station, various operations performed for communication with a terminal may be performed by the base station, one or more network nodes other than the base station (such as, but not limited to, a Mobility Management Entity (MME), a Serving-Gateway (S-GW), etc.), or a combination thereof.

[0373] Each aspect / embodiment described in this disclosure may be used alone, in combination, or switched depending on the implementation. Furthermore, the order of the processing procedures, sequences, flowcharts, etc. of each aspect / embodiment described in this disclosure may be changed unless inconsistent. For example, the methods described in this disclosure present elements of various steps using an example order, and are not limited to the particular order presented.

[0374] Each aspect / embodiment described in the present disclosure may be a technology other than Long Term Evolution (LTE), LTE-Advanced (LTE-A), LTE-Beyond (LTE-B), SUPER 3G, IMT-Advanced, 4th generation mobile communication system (4G), 5th generation mobile communication system (5G), 6th generation mobile communication system (6G), xth generation mobile communication system (xG (x is, for example, an integer or decimal number)), Future Radio Access (FRA), New-Radio Access Technology (RAT), New Radio (NR), New radio access (NX), Future generation radio access (FX), Global System for Mobile communications (GSM (registered trademark)), CDMA2000, Ultra Mobile Broadband (UMB), IEEE 802.11 (Wi-Fi (registered trademark)), IEEE 802.16 (WiMAX (registered trademark)), IEEE 802.17 (WiMAX (registered trademark)), IEEE 802.19 (WiMAX (registered trademark)), IEEE 802.20 (WiMAX (registered trademark)), IEEE 802.21 (Wi-Fi (registered trademark)), IEEE 802.22 (WiMAX (registered trademark)), IEEE 802.23 (WiMAX (registered trademark)), IEEE 802.24 (WiMAX (registered trademark)), IEEE 802.25 (WiMAX (registered trademark)), IEEE 802.26 (WiMAX (registered trademark)), IEEE 802.27 (WiMAX (registered trademark)), IEEE 802.28 (WiMAX (registered trademark)), IEEE 802.29 (WiMAX (registered trademark)), IEEE 802.30 (WiMAX (registered trademark)), IEEE 802.31 (Wi-Fi (registered trademark)), IEEE 802.32 (WiMAX (registered trademark)), IEEE 802.33 (WiMAX (registered trademark)), IEEE 802. The present invention may be applied to systems that use IEEE 802.20, Ultra-WideBand (UWB), Bluetooth (registered trademark), or other suitable wireless communication methods, or to next-generation systems that are expanded, modified, created, or defined based on these. Furthermore, the present invention may be applied to a combination of multiple systems (e.g., a combination of LTE or LTE-A and 5G).

[0375] As used in this disclosure, the phrase "based on" does not mean "based only on," unless expressly stated otherwise. In other words, the phrase "based on" means both "based only on" and "based at least on."

[0376] As used in this disclosure, any reference to an element using a designation such as "first," "second," etc. does not generally limit the quantity or order of those elements. These designations may be used in this disclosure as a convenient method of distinguishing between two or more elements. Thus, a reference to a first and a second element does not imply that only two elements may be employed or that the first element must in some way precede the second element.

[0377] The term "determining" as used in this disclosure may encompass a wide variety of actions. For example, "determining" may be considered to be judging, calculating, computing, processing, deriving, investigating, looking up, search, inquiry (e.g., looking up in a table, database, or another data structure), ascertaining, etc.

[0378] Additionally, "determining" may be considered to be "determining" receiving (e.g., receiving information), transmitting (e.g., sending information), input, output, accessing (e.g., accessing data in memory), etc.

[0379] Furthermore, "determination" may be considered to be "determining" resolving, selecting, choosing, establishing, comparing, etc. In other words, "determination" may be considered to be "determining" some kind of action. In the present disclosure, "determination" may be read interchangeably with the above-mentioned actions.

[0380] Furthermore, in this disclosure, "determine / determining" may be interchangeably read as "assume / assuming," "expect / expecting," "consider / considering," etc. Furthermore, in this disclosure, "does not expect to do..." may be interchangeably read as "assumes not to do...."

[0381] In the present disclosure, "expect" may be interchangeably read as "be expected." For example, "expect(s) ..." ("..." may be expressed, for example, as a that clause, a to-infinitive, etc.) may be interchangeably read as "be expected ..." or "do ... (if the above "..." is a to-infinitive, a verb with "to")," etc. "does not expect ..." may be interchangeably read as "be not expected ..." or "does not ... (if the above "..." is a to-infinitive, a verb with "to")," etc. Furthermore, "An apparatus A is not expected ..." may be interchangeably read as "an apparatus B other than apparatus A does not expect ... from apparatus A" (for example, if apparatus A is a UE, apparatus B may be a base station).

[0382] The "maximum transmit power" in this disclosure may mean the maximum value of transmit power, the nominal UE maximum transmit power, or the rated UE maximum transmit power.

[0383] As used in this disclosure, the terms "connected," "coupled," or any variation thereof, refer to any direct or indirect connection or coupling between two or more elements, and may include the presence of one or more intermediate elements between two elements that are "connected" or "coupled" to each other. The coupling or connection between elements may be physical, logical, or a combination thereof. For example, "connected" may be read as "access."

[0384] In this disclosure, when two elements are connected, they may be considered to be "connected" or "coupled" to one another using one or more wires, cables, printed electrical connections, etc., as well as using electromagnetic energy having wavelengths in the radio frequency range, microwave range, light (both visible and invisible) range, etc., as some non-limiting and non-exhaustive examples.

[0385] In the present disclosure, the term "A and B are different" may mean "A and B are different from each other." The term may also mean "A and B are each different from C." Terms such as "separate" and "coupled" may also be interpreted in the same way as "different."

[0386] When the terms "include," "including," and variations thereof are used in this disclosure, these terms are intended to be inclusive, similar to the term "comprising." Furthermore, when the term "or" is used in this disclosure, it is not intended to be an exclusive or.

[0387] In this disclosure, where articles are added by translation, such as a, an, and the in English, the disclosure may include that the nouns following these articles are in the plural form.

[0388] In the present disclosure, terms such as "less than or equal to," "less than," "greater than," "more than," "equal to," etc. may be interchangeable. Furthermore, in the present disclosure, terms meaning "good," "bad," "big," "small," "high," "low," "fast," "slow," "wide," "narrow," etc. may be interchangeable, not limited to the positive, comparative, and superlative. Furthermore, in the present disclosure, terms meaning "good," "bad," "big," "small," "high," "low," "fast," "slow," "wide," "narrow," etc. may be interchangeable, not limited to the positive, comparative, and superlative, as expressions with "i-th" (i is an arbitrary integer) attached (for example, "highest" may be interchangeable with "i-th highest").

[0389] In this disclosure, the terms "of," "for," "regarding," "related to," "associated with," etc. may be read interchangeably.

[0390] In the present disclosure, terms such as "when A, B," "if A, (then) B," "B upon A," "B in response to A," "B based on A," "B during / while A," "B before A," "B at (the same time as) / on A," "B after A," "B since A," and "B until A" may be interchangeable. Note that A, B, and the like herein may be replaced with appropriate expressions such as nouns, gerunds, and regular sentences, depending on the context. Note that the time difference between A and B may be approximately zero (immediately after or immediately before). A time offset may also be applied to the time at which A occurs. For example, "A" may be interchangeable with "before / after a time offset at which A occurs." The time offset (eg, one or more symbols / slots) may be predefined or may be specified by the UE based on signaled information.

[0391] In the present disclosure, timing, time, duration, time instance, any time unit (e.g., slot, subslot, symbol, subframe), period, occasion, resource, etc. may be read interchangeably.

[0392] Although the invention according to the present disclosure has been described in detail above, it is clear to those skilled in the art that the invention according to the present disclosure is not limited to the embodiments described in the present disclosure. The description of the present disclosure is for illustrative purposes only and does not impose any limiting meaning on the invention according to the present disclosure.

[0393] This application is based on Japanese Patent Application No. 2024-083247, filed May 22, 2024, the contents of which are incorporated herein in their entirety.

Claims

1. A terminal having a transceiver unit that transmits information regarding a period related to offline engineering and receives instructions regarding the execution of offline engineering, and a control unit that activates a model based on at least one of the information and the instructions.

2. The terminal of claim 1, wherein the information includes information about a period of time from a time when the model and / or information about the model is received to a time when the model or a corresponding function can be activated.

3. The terminal according to claim 1, wherein the instructions include information regarding requirements for a period of time from the time of receiving the model and / or information about the model to the time at which the model or a corresponding function can be activated.

4. The terminal according to claim 1, wherein the control unit does not assume that a period shorter than the period corresponding to the information is instructed by the instruction.

5. A wireless communication method for a terminal, comprising the steps of: transmitting information regarding a period related to offline engineering; and receiving instructions regarding the execution of offline engineering; and performing activation of a model based on at least one of the information and the instructions.

6. A base station having a transceiver unit that receives information regarding a period related to offline engineering and transmits instructions regarding the execution of offline engineering, and a control unit that uses at least one of the information and the instructions to instruct the execution of model activation.

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