Terminal, wireless communication method, and base station

Abstract

A terminal according to one embodiment of the present disclosure includes a reception unit that receives information related to consistency for model identification, and a control unit that applies a specific assumption related to consistency based on the presence or absence of a specific parameter included in the information, the control unit assuming that a characteristic of a reference signal (RS) or a channel corresponding to the specific parameter is consistent in a case where the specific parameter is set or activated.

Description

Technical Field

[0001] This disclosure relates to terminals, wireless communication methods, and base stations in next-generation mobile communication systems. Background Technology

[0002] In Universal Mobile Telecommunications System (UMTS) networks, Long Term Evolution (LTE) was standardized with the aim of achieving higher data rates and lower latency (Non-Patent Document 1). Furthermore, LTE-Advanced (3GPP Rel. 10-14) was standardized with the aim of further increasing capacity and improving the height of LTE (Third Generation Partnership Project (3GPP) Release (Rel.) 8, 9).

[0003] The development of successor systems to LTE is also underway (e.g., also known as the 5th generation mobile communication system (5G), 5G+ (plus), the 6th generation mobile communication system (6G), New Radio (NR), 3GPP Rel.15 and later, etc.).

[0004] Existing technical documents

[0005] Non-patent literature

[0006] Non-patent document 1: 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 Summary of the Invention

[0007] The problem that the invention aims to solve

[0008] Regarding future wireless communication technologies, research is underway to apply artificial intelligence (AI) technologies, such as machine learning (ML), to the control and management of networks / devices.

[0009] As an application of AI models, research is underway on spatial domain downlink (DL) beam prediction, temporal DL beam prediction, and positioning. Such beam prediction methods can also be referred to as AI-based beam prediction (beam reporting), AI-based positioning, and AI-based beam management (BM). Temporal DL beam prediction can also be called temporal channel state information (CSI) prediction.

[0010] In the application of AI in this way, research is underway to introduce various types of lifecycle management (LCM), but there is a lack of sufficient research in this area. This lack of research hinders appropriate overhead reduction, channel estimation, and resource utilization, raising concerns that improvements in communication throughput and quality may be suppressed.

[0011] Therefore, one of the purposes of this disclosure is to provide a terminal, wireless communication method, and base station that can achieve appropriate overhead reduction / channel estimation / resource utilization.

[0012] Methods for solving problems

[0013] One aspect of this disclosure relates to a terminal comprising: a receiving unit for receiving information related to consistency for model recognition; and a control unit for applying a specific assumption related to consistency based on the presence or absence of a specific parameter contained in the information, wherein, when the specific parameter is set or activated, the control unit assumes that the characteristics of a reference signal (RS) or channel corresponding to the specific parameter are consistent.

[0014] Invention Effects

[0015] According to one method of this disclosure, appropriate overhead reduction / channel estimation / resource utilization can be achieved. Attached Figure Description

[0016] Figure 1 This is a diagram illustrating an example of a framework for managing AI models.

[0017] Figure 2This is a diagram illustrating a specific example of an AI model.

[0018] Figure 3 This is a conceptual diagram illustrating an example of an ID-based method for model recognition.

[0019] Figure 4 This is a conceptual diagram illustrating an example of a non-ID-based method for model recognition.

[0020] Figure 5A and Figure 5B This is a diagram illustrating an example of the reception timing (start point) of an ID / consistency indication related to consistency.

[0021] Figure 6A and Figure 6B This is a diagram illustrating an example of the reception timing (end point) of an ID / consistency indication related to consistency.

[0022] Figure 7A and Figure 7B This is a diagram illustrating an example of the reception timing (end point) of an ID / consistency indication related to consistency.

[0023] Figure 8 This is a diagram showing an example of RRC parameters related to CSI report settings.

[0024] Figure 9 This is a diagram illustrating an example of the schematic structure of a wireless communication system according to one embodiment.

[0025] Figure 10 This is a diagram illustrating an example of the structure of a base station according to one embodiment.

[0026] Figure 11 This is a diagram illustrating an example of the structure of a user terminal according to one embodiment.

[0027] Figure 12 This is a diagram illustrating an example of the hardware structure of a base station and a user terminal according to one embodiment.

[0028] Figure 13 This is a diagram illustrating an example of a vehicle according to one embodiment. Detailed Implementation

[0029] (Application of Artificial Intelligence (AI) technology to wireless communication)

[0030] Regarding future wireless communication technologies, research is underway on the application of AI technologies such as machine learning (ML) in the control and management of networks / devices.

[0031] For example, research is underway on using AI technologies by terminals (user terminals, user equipment (UE)) / base stations to improve channel state information (CSI) feedback (e.g., reduced overhead, improved accuracy, prediction), beam management (e.g., improved accuracy, prediction in the time / spatial domain), and location measurement (e.g., improved location estimation / prediction).

[0032] AI models can also output at least one of the following information based on the input information: estimated value, predicted value, selected operation, classification, etc. UE / BS can also input channel state information, reference signal measurements, etc., into the AI ​​model and output high-precision channel state information / measurements / beam selection / location, future channel state information / wireless link quality, etc.

[0033] Additionally, in this disclosure, AI can also be rewritten as an object (also referred to as an object, subject, data, function, program, etc.) having at least one of the following characteristics:

[0034] • Estimation based on observed or collected information;

[0035] • Selection based on observed or collected information;

[0036] • Predictions based on observed or collected information.

[0037] In this disclosure, estimation, prediction, and inference can be rewritten interchangeably. Furthermore, in this disclosure, making an estimate, making a prediction, and inferring can also be rewritten interchangeably.

[0038] In this disclosure, the object may be, for example, a device or equipment such as a UE or BS. Furthermore, in this disclosure, the object may also be equivalent to a program / model / entity operating within that device.

[0039] Furthermore, in this disclosure, the AI ​​model can also be rewritten as an object having at least one of the following characteristics:

[0040] • By providing (feeding) information, estimates are generated;

[0041] • By providing information, predict estimated values;

[0042] • Discover characteristics by providing information;

[0043] • Select an action by providing information.

[0044] Furthermore, in this disclosure, AI model can also refer to a data-driven algorithm that uses AI technology to generate a set of outputs based on a set of inputs.

[0045] Furthermore, in this disclosure, AI models, models, ML models, predictive analytics, predictive analytics models, tools, autoencoders, encoders, decoders, neural network models, AI algorithms, schemes, etc., can be rewritten interchangeably. Additionally, AI models can be derived using at least one of regression analysis (e.g., linear regression analysis, multiple regression analysis, logistic regression analysis), support vector machines, random forests, neural networks, deep learning, etc.

[0046] In this disclosure, the autoencoder can also be rewritten with any autoencoder such as a stacked autoencoder or a convolutional autoencoder. The encoder / decoder of this disclosure can also adopt models such as Residual Network (ResNet), Dense Network (DenseNet), and RefineNet.

[0047] Furthermore, in this disclosure, encoder, encoding, encoding / encoded, modification / change / control by encoder, compression, compression / compressed, generating, and generating / generated can also be rewritten in different ways.

[0048] Furthermore, in this disclosure, the terms decoder, decoding, decoding / being decoded, modification / change / control by decoder, decompressing, decompressing / being decompressed, reconstructing, and reconstructing / being reconstructed can also be rewritten in different ways.

[0049] In this disclosure, the layers (regarding the AI ​​model) can also be rewritten with the layers (input layer, intermediate layer, etc.) used in the AI ​​model. The layers in this disclosure can be equivalent to at least one of the following: input layer, intermediate layer, output layer, batch normalization layer, convolutional layer, activation layer, dense layer, normalization layer, pooling layer, attention layer, dropout layer, fully connected layer, etc.

[0050] In this disclosure, the training methods for AI models can also include supervised learning, unsupervised learning, reinforcement learning, federated learning, etc. Supervised learning can also refer to training the model based on inputs and corresponding labels. Unsupervised learning can also refer to training the model using unlabeled data. Reinforcement learning can also refer to training the model in an interactive environment based on inputs (in other words, states) and feedback signals (in other words, rewards) generated from the model's outputs (in other words, actions).

[0051] In this disclosure, the terms "generation," "computation," and "derivation" can be rewritten interchangeably. In this disclosure, the terms "implementation," "running," "operation," and "execution" can also be rewritten interchangeably. In this disclosure, the terms "training," "learning," "updating," and "retraining" can also be rewritten interchangeably. In this disclosure, the terms "inference," "after-training," "formal utilization," and "actual utilization" can also be rewritten interchangeably. In this disclosure, "signal" can also be rewritten interchangeably with "signal / channel."

[0052] Figure 1 This is a diagram illustrating an example of a framework for managing an AI model. In this example, the stages associated with the AI ​​model are represented by blocks. This example also represents the lifecycle management (LCM) of an AI model.

[0053] The data collection phase is equivalent to the phase of collecting data for the generation / updating of AI models. The data collection phase may also include data preparation (e.g., deciding which data to transmit for model training / inference), data transmission (e.g., transmitting data to entities performing model training / inference (e.g., UE, gNB), etc.).

[0054] Additionally, data collection can also refer to the processing of data collected by network nodes, management entities, or UEs for the purpose of AI model training / data analysis / inference. In this disclosure, processing and procedures can also be rewritten interchangeably. Furthermore, in this disclosure, collection can also refer to obtaining a dataset (e.g., capable of being used as input / output) for training / inference of AI models based on measurements (channel measurements, beam measurements, wireless link quality measurements, location estimation, etc.).

[0055] In this disclosure, offline field data can also refer to data collected from the field (real world) and used for offline training of AI models. Furthermore, in this disclosure, online field data can also refer to data collected from the field (real world) and used for online training of AI models.

[0056] In the model training phase, the model is trained based on the data transferred from the collection phase (training data). This phase may also include data preparation (e.g., implementation of data preprocessing, cleaning, formatting, transformation, etc.), model training / validation (validation), model testing (e.g., confirming whether the trained model meets performance thresholds), model exchange (e.g., transfer of models for distributed learning), and model deployment / update (deploying / updating the model to entities performing model inference), etc.

[0057] In addition, AI model training can also refer to the process of training an AI model using data-driven methods and obtaining the trained AI model for inference.

[0058] Furthermore, AI model validation can also refer to a subprocess used to evaluate the quality of an AI model using a dataset different from the dataset used in model training. This subprocess helps to select model parameters that generalize beyond the dataset used in model training.

[0059] Furthermore, AI model testing can also refer to the training subprocess used to evaluate the performance of the final AI model using a different dataset than that used in model training / validation. Additionally, unlike validation, testing can be independent of subsequent model tuning.

[0060] In the model inference phase, model inference is performed based on the data transmitted from the collection phase (inference data). This phase may also include data preparation (e.g., implementation of data preprocessing, cleaning, formatting, transformation, etc.), model inference, model monitoring (e.g., monitoring the performance of model inference), model performance feedback (providing model performance feedback to the entities that trained the model), and output (providing the model's output to the actors).

[0061] Additionally, AI model inference can also refer to the process of using a trained AI model to produce a set of outputs based on a set of inputs.

[0062] Furthermore, a UE-side model can also refer to an AI model where the inference is implemented entirely within the UE. Similarly, a network-side model can refer to an AI model where the inference is implemented entirely within the network (e.g., gNB).

[0063] Furthermore, a one-sided model can also refer to a UE-side model or a network-side model. A two-sided model can also refer to a pair of AI models performing joint inference. Here, joint inference can also include AI inference that is performed jointly across the UE and the network; for example, the first part of the inference can be performed by the UE first, and the remaining part by the gNB (or vice versa).

[0064] In addition, AI model monitoring can also refer to the processing used to monitor the inference performance of AI models, and can be interchanged with model performance monitoring, performance monitoring, etc.

[0065] Additionally, model registration can also mean assigning a version identifier to a model, compiling it in specific hardware used during the inference phase, and enabling the model to execute (registering the model). Furthermore, model deployment can also mean distributing a fully developed and tested runtime image (or execution environment image) of the model to the target implementing inference (e.g., UE / gNB) (or activating it on that target).

[0066] The actor phase can also include action triggers (e.g., deciding whether to trigger an action on other entities), feedback (e.g., providing feedback on training data / inference data / performance feedback, etc.).

[0067] Furthermore, training models for mobility optimization, for example, can also be performed within the network (NW) through operations, administration, and maintenance (OAM) / gNodeB (gNB). In the former case, interoperability, large-capacity storage, operator manageability, and model flexibility (feature engineering, etc.) are advantageous. In the latter case, advantages include the elimination of latency associated with model updates and the exchange of data for model deployment. Inference for the aforementioned models can also be performed, for example, within the gNB.

[0068] The entities used for training / inference can also vary depending on the use case (in other words, the function of the AI ​​model). The functions of an AI model can also include beam management, beam prediction, autoencoder (or information compression), CSI feedback, localization, etc.

[0069] For example, regarding AI-assisted beam management based on measurement reports, OAM / gNB can be used for model training, and gNB can be used for model inference.

[0070] Regarding AI-assisted UE assisted positioning, the Location Management Function (LMF) can also be used for model training, and the LMF can also be used for model inference.

[0071] Regarding CSI feedback / channel estimation using autoencoders, OAM / gNB / UE can also perform model training, and gNB / UE can also (jointly) perform model inference.

[0072] Regarding AI-assisted beam management based on beam measurement or AI-assisted UE-based positioning, OAM / gNB / UE can also perform model training, and UE can also perform model inference.

[0073] Additionally, model activation can also mean activating an AI model for a specific function. Model deactivation can also mean deactivating an AI model for a specific function. Model switching can also mean deactivating the currently activated AI model for a specific function and activating a different AI model.

[0074] Furthermore, model transfer can also refer to the distribution of an AI model over an air interface. This distribution may include distributing one or both of the following: parameters of a model structure known on the receiving side, or a new model with parameters. Additionally, the distribution may include a complete model or a portion of the model. Model download can also refer to model transfer from the network to the UE. Model upload can also refer to model transfer from the UE to the network.

[0075] Figure 2 This diagram illustrates an example of a specified AI model. In this example, the UE and NW (e.g., the base station (BS)) are able to identify model #1 and model #2 (the details of the models may not be fully understood). The UE can, for example, report the performance of model #1 and model #2 to the NW, and the NW can also indicate to the UE which AI model is being used.

[0076] (Lifecycle Management (LCM))

[0077] In future wireless communication systems (e.g., after Rel.18), the introduction of multiple LCMs is being studied.

[0078] These multiple LCMs can also be function-based LCMs or model-ID-based LCMs. Function-based LCMs can also be called function-based LCMs, and model-ID-based LCMs can also be called model-ID-based LCMs.

[0079] In a function-based LCM, the NW (e.g., base station / NW node) can also indicate the operations involved in the functionality of AI / ML (e.g., activation, deactivation, fallback operation, handover).

[0080] The UE may also perform model-level LCM (e.g., at least one of model switching and model selection) within the indicated functionality.

[0081] In terms of functionality, which model is activated / deactivated can also be transparent.

[0082] The notification of supported functionalities may also include a report of UE Capability information.

[0083] In model-ID-based LCM, NWs (e.g., base stations / NW nodes) can also indicate the operations (e.g., activation, deactivation, rollback, handover) involved by individual AI / ML models via model ID.

[0084] The UE can also perform model-level LCM (e.g., at least one of model switching and model selection) based on NW instructions.

[0085] Models can also be defined in NW by a model identifier (ID).

[0086] (Scenarios involved in model distribution (delivery) / transfer)

[0087] Regarding model distribution / transmission, three scenarios are specified in the existing context when training a model by NW.

[0088] [Scenario y]

[0089] First, NW trains the model and distributes it to UEs outside the 3GPP network based on offline projects from multiple vendors.

[0090] Next, the UE reports its support for the distributed models (this step can also be called model identification).

[0091] [Scenario z2]

[0092] First, NW trains its models using offline projects from multiple vendors and saves them in a proprietary format. A proprietary format can also refer to a format defined for each vendor.

[0093] Next, the UE reports the utilization of the stored model in the 3GPP network (this step can also be called model identification).

[0094] Next, the model is transferred.

[0095] Next, the UE reports its support for the transmitted model (this step can also be called model identification).

[0096] [Scenario z4]

[0097] First, the UE reports the supported model structure (this step can also be called model identification).

[0098] Next, NW transmits the model parameters of the model structure it supports.

[0099] Next, the UE reports its support for the transmitted model (this step can also be called model identification).

[0100] (functionality identification)

[0101] As a functional identification process, for example, one could consider the UE reporting specific conditions in its UE capabilities (capability information). In this case, the NW could also set the corresponding functionality based on the reported conditions.

[0102] Here, functionality can refer to a feature / feature group (FG) activated by a certain setting and available in AI / ML, such as a set of RRC parameters / LPP parameters. This setting can be supported based on conditions indicated by UE capabilities. Furthermore, functionality can refer to the unit that the NW can control on the UE side during LCM operations (activation / deactivation / switching).

[0103] Functional LCM-based operations can also be controlled based on the settings of features / feature groups that can be utilized in AI / ML as described above. Here, we are investigating the signaling (signaling for activation / deactivation / switching) used to support this functional LCM-based operation.

[0104] In addition, the UE can also report updates to the available functionalities. For example, it is necessary to study the mechanism for updating the applicable models after model identification.

[0105] (Model identification)

[0106] Models identified by model IDs can also be associated with settings / conditions / additional conditions (specific scenarios, sites, datasets, etc.). A model can also represent a unit that the NW can control on the UE side during LCM operations (activation / deactivation / switching).

[0107] LCM operation based on model ID can also be controlled based on the identified model. Here, the model can also be associated with specific settings / conditions related to the UE capabilities of features / feature groups that can be utilized in AI / ML, as well as additional conditions determined / identified between the UE side and the NW side.

[0108] Furthermore, it is envisioned that the identification process and control unit differ between functionally based LCMs and model ID-based LCMs. Here, we are investigating the sharing of activation / deactivation / switching processes in both functionally based and model ID-based LCMs.

[0109] In addition, the following types are being studied as part of the model recognition process.

[0110] • Type A: Model information and model ID are associated without signaling. The UE reports the supported model IDs to the NW. That is, the mapping between model ID and model information is recognized by the NW and UE without signaling. The NW and UE identify the corresponding model information based on the received model ID.

[0111] • Type B1: Model information is reported from the UE to the NW via the air interface (signaling). Model identification is initiated by the UE, and the NW assists (undertakes) the remaining steps of model identification. During model identification, a model ID can also be assigned to the model.

[0112] • Type B2: Model information is reported from the NW to the UE via the air interface (signaling). Model identification is initiated by the NW, and the UE responds to the remaining steps of model identification. During model identification, a model ID can also be assigned to the model.

[0113] Type B1 can be further classified into Type B1-1 and Type B1-2.

[0114] <Type B1-1>

[0115] Type B1-1 refers to the type of model identified by the ID assigned through NW, and may include the following processes.

[0116] • The UE retrains the new model and deploys it.

[0117] • The UE reports the existence of the new model along with the associated additional conditions.

[0118] • NW indicates the model ID assigned to the reported model.

[0119] <Type B1-2>

[0120] Type B1-2 refers to the type identified by the model assigned the ID by the UE, which may include the following processes.

[0121] • UE retrains the new model.

[0122] • The UE assigns a model ID to the new model.

[0123] • The UE reports the existence of a new model along with the additional conditions and the associated model ID.

[0124] Type B2 can be further classified into Type B2-1 and Type B2-2.

[0125] <Type B2-1>

[0126] Type B2-1 refers to the type of model recognition corresponding to model transfer, which may include the following processes.

[0127] • The model information that the UE report can support.

[0128] • NW retrains the new model.

[0129] • The new model (assigning a model ID to the new model) is transmitted to the UE along with the model ID.

[0130] <Type B2-2>

[0131] Type B2-2 refers to the type of model identification corresponding to the start of data collection, which may include the following processes.

[0132] • NW enables UE to begin collecting the dataset for model training and assign model IDs.

[0133] • UE trains the model based on the collected dataset.

[0134] • The UE notifies that the model associated with the model ID has been deployed.

[0135] (Meta-information)

[0136] The UE may also receive at least one of the following as metadata.

[0137] Furthermore, the term "meta-information" in this disclosure is merely one example; meta-information can also refer to at least one of specific setting information, scenario information, environmental information, auxiliary information, and model information. In this disclosure, meta-information, setting information, scenario information, environmental information, auxiliary information, and model information can also be rewritten interchangeably.

[0138] The metadata used by the UE / NW may also include at least one of the following: information related to NW settings / configuration (deployment), information related to the environment, information related to the AI / ML model on the NW side, and information related to the model requested by the NW.

[0139] Information related to NW settings / configuration may also include information related to antenna settings.

[0140] Information related to antenna settings may also represent at least one of the following: number of horizontal / vertical antenna elements / panels, number of ports, antenna spacing, antenna position, panel position, and transceiver unit (TxRU) mapping.

[0141] Information related to NW settings / configuration may also include information related to beam settings.

[0142] Information related to beam setting may include, for example, at least one of beamwidth, number of beams, and beam direction.

[0143] Information related to NW settings / configuration may also include information related to TRP.

[0144] Information related to beam setting may include, for example, the height of the TRP and at least one of the relative positions of multiple TRPs.

[0145] Environment-related information may also include information related to the configuration scenario.

[0146] Information related to the configuration scenario may also represent at least one of Urban Macro (UMa), Urban Micro (Umi), and Indoor Hotspot (InH).

[0147] Information related to the environment may also include information related to indoors or outdoors.

[0148] Information related to indoor or outdoor conditions can also represent indoor / outdoor probabilities, for example.

[0149] Information related to the environment can also be information related to objects around the UE / base station.

[0150] Information related to objects around the UE / base station can also represent the configuration of objects around the UE / base station.

[0151] Information related to the environment may also include, for example, the scenario setting format (meta-information) described below.

[0152] The use cases of AI models can also be associated with scenario setting formats consisting of long-term features.

[0153] Furthermore, long-term characteristics can be interchanged with short-term / medium-term / long-term characteristics, or simply referred to as characteristics. Additionally, scenario setting formats can be interchanged with meta-information, meta-information formats, scenario and configuration formats, scenario structure formats, scenario formats, configuration formats, usage format, environment format, and meta-formats. Furthermore, formats can be interchanged with type, mode, data, and settings.

[0154] The above features may also include a combination of one or more of the following elements:

[0155] • Scenarios / models (Urban Macro (UMa)), Urban Micro (Umi)), Indoor, Outdoor, Indoor Hotspot (InH), etc.).

[0156] • Frequency / frequency range.

[0157] • Parameter set (or subcarrier spacing).

[0158] • The distribution / set of general channel parameters (e.g., inter-site distances (ISD)), gNB height, delay spread, angular spread, Doppler spread, etc.) in a single scenario / model.

[0159] • UE distribution.

[0160] • UE speed.

[0161] • UE trajectory.

[0162] • Number of transmit beams / number of receive beams.

[0163] • UE rotation mode.

[0164] • gNB / UE antenna structure (e.g., transmit and receive antenna vectors).

[0165] • Number of cells / Number of sectors.

[0166] • Bandwidth.

[0167] • UE payload.

[0168] • Channel quality (e.g., RSRP, SINR).

[0169] • Beam configuration ID.

[0170] • Physical Cell ID (PCI)

[0171] • Global Cell ID (GCI).

[0172] • Absolute Radio Frequency Channel Number (ARFCN)

[0173] • The probability of line of sight (LOS) / non-line of sight (NLOS).

[0174] It is also possible to expect a model where the scenario setting format associated with the UE being set / registered (registered) is consistent with the UE's settings / state.

[0175] Furthermore, it can be expected that the scenario setting format associated with UE activation will be consistent with the UE's settings / state.

[0176] The correspondence between use cases and scenario setting formats can be specified in the standard or by notifying the UE of information related to that correspondence. Furthermore, the features included in the scenario setting format corresponding to the use case can be specified in the standard or by notifying the UE of information related to those features.

[0177] Information related to AI / ML models on the NW side may also include information related to paired models that can be used on the NW side.

[0178] Information related to the paired model that can be used on the NW side can also represent, for example, the paired decoder used for CSI compression.

[0179] Information related to the AI / ML model on the NW side may also include information related to preprocessing / postprocessing that can be utilized on the NW side.

[0180] Information related to preprocessing / postprocessing available on the NW side may include, for example, at least one of quantization / dequantization, DFT transform, IDFT transform, FFT transform, and IFFT transform.

[0181] (UE assistance information)

[0182] UE can also report auxiliary information / metadata (meta-information) of AI / ML models.

[0183] Auxiliary information may include at least one of the following: user status.

[0184] • Overheating assistance information

[0185] • DRX parameter preferences

[0186] Priorities related to maximum aggregate bandwidth

[0187] • Preference for the maximum number of MIMO layers.

[0188] The AI / ML model can also be an AI / ML model that has been registered, configured, compiled, or activated in the UE.

[0189] Auxiliary information / metadata of the AI / ML model can be sent along with beam information, or sent in place of beam information. This beam information can, for example, be information related to the UE's antenna / beam.

[0190] The auxiliary information / metadata of the AI / ML model may also be at least one of the following.

[0191] The auxiliary information / metadata of an AI / ML model can also be the ID of the AI / ML model.

[0192] The ID of an AI / ML model can also be a global / local AI / ML model ID.

[0193] The auxiliary information / metadata of AI / ML models can also be information related to the bandwidth that can be applied to the AI / ML model ID.

[0194] This bandwidth can also be expressed as the minimum / maximum bandwidth that can be applied.

[0195] Information related to this bandwidth may also include, for example, information representing a frequency band indicator (e.g., "freqBandIndicatorNR"). The information representing the frequency band indicator may also be represented by a specific number of bits (e.g., 10 bits).

[0196] Information related to this bandwidth may include, for example, information indicating the bandwidth of the RS associated with the corresponding AI / ML model (e.g., “supportedBandwidth”).

[0197] Information indicating the bandwidth of the RS associated with the corresponding AI / ML model can also represent the frequency of each frequency range (e.g., FR1 / FR2 (FR2-1 / FR2-2) / FR3 / FR4 / FR5).

[0198] The auxiliary information / metadata of AI / ML models can also be information related to the applicable region corresponding to the AI / ML model ID.

[0199] Information related to the applicable region corresponding to the AI / ML model may also include at least one of the following (a list of information):

[0200] • Region ID.

[0201] • The global ID of the (NR) cell.

[0202] • (NR) Physical cell ID (Identifier).

[0203] • ARFCN (Absolute Radio Frequency Channel Number).

[0204] • Global ID (ECGI) of Evolved Cell.

[0205] The region ID may also include at least one of the NR cell's global ID, the NR's physical cell ID, and the ARFCN.

[0206] The auxiliary information / metadata of AI / ML models can also be antenna settings / beam information corresponding to the AI / ML model ID.

[0207] (KPI)

[0208] Regarding the performance monitoring of AI models, we are researching public key performance indicators (KPIs).

[0209] Below is an initial list of common KPIs used to evaluate the performance of AI / ML-based models:

[0210] • Performance

[0211] Intermediate KPIs

[0212] • Link-level and system-level performance

[0213] Generalization performance

[0214] • Over-the-air expenses

[0215] • Cost of auxiliary information

[0216] • Data collection overhead,

[0217] • The overhead of model delivery / transfer

[0218] • Other signaling overhead associated with AI / ML models,

[0219] • Inference complexity

[0220] • Computational complexity of model inference: floating-point operations (FLOPs, where 's' is lowercase) (this refers to the number of floating-point operations).

[0221] • Computational complexity of pre- and post-processing

[0222] • Model complexity (number of parameters / data size (e.g., Mbytes) etc.)

[0223] • Training complexity

[0224] • LCM-related complexity and storage overhead

[0225] • Delay (e.g., inference delay).

[0226] In addition, the above KPIs are just one example, and other KPIs can be added to the list (e.g., KPIs associated with model training, use case-specific KPIs for a given use case, etc.).

[0227] Among the KPIs mentioned above, those related to performance can also be called performance KPIs.

[0228] (Functional related information)

[0229] The UE can also report the supported (or supported) functionalities.

[0230] Functionality can also be associated with specific information. Furthermore, functionality can also contain specific information. Additionally, functionality can belong to specific information.

[0231] In this disclosure, the terms "be associated with", "include", "belong to", and "correspond to" may be used interchangeably.

[0232] This specific information may also be at least one of the following. Furthermore, specific information and functionally related information may be modified from each other.

[0233] This specific information can also be related to the conditions / settings that can be applied.

[0234] This specific information could be, for example, an applicable NW setting. For instance, the applicable parameters involved in this NW setting could be at least one of system information parameters and auxiliary information parameters.

[0235] This specific information could also be, for example, an applicable UE setting. For instance, the applicable parameters involved in this UE setting could also be higher-layer (e.g., RRC) parameters.

[0236] This specific information may also be information related to the applicable scenario. This information may also be information representing at least one of NLOS / LOS, UE distribution, SINR, RSRP, bandwidth, frequency, indoor / outdoor, and configuration (deployment) scenarios (e.g., at least one of Urban Macro (UMa), Urban Micro (Umi), and Indoor Hotspot (InH)).

[0237] This specific information may also be information related to the applicable configuration. This information may also be information indicating at least one of the following: applicable antenna settings (e.g., the number of antenna elements / panels in the horizontal / vertical direction, the number of ports, the antenna spacing, the antenna position, the panel position, the transceiver unit (TxRU) mapping), beam settings (e.g., at least one of beamwidth, the number of beams, and the beam direction), and TRP information (e.g., the height of the TRP, at least one of the relative positions of multiple TRPs).

[0238] This specific information could be, for example, information related to the site to which it can be applied. This information could also be, for example, information representing at least one of the following: region ID, NR cell global ID, NR physical cell ID, a specific frequency (e.g., ARFCN), and ECGI.

[0239] This specific information could, for example, be related to the paired model that can be applied. The paired model could, for example, be a combination of two (or more) NW-side models. This information could also, for example, be information representing the paired model used for CSI compression.

[0240] This specific information could be, for example, information related to the time to which it can be applied. This information could also be, for example, information representing the period (period / interval / duration) to which it can be applied. This period could also be represented using a specific time unit (e.g., slot / symbol / subslot / millisecond / second).

[0241] The applicable conditions / settings can be predefined in the specification or determined / identified using specific IDs / tokens. For example, the applicable settings / situations / conditions can be specified as specific parameters (e.g., test parameters) or represented using specific IDs / tokens.

[0242] Alternatively, it can be conceived that functional performance (performance, such as prediction accuracy or positional error) is better than (e.g., higher than) a specific threshold under applicable conditions / settings. These specific conditions / settings could, for example, be conditions / settings in a specific test.

[0243] This threshold / performance requirement can be predefined in the specification or determined / identified using specific IDs / terms.

[0244] With the threshold / performance requirement based on a specific ID / term, each vendor / operator is able to define and utilize the desired threshold / performance.

[0245] (consistency)

[0246] As part of the model recognition process, types B1 and B2 are being studied. In type B1, model recognition begins with the User Experience (UE), while in type B2, it begins with the New Wave (NW).

[0247] However, the specific processes involved are still unclear.

[0248] Furthermore, models specifically designed for a particular deployment (configuration) / scenario are considered to perform better than general models (models with universality). For example, a model trained on a dataset collected in a particular environment (let's say environment ID=A) is considered to perform well in that environment, but may not necessarily perform well in a different environment (let's say environment ID=B).

[0249] On the other hand, if different environments (let's call them environment ID=C) are similar to a certain environment (environment ID=A), then a model trained on a dataset collected in a certain environment (environment ID=A) is considered to be able to achieve good performance in different environments (let's call them environment ID=C).

[0250] In other words, in model identification, associating a model with a suitable deployment / scenario is essential to maximizing the model's performance. On the other hand, gNB / UE vendors try to avoid disclosing model implementation information (such as beam mapping and other information related to determining various inputs used for model training) as much as possible.

[0251] As stated above, when an ID is used to indicate a specific deployment / scenario, there is a concern from the perspective of the gNB / UE vendor that information related to a particular deployment / scenario may be determined based on that ID.

[0252] Therefore, the following model recognition method (process) can be envisioned.

[0253] <Methods for Model Recognition>

[0254] ID-based methods

[0255] Figure 3 This is a conceptual diagram illustrating an example of an ID-based method for model recognition.

[0256] In the ID-based scenario, the NW triggers data collection on the UE side and assigns IDs without notifying the deployment / scenario. Based on the assigned ID, the NW indicates the model that should be utilized.

[0257] like Figure 3 As shown, the UE can receive ID-related information from the gNB (NW). Here, the ID received by the UE can represent an ID corresponding to at least one of the following: dataset, model, period, measurement settings, and channel / RS properties (used to determine at least one of them).

[0258] The ID received by the UE may contain information related to the ID, information indicating the ID, etc. Information related to data collection, model training, and performance monitoring can be associated with this ID.

[0259] Upon receiving the aforementioned ID, the UE can assume that the characteristics of the collected dataset, model, or channel / RS are consistent over a certain period of time.

[0260] like Figure 3 As shown, the UE can report the IDs supported for a specific function. For example, the UE can report the model IDs supported for a specific function. The reported IDs can be used for model management among the supported IDs.

[0261] In this disclosure, functionality may refer to features (requiring AI / ML capabilities) such as reporting information based on CSI prediction / CSI compression / temporal beam prediction / spatial domain beam prediction.

[0262] Non-ID-based methods

[0263] Figure 4 This is a conceptual diagram illustrating an example of a non-ID-based method for model recognition.

[0264] In a deployment / scenario, NW can indicate consistency only for a specific period. In this case, the UE cannot trace deployments / scenarios corresponding to past deployments / scenarios.

[0265] like Figure 4 As shown, the UE can receive information related to consistency indication from the gNB (NW). That is, in implementation 0-2, the UE can receive information related to consistency indication instead of the ID (based on ID) mentioned above.

[0266] The consistency received by the UE may include consistency-related information, information indicating consistency (consistency indication information), etc. Information related to data collection, model training, and performance monitoring may be associated with the consistency.

[0267] Upon receiving information related to the above consistency indication, the UE may assume that the specific characteristics of the collected dataset, model or channel / RS are consistent during certain duration.

[0268] The UE may monitor the performance of functions / models and report supported / applicable functions / models within a certain duration. This certain duration may also be referred to as consistency application time, consistency indication time, consistency duration, etc.

[0269] as shown in Figure 4 , the UE may report supported models / functions. The reported models / functions may be used for model management among the supported models / functions.

[0270] In this way, model identification can be properly controlled through ID-based or non-ID-based methods.

[0271] <Reception of ID / consistency indication>

[0272] <Reception Timing>

[0273] Figure 5A and Figure 5B are diagrams illustrating an example of the reception timing (start point) of the ID / consistency indication. Figure 6A and Figure 6B are diagrams illustrating an example of the reception timing (end point) of the ID / consistency indication. Figure 7A and Figure 7B are diagrams illustrating an example of the reception timing (end point) of the ID / consistency indication.

[0274] The reception timing (start point and end point) at which the UE receives the ID-related information / information related to the consistency indication may be determined by the following methods.

[0275] In the present disclosure, the time (period) during which an ID / consistency indication can be received may also be interchanged with the time duration corresponding to the received ID (received ID), consistency duration, consistency indication time, consistency application time, ID / consistency receivable time, receivable time, etc.

[0276] In this disclosure, the unit of time can be any of a symbol / slot / subframe / radio frame. The same applies to the duration and time offset X / Y / Z / x described later.

[0277] (Starting point of reception)

[0278] The starting point can also be the timing of a time offset X before or after the initial / final receipt of an ID / consistency indication. The time offset X can represent the offset relative to the starting point.

[0279] For example, such as Figure 5A As shown, the starting point of the duration corresponding to ID#1 can also be a timing offset X that is earlier than the timing of the initial / last received ID / consistency indication.

[0280] Or, such as Figure 5B As shown, the starting point of the duration corresponding to ID#1 can also be a timing offset X from the timing of the initial / last received ID / consistency indication.

[0281] In this disclosure, the start point, start timing, and start time can be interchanged.

[0282] In this disclosure, the time offset and the length of the duration (receivable time) can be interchanged.

[0283] The value of X can be set / indicated by the NW via higher-layer / physical-layer signaling, predefined by specifications, or determined based on UE capabilities. For example, X can be determined based on parameters contained in information related to ID / conformity indication sent from the NW. Furthermore, the value of X can vary depending on a set of parameters (e.g., subcarrier spacing (SCS)) and frequency range.

[0284] (End point of reception)

[0285] The endpoint can be determined by at least one of the following options 1 to 6.

[0286] In this disclosure, the end point, end timing, and end time can be interchanged.

[0287] <Option 1>

[0288] The end point can also be a time interval that occurs after the start point of the duration (from the start point) and after a certain duration has elapsed. For example, ... Figure 6A As shown, the duration can be the same as the time from the start point to the end point (acceptable time).

[0289] <Option 2>

[0290] The endpoint can also be a time interval elapsed after the initial / last receipt of the ID / consistency indication (from the start of reception). That is, as... Figure 6B As shown, the duration (the time from the time the ID / consistency indication is received to the end point) can be longer than the time from the start point to the end point (receivable time).

[0291] <Option 3>

[0292] The endpoint can be a time offset Y that is received before or after the initial / final receipt of information related to the termination of ID / consistency. The time offset Y can represent the offset relative to the endpoint.

[0293] For example, such as Figure 7A As shown, the end point of the receivable time can be a time offset Y elapsed from the time the ID / consistency indication is received. That is, even after the ID / consistency indication is received, the receivable time can continue for an amount of offset Y.

[0294] The value of Y can be set / indicated by the NW via higher-layer / physical-layer signaling, predefined by specifications, or determined based on UE capabilities. For example, Y can be determined based on parameters contained in information related to ID / consistency indication sent from the NW. Furthermore, the value of Y can vary depending on a set of parameters (e.g., subcarrier spacing (SCS)) and frequency range.

[0295] <Option 4>

[0296] The endpoint can also be the timing of the time offset Y before or after receiving other IDs / consistency indications (related information) that indicate different IDs / consistency.

[0297] <Option 5>

[0298] The end point can also be the start point of a duration corresponding to another ID / consistency indication (indicating a different ID / consistency). For example, as... Figure 7B As shown, the end point can also be the point (start point #2) that is the start point of the duration (second receivable time) corresponding to ID#2 after the end of the duration (first receivable time) corresponding to ID#1 and after a time offset Y.

[0299] <Option 6>

[0300] The endpoint can also be the timing of the time offset Y before / after a specific event (e.g., RRC reconfiguration, radio link failure, beam failure detection, handover command reception, handover execution).

[0301] Receiving Method

[0302] The UE can receive the ID / consistency indication, for example, via the following signaling.

[0303] • Requests for specific signaling or UE capabilities.

[0304] • System information (e.g., SIB).

[0305] • Group-common signaling (e.g., multicast / broadcast).

[0306] All / specific RS resources / channels can be associated with an ID / consistency indicator.

[0307] For example, the RS resource / channel associated with the ID / consistency indication can also be at least one of the following.

[0308] • Specific frequency band / bandwidth / BWP / RS / channel within the serving cell.

[0309] • Specific RS settings.

[0310] • A specific set of RS resources / RS resources.

[0311] • RS / channels within a specific CORESET / search space.

[0312] • Specific types of RS / channels (e.g., PRS, CSI-RS).

[0313] • Specific frequency layers.

[0314] The RS resources / channels associated with the ID / conformity indication can be determined based on parameters that are set / indicated / predefined, or parameters reported in UE capabilities / associated functionality.

[0315] In addition to receiving ID / consistency indications, the UE can also receive the following information associated with the ID.

[0316] • Represents the supplier's information / ID (type assignment code).

[0317] • International Mobile Equipment Identity (IMEI)

[0318] • Type allocation code.

[0319] • Final assembly code.

[0320] • Check digit (CD) / Spare digit (SD).

[0321] For example, IMEI can be represented by 15 bits as follows.

[0322] IMEI (15 bits) = TAC (6 digits) + FAC (2 digits) + Serial Number (SNR) (6 digits) + Check Digit (1 digit)

[0323] The Type Assignment Code (TAC) is a code used to identify the manufacturer and device type, and also to identify the supplier / device. In this disclosure, the first 6 bits / 8 bits of the IMEI can also represent the TAC.

[0324] The Final Assembly Code (FAC) is a code used to identify the country of manufacture of the equipment. In this disclosure, the FAC may or may not be part of the TAC (or may be separate from the TAC).

[0325] CD / SD uses a single bit of information to verify the IMEI.

[0326] <IDs supported in consistency indicators>

[0327] The IDs that can be supported in the consistency indication are preferably those that satisfy at least one of the following conditions.

[0328] <Condition 1>

[0329] A specific metric (metric) is derived from the dataset (measurement results) collected / measured within the duration corresponding to that ID and is greater than / less than a certain threshold. The specific metric or threshold can be set / indicated through higher-layer signaling / physical layer signaling, defined in advance through specifications, or determined based on UE capabilities.

[0330] <Condition 2>

[0331] The model / functionality can be trained / derived based on the dataset (measurement results) collected / measured within the duration corresponding to that ID. For example, the model / functionality can be trained / derived based on a certain number or more of data samples (measurement results / measurement values) collected / measured within the duration corresponding to that ID.

[0332] The specific quantity can be set / indicated through higher-layer signaling / physical layer signaling, defined in advance through specifications, or determined based on UE capabilities.

[0333] According to condition 2, the model can be trained / fine-tuned using the dataset corresponding to a specific ID.

[0334] <Condition 3>

[0335] The UE can determine / judge the supported ID based on at least one of the conditions shown in options 1 to 4 below.

[0336] <Option 1>

[0337] The UE can determine / judge the supported IDs based on performance-related KPIs (also known as performance KPIs). More specifically, the UE can determine / judge the supported IDs based on whether the performance KPI is greater than or less than a specific requirement (threshold).

[0338] This threshold can be set / indicated by higher-level signaling / physical-level signaling, or it can be defined in advance by specifications.

[0339] Performance KPIs can also be set / indicated via higher-layer signaling / physical layer signaling.

[0340] Performance KPIs can also be calculated over a certain period of time. For example, the average performance over a certain period can also be used as the performance KPI.

[0341] If the performance KPI is greater than a certain threshold, the UE can determine / judge that it can support the corresponding ID. Conversely, if the KPI is less than a certain threshold, the UE can determine / judge that it cannot support the corresponding ID.

[0342] <Option 2>

[0343] The UE can determine / judge the supported IDs based on the UE status shown in Options 2-1 to 2-4.

[0344] • Overheating condition (option 2-1)

[0345] · Computational resources (option 2-2),

[0346] · Memory storage (option 2-3),

[0347] · Power battery (option 2-4).

[0348] For example, regarding the status of the above options 2-1 to 2-4, UE may compare the status with a specific threshold, and determine / judge the supported ID based on the comparison result.

[0349] <Option 3>

[0350] UE may determine / judge the supported ID based on assistance information received from NW. For example, if the status / condition of a model / function is consistent with the assistance information received from NW, UE may determine / judge that it can support the ID.

[0351] <Option 4>

[0352] UE may determine / judge the supported ID based on sensing information (detection information). Sensing information may be any information detected by UE (such as measured values / detected values), for example, it may be L1-RSRP / SINR, and information related to the surrounding environment.

[0353] For example, if the status / condition of a model / function is consistent with the sensing information, UE may determine / judge that it can support the ID.

[0354] Regarding each of the above options, UE may also be configured with higher layer parameters for determining whether to apply any option (whether to determine / judge the supported ID based on any option).

[0355] (Correspondence (mapping) between measurement and reporting)

[0356] <CSI report (CSI report or reporting)>

[0357] In Rel.15 / 16 NR, a terminal (also known as a user terminal, user equipment (UE), etc.) generates (also known as deciding, calculating, estimating, measuring, etc.) Channel State Information (CSI) based on a Reference Signal (RS) (or the resources used by that RS) and sends (also known as reporting, feedback, etc.) the generated CSI to the network (e.g., a base station). This CSI may also be sent to the base station using, for example, an uplink control channel (e.g., a Physical Uplink Control Channel (PUCCH)) or an uplink shared channel (e.g., a Physical Uplink Shared Channel (PUSCH)).

[0358] The RS used to generate CSI can be, for example, at least one of the following: Channel State Information Reference Signal (CSI-RS), Synchronization Signal / Physical Broadcast Channel (SS / PBCH) block, Synchronization Signal (SS), DeModulation Reference Signal (DMRS), etc.

[0359] CSI-RS can also include at least one of Non-Zero Power (NZP) CSI-RS and CSI Interference Management (CSI-IM). An SS / PBCH block is a block containing SS and PBCH (and their corresponding DMRS), and can also be called an SS block (SSB), etc. Furthermore, SS can also include at least one of Primary Synchronization Signal (PSS) and Secondary Synchronization Signal (SSS).

[0360] Additionally, CSI may include at least one of the following: Channel Quality Indicator (CQI), Precoding Matrix Indicator (PMI), CSI-RS Resource Indicator (CRI), SS / PBCH Block Resource Indicator (SSBRI), Layer Indicator (LI), Rank Indicator (RI), L1-RSRP (Layer 1 Reference Signal Received Power), L1-RSRQ (Reference Signal Received Quality), L1-SINR (Signal to Interference plus Noise Ratio), and L1-SNR (Signal to Noise Ratio).

[0361] The UE can receive information related to CSI reports (report configuration information) and control CSI reporting based on this report configuration information. This report configuration information can be, for example, the Radio Resource Control (RRC) Information Element (IE) "CSI-ReportConfig". Furthermore, in this disclosure, the RRC IE can also be interleaved with RRC parameters, higher-layer parameters, etc.

[0362] The report configuration information (e.g., “CSI-ReportConfig” in RRC IE) may also include at least one of the following.

[0363] • Information related to the type of CSI report (report type information, such as "reportConfigType" in RRC IE)

[0364] • Information related to more than one quantity of CSI that should be reported (more than one CSI parameter) (report quantity information, e.g., "reportQuantity" in RRC IE)

[0365] • Information related to the RS resources used in generating this quantity (the CSI parameter) (resource information, such as "CSI-ResourceConfigId" in RRC IE).

[0366] • Information related to the frequency domain of the object being reported by CSI (frequency domain information, such as RRC IE's "reportFreqConfiguration")

[0367] For example, report type information can also indicate periodic CSI (P-CSI) reports, aperiodic CSI (A-CSI) reports, or semi-permanent CSI (SP-CSI) reports.

[0368] In addition, the reporting volume information can also specify a combination of at least one of the above CSI parameters (e.g., CRI, RI, PMI, CQI, LI, L1-RSRP, etc.).

[0369] In Rel.15 / 16, the CRI / SSBRI fields are determined based on the number of CSI-RS resources or the number of SS / PBCH blocks within the resource set, respectively.

[0370] <Correspondence / mapping between the measured RS / beam and the reported RS / beam>

[0371] The UE can also decide separately which RS to measure (e.g., CSI-RS / SSB) and which RS to report.

[0372] The UE can also report the L1-RSRP of RSs that are different from the RS to be measured. The UE can also support reporting the L1-RSRP of RSs that are different from the RS to be measured.

[0373] The UE may also make a decision on the RS to be measured and the RS to be reported according to at least one of the following options 1 to 5.

[0374] Option 1

[0375] The UE can also use specific RRC parameters to determine the RS.

[0376] For example, the UE can also use the existing (as specified up to Rel. 16 / 17) RRC parameters to determine the RS.

[0377] This RRC parameter can also be included, for example, in parameters used to configure resources for channel / interference measurements. This RRC parameter can also be included, for example, in CSI report settings (e.g., CSI-ReportConfig).

[0378] The UE can also be configured with CSI resource settings (e.g., CSI-ResourceConfig) that include CSI reported in beam prediction.

[0379] For beam prediction calculations (e.g., input to an AI model), the UE can also refer to / determine resources corresponding to existing RRC parameters (e.g., parameters for channel measurement resources (e.g., resourceForChannelMeasurement) and parameters for interference measurement resources (e.g., csi-IM-ResourcesForInterference)).

[0380] Figure 8 This is a diagram illustrating an example of RRC parameters related to CSI report settings. Figure 8 In the example shown, the CSI report configuration (CSI-ReportConfig) includes a parameter (resourcesForReporting) that represents the resources used for reporting. The parameter (resourcesForReporting) refers to the ID of the CSI resource configuration (CSI-ResourceConfigId).

[0381] The UE determines the resource to be reported based on the referenced CSI-ResourceConfigId.

[0382] Option 2

[0383] The UE can also use specific RRC parameters to determine the RS.

[0384] For example, the UE can also use the new RRC parameters (specified after Rel.18 / 19) to determine the RS.

[0385] The RRC parameter can also be an RRC parameter included in the CSI report settings (e.g., CSI-ReportConfig).

[0386] The RRC parameter can also be set to the UE using CSI resource settings that include resources for channel measurements used for beam prediction.

[0387] The RRC parameter can also be set to the UE using CSI resource settings that include resources for interference measurement / interference beam measurement for beam prediction.

[0388] The RRC parameter can also be set to the UE using the CSI resource settings of the resources included in the CSI reported in beam prediction.

[0389] Option 3

[0390] The UE can also use specific RRC parameters to determine the RS (Resource Set of RS).

[0391] The parameters set in CSI resource configuration (e.g., CSI-ResourceConfig) can also be extended.

[0392] The UE can also be configured with a resource set associated with the CSI reported after beam prediction.

[0393] A CSI resource setting parameter (e.g., CSI-ResourceConfig) may also include both information related to the reported resource set and information related to the resource set being measured for beam prediction (Option 2-1-3-1).

[0394] A CSI resource setting parameter (e.g., CSI-ResourceConfig) may also include either information related to the reported resource set or information related to the resource set measured for beam prediction (Option 2-1-3-2). In this case, more than two CSI resource setting parameters (e.g., CSI-ResourceConfig) may also be set for the UE.

[0395] Option 4

[0396] The UE can also use specific RRC parameters to determine the RS (resources of the RS).

[0397] The parameters related to the resource set can also be extended.

[0398] For example, the UE can also be configured with parameters related to a resource set that includes reported resources and resources measured for beam prediction (e.g., NZP-CSI-RS-ResourceSet).

[0399] Option 5

[0400] It is also possible to specify a list containing at least one of the resources of the reported RS and the resources of the RS measured for beam prediction.

[0401] The UE can also use this list to determine at least one of the resources of the reported RS and the resources of the measured RS.

[0402] For example, the UE can also be configured to include a list of resource IDs / resource set IDs / CSI resource settings for the reported resources.

[0403] For example, the UE can also be configured to include a list of resource IDs / resource set IDs / CSI resource settings for resources measured for beam prediction.

[0404] A list can also contain both information related to the resources of the reported RS and information related to the resources of the RS being measured for beam prediction.

[0405] A list may also contain either information related to the resources of the reported RS or information related to the resources of the RS being measured for beam prediction.

[0406] You can also combine at least two of the above options 1 to 5.

[0407] Furthermore, in this disclosure, the CSI-RS resource set, the CSI-RS resource set setting parameters, the NZP CSI-RS resource set, the NZP CSI-RS resource set setting parameters (NZP-CSI-RS-ResourceSet), the CSI measurement SSB resource set setting parameters (CSI-SSB-ResourceSet), and the CSI-IM resource set setting parameters (CSI-IM-ResourceSet) can be mutually modified.

[0408] Furthermore, in this disclosure, the CSI-RS resource, the setting parameters of the CSI-RS resource, the NZP CSI-RS resource, and the setting parameters of the NZPCSI-RS resource (NZP-CSI-RS-Resource) can also be modified to each other.

[0409] (Valid area)

[0410] The valid area is defined as the area used for measurement reporting in RRC_idle and RRC_inactive (i.e., when RRC is idle and when RRC is inactive). The UE can perform measurements within the valid area.

[0411] The parameters related to the valid area (validityAreaList) may include at least one of the following.

[0412] • Absolute radio-frequency channel number (ARFCN-ValueNR)

[0413] • Valid cell list (ValidityCellList).

[0414] validityAreaList represents a list of frequencies, and as an option, it can represent a list of cells within the UE required for the UE to perform measurements in RRC_idle and RRC_inactive for each frequency.

[0415] ARFCN-ValueNR can be rewritten with and without the carrier frequency (carrierFreq).

[0416] ValidityCellList can refer to a list of physical cell ID ranges (PCI ranges).

[0417] A higher-level parameter (PCI range) can refer to the set of physical cell IDs (PCIs) represented by a start index and range.

[0418] A PCI range is used to encode one or more (sets of) PCIs. Here, the range uses a start value and is encoded by representing the number of consecutive PCIs within the range (including the start value).

[0419] When a field contains multiple PCI ranges (PCI-Range), the network can also set the overlapping range of PCIs.

[0420] As mentioned above, a range can represent the number of PCIs within that range (including the start value). In the absence of a range-related field, the UE should apply a value of 1, in which case only the PCI value represented by start is applied. Alternatively, the start value can represent the lowest PCI within the range.

[0421] (analyze)

[0422] As mentioned above, the process of model recognition is not yet fully understood, and the following topics are being studied.

[0423] <Topic 1>

[0424] How to ensure consistency between set A (predicted values ​​(e.g., predicted CSI)) and set B (measured values ​​(e.g., measured CSI))?

[0425] <Topic 2>

[0426] During data collection, how does the UE understand / identify the specific correspondence between set A and set B (gNB-preferred correspondence)?

[0427] <Topic 3>

[0428] How UE reports the functions / capabilities for a specific correspondence between set A and set B.

[0429] <Topic 4>

[0430] Clarification of the method for setting information related to set A based on set B in UE reports.

[0431] If these elements are not clearly defined, appropriate overhead reduction, channel estimation, and resource utilization cannot be achieved, raising concerns about inhibiting improvements in communication throughput and quality.

[0432] Therefore, the inventors of this invention conceived of a model recognition method (process) to solve these problems.

[0433] (Various rewrites)

[0434] In this disclosure, terms enclosed in parentheses "()" can also indicate explanations of the preceding term (e.g., spelling notes), rewrites, specific examples, supplementary explanations, etc. Furthermore, in this disclosure, terms enclosed in square brackets "[]" can be interpreted either by including them (or ignoring) them. Additionally, "()" and "[]" can also be used for purposes / meanings other than those listed above.

[0435] In this disclosure, "A / B" and "at least one of A and B" may be rewritten as each other. In addition, in this disclosure, "A / B / C" may also mean "at least one of A, B and C".

[0436] In this disclosure, terms such as notification, activation, deactivation, indication (or indication), selection, configuration, update, and determination can be overridden. Similarly, terms such as support, control, ability to control, operation, and ability to operate can also be overridden.

[0437] In this disclosure, Radio Resource Control (RRC), RRC parameters, RRC messages, higher-level parameters, fields, Information Elements (IE), settings, etc., can also be modified interchangeably. In this disclosure, Medium Access Control (MAC) elements (MAC ControlElement (CE)), update commands, activation / deactivation commands, etc., can also be modified interchangeably.

[0438] In this disclosure, higher-layer signaling may also be any one or a combination of the following: Radio Resource Control (RRC) signaling, Medium Access Control (MAC) signaling, broadcast information, other messages (e.g., positioning protocol messages (e.g., NR Positioning Protocol A (NRPPa) / LTE Positioning Protocol (LPP) messages, etc. from the core network)).

[0439] In this disclosure, MAC signaling may also use, for example, a MAC Control Element (MACCE) or a MAC Protocol Data Unit (PDU). Broadcast information may also be, for example, a Master Information Block (MIB), a System Information Block (SIB), a Minimum System Information (Remaining Minimum System Information (RMSI)), or Other System Information (OSI).

[0440] In this disclosure, physical layer signaling may also be, for example, downlink control information (DCI) or uplink control information (UCI).

[0441] In this disclosure, indexes, identifiers (IDs), indicators, indications, resource IDs, etc., can be interchanged. Sequences, lists, sets, groups, clusters, subsets, etc., can also be interchanged.

[0442] In this disclosure, the following terms are used: panel, UE panel, panel group, beam, beam group, precoder, uplink (UL) transmitting entity, transmission / reception point (TRP), base station, spatial relation information (SRI), spatial relation, SRS resource indicator (SRI), control resource set (CORESET), physical downlink shared channel (PDSCH), codeword (CW), transport block (TB), reference signal (RS), antenna port (e.g., demodulation reference signal (DMRS)) port, antenna port group (e.g., DMRS port group), group (e.g., spatial relation group, code division multiplexing (CDM) group, reference signal group, CORESET group, physical uplink control channel). Channel (PUCCH) groups, PUCCH resource groups, resources (e.g., reference signal resources, SRS resources), resource sets (e.g., reference signal resource sets), CORESET pools, downlink transmission configuration indication states (TCI states) (DL TCI states), uplink TCI states (UL TCI states), unified TCI states, common TCI states, quasi-co-location (QCL) and QCL concepts can also be rewritten.

[0443] In this disclosure, CSI-RS, Non-Zero Power (NZP) CSI-RS, Zero Power (ZP) CSI-RS, and CSI Interference Measurement (CSI-IM) can be rewritten interchangeably. Furthermore, CSI-RS can also include other reference signals.

[0444] In this disclosure, the RS being measured / reported may also mean the RS being measured / reported for the purpose of CSI reporting.

[0445] In this disclosure, timing, moment, time, time slot, sub-time slot, code element, subframe, etc., can also be rewritten to each other.

[0446] In this disclosure, direction, axis, dimension, domain, polarization, polarization components, etc., can also be rewritten in relation to each other.

[0447] In this disclosure, estimation, prediction, and inference can be rewritten interchangeably. Furthermore, in this disclosure, making an estimate, making a prediction, and making an inference can also be rewritten interchangeably.

[0448] In this disclosure, autoencoders, encoders, decoders, etc., can also be rewritten as at least one of models, ML models, neural network models, AI models, AI algorithms, etc. Furthermore, autoencoders can be rewritten with any autoencoder such as stacked autoencoders or convolutional autoencoders. The encoder / decoder of this disclosure can also employ models such as Residual Networks (ResNet), Dense Networks (DenseNet), and RefineNet.

[0449] In this disclosure, bits, bit strings, bit sequences, sequences, values, information, values ​​derived from bits, and information derived from bits can also be rewritten in relation to each other.

[0450] In this disclosure, the layers (regarding the encoder) can also be rewritten with layers (input layers, intermediate layers, etc.) used in AI models. The layers in this disclosure can also be equivalent to at least one of the following: input layer, intermediate layer, output layer, batch normalization layer, convolutional layer, activation layer, dense layer, normalization layer, pooling layer, attention layer, dropout layer, fully connected layer, etc.

[0451] In this disclosure, RSRP can also be rewritten with any parameters related to received power / received quality (e.g., RSRQ, SINR, CSI).

[0452] In this disclosure, RS can also be, for example, CSI-RS, SS / PBCH block (SS block (SSB)), etc. Furthermore, RS index can also be CSI-RS resource indicator (CSI-RS Resource Indicator (CRI)), SS / PBCH block indicator (SS / PBCH Block Indicator (SSBRI)), etc.

[0453] In this disclosure, channel measurement / estimation may also be performed using at least one of the following: Channel State Information Reference Signal (CSI-RS), Synchronization Signal (SS), Synchronization Signal / Physical Broadcast Channel (SS / PBCH) block, DeModulation Reference Signal (DMRS), and Sounding Reference Signal (SRS).

[0454] In this disclosure, the receiving beam design, the number of receiving beams, the index of the receiving beams, the selection of the receiving beams, the setting of the receiving beams, and the indication of the receiving beams can be mutually modified. In this disclosure, the receiving beam, the transmitting beam, the DL receiving beam, the DL transmitting beam, and the pair of transmitting and receiving beams can also be mutually modified. In this disclosure, the transmitting / receiving beams can also be mutually modified with the transmitting / receiving beams used for beam prediction and the transmitting / receiving beams used for CSI measurement / reporting for beam prediction.

[0455] In this disclosure, "functionality" can refer to either the purpose of a model or the physical meaning of its inputs / outputs. Multiple models may also have the same functionality. Monitoring (performance verification) / activation / deactivation / toggle / rollback / update can also be indicated (controlled) based on functionality (e.g., per function).

[0456] In this disclosure, functionality may refer to features (requiring AI / ML capabilities) such as reporting information based on CSI prediction / CSI compression / temporal beam prediction / spatial domain beam prediction.

[0457] Furthermore, a model ID can also refer to an identifier for a model (or a collection of models). Multiple models can also be assigned the same model ID in an actual deployment. In this case, these models are actually different models (e.g., different numbers of layers, etc.), but can be treated as the same model.

[0458] Furthermore, in this disclosure, the model ID can be interchanged with the ID of the metadata (or a set of metadata). The metadata (or metadata ID) can also be associated with information related to model / functionality applicability, environment, UE / gNB settings, etc.

[0459] In this disclosure, functionality can also be simply rewritten as "function".

[0460] In this disclosure, functionality, function, functional ID, model, and model ID can be overridden.

[0461] In this disclosure, applicable update, updating applicable models / functionality, updating the applicability of models / functionality, and applicable update can be overridden with each other.

[0462] In this disclosure, updates, reports, and transmissions can be overridden.

[0463] In this disclosure, the applicability report and the applicable report can be rewritten from each other.

[0464] In this disclosure, metadata, auxiliary information, perception information, KPIs, performance KPIs, UE status, and status can be interchanged.

[0465] In this disclosure, terms such as discard, abort, cancel, puncture, rate matching, postpone, and do not send can be rewritten interchangeably.

[0466] In this disclosure, consistency, coherence, and consistency can be interchanged.

[0467] In this disclosure, consistency and integration can be interchanged.

[0468] In this disclosure, ID can represent an ID corresponding to at least one of the properties of a dataset, model, or channel / RS (used to determine at least one of those properties). That is, in this disclosure, ID, dataset ID, model ID, and channel / RS property ID can be overridden with each other.

[0469] In this disclosure, the start of a report and the triggering of a report can be rewritten.

[0470] In this disclosure, ID, consistency, consistency ID, and consistency indicator can be overridden.

[0471] In this disclosure, receiving an ID, receiving information related to the ID, and receiving a consistency indication (related information) can be overridden.

[0472] In this disclosure, the specific duration of receiving ID / consistency indication, duration, duration corresponding to receiving ID, consistency duration, consistency indication time, consistency application time, ID / consistency receivable time, and receivable time can be interchanged.

[0473] (Wireless communication method)

[0474] The embodiments disclosed herein can be broadly categorized as follows.

[0475] • First implementation method: Consistency ID / Consistency Indicator.

[0476] • Second implementation method: A specific correspondence between set A and set B (a gNB-preferred correspondence).

[0477] • Third implementation method: Reporting of beam prediction / CSI prediction.

[0478] The following describes each implementation method based on this information. Each implementation method / option can be applied individually or in combination.

[0479] In this disclosure, the application of AI models is primarily illustrated by beam prediction / CSI prediction [in the spatial / temporal domains]. However, it is not limited to this, and the content of this disclosure can also be applied to other applications.

[0480] In this disclosure, the beams / RS associated with the output (prediction result) of the AI ​​model may also be referred to as set A. The beams / RS associated with the input of the AI ​​model may also be referred to as set B.

[0481] More specifically, in the cases of beam prediction and CSI prediction, set A / set B can be interchanged with resource A / resource B, respectively. Resource A can refer to the resource associated with the predicted value. Resource B can refer to the resource that is measured to derive the predicted value (i.e., the resource associated with the measured value).

[0482] Furthermore, in the case of CSI prediction, set A / set B can be interchanged with antenna port A / antenna port B, respectively. Antenna port A can refer to the antenna port associated with the predicted value (predicted CSI). Antenna port B can refer to the antenna port measured to derive the predicted value.

[0483] In addition, in the case of CSI prediction, resource A and antenna port A can be combined to form set A, and resource B and antenna port B can be combined to form set B.

[0484] In this disclosure, set A, resource A, antenna port A, and predicted values ​​can be interchanged. Furthermore, set B, resource B, antenna port B, and measured values ​​can be interchanged.

[0485] In this disclosure, consistency indicators can be overridden with consistency flags.

[0486] In this disclosure, “consistent” can mean “same” or “similar”, that is, the collected measurements (predictions) show the same (similar) data distribution characteristics (trends).

[0487] The UE / NW (gNB) can apply the various implementation methods shown below to perform model identification / beam prediction / CSI prediction.

[0488] The UE can receive various settings for model identification / beam prediction / CSI prediction / reporting. Furthermore, the UE can report / send the corresponding prediction results to the NW.

[0489] The NW can send various settings to the UE for model identification, beam prediction, CSI prediction, and reporting. Furthermore, the NW can receive the corresponding prediction results (reports) from the UE.

[0490] In this disclosure, beam prediction and predicted beam can be interchanged. Furthermore, CSI prediction and predicted CSI can be interchanged.

[0491] <First Implementation Method>

[0492] The first implementation corresponds to the above-mentioned issue 1 and involves consistency ID / consistency indication.

[0493] <<Method 1-1>>

[0494] Method 1-1 involves the concept of the gNB side (transmitting side).

[0495] The UE can apply specific assumptions about consistency based on the presence or absence of specific settings related to consistency (settings of parameters indicating consistency).

[0496] Specifically, when a parameter indicating consistency (consistency ID / consistency indication) is set (activated) in a specific setting (configX), and / or when a specific setting ID (configID) is set / indicated via higher-layer signaling / physical layer signaling, the UE may envision at least one of the following for the RS / channel associated with that setting.

[0497] For example, the UE can assume that the characteristics of the RS / channel are consistent. An example of such a characteristic is given below.

[0498] (gNB beam-related concepts)

[0499] For each RS / channel associated with a resource / resource set, the UE can assume that at least one of the following characteristics is consistent.

[0500] • The spatial transmission filter used.

[0501] • Boresight (pointing direction) (horizontal axis / vertical axis).

[0502] • Relative pointing direction / pointing direction related relationships between resources (e.g., angle of resource #1 < angle of resource #2 < angle of resource #3).

[0503] • Beam shape (e.g., beamwidth).

[0504] • Relative power. Relative power can be a value per angle / per beam / per TRP.

[0505] QCL.

[0506] Each of the above characteristics can be associated with a specific ID (consistent ID).

[0507] (Send-related ideas from gNB)

[0508] For each RS / channel associated with a resource / resource set, the UE can assume that at least one of the following characteristics is consistent.

[0509] • Doppler offset / Doppler spread / average delay / delay spread.

[0510] • TRP / antenna / antenna panel / RF chain (e.g., the UE may envision that the RS / channel is transmitted through the same TRP / antenna / antenna panel / RF chain).

[0511] • Relative position / relative distance between multiple panels.

[0512] • Carrier / baseband frequency.

[0513] • Frame / subframe / signaling timing.

[0514] • Antenna spacing of gNB / Transmitter layout.

[0515] Each of the above characteristics can be associated with a specific ID (consistent ID).

[0516] (Specific settings (configX))

[0517] A specific setting (configX) can be at least one of the following.

[0518] • Reporting configuration.

[0519] • Resource settings.

[0520] • Resource set settings.

[0521] Specifically, it can be used to instantiate CSI-ReportConfig, CSI-ResourceConfig, nzp-CSI-RS-ResourceSet, nzp-CSI-RS-Resource, CSI-SSB-ResourceSet, SSB-Index, CSI-IM-ResourceSet, and CSI-IM-Resource.

[0522] (Consistent ID)

[0523] The consistency ID can be at least one of the following.

[0524] • Dataset ID.

[0525] Model ID.

[0526] • Data collection setting ID.

[0527] • Report setting ID.

[0528] • Resource setting ID.

[0529] • Resource set ID.

[0530] Specifically, it can instantiate reportConfigId, CSI-ResourceConfigId, nzp-CSI-ResourceSetId, nzp-CSI-ResourceId, csi-SSB-ResourceSetId, SSB-Index, CSI-IM-ResourceSetId, and CSI-IM-ResourceId.

[0531] (Specific configuration ID (configID))

[0532] A specific configuration ID (configID) can be at least one of the following.

[0533] • Report setting ID.

[0534] • Resource setting ID.

[0535] • Resource set ID.

[0536] Specifically, it can instantiate reportConfigId, CSI-ResourceConfigId, nzp-CSI-ResourceSetId, nzp-CSI-ResourceId, csi-SSB-ResourceSetId, SSB-Index, CSI-IM-ResourceSetId, and CSI-IM-ResourceId.

[0537] In addition, specific configurations (configX) / consistency IDs / specific configuration IDs (configID) are not limited to those listed above (e.g., existing parameters), and can also be specified separately through the specification as unique values ​​(parameters) related to consistency.

[0538] (Assuming it is set as a valid region / time / frequency)

[0539] The following can be exemplified as a valid area (validity area) as described above. This area may also simply be referred to as a valid area, etc.

[0540] • All regions.

[0541] • A specific region. For example, a region ID / NR cell global ID / NR physical cell ID / Evolved Cell Global Identifier (ECGI) or a set of these IDs.

[0542] Parameters related to the valid area (e.g., validityAreaList above) may include ARFCN-ValueNR and a list of physical cells (e.g., ValidityCellList). The list of cells may also consist of PCI-Range or PCI. Here, PCI-Range may also be a set of physical cells (one or more) represented by a start value (start index, start value) and a range.

[0543] Parameters related to the effective area can be defined in advance through specifications or set / indicated through higher-layer signaling / physical layer signaling.

[0544] The following can be an example of what is meant by setting the above-mentioned time as the validity period. This time can also simply be referred to as the validity period, etc.

[0545] • All durations.

[0546] • A specific time duration. This duration can be one of the durations mentioned above (e.g., consistency application time).

[0547] The following can be an example of what is meant by setting the frequency as valid (validity frequency). This frequency can also simply be referred to as the valid frequency, etc.

[0548] • All frequencies.

[0549] • A specific frequency. For example, a specific frequency band / bandwidth / BWP ID / ARFCN (Absolute radio-frequency channel number), or a set of these.

[0550] This approach allows for a clear understanding of the consistency requirements on the sending side (gNB side).

[0551] <<Method 1-2>>

[0552] Methods 1-2 involve the assumptions / methods (manners) on the UE side (receiving side).

[0553] The UE can control the reception of RS / channels by applying specific assumptions / methods (manners) related to consistency based on the presence or absence of specific settings (settings of parameters indicating consistency).

[0554] Specifically, when a parameter indicating consistency (consistency ID / consistency indication) is set (activated) in a specific setting (configX), and / or when a specific setting ID (configID) is set / indicated via higher-layer signaling / physical layer signaling, the UE may, for the RS / channel associated with that setting, envision at least one of the following (applying at least one of the following methods) thereby controlling reception.

[0555] For example, the UE can assume that the characteristics of the RS / channel are consistent and control the reception of the RS / channel. An example of a characteristic is given below.

[0556] (UE beam-related [concept])

[0557] For each RS / channel associated with a resource / resource set, the UE can assume that at least one of the following characteristics is consistent.

[0558] • The space receiving filter used.

[0559] • Direction of view.

[0560] • Relative pointing direction / Relationship between pointing directions of resources (e.g., angle of resource #1 < angle of resource #2 < angle of resource #3).

[0561] • Beam shape (e.g., beamwidth).

[0562] • Relative power. Relative power can be a value per angle / per beam / per TRP.

[0563] • The method / mechanism for determining the receive beam (e.g., random selection of the receive beam, or selection of the best receive beam based on past measurements).

[0564] Each of the above characteristics can be associated with a specific ID (consistent ID).

[0565] (UE reception related [concept])

[0566] For each RS / channel associated with a resource / resource set, the UE can assume that at least one of the following characteristics is consistent.

[0567] • TRP / antenna / antenna panel / RF chain (e.g., the UE can use the same TRP / antenna / antenna panel / RF link to receive RS / channel).

[0568] • Relative position / relative distance between multiple panels.

[0569] • Carrier / baseband frequency.

[0570] • Frame / subframe / signaling timing.

[0571] • UE antenna spacing / receiver layout.

[0572] Each of the above characteristics can be associated with a specific ID (consistent ID).

[0573] (Region / Time / Frequency of Application Reception Manner)

[0574] The area (validity area) where the above receiving method is applied can be exemplified below. This area may also be simply referred to as the valid area, etc.

[0575] • All regions.

[0576] • A specific region. For example, a region ID / NR cell global ID / NR physical cell ID / Evolved Cell Global Identifier (ECGI) or a set of these IDs.

[0577] Parameters related to the valid area (e.g., validityAreaList above) may include ARFCN-ValueNR and a list of physical cells (e.g., ValidityCellList). The list of cells may also consist of PCI-Range or PCI. Here, PCI-Range may also be a set of physical cells (one or more) represented by a start value (start index, start value) and a range.

[0578] Parameters related to the effective area can be defined in advance through specifications or set / indicated through higher-layer signaling / physical layer signaling.

[0579] The validity time (validity time) of applying the above receiving method can be exemplified as follows. This time can also be simply referred to as the validity time, etc.

[0580] • All durations.

[0581] • A specific time duration. This duration can be one of the durations mentioned above (e.g., consistency application time).

[0582] The frequency (validity frequency) used in the above receiving method can be exemplified as follows. This frequency may also be referred to simply as the effective frequency, etc.

[0583] • All frequencies.

[0584] • A specific frequency. For example, a specific frequency band / bandwidth / BWP ID / ARFCN (Absolute radio-frequency channel number), or a set of these.

[0585] Based on this method, the concept of consistency on the receiving side (UE side) can be clearly defined.

[0586] According to this implementation, the UE can clearly define the consistent assumptions in specific use cases of the AI ​​model (such as beam prediction / CSI prediction).

[0587] <Second Implementation Method>

[0588] The second implementation corresponds to issues 2-3 above and involves a specific correspondence between set A and set B (a gNB-preferred correspondence). This correspondence can be rewritten with consistency.

[0589] <<Method 2-1>>

[0590] Method 2-1 involves beam prediction.

[0591] (Receiving information related to consistency)

[0592] The UE can receive requests for the ability / requirement to report beam prediction related to time-related information (details will be described later) of resource A (set A) / resource B (set B) / prediction values.

[0593] The UE can receive the above information (a request to report beam prediction capability / requirements) using the signaling shown below. This information can also be referred to as consistency-related information.

[0594] • Dedicated signaling (e.g., requests for higher-layer / physical-layer signaling or UE capabilities). Alternatively, this request may be included in the RRC reconfiguration message.

[0595] • System information (e.g., SIB / MIB).

[0596] • Group common signaling (e.g., multicast / broadcast).

[0597] Resource A (set A) / Resource B (set B) can also be indicated / represented by a specific configuration ID / consistency ID / a specific configuration ID (configID) or a set of these IDs.

[0598] Upon receiving the above information (a request to report the capability / requirement of beam prediction), the UE can expect that: the conformance ID / conformance indication is set (activated) within a specific setting / specific setting ID.

[0599] (Report on beam prediction capabilities / requirements)

[0600] The UE can report / transmit beam prediction capabilities / requirements associated with time-related information of resource A (set A) / resource B (set B) / predictions.

[0601] Resource A (set A) / Resource B (set B) can also be indicated / represented by a consistent ID / a specific configuration ID (configID) or a set of these IDs.

[0602] When a consistency ID / consistency indicator is set (activated) in a specific configuration ID, the UE can report / send that specific configuration ID using higher-layer signaling / physical-layer signaling. Alternatively, this report can also be included in the RRC reconfiguration completion message.

[0603] According to this approach, in the case of beam prediction, terminal capabilities for consistent resources A (set A) / resources B (set B) can be shared between the UE and gNB.

[0604] <<Method 2-2>>

[0605] Method 2-2 involves CSI prediction. Method 2-2 can be applied by rewriting "resources" / "sets" in Method 2-1 with "antenna ports". Alternatively, Method 2-1 can also be directly applied to CSI prediction.

[0606] (Receiving information related to consistency)

[0607] The UE can receive requests for the ability / requirement to report CSI predictions associated with time-related information (details will be described later) of antenna port A (resource A / set A) / antenna port B (resource B / set B) / predicted values.

[0608] The UE can receive the above information (a request to report beam prediction capability / requirements) using the signaling shown below. This information can also be referred to as consistency-related information.

[0609] • Dedicated signaling (such as requests for higher-layer signaling / physical layer signaling or UE capabilities). Alternatively, this request can also be included in the RRC reconfiguration message.

[0610] • System information (e.g., SIB / MIB).

[0611] • Group common signaling (e.g., multicast / broadcast).

[0612] Antenna port A (resource A / set A) / antenna port B (resource B / set B) can also be indicated / represented by a specific configuration / consistency ID / specific configuration ID (configID) or a set of these IDs.

[0613] Upon receiving the above information (a request to report the capability / requirement of beam prediction), the UE can expect that: the conformance ID / conformance indication is set (activated) within a specific setting / specific setting ID.

[0614] (Report on CSI forecasting capabilities / requirements)

[0615] The UE can report / transmit the beam prediction capability / requirement associated with the time-related information of antenna port A (resource A / set A) / antenna port B (resource B / set B) / prediction values.

[0616] Antenna port A (resource A / set A) / antenna port B (resource B / set B) can also be indicated / represented by a consistency ID / specific configuration ID (configID) or a set of these IDs.

[0617] When a consistency ID / consistency indicator is set (activated) in a specific configuration ID, the UE can report / send that specific configuration ID using higher-layer signaling / physical-layer signaling. Alternatively, this report can also be included in the RRC reconfiguration completion message.

[0618] According to this approach, in the case of CSI prediction, it is possible to share terminal capabilities for antenna port A (resource A / set A) / antenna port B (resource B / set B) with guaranteed consistency between the UE and gNB.

[0619] According to this implementation, in the case of beam prediction / CSI prediction, UE capabilities between the UE and gNB can be shared between set A and set B, where a specific correspondence (consistency) is guaranteed.

[0620] <Third Implementation Method>

[0621] The third implementation corresponds to issue 4 above and involves a report on beam prediction / CSI prediction.

[0622] <<Method 3-1>>

[0623] Method 3-1 involves the case of beam prediction.

[0624] The UE can be configured / instructed to report beam prediction information based on resource B (set B) and related to the time-dependent information of resource A (set A) / prediction values. This configuration / instruction can be implemented via higher-layer signaling / physical-layer signaling.

[0625] Resource A (set A) / Resource B (set B) can also be set / indicated by a specific setting (configX) / consistency ID / specific setting ID (configID) or a set of these.

[0626] The UE can be envisioned as having a consistency ID / consistency indicator set (activated) in a specific setting (configX) or a setting associated with a specific setting ID (configID).

[0627] The UE may not expect to be configured / instructed to report beam prediction information associated with resources A / B that are not covered by the capability of the second embodiment described above (inactive resources A / B). That is, the UE may also envision not being configured / instructed to report beam prediction information associated with inactive resources A / B.

[0628] The beam prediction information that is reported may include at least one of the following.

[0629] • Beam information (e.g., CQI / SSBRI) related to the top K beams (e.g., CRI) between resources A.

[0630] • Beam information related to the top K beams of prediction between resources A (e.g., CQI / SSBRI), and RSRP related to the top K beams of prediction between resources A.

[0631] • Beam information related to the top K beams of prediction between resources A (e.g., CQI / SSBRI), and probability information related to the top 1 / top K beams of prediction between resources A.

[0632] • Beam information related to the top K beams of prediction between resources A (e.g., CQI / SSBRI), RSRP related to the top K beams of prediction between resources A, and confidence information of that RSRP.

[0633] In addition, the information listed above can be measured / predicted values ​​that are associated with [time-related information].

[0634] According to this method, the UE can appropriately report beam prediction information.

[0635] <<Method 3-2>>

[0636] Method 3-2 pertains to CSI prediction. Method 3-2 can be applied by rewriting "resources" / "sets" in Method 3-1 as "antenna ports". Alternatively, Method 3-1 can also be directly applied to CSI prediction.

[0637] The UE can be configured / instructed to report CSI prediction information based on the time-related information of antenna port B (resource B / set B) and antenna port A (resource A / set A) / prediction value. This configuration / instruction can be implemented via higher-layer signaling / physical-layer signaling.

[0638] Antenna port A (resource A / set A) / antenna port B (resource B / set B) can also be configured / indicated by a specific setting (configX) / consistency ID / specific setting ID (configID) or a set of these.

[0639] The UE can be envisioned as having a consistency ID / consistency indicator set (activated) in a specific setting (configX) or a setting associated with a specific setting ID (configID).

[0640] The UE may not expect to be configured / instructed to report CSI prediction information associated with antenna ports A / B (inactive antenna ports A / B) that are not covered by the capability supporting the second embodiment described above. That is, the UE may also envision not being configured / instructed to report CSI prediction information associated with inactive antenna ports A / B.

[0641] The CSI forecast information that is the subject of the report may include at least one of the following.

[0642] • Channel resource information (e.g., CRI).

[0643] • Prediction matrix information / channel matrix information (e.g., PMI, eigenvector).

[0644] · Channel quality information (e.g., CQI).

[0645] · Rank indicator (e.g., RI).

[0646] In addition, each item of information listed above may be a measured value / predicted value associated with [time association information].

[0647] According to this method, a UE can properly report CSI prediction information.

[0648] According to this embodiment, the UE can appropriately control the reporting of predicted values according to specific usage scenarios (beam prediction / CSI prediction).

[0649] <Supplement>

[0650] <<AI model information>>

[0651] In the present disclosure, AI model information may also refer to information including at least one of the following:

[0652] · Input / output information of the AI model.

[0653] · Information on pre-processing / post-processing for input / output of the AI model.

[0654] · Parameter information of the AI model.

[0655] · Training information for the AI model (training information).

[0656] · Inference information for the AI model.

[0657] · Performance information related to the AI model.

[0658] Here, the input / output information of the above AI model may also include information related to at least one of the following:

[0659] · Content of input / output data (e.g., RSRP, SINR, amplitude / phase information in a channel matrix (or precoding matrix), information related to Angle of Arrival (AoA), information related to Angle of Departure (AoD), position information).

[0660] · Auxiliary information of data (also referred to as meta-information).

[0661] · Type of input / output data (e.g., immutable value, floating-point number).

[0662] • Bit width of input / output data (e.g., 64 bits for each input value).

[0663] • Quantization interval (quantization step size) of input / output data (e.g., 1 dBm for L1-RSRP).

[0664] • The range of input / output data that can be taken (e.g., [0, 1]).

[0665] Additionally, in this disclosure, the information related to AoA may also include information related to at least one of the azimuth angle of arrival and the zenith angle of arrival (ZoA). Furthermore, the information related to AoD may, for example, include information related to at least one of the azimuth angle of departure and the zenith angle of departure (ZoD).

[0666] In this disclosure, location information can also be location information related to the UE / NW. Location information may also include at least one of the following: information obtained using a positioning system (e.g., a satellite positioning system such as Global Navigation Satellite System (GNSS), Global Positioning System (GPS), etc.) (e.g., latitude, longitude, altitude); information about a BS adjacent to (or serving) the UE (e.g., the BS / cell identifier (ID), the distance between the BS and the UE, the direction / angle of the BS (UE) as observed from the UE (BS), the coordinates of the BS (UE) as observed from the UE (BS) (e.g., X / Y / Z axis coordinates), etc.); and a specific address of the UE (e.g., an Internet Protocol (IP) address), etc. The UE's location information is not limited to information based on the location of the BS, but can also be information based on a specific point.

[0667] Location information can also include implementation-related information (e.g., antenna location / position / orientation, antenna panel location / orientation, number of antennas, number of antenna panels, etc.).

[0668] Location information may also include mobility information. Mobility information may also include information indicating the type of mobility and information indicating at least one of the following: the UE's moving speed, the UE's acceleration, and the UE's moving direction.

[0669] Here, the mobility type can also be equivalent to at least one of the following: fixed location UE, movable / moving UE, no mobility UE, low mobility UE, middle mobility UE, high mobility UE, cell-edge UE, and not-cell-edge UE.

[0670] In this disclosure, the environmental information (used for the data) may also be information related to the environment in which the data is acquired / utilized, such as frequency information (band ID, etc.), environmental type information (information indicating at least one of indoor, outdoor, urban macro (UMa) and urban micro (Umi)), information indicating line of sight (LOS) / non-line of sight (NLOS)), etc.

[0671] Here, LOS can also mean that the UE and BS are in an environment where they can see each other (or there are no obstructions), and NLOS can also mean that the UE and BS are not in an environment where they can see each other (or there are obstructions). The information representing LOS / NLOS can represent either a soft value (e.g., the probability of LOS / NLOS) or a hard value (e.g., either LOS or NLOS).

[0672] In this disclosure, metadata can also refer to information related to input / output information suitable for an AI model, information related to data that has been acquired / can be acquired, etc. Specifically, metadata may also include information related to the beams of RS (e.g., CSI-RS / SRS / SSB, etc.) (e.g., the angle pointed to by each beam, 3dB beamwidth, shape of the pointed beam, number of beams), antenna layout information of gNB / UE, frequency information, environmental information, metadata ID, etc. In addition, metadata can also be used as input / output of an AI model.

[0673] The aforementioned preprocessing / postprocessing information for the input / output of the AI ​​model may also include information related to at least one of the following:

[0674] • Whether to apply normalization (e.g., Z-score normalization, min-max normalization).

[0675] • Parameters used for normalization (e.g., normalizing to mean / variance for Z-scores, and to minimum / maximum for minimum-maximum).

[0676] • Whether a specific numerical conversion method is applied (e.g., one-hot encoding, label encoding, etc.).

[0677] • Selection rules for whether or not it is used as training data.

[0678] For example, the input to the AI ​​model can also be used as preprocessing to normalize the Z-score of the input information x (x new = (x - μ) / σ. Here, μ is the mean of x, and σ is the standard deviation. The normalized input information x is obtained by... new It can also be used for the output y from the AI ​​model out The final output y is obtained by post-processing.

[0679] The parameters of the aforementioned AI model may also include information related to at least one of the following:

[0680] • Weight information in AI models (e.g., the coefficients of neurons (coupling coefficients)).

[0681] • The structure of AI models.

[0682] • Types of AI models that serve as model components (e.g., Residual Network (ResNet), DenseNet, RefineNet, Transformer models, CR Blocks, Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM), Gated Recurrent Units (GRU))

[0683] • The functionality of the AI ​​model as a model component (e.g., decoder, encoder).

[0684] In addition, the weight information in the above AI model may also include information related to at least one of the following:

[0685] • Bit width (size) of weight information.

[0686] • Quantization interval of weight information.

[0687] • Granularity of weight information.

[0688] • The range of acceptable weight information.

[0689] • The parameters of the weights in the AI ​​model.

[0690] • Information on the difference between the AI ​​model before and after the update (in the case of an update).

[0691] • Weight initialization methods (e.g., zero initialization, random initialization (based on normal / uniform / truncated normal distribution), Xavier initialization (oriented towards sigmoid function), He initialization (oriented towards rectified linear units (ReLU))).

[0692] Furthermore, the structure of the aforementioned AI model may also include information related to at least one of the following:

[0693] • Number of floors.

[0694] • Layer type (e.g., convolutional layer, activation layer, dense layer, normalization layer, pooling layer, attention layer).

[0695] • Layer information.

[0696] • Parameters specific to time series (e.g., bidirectionality, time step).

[0697] • Parameters used for training (e.g., the type of feature (L2 regularization, dropout feature, etc.) and where to place the feature (e.g., after which layer)).

[0698] The above layer information may also include information related to at least one of the following:

[0699] • The number of neurons in each layer.

[0700] • Kernel size.

[0701] • The stride used for pooling / convolutional layers.

[0702] • Pooling methods (Max Pooling, Average Pooling, etc.).

[0703] • Information about the residual block.

[0704] • Number of heads.

[0705] • Normalization methods (batch normalization, instance normalization, layer normalization, etc.).

[0706] • Activation functions (sigmoid, tanh function, ReLU, Leaky ReLU, Maxout, Softmax).

[0707] An AI model can also be included as a component of other AI models. For example, an AI model can be processed in the following order: ResNet as model component #1, a transformer model as model component #2, dense layers, and normalization layers.

[0708] The training information used for AI models may also include information related to at least one of the following:

[0709] • Information used to optimize the algorithm (e.g., the type of optimization (Stochastic Gradient Descent (SGD)), AdaGrad, Adam, etc.), optimization parameters (learning rate, momentum information, etc.)).

[0710] • Information about the loss function (e.g., information related to the metrics of the loss function (Mean Absolute Error (MAE)), Mean Square Error (MSE)), Cross Entropy Loss, NLLLoss, Kullback-Leibler (KL) Divergence, etc.)).

[0711] • Parameters that should be frozen for training purposes (e.g., layers, weights).

[0712] • Parameters that should be updated (e.g., layer, weight).

[0713] • Parameters that should be used as initial parameters for training (e.g., layers, weights).

[0714] • Training / update methods for AI models (e.g., (recommended) number of epochs, batch size, amount of data used for training).

[0715] The inference information used for the AI ​​model may also include information related to branch pruning of the decision tree, parameter quantization, and the functionality of the AI ​​model. Here, the functionality of the AI ​​model may be equivalent to at least one of the following: temporal beam prediction, spatial beam prediction, autoencoder for CSI feedback, and autoencoder for beam management.

[0716] An autoencoder for CSI feedback can also be used as follows:

[0717] • The UE inputs the CSI / channel matrix / precoding matrix into the encoder's AI model and sends the output encoded bits as CSI feedback (CSI report).

[0718] • The BS inputs the received encoded bits into the AI ​​model of the decoder and reconstructs the output CSI / channel matrix / precoding matrix.

[0719] In spatial domain beam prediction, the UE / BS can also input measurements (beam quality, e.g., RSRP) based on sparse (or thick) beams into the AI ​​model and output dense (or narrow) beam quality.

[0720] In time-domain beam prediction, the UE / BS can also input time-series (past, present, etc.) measurement results (beam quality, e.g., RSRP) into the AI ​​model and output the future beam quality.

[0721] The aforementioned performance information related to the AI ​​model may also include information related to the expected value of the loss function defined for the AI ​​model.

[0722] The AI ​​model information in this disclosure may also include information related to the application scope (applicable scope) of the AI ​​model. This application scope may also be represented by physical cell ID, serving cell index, etc. Information related to the application scope may also be included in the aforementioned environmental information.

[0723] AI model information associated with a specific AI model can be predetermined in the standard or notified to the UE from the network (NW). The AI ​​model specified in the standard can also be referred to as a reference AI model. AI model information associated with the reference AI model can also be referred to as reference AI model information.

[0724] Additionally, the AI ​​model information in this disclosure may also include an index for identifying the AI ​​model (e.g., it may also be referred to as the AI ​​model index, AI model ID, model ID, etc.). The AI ​​model information in this disclosure may also include the AI ​​model index, which, in addition to / instead of the aforementioned AI model input / output information, may also include the AI ​​model index. The association between the AI ​​model index and the AI ​​model information (e.g., the AI ​​model input / output information) can be predetermined in the standard or notified to the UE from the NW.

[0725] The AI ​​model information in this disclosure can also be associated with an AI model and can be referred to as AI model-related information, or simply as related information. AI model-related information may not explicitly include information used to identify the AI ​​model. For example, AI model-related information may only contain metadata.

[0726] In this disclosure, the model ID can also be interchanged with the ID of the set corresponding to the AI ​​model (model set ID). Furthermore, in this disclosure, the model ID can also be interchanged with the metadata ID. As mentioned above, metadata (or metadata ID) can also be associated with beam-related information (beam setting). For example, metadata (or metadata ID) can be used by the UE to consider which beam the BS is using to select the AI ​​model, or it can be used to notify the BS which beam should be used to apply the AI ​​model deployed by the UE. Additionally, in this disclosure, the metadata ID can also be interchanged with the ID of the set corresponding to the metadata (metadata set ID).

[0727] In this disclosure, functionality may mean: a set of parameters that can be supported based on conditions indicated by the UE capability (e.g., a set of parameters for CSI prediction / beam prediction / CSI compression).

[0728] The UE can report parameter values ​​associated with functionality / model as conditions to the NW via higher-layer signaling (e.g., RRC, MAC CE) / physical-layer signaling (e.g., DCI). For example, the UE can also report conditions using reports of UE capabilities / features / feature groups.

[0729] The UE can report parameter values ​​associated with functionality / model as additional conditions to the NW using either higher-layer signaling / physical layer signaling or other methods such as signaling via the NW's air interface (e.g., operator's configurations, pre-set messages, etc.), or it can be instructed to provide such parameter values.

[0730] The UE can use either higher-layer signaling / physical layer signaling or signaling other than those via the NW's air interface (e.g., operator's configurations, pre-set messages, etc.) as information / indications related to additional conditions, to report information / indications about the parameters corresponding to them (e.g., parameter names), or to be indicated with such information / indications.

[0731] For example, the UE can also report device ID, vendor ID, etc., as additional information. Furthermore, the UE can also be notified of the cell ID as an additional condition. In addition, the UE can report information such as cell ID / UE ID, or be instructed on this information, instead of using parameter names.

[0732] Methods other than signaling via the NW's air interface can be methods related to the UE's pre-configuration (e.g., configuration by the UE vendor) or operator configuration provided by the NW operator.

[0733] (Time-related information)

[0734] In this disclosure, time-related information may include at least one of the following.

[0735] • The time offset between each timing associated with the predicted value and a reference timing. The reference timing may refer to a CSI reference resource, a CSI reporting time slot, or a measurement opportunity used to derive the predicted value.

[0736] • A reporting window associated with the forecast. The starting point of the reporting window can be indicated by a time offset and a reference timing. This reference timing can refer to a CSI reference resource, a CSI reporting time slot, or a measurement opportunity used to derive the forecast. The reporting window can be determined by the intervals between the various timings associated with the forecast.

[0737] <<Information Notification to UE>>

[0738] The notification of any information from the network (NW) (e.g., base station (BS)) to the UE in the above-described embodiments (in other words, the reception of any information from the BS in the UE) can also be performed using physical layer signaling (e.g., DCI), higher layer signaling (e.g., RRC signaling, MAC CE), specific signals / channels (e.g., PDCCH, PDSCH, reference signals), or combinations thereof.

[0739] In the case where the above notification is made via MAC CE, the MAC CE can also be identified by including a new Logical Channel ID (LCID) in the MAC subheader that is not specified in the existing standard.

[0740] When the above notification is made through a DCI, the notification can also be made through specific fields of the DCI, the Radio Network Temporary Identifier (RNTI) used in the scrambling of the Cyclic Redundancy Check (CRC) bits assigned to the DCI, the format of the DCI, etc.

[0741] Furthermore, the notification of any information to the UE in the above embodiments can also be carried out periodically, semi-persistently, or non-periodically.

[0742] <<Notifications from UE>>

[0743] The notification of any information from the UE to the NW in the above embodiments (in other words, the transmission / reporting of any information from the UE to the BS) can also be performed using physical layer signaling (e.g., UCI), higher layer signaling (e.g., RRC signaling, MACCE), specific signals / channels (e.g., PUCCH, PUSCH, PRACH, reference signals), or combinations thereof.

[0744] In the case where the above notification is delivered via MAC CE, the MAC CE can also be identified by including a new LCID in the MAC sub-header that is not specified in the existing standard.

[0745] In cases where the above notification is sent via UCI, the above notification may also be sent using PUCCH or PUSCH.

[0746] Furthermore, the notification of any information from the UE in the above embodiments can also be carried out periodically, semi-persistently, or non-periodically.

[0747] <<Application of Each Implementation Method>>

[0748] In the UE / BS, specific processing / operation / control / conception / information regarding at least one of the above embodiments may also be applied (used) if any one or more of the following conditions are met:

[0749] • This indicates that the specific high-level parameters for the aforementioned processing / operation / control / conception / information have been set;

[0750] The specific processing / operation / control / concept / information mentioned above is determined based on relevant high-level parameters;

[0751] • The aforementioned specific processing / operation / control / conception / information is specified / activated / triggered via MAC CE / DCI / UCI / resource / channel / RS;

[0752] • The report or support indicates the specific UE capability (or related) to the aforementioned specific processing / operation / control / conception / information;

[0753] The application of the aforementioned specific processing / operation / control / conception / information is judged based on specific conditions.

[0754] The aforementioned specific UE capabilities can also represent at least one of the following:

[0755] • Supports the specific processing / operation / control / concept / information mentioned above.

[0756] • Supports functional LCM.

[0757] • Consistency indicators in use cases that support the application of AI models (such as beam prediction / CSI prediction).

[0758] Furthermore, the aforementioned specific UE capabilities can be capabilities applied across the entire frequency range (commonly independent of frequency), capabilities for each frequency (e.g., one or a combination of cells, bands, band combinations, BWPs, component carriers, etc.), capabilities for each frequency range (e.g., Frequency Range 1 (FR1)), FR2, FR3, FR4, FR5, FR2-1, FR2-2), capabilities for each subcarrier spacing (SCS) or capabilities for each feature set (FS) or feature set per component-carrier (FSPC)

[0759] Furthermore, the aforementioned specific UE capabilities can be either capabilities that apply to all duplex modes (commonly regardless of the duplex mode) or capabilities that apply to each duplex mode (e.g., Time Division Duplex (TDD) and Frequency Division Duplex (FDD)).

[0760] If the above conditions are not met, the UE / BS may also follow the operations specified in the existing 3GPP version.

[0761] (Postscript)

[0762] Regarding one embodiment of this disclosure (the first embodiment), the invention is described below.

[0763] [Postscript 1]

[0764] A terminal having:

[0765] The receiving unit receives information related to consistency used for model recognition; and

[0766] The control unit, based on the presence or absence of specific parameters contained in the information, applies specific assumptions related to consistency.

[0767] When the specific parameter is set or activated, the control unit assumes that the characteristics of the reference signal (RS) or channel corresponding to the specific parameter are consistent.

[0768] [Postscript 2]

[0769] The terminal as described in Appendix 1, wherein,

[0770] The control unit is envisioned to be consistent in at least one of the following as characteristics of the RS or the channel: spatial transmission filter, line-of-sight direction, relative pointing direction, beam shape, relative power, and quasi-co-addressable (QCL).

[0771] [Postscript 3]

[0772] The terminal as described in Appendix 1 or Appendix 2, wherein,

[0773] The control unit is envisioned to be consistent in at least one of the following characteristics associated with a resource or resource set: Doppler offset, transmit / receive point (TRP), relative position between multiple panels, carrier, frame, and transmit / receive layout.

[0774] [Postscript 4]

[0775] The terminal as described in any one of Annexes 1 to 3, wherein,

[0776] The specific parameters include at least one of the following: dataset ID, model ID, data collection ID, report setting ID, resource setting ID, and resource set setting ID.

[0777] (Postscript)

[0778] Regarding one embodiment (second to third embodiments) of this disclosure, the following invention is noted.

[0779] [Postscript 1]

[0780] A terminal having:

[0781] The receiving unit receives information related to consistency used for model recognition; and

[0782] The control unit, based on the presence or absence of specific parameters contained in the information, applies specific assumptions related to consistency.

[0783] The receiving unit receives a request for the ability to report beam prediction or channel state information (CSI) predictions related to a set A associated with the model's output and a set B associated with the model's input.

[0784] The control unit reports the capability based on the request.

[0785] [Postscript 2]

[0786] The terminal as described in Appendix 1, wherein,

[0787] When the receiving unit receives the request, the control unit expects the specific parameter to be set or activated.

[0788] [Postscript 3]

[0789] The terminal as described in Appendix 1 or Appendix 2, wherein,

[0790] The set A or the set B is indicated by a consistent ID contained in the specific parameter.

[0791] [Postscript 4]

[0792] The terminal as described in any of Appendix 1 to Appendix 3, wherein...

[0793] The control unit controls the reporting of beam prediction information or CSI prediction information based on set B and associated with set A.

[0794] (Wireless communication system)

[0795] The structure of a wireless communication system according to one embodiment of this disclosure will now be described. In this wireless communication system, communication is performed using any one or a combination of the wireless communication methods according to the above embodiments of this disclosure.

[0796] Figure 9This is a diagram illustrating an example of the schematic structure of a wireless communication system according to one embodiment. The wireless communication system 1 (also referred to simply as System 1) may also be a system that uses Long Term Evolution (LTE) or 5th generation mobile communication system New Radio (5GNR) as standardized by the Third Generation Partnership Project (3GPP).

[0797] Furthermore, the wireless communication system 1 can also support dual connectivity between multiple radio access technologies (RATs) (Multi-RAT Dual Connectivity (MR-DC)). MR-DC can also 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.

[0798] In EN-DC, the LTE (E-UTRA) base station (eNB) is the Master Node (MN), and the NR base station (gNB) is the 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.

[0799] Wireless communication system 1 can also support dual connectivity between multiple base stations within the same RAT (e.g., MN and SN are dual connectivity between NR base stations (gNB) (NR-NR Dual Connectivity (NN-DC))).

[0800] The wireless communication system 1 may also include a base station 11 forming a macro cell C1 with a relatively wide coverage area, and a base station 12 (12a-12c) configured within the macro cell C1 and forming a small cell C2 narrower than the macro cell C1. The user terminal 20 may also be located within at least one cell. The configuration, number, shape, size, etc., of each cell and the user terminal 20 are not limited to the manner shown in the figure. Hereinafter, without distinguishing between base stations 11 and 12, they will be collectively referred to as base station 10.

[0801] Alternatively, the wireless communication system 1 can also utilize Multiple Input Multiple Output (MIMO). For example, a cell can be formed by one antenna / base station 10 or by multiple antennas / base stations 10. A [virtual] cell (e.g., also called a supercell) can also be composed of multiple [virtual] cells (e.g., also called subcells). A supercell can also be equivalent to a cell with a fixed physical range, and a subcell can also be equivalent to a cell with a semi-static / dynamically varying physical range. In this case, the wireless communication system 1 can also be called a cellless system.

[0802] User terminal 20 may also connect to at least one of multiple base stations 10. User terminal 20 may also utilize at least one of carrier aggregation (CA) using multiple component carriers (CC) and dual connectivity (DC).

[0803] Each CC can also be included in at least one of the first frequency band (Frequency Range 1 (FR1)) and the second frequency band (Frequency Range 2 (FR2)). Macro cell C1 can also be included in FR1, and small cell C2 can also be included in FR2. For example, FR1 can also be a frequency band below 6 GHz (sub-6 GHz), and FR2 can also be a frequency band above 24 GHz (above-24 GHz). In addition, the frequency bands, definitions, etc. of FR1 and FR2 are not limited to these; for example, FR1 can also correspond to a frequency band higher than FR2.

[0804] In addition, in each CC, the user terminal 20 may also use at least one of Time Division Duplex (TDD) and Frequency Division Duplex (FDD) for communication.

[0805] Multiple base stations 10 can also be connected via wired (e.g., fiber optic based on the Common Public Radio Interface (CPRI), X2 / Xn interface, etc.) or wireless (e.g., NR communication). For example, when NR communication between base stations 11 and 12 is used as a backhaul, base station 11, which is equivalent to a host station, can also be referred to as an Integrated Access Backhaul (IAB) donor, and base station 12, which is equivalent to a relay station, can also be referred to as an IAB node.

[0806] Base station 10 may also be connected to core network 30 via other base stations 10 or directly. Core network 30 may include, for example, at least one of Evolved Packet Core (EPC), 5G Core Network (5GCN), Next Generation Core (NGC), etc.

[0807] The core network 30 may also include, for example, user plane functions (UPF), access and mobility management functions (AMF), session management functions (SMF), unified data management (UDM), application functions (AF), data network (DN), location management functions (LMF), and network functions (NF) such as operation, administration and maintenance (OAM). Alternatively, multiple functions can be provided through a single network node. Furthermore, communication with external networks (e.g., the Internet) can also be achieved via the DN.

[0808] User terminal 20 can also be a terminal that supports at least one of the following communication methods: LTE, LTE-A, 5G, etc.

[0809] In wireless communication system 1, wireless access methods based on Orthogonal Frequency Division Multiplexing (OFDM) can also be used. For example, in at least one of the downlink (DL) and uplink (UL) links, Cyclic Prefix OFDM (CP-OFDM), Discrete Fourier Transform Spread OFDM (DFT-s-OFDM), Orthogonal Frequency Division Multiple Access (OFDMA), and Single Carrier Frequency Division Multiple Access (SC-FDMA) can also be used.

[0810] The wireless access method can also be referred to as a waveform. In addition, in the wireless communication system 1, other wireless access methods (e.g., other single-carrier transmission methods, other multi-carrier transmission methods) can also be used in the wireless access methods of UL and DL.

[0811] As a downlink channel, the wireless communication system 1 can also use downlink shared channels (Physical Downlink Shared Channel (PDSCH)), broadcast channels (Physical Broadcast Channel (PBCH)), downlink control channels (Physical Downlink Control Channel (PDCCH)) and so on, which are shared among the user terminals 20.

[0812] In addition, as uplink channels, the wireless communication system 1 may also use uplink shared channels (Physical Uplink Shared Channel (PUSCH)), uplink control channels (Physical Uplink Control Channel (PUCCH)), random access channels (Physical Random Access Channel (PRACH)) and so on, which are shared by each user terminal 20.

[0813] Additionally, base station 10 can be divided into three elements: Radio Unit (RU), Distributed Unit (DU), and Central Unit (CU). For example, the RU can implement RF processing (digital beamforming, digital-to-analog conversion, analog beamforming, etc.) and lower-level physical layer functions (precoding, IFFT, FFT, etc.). The DU can implement higher-level physical layer functions (from coding to resource element mapping, etc.), MAC layer functions, and RLC layer functions. The CU can implement PDCP layer, Service Data Adaptation Protocol (SDAP) layer, and RRC layer functions.

[0814] In this disclosure, base station 10 may include a single device that implements all the functions of RU, DU, and CU, or it may include multiple devices that implement a portion of the functions of RU, DU, and CU respectively and are interconnected. In this disclosure, base station 10 may also be rewritten in relation to RU / DU / CU.

[0815] User data, high-level control information, and System Information Blocks (SIBs) are transmitted via the PDSCH. User data and high-level control information can also be transmitted via the PUSCH. In addition, Master Information Blocks (MIBs) can also be transmitted via the PBCH.

[0816] Lower-layer control information can also be transmitted via PDCCH. This lower-layer control information may include, for example, downlink control information (DCI), which includes scheduling information for at least one of PDSCH and PUSCH.

[0817] Additionally, the DCI that schedules PDSCH can also be called DL allocation, DL DCI, etc., and the DCI that schedules PUSCH can also be called UL authorization, UL DCI, etc. Furthermore, PDSCH can be rewritten as DL data, and PUSCH can be rewritten as UL data.

[0818] In PDCCH detection, a Control Resource Set (CORESET) and a search space can be utilized. A CORESET corresponds to the resources used to search for DCIs. The search space corresponds to the search area and search method for PDCCH candidates. A CORESET can also be associated with one or more search spaces. The UE can also monitor CORESETs associated with a specific search space based on search space settings.

[0819] A search space can also correspond to a PDCCH candidate corresponding to one or more aggregation levels. One or more search spaces can also be referred to as a search space set. In addition, the terms "search space", "search space set", "search space setting", "search space set setting", "CORESET", and "CORESET setting" in this disclosure can be rewritten interchangeably.

[0820] The PUCCH can also transmit uplink control information (uplink control information (UCI)) that includes at least one of the following: Channel State Information (CSI), delivery confirmation information (e.g., also known as Hybrid Automatic Repeat Request ACK Knowledge (HARQ-ACK), ACK / NACK, etc.), and Scheduling Request (SR). The PRACH can also transmit random access preambles used for establishing connections with the cell.

[0821] In addition, in this disclosure, downlink, uplink, etc., may be described without the word "link". Furthermore, various channels may be described without the word "physical".

[0822] In wireless communication system 1, synchronization signals (SS) and downlink reference signals (DL-RS) can also be transmitted. In wireless communication system 1, DL-RS can also transmit cell-specific reference signals (CRS), channel state information reference signals (CSI-RS), demodulation reference signals (DMRS), positioning reference signals (PRS), and phase tracking reference signals (PTRS).

[0823] Synchronization signals can be, for example, at least one of a primary synchronization signal (PSS) and a secondary synchronization signal (SSS). A signal block containing SS (PSS, SSS) and PBCH (and DMRS for PBCH) can also be called an SS / PBCH block, SS block (SSB), etc. In addition, SS, SSB, etc. can also be called reference signals.

[0824] Furthermore, in wireless communication system 1, the uplink reference signal (UL-RS) can also transmit measurement reference signals (sounding reference signals (SRS)) and demodulation reference signals (DMRS). Additionally, DMRS can also be referred to as user terminal-specific reference signals (UE-specific reference signals).

[0825] (Base station)

[0826] Figure 10This diagram illustrates an example of the structure of a base station according to one embodiment. The base station 10 includes a control unit 110, a transmit / receive unit 120, a transmit / receive antenna 130, and a transmission path interface (transmission line interface) 140. Alternatively, the control unit 110, the transmit / receive unit 120, the transmit / receive antenna 130, and the transmission path interface 140 may each be provided in more than one manner.

[0827] Furthermore, while this example primarily illustrates the functional blocks of the characteristic portions of this embodiment, it can also be envisioned that the base station 10 also possesses other functional blocks required for wireless communication. Some of the processing of each unit described below may also be omitted.

[0828] The control unit 110 performs overall control of the base station 10. The control unit 110 can be composed of a controller, control circuit, etc., which are described based on common knowledge in the art to which this disclosure pertains.

[0829] The control unit 110 can also control signal generation and scheduling (e.g., resource allocation, mapping). The control unit 110 can also control transmission, reception, and measurement using the transmit / receive unit 120, transmit / receive antenna 130, and transmission path interface 140. The control unit 110 can also generate data, control information, sequences, etc., to be transmitted as signals and forward them to the transmit / receive unit 120. The control unit 110 can also perform call processing (setting, releasing, etc.) of the communication channel, status management of the base station 10, and management of wireless resources.

[0830] The transmitting / receiving unit 120 may also include a baseband unit 121, a radio frequency (RF) unit 122, and a measurement unit 123. The baseband unit 121 may also include a transmitting processing unit 1211 and a receiving processing unit 1212. The transmitting / receiving unit 120 may be composed of transmitters / receivers, RF circuits, baseband circuits, filters, phase shifters, measurement circuits, transmitting / receiving circuits, etc., as described based on common knowledge in the art to which this disclosure pertains.

[0831] The transmitting and receiving unit 120 can be configured as a single integrated transmitting and receiving unit, or it can be composed of a transmitting unit and a receiving unit. The transmitting unit can also be composed of a transmitting processing unit 1211 and an RF unit 122. The receiving unit can also be composed of a receiving processing unit 1212, an RF unit 122, and a measurement unit 123.

[0832] The transmitting and receiving antenna 130 can be constructed from an antenna, such as an array antenna, as described based on common knowledge in the art to which this disclosure pertains.

[0833] The transmitting / receiving unit 120 can also transmit the aforementioned downlink channel, synchronization signal, downlink reference signal, etc. The transmitting / receiving unit 120 can also receive the aforementioned uplink channel, uplink reference signal, etc.

[0834] The transmitting and receiving unit 120 may also use digital beamforming (e.g., precoding), analog beamforming (e.g., phase rotation), etc., to form at least one of the transmitting beam and the receiving beam.

[0835] The transmitting and receiving unit 120 (transmitting processing unit 1211) may, for example, perform processing at the Packet Data Convergence Protocol (PDCP) layer, Radio Link Control (RLC) layer (e.g., RLC retransmission control), and Medium Access Control (MAC) layer (e.g., HARQ retransmission control) on the data and control information obtained from the control unit 110, and generate a bit string to be transmitted.

[0836] The transmitting and receiving unit 120 (transmitting processing unit 1211) can also perform transmission processing such as channel coding (which may also include error correction coding), modulation, mapping, filter processing (filtering processing), Discrete Fourier Transform (DFT) processing (as needed), Inverse Fast Fourier Transform (IFFT) processing, precoding, and digital-to-analog conversion on the bit string to be transmitted, and output the baseband signal.

[0837] The transmitting and receiving unit 120 (RF unit 122) can also perform modulation, filtering, amplification, etc. on the baseband signal to the wireless frequency band, and transmit the wireless frequency band signal through the transmitting and receiving antenna 130.

[0838] On the other hand, the transmitting and receiving unit 120 (RF unit 122) can also amplify, filter, and demodulate the signals of the wireless frequency band received through the transmitting and receiving antenna 130 into the baseband signal.

[0839] The transmitting and receiving unit 120 (receiving and processing unit 1212) can also perform receiving and processing on the acquired baseband signal, including analog-to-digital conversion, Fast Fourier Transform (FFT) processing, Inverse Discrete Fourier Transform (IDFT) processing (as needed), filter processing, demapping, demodulation, decoding (which may also include error correction decoding), MAC layer processing, RLC layer processing, and PDCP layer processing, to acquire user data, etc.

[0840] The transmitting / receiving unit 120 (measurement unit 123) can also perform measurements related to the received signal. For example, the measurement unit 123 can also perform radio resource management (RRM) measurements, channel state information (CSI) measurements, etc., based on the received signal. The measurement unit 123 can also 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 can also be output to the control unit 110.

[0841] The transmission path interface 140 can also transmit and receive signals (backhaul signaling) between the device included in the core network 30 (e.g., the network node providing the NF), other base stations 10, etc., and can also acquire and transmit user data (user plane data), control plane data, etc. for the user terminal 20.

[0842] In addition, the transmitting unit and receiving unit of the base station 10 in this disclosure may also be composed of at least one of a transmitting / receiving unit 120, a transmitting / receiving antenna 130, and a transmission path interface 140.

[0843] Additionally, base station 10 can be divided into three elements: Radio Unit (RU), Distributed Unit (DU), and Central Unit (CU). For example, the RU can implement RF processing (digital beamforming, digital-to-analog conversion, analog beamforming, etc.) and lower-level physical layer functions (precoding, IFFT, FFT, etc.). The DU can implement higher-level physical layer functions (from coding to resource element mapping, etc.), MAC layer functions, and RLC layer functions. The CU can implement PDCP layer, Service Data Adaptation Protocol (SDAP) layer, and RRC layer functions.

[0844] In this disclosure, base station 10 may include a single device that implements all the functions of RU, DU, and CU, or it may include multiple devices that implement a portion of the functions of RU, DU, and CU respectively and are interconnected. In this disclosure, base station 10 may also be rewritten in relation to RU / DU / CU.

[0845] Additionally, the transmitting / receiving unit 120 can transmit information related to consistency for model recognition. The control unit 110 can control the generation of the information so that the terminal applies a specific assumption related to consistency based on specific parameters contained in the information. When the specific parameters are set or activated, the control unit 110 can control the reception of reports from terminals that are assumed to have characteristics consistent with the reference signal (RS) or channel corresponding to the specific parameters.

[0846] The transmitting / receiving unit 120 can send a request for reporting the capability of beam prediction or channel state information (CSI) prediction related to a set A associated with the model's output and a set B associated with the model's input. The control unit 110 can, based on the request, control the reception of reports of the capability sent from the terminal.

[0847] (User terminal)

[0848] Figure 11 This diagram illustrates an example of the structure of a user terminal according to one embodiment. The user terminal 20 includes a control unit 210, a transmitting / receiving unit 220, and a transmitting / receiving antenna 230. Alternatively, the control unit 210, the transmitting / receiving unit 220, and the transmitting / receiving antenna 230 may each be provided as one or more.

[0849] Furthermore, while this example primarily illustrates the functional blocks of the characteristic portions of this embodiment, it is also conceivable that the user terminal 20 may also have other functional blocks required for wireless communication. Some of the processing of each unit described below may also be omitted.

[0850] The control unit 210 performs overall control of the user terminal 20. The control unit 210 can be composed of a controller, control circuit, etc., which are described based on common knowledge in the technical field to which this disclosure pertains.

[0851] The control unit 210 can also control signal generation, mapping, etc. The control unit 210 can also control transmission, reception, measurement, etc., using the transmission / reception unit 220 and the transmission / reception antenna 230. The control unit 210 can also generate data, control information, sequences, etc., to be transmitted as signals and forward them to the transmission / reception unit 220.

[0852] The transmitting / receiving unit 220 may also include a baseband unit 221, an RF unit 222, and a measurement unit 223. The baseband unit 221 may also include a transmitting processing unit 2211 and a receiving processing unit 2212. The transmitting / receiving unit 220 may be composed of a transmitter / receiver, RF circuit, baseband circuit, filter, phase shifter, measurement circuit, transmitting / receiving circuit, etc., as described based on common knowledge in the art to which this disclosure pertains.

[0853] The transmitting and receiving unit 220 can be configured as a single integrated transmitting and receiving unit, or it can be composed of a transmitting unit and a receiving unit. The transmitting unit can also be composed of a transmitting processing unit 2211 and an RF unit 222. The receiving unit can also be composed of a receiving processing unit 2212, an RF unit 222, and a measurement unit 223.

[0854] The transmitting and receiving antenna 230 can be constructed from an antenna, such as an array antenna, as described based on common knowledge in the art to which this disclosure pertains.

[0855] The transmitting / receiving unit 220 can also receive the downlink channel, synchronization signal, downlink reference signal, etc., mentioned above. The transmitting / receiving unit 220 can also transmit the uplink channel, uplink reference signal, etc., mentioned above.

[0856] The transmitting and receiving unit 220 may also use digital beamforming (e.g., precoding), analog beamforming (e.g., phase rotation), etc., to form at least one of the transmitting beam and the receiving beam.

[0857] The transmitting and receiving unit 220 (transmitting processing unit 2211) may, for example, perform PDCP layer processing, RLC layer processing (e.g., RLC retransmission control), MAC layer processing (e.g., HARQ retransmission control) on the data and control information obtained from the control unit 210, and generate the bit string to be transmitted.

[0858] The transmitting and receiving unit 220 (transmitting processing unit 2211) can also perform channel coding (which may include error correction coding), modulation, mapping, filter processing, DFT processing (as needed), IFFT processing, precoding, digital-to-analog conversion and other transmission processing on the bit string to be transmitted, and output the baseband signal.

[0859] Furthermore, whether or not to apply DFT processing can be based on the settings of transform precoding. For a certain channel (e.g., PUSCH), if transform precoding is enabled, the transmit / receive unit 220 (transmit processing unit 2211) can perform DFT processing as described above in order to transmit the channel using the DFT-s-OFDM waveform. If not, the transmit / receive unit 220 (transmit processing unit 2211) can perform the above transmission processing without performing DFT processing.

[0860] The transmitting and receiving unit 220 (RF unit 222) can also perform modulation, filtering, amplification, etc. on the baseband signal to the wireless frequency band, and transmit the wireless frequency band signal through the transmitting and receiving antenna 230.

[0861] On the other hand, the transmitting and receiving unit 220 (RF unit 222) can also amplify, filter, demodulate, etc., the signals of the wireless frequency band received by the transmitting and receiving antenna 230.

[0862] The transmitting and receiving unit 220 (receiving and processing unit 2212) can also perform receiving and processing on the acquired baseband signal, such as analog-to-digital conversion, FFT processing, IDFT processing (as needed), filter processing, demapping, demodulation, decoding (which may also include error correction decoding), MAC layer processing, RLC layer processing, and PDCP layer processing, to acquire user data.

[0863] The transmitting / receiving unit 220 (measurement unit 223) can also perform measurements related to the received signal. For example, the measurement unit 223 can also perform RRM measurements, CSI measurements, etc., based on the received signal. The measurement unit 223 can also 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 can also be output to the control unit 210.

[0864] Additionally, the measurement unit 223 can also derive channel measurements for CSI calculation based on channel measurement resources. Channel measurement resources can be, for example, non-zero power (NZP) CSI-RS resources. Furthermore, the measurement unit 223 can also derive interference measurements for CSI calculation based on interference measurement resources. Interference measurement resources can be at least one of NZP CSI-RS resources for interference measurement, CSI-Interference Measurement (IM) resources, etc. Additionally, CSI-IM can also be referred to as CSI-Interference Management (IM), and can be interchanged with zero power (ZP) CSI-RS. Furthermore, in this disclosure, CSI-RS, NZPCSI-RS, ZP CSI-RS, CSI-IM, CSI-SSB, etc., can also be interchanged.

[0865] Alternatively, the transmitting and receiving units of the user terminal 20 in this disclosure may also be composed of at least one transmitting / receiving unit 220 and transmitting / receiving antenna 230.

[0866] Additionally, the transmit / receive unit 220 can receive information related to consistency for model recognition. The control unit 210 can apply specific assumptions related to consistency based on the presence or absence of specific parameters contained in the information. When the specific parameters are set or activated, the control unit 210 can assume that the characteristics of the reference signal (RS) or channel corresponding to the specific parameters are consistent. The control unit 210 can assume that at least one of the following characteristics of the RS or the channel is consistent: spatial transmit filter, line-of-sight direction, relative pointing direction, beamform, relative power, and quasi-co-location (QCL). The control unit 210 can assume that at least one of the following characteristics of the RS or the channel associated with a resource or resource set is consistent: Doppler offset, transmit / receive point (TRP), relative position between multiple panels, carrier, frame, and transmit / receiver layout. The specific parameters may include at least one of dataset ID, model ID, data collection ID, report setting ID, resource setting ID, and resource set setting ID.

[0867] The transmit / receive unit 220 can receive a request for reporting the capability of beam prediction or channel state information (CSI) prediction associated with set A related to the model's output and set B related to the model's input. The control unit 210 can control the reporting of this capability based on the request. Upon receiving the request, the control unit 210 can expect the specific parameter to be set or activated. Set A or set B can be indicated by a consistency ID included in the specific parameter. The control unit 210 can control the reporting of beam prediction information or CSI prediction information associated with set A based on set B.

[0868] (Hardware structure)

[0869] Furthermore, the block diagrams used in the description of the above embodiments illustrate functional units. These functional blocks (structural units) are implemented through any combination of at least one of hardware and software. Moreover, the implementation method of each functional block is not particularly limited. That is, each functional block can be implemented using a single device that is physically or logically combined, or it can be implemented by directly or indirectly (e.g., using wired, wireless, etc.) connecting two or more physically or logically separate devices. A functional block can also be implemented by combining the aforementioned single device or multiple devices with software.

[0870] Here, the functions include judgment, decision, determination, calculation, calculation, processing, export, investigation, search, confirmation, receiving, sending, output, access, resolution, selection, selection, establishment, comparison, assumption, expectation, regard as, broadcasting, notifying, communicating, forwarding, configuring, reconfiguring, allocating, mapping, and assigning, but are not limited to these. For example, a functional block (structural unit) that implements the sending function can also be called a transmitting unit, transmitter, etc. Each of these, as described above, is not particularly limited in its implementation method.

[0871] For example, in one embodiment of this disclosure, the base station, user terminal, etc., can also function as a computer for processing the wireless communication method of this disclosure. Figure 12 This diagram illustrates an example of the hardware structure of a base station and a user terminal according to one embodiment. The base station 10 and the user terminal 20 described above can also be physically configured as a computer device including a processor 1001, a memory 1002, a storage device 1003, a communication device 1004, an input device 1005, an output device 1006, and a bus 1007.

[0872] Furthermore, in this disclosure, terms such as apparatus, circuit, device, section, and unit can be interchanged. The hardware structure of base station 10 and user terminal 20 can be configured to include one or more of the apparatuses shown in the figures, or it can be configured not to include any of the apparatuses.

[0873] For example, only one processor 1001 is shown, but there can be multiple processors. Furthermore, processing can be performed by one processor, or simultaneously, sequentially, or by two or more processors using other methods. Additionally, processor 1001 can be implemented using more than one chip.

[0874] Regarding the functions in base station 10 and user terminal 20, for example, by reading specific software (programs) into hardware such as processor 1001 and memory 1002, so that processor 1001 performs calculations and controls communication via communication device 1004, or by controlling at least one of reading and writing data in memory 1002 and storage device 1003.

[0875] The processor 1001 enables the operating system to operate and control the computer as a whole. The processor 1001 may also be a central processing unit (CPU) that includes interfaces with peripheral devices, control devices, arithmetic devices, registers, etc. For example, at least a portion of the control unit 110 (210), the transmit / receive unit 120 (220), etc., described above may also be implemented by the processor 1001.

[0876] Furthermore, the processor 1001 reads programs (program code), software modules, data, etc., from at least one of the storage 1003 and the communication device 1004 into the memory 1002, and performs various processes accordingly. As a program, a program that causes the computer to perform at least a portion of the operations described in the above embodiments can be used. For example, the control unit 110 (210) can also be implemented by a control program stored in the memory 1002 and operated in the processor 1001; similar implementations can be made for other functional blocks.

[0877] The memory 1002 may also be a computer-readable recording medium, such as being composed of at least one of a read-only memory (ROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a random access memory (RAM), or other suitable storage media. The memory 1002 may also be referred to as a register, cache, main memory (main storage device), etc. The memory 1002 is capable of storing executable programs (program code), software modules, etc., for implementing the wireless communication method according to an embodiment of this disclosure.

[0878] Storage device 1003 may also be a computer-readable recording medium, such as a flexible disc, floppy disk, optical disk (e.g., a compact disc ROM), digital multifunction disk, Blu-ray disc, removable disk, hard disk drive, smart card, flash memory device (e.g., a card, stick, key drive), magnetic stripe, database, server, or at least one other suitable storage medium. Storage device 1003 may also be referred to as an auxiliary storage device.

[0879] The communication device 1004 is hardware (transmitting and receiving device) used for communication between computers via at least one of a wired network and a wireless network. It is also referred to as a network device, network controller, network interface card (NIC), communication module, etc. To implement at least one of, for example, Frequency Division Duplex (FDD) and Time Division Duplex (TDD), the communication device 1004 may be configured to include a high-frequency switch, a duplexer, a filter, a frequency synthesizer, etc. For example, the aforementioned transmit / receive unit 120 (220) and transmit / receive antenna 130 (230) may also be implemented by the communication device 1004. The transmit / receive unit 120 (220) may also be implemented by physically or logically separating the transmit unit 120a (220a) and the receive unit 120b (220b).

[0880] Input device 1005 is an input device that receives input from external sources (e.g., keyboard, mouse, microphone, switch, button, sensor, etc.). Output device 1006 is an output device that performs output to external sources (e.g., display, speaker, light-emitting diode (LED) lamp, etc.). Alternatively, input device 1005 and output device 1006 can also be an integrated structure (e.g., a touch panel).

[0881] Furthermore, the processor 1001, memory 1002, and other devices are connected via a bus 1007 for communicating information. The bus 1007 can be configured as a single bus or as different buses between the devices.

[0882] Furthermore, the base station 10 and the user terminal 20 can also 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 can also use this hardware to implement part or all of the functional blocks. For example, the processor 1001 can also be implemented using at least one of these hardware components.

[0883] In addition, the devices included in the core network 30 (e.g., network nodes providing NF) can also be implemented through the above-described functional block / hardware structure.

[0884] (Variation example)

[0885] Furthermore, the terms described in this disclosure, as well as those necessary for understanding this disclosure, may be replaced with terms that have the same or similar meanings. For example, channel, symbol, and signal (signal or signaling) may be interchanged. Additionally, a signal may also be a message. A reference signal can also be abbreviated as RS, and may be referred to as pilot, pilot signal, etc., depending on the applied standard. Furthermore, a component carrier (CC) may also be referred to as cell, frequency carrier, carrier frequency, etc.

[0886] A radio frame can also be composed of one or more periods (frames) in the time domain. Each of these periods (frames) that constitute a radio frame can also be called a subframe. Furthermore, a subframe can also be composed of one or more time slots in the time domain. A subframe can also be a fixed time length (e.g., 1 ms) independent of the parameter set (numerology).

[0887] Here, the parameter set can also be communication parameters applied in at least one of the transmission and reception of a signal or channel. For example, the parameter set can also represent at least one of the following: subcarrier spacing (SCS), bandwidth, symbol length, cyclic prefix length, transmission time interval (TTI), number of symbols per TTI, radio frame structure, specific filtering processing performed by the transmitter and receiver in the frequency domain, specific windowing processing performed by the transmitter and receiver in the time domain, etc.

[0888] In the time domain, a time slot can also be composed of one or more symbols (Orthogonal Frequency Division Multiplexing (OFDM) symbols, Single Carrier Frequency Division Multiple Access (SC-FDMA) symbols, etc.). In addition, a time slot can also be a time unit based on a set of parameters.

[0889] A time slot can also contain multiple mini-time slots. Each mini-time slot can also consist of one or more symbols in the time domain. Furthermore, a mini-time slot can also be called a sub-time slot. A mini-time slot can also consist of fewer symbols than a time slot. A PDSCH (or PUSCH) transmitted in a time unit larger than a mini-time slot can also be called PDSCH (PUSCH) mapping type A. A PDSCH (or PUSCH) transmitted using mini-time slots can also be called PDSCH (PUSCH) mapping type B.

[0890] Radio frames, subframes, time slots, mini-time slots, and symbols all represent time units for transmitting signals. Radio frames, subframes, time slots, mini-time slots, and symbols can also use their respective other names. Furthermore, the time units such as frames, subframes, time slots, mini-time slots, and symbols in this disclosure can be interchanged.

[0891] For example, a subframe can also be called a TTI, multiple consecutive subframes can also be called a TTI, and a time slot or a mini-time slot can also be called a TTI. That is, at least one of a subframe and a TTI can be a subframe in existing LTE (1ms), a period shorter than 1ms (e.g., 1-13 symbols), or a period longer than 1ms. In addition, the unit representing TTI may not be called a subframe, but rather a time slot, mini-time slot, etc.

[0892] Here, TTI refers, for example, to the smallest unit of time for scheduling in wireless communication. For instance, in an LTE system, the base station schedules radio resources (frequency bandwidth, transmit power, etc., available to each user terminal) in TTI units. However, the definition of TTI is not limited to this.

[0893] TTI can also be a unit of time for transmitting channel-coded data packets (transmission blocks), code blocks, codewords, etc., and can also be a unit of processing such as scheduling and link adaptation. In addition, when a TTI is given, the actual time interval (e.g., the number of symbols) mapped to transmission blocks, code blocks, codewords, etc. can be shorter than the TTI.

[0894] Additionally, where a time slot or a mini-time slot is referred to as a TTI, more than one TTI (i.e., more than one time slot or more than one mini-time slot) can also serve as the minimum time unit for scheduling. Furthermore, the number of time slots (mini-time slots) constituting the minimum time unit of the schedule can also be controlled.

[0895] A TTI with a duration of 1ms can also be referred to as a normal TTI (TTI in 3GPPRel.8-12), a standard TTI, a long TTI, a normal subframe, a standard subframe, a long subframe, a time slot, etc. A TTI shorter than a normal TTI can also be referred to as a shortened TTI, a short TTI, a partial TTI (partial or fractional TTI), a shortened subframe, a short subframe, a mini time slot, a sub-time slot, a time slot, etc.

[0896] In addition, a long TTI (e.g., a normal TTI, a subframe, etc.) can also be rewritten as a TTI with a duration of more than 1 ms, and a short TTI (e.g., a shortened TTI, etc.) can also be rewritten as a TTI with a duration of less than a long TTI but more than 1 ms.

[0897] A resource block (RB) is a unit of resource allocation in both the time and frequency domains. In the frequency domain, it can also contain one or more consecutive subcarriers. The number of subcarriers in an RB can be the same regardless of the parameter set, for example, it can be 12. The number of subcarriers in an RB can also be determined based on the parameter set.

[0898] Furthermore, an RB can contain one or more symbols in the time domain, and can also be a time slot, a mini-time slot, a subframe, or the length of a TTI. A TTI, a subframe, etc., can also be composed of one or more resource blocks.

[0899] In addition, one or more RBs can also be referred to as Physical Resource Blocks (PRBs), Sub-Carrier Groups (SCGs), Resource Element Groups (REGs), PRB pairs, RB pairs, etc.

[0900] Furthermore, a resource block can also consist of one or more resource elements (REs). For example, an RE can also be a radio resource area consisting of a subcarrier and a symbol.

[0901] The Bandwidth Part (BWP) (also referred to as partial bandwidth, etc.) can also represent a subset of consecutive common resource blocks (RBs) used for a certain parameter set in a certain carrier. Here, common RBs can also be determined by the index of RBs based on the common reference point of the carrier. PRBs can also be defined in a BWP and appended with numbers within that BWP.

[0902] A BWP can also include a UL BWP (BWP for UL) and a DL BWP (BWP for DL). For a UE, one or more BWPs can also be set within a single carrier.

[0903] At least one of the configured BWPs can be active, and the UE may not intend to transmit or receive specific signals / channels outside of the active BWPs. Additionally, terms such as "cell" and "carrier" in this disclosure may be replaced with "BWP".

[0904] Furthermore, the structures described above, such as radio frames, subframes, time slots, mini-time slots, and symbols, are merely illustrative. For example, the number of subframes contained in a radio frame, the number of time slots in each subframe or radio frame, the number of mini-time slots contained within a time slot, the number of symbols and RBs contained in a time slot or mini-time slot, the number of subcarriers contained in an RB, and the number of symbols in a TTI, symbol length, and cyclic prefix (CP) length can be varied in many ways.

[0905] Furthermore, the information, parameters, etc., described in this disclosure can be represented by absolute values, relative values ​​with respect to a specific value, or other corresponding information. For example, wireless resources can also be indicated by a specific index.

[0906] In this disclosure, the names used for parameters, etc., are not limiting names in any respect. Furthermore, the mathematical expressions, etc., using these parameters may differ from those explicitly disclosed in this disclosure. Various channels (PUCCH, PDCCH, etc.) and information elements can be identified by any suitable name; therefore, the various names assigned to these various channels and information elements are not limiting names in any respect.

[0907] The information, signals, etc., described in this disclosure can also be represented using any of a variety of different technologies. For example, data, instructions, commands, information, signals, bits, symbols, chips, etc., which may be mentioned throughout the above description, can also be represented by voltage, current, electromagnetic waves, magnetic fields or magnetic particles, light fields or photons, or any combination thereof.

[0908] Furthermore, information, signals, etc., can be output in at least one of the following directions: from higher level (upper layer) to lower level (lower layer), and from lower layer to higher level. Information, signals, etc., can also be input and output via multiple network nodes.

[0909] Input and output information, signals, etc., can be stored in a specific location (e.g., memory) or managed using a management table. Input and output information, signals, etc., can be overwritten, updated, or appended. Output information, signals, etc., can also be deleted. Input information, signals, etc., can also be sent to other devices.

[0910] Regarding any information (e.g., variables, constants, parameters) recorded in this disclosure, even if not specifically stated in the above embodiments, information representing / determining the value of such arbitrary information (or information related to such arbitrary information) may be notified from any first device (e.g., UE / base station) to any second device (e.g., base station / UE).

[0911] The notification of information is not limited to the methods / implementations described in this disclosure, and may also be carried out by other methods. For example, the notification of information in this disclosure may also be implemented by physical layer signaling (e.g., downlink control information (DCI), uplink control information (UCI), etc.), higher layer signaling (e.g., radio resource control (RRC) signaling, broadcast information (Master Information Block (MIB), System Information Block (SIB) etc.), medium access control (MAC) signaling), other signals, or combinations thereof.

[0912] In addition, physical layer signaling can also be referred to as Layer 1 / Layer 2 (L1 / L2) control information (L1 / L2 control signals), L1 control information (L1 control signals), etc. Furthermore, RRC signaling can also be referred to as RRC messages, such as RRC connection setup messages, RRC connection reconfiguration messages, etc. Additionally, MAC signaling can also be notified using, for example, the MAC control element (CE).

[0913] Furthermore, notification of specific information (e.g., a notification of “is X”) is not limited to explicit notification, but can also be implicit (e.g., by not providing that specific information, or by providing other information).

[0914] The determination can be made by a value represented by a single bit (0 or 1), by a true or false value (boolean), or by a comparison of values ​​(e.g., by comparison with a specific value).

[0915] Whether software is called software, firmware, middleware, microcode, hardware description language, or any other name, it should be broadly interpreted to refer to instructions, instruction sets, code, code segments, program code, programs, subprograms, software modules, applications, software applications, software packages, routines, subroutines, objects, executable files, execution threads, procedures, functions, etc.

[0916] Furthermore, software, instructions, information, etc., can also be sent and received via a transmission medium. For example, when software is sent from a website, server, or other remote source using at least one of wired technologies (coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL) etc.) and wireless technologies (infrared, microwave, etc.), at least one of these wired and wireless technologies is included within the definition of transmission medium.

[0917] The terms “system” and “network” as used in this disclosure are interchangeable. “Network” may also mean devices included in a network (e.g., base stations).

[0918] In this disclosure, the terms “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”, “beamwidth”, “beam angle”, “antenna”, “antenna element”, “panel”, “UE panel”, “transmitting entity”, and “receiving entity” are used interchangeably.

[0919] Furthermore, in this disclosure, the antenna port can also be rewritten with an antenna port used for any signal / channel (e.g., a DeModulation Reference Signal (DMRS) port). In this disclosure, resources can also be rewritten with resources used for any signal / channel (e.g., reference signal resources, SRS resources, etc.). Additionally, resources can also include time / frequency / code / space / power resources. Moreover, the spatial domain transmission filter can also include at least one of a spatial domain transmission filter and a spatial domain reception filter.

[0920] The aforementioned groups may include, for example, at least one of the following: spatial relation group, code division multiplexing (CDM) group, reference signal (RS) group, control resource set (CORESET) group, PUCCH group, antenna port group (e.g., DMRS port group), layer group, resource group, beam group, antenna group, panel group, etc.

[0921] Furthermore, in this disclosure, beam, SRS Resource Indicator (SRI), CORESET, CORESET pool, PDSCH, PUSCH, Codeword (CW), Transport Block (TB), RS, etc., can also be rewritten to each other.

[0922] Furthermore, in this disclosure, the TCI state, downlink TCI state (DL TCI state), uplink TCI state (UL TCI state), unified TCI state, common TCI state, and joint TCI state can also be rewritten to each other.

[0923] Furthermore, in this disclosure, terms such as "QCL", "QCL concept", "QCL relationship", "QCL type information", "QCL property (QCLproperty / properties)", "specific QCL type (e.g., type A, type D) property", and "specific QCL type (e.g., type A, type D)" can be rewritten interchangeably.

[0924] In this disclosure, indexes, identifiers (IDs), indicators, indications, resource IDs, etc., can be interchanged. Sequences, lists, sets, groups, clusters, subsets, etc., can also be interchanged.

[0925] Furthermore, the spatial relationship information identifier (Identifier (ID)) (TCI state ID) and the spatial relationship information (TCI state) can be interchanged. "Spatial relationship information (TCI state)" can also be interchanged with "a set of spatial relationship information (TCI states)," "one or more spatial relationship information," etc. TCI state and TCI can also be interchanged. Spatial relationship information and spatial relationship can also be interchanged.

[0926] In this disclosure, the terms "Base Station (BS)", "Wireless 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", and "Component Carrier" are used interchangeably. There are also instances where the terms macro cell, small cell, femtocell, and picocell are used to refer to a base station.

[0927] A base station can accommodate one or more (e.g., three) cells. When a base station accommodates multiple cells, its overall coverage area can be divided into several smaller areas, each of which can also provide communication services through a base station subsystem (e.g., a small indoor base station (Remote Radio Head (RRH))). Terms such as "cell" or "sector" refer to a portion or all of the coverage area of ​​at least one of the base station and base station subsystem providing communication services within that coverage area.

[0928] In this disclosure, the act of a base station sending information to a terminal can also be rewritten in relation to the act of the base station instructing the terminal to perform control / operation based on that information.

[0929] In this disclosure, the terms “Mobile Station (MS)”, “user terminal”, “user equipment (UE)”, and “terminal” are used interchangeably.

[0930] There are also instances where mobile stations are referred to as subscriber stations, mobile units, subscriber units, wireless units, remote units, mobile devices, wireless devices, wireless communication devices, remote devices, mobile subscriber stations, access terminals, mobile terminals, wireless terminals, remote terminals, handsets, user agents, mobile clients, clients, or several other appropriate terms.

[0931] At least one of the base station and the mobile station can also be referred to as a transmitting device, a receiving device, a wireless communication device, etc. Additionally, at least one of the base station and the mobile station can also be a device mounted on a moving object, the moving object itself, etc.

[0932] The term "mobile body" refers to a movable object whose speed is arbitrary, including situations where the body is stationary. Examples of mobile bodies include vehicles, transport vehicles, automobiles, motorcycles, bicycles, connected cars, excavators, bulldozers, wheel loaders, dump trucks, forklifts, trains, buses, handcarts, rickshaws, ships (ships and other watercraft), airplanes, rockets, artificial satellites, drones, multicopters, quadcopters, hot air balloons, and objects carried on them, but are not limited to these. Furthermore, the mobile body can also be a mobile body that moves autonomously based on operational commands.

[0933] The mobile entity can be a means of transportation (e.g., a vehicle, an airplane, etc.), a mobile entity moving in an unmanned manner (e.g., a drone, an autonomous vehicle, etc.), or a robot (humanized or unmanned). Additionally, at least one of the base station and the mobile station includes a device that does not necessarily move during communication operations. For example, at least one of the base station and the mobile station can also be an Internet of Things (IoT) device such as a sensor.

[0934] Figure 13 This is a diagram illustrating an example of a vehicle according to one 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, a speed sensor 51, a 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.

[0935] The drive unit 41 is comprised of at least one of an engine, a motor, or a combination of an engine and a motor. The steering unit 42 is configured to include at least a steering wheel (also called a steering handle) that steers at least one of the front wheels 46 and the rear wheels 47 based on the operation of the steering wheel by the user.

[0936] The electronic control unit 49 consists of a microprocessor 61, a memory (ROM, RAM) 62, and a communication port (e.g., an input / output (IO) port) 63). Signals from various sensors 50-58 present in the vehicle are input to the electronic control unit 49. The electronic control unit 49 can also be referred to as an electronic control unit (ECU).

[0937] The signals from various sensors 50-58 include the following: current signal from current sensor 50 sensing the current of the motor; rotational speed signal of the front wheel 46 / rear wheel 47 obtained by speed sensor 51; air pressure signal of the front wheel 46 / rear wheel 47 obtained by air pressure sensor 52; vehicle speed signal obtained by vehicle speed sensor 53; acceleration signal obtained by acceleration sensor 54; accelerator pedal 43 depress amount signal obtained by accelerator pedal sensor 55; brake pedal 44 depress amount signal obtained by brake pedal sensor 56; shift lever 45 operation signal obtained by shift lever sensor 57; and detection signal obtained by object detection sensor 58 for detecting obstacles, vehicles, pedestrians, etc.

[0938] The information service unit 59 comprises various devices such as a navigation system, audio system, speakers, display, television, and radio, used to provide (output) various information such as driving information, traffic information, and entertainment information, and one or more ECUs that control these devices. The information service unit 59 uses information obtained from external devices via the communication module 60, etc., to provide various information / services (e.g., multimedia information / multimedia services) to the occupants of the vehicle 40.

[0939] The information service unit 59 may include input devices that accept input from the outside (e.g., keyboard, mouse, microphone, switch, button, sensor, touch panel, etc.) or output devices that implement output to the outside (e.g., display, speaker, LED light, touch panel, etc.).

[0940] The driver assistance system unit 64 comprises various devices used to provide functions for preventing accidents or reducing the driver's workload, such as millimeter-wave radar, light detection and ranging (LiDAR), cameras, positioning detectors (e.g., Global Navigation Satellite System (GNSS), map information (e.g., High Definition (HD) maps, Autonomous Vehicle (AV) maps), gyroscope systems (e.g., Inertial Measurement Unit (IMU), Inertial Navigation System (INS)), artificial intelligence (AI) chips, and AI processors, and one or more ECUs that control these devices. Furthermore, the driver assistance system unit 64 sends and receives various information via communication module 60 to realize driver assistance functions or autonomous driving functions.

[0941] The communication module 60 can communicate with the microprocessor 61 and the structural elements of the vehicle 40 via the communication port 63. For example, the communication module 60 sends and receives data (information) with the drive unit 41, steering unit 42, accelerator pedal 43, brake pedal 44, gear shift lever 45, left and right front wheels 46, left and right rear wheels 47, axles 48, microprocessor 61 and memory (ROM, RAM) 62 in the electronic control unit 49 of the vehicle 40, and various sensors 50-58 via the communication port 63.

[0942] The communication module 60 can be controlled by the microprocessor 61 of the electronic control unit 49 and is a communication device capable of communicating with external devices. For example, it can transmit and receive various types of information with external devices via wireless communication. The communication module 60 can be located both inside and outside the electronic control unit 49. The external device can be, for example, the aforementioned base station 10, user terminal 20, etc. Furthermore, the communication module 60 can be, for example, at least one of the aforementioned base station 10 and user terminal 20 (or it can function as at least one of the base station 10 and user terminal 20).

[0943] The communication module 60 can also wirelessly transmit at least one of the signals input to the electronic control unit 49 from the various sensors 50-58 described above, the information obtained based on these signals, and the information based on input from an external (user) source obtained via the information service unit 59 to an external device. The electronic control unit 49, the various sensors 50-58, the information service unit 59, etc., can also be referred to as input units that receive input. For example, the PUSCH transmitted via the communication module 60 can also contain information based on the aforementioned inputs.

[0944] The communication module 60 receives various information (traffic information, signal information, workshop information, etc.) sent from external devices and displays it on the vehicle's information service unit 59. The information service unit 59 can also be referred to as an output unit that outputs information (for example, outputs information to devices such as displays and speakers based on the PDSCH received by the communication module 60 (or the data / information decoded from the PDSCH).

[0945] Furthermore, the communication module 60 stores various types of information received from external devices into a memory 62 that can be utilized by the microprocessor 61. Based on the information stored in the memory 62, the microprocessor 61 can also control the drive unit 41, steering unit 42, accelerator pedal 43, brake pedal 44, gear shift lever 45, left and right front wheels 46, left and right rear wheels 47, axles 48, and various sensors 50-58, etc., of the vehicle 40.

[0946] Furthermore, the base station in this disclosure can also be rewritten as a user terminal. For example, various methods / implementations of this disclosure can be applied to structures where communication between the base station and the user terminal is replaced by communication between multiple user terminals (e.g., also referred to as device-to-device (D2D) or vehicle-to-everything (V2X)). In this case, it can also be configured such that the user terminal 20 has the functions of the base station 10 described above. In addition, terms such as "uplink" and "downlink" can be rewritten as terms corresponding to inter-terminal communication (e.g., "sidelink"). For example, uplink channel, downlink channel, etc., can also be rewritten as sidelink channel.

[0947] Similarly, the user terminal in this disclosure can also be rewritten as a base station. In this case, it can also be configured such that the base station 10 has the functions of the user terminal 20 described above.

[0948] In this disclosure, operations are assumed to be performed by the base station, and sometimes, depending on the circumstances, by its upper node. In a network containing one or more network nodes having a base station, the various operations performed for communication with a terminal can obviously be performed by the base station, one or more network nodes other than the base station (e.g., considering a Mobility Management Entity (MME), a Serving-Gateway (S-GW), etc., but not limited to these), or combinations thereof.

[0949] The various methods / implementations described in this disclosure can be used individually or in combination, and can be switched as needed during execution. Furthermore, the processing procedures, timing sequences, flowcharts, etc., of the various methods / implementations described in this disclosure can be rearranged as long as they do not contradict each other. For example, for the method described in this disclosure, the illustrated order is used to indicate various steps, but the order in which they are indicated is not limited.

[0950] The various methods / implementations described in this disclosure can also be applied to Long Term Evolution (LTE), LTE-Advanced (LTE-A), LTE-Beyond (LTE-B), SUPER 3G, IMT-Advanced, 4th generation mobile communication system (4G), 5th generation mobile communication system (5G), 6th generation mobile communication system (6G), xth generation mobile communication system (xG, where x is, for example, an integer or a decimal)), Future Radio Access (FRA), New-Radio Access Technology (RAT), New Radio (NR), New Radio Access (NX), Futuregeneration Radio Access (FX), Global System for Mobile Communications (GSM (registered trademark)), CDMA2000, Ultra Mobile Broadband (UMB), IEEE This includes 802.11 (Wi-Fi (registered trademark)), IEEE 802.16 (WiMAX (registered trademark)), IEEE 802.20, Ultra-Wideband (UWB)), Bluetooth (registered trademark), systems utilizing other suitable wireless communication methods, and next-generation systems derived from, modified, generated, or specified based on these methods. Furthermore, multiple systems can be combined (e.g., LTE or LTE-A, combinations with 5G, etc.) for application.

[0951] As used in this disclosure, the term "based on" does not mean "based on only" unless otherwise specified. In other words, the term "based on" means both "based on only" and "based on at least".

[0952] Any reference to an element using the designations "first," "second," etc., as used in this disclosure does not comprehensively limit the quantity or order of these elements. These designations may be used in this disclosure as a convenient method of distinguishing between two or more elements. Therefore, reference to the first and second elements does not imply that only two elements may be used, or that the first element must take precedence over the second element in some form.

[0953] The term "determining" as used in this disclosure can encompass a wide variety of operations. For example, "determining" can also refer to judging, calculating, computing, processing, deriving, investigating, looking up (search, inquiry) (e.g., searching in a table, database or other data structure), and ascertaining.

[0954] In addition, "judgment (decision)" can also refer to receiving (e.g., receiving information), transmitting (e.g., sending information), inputting, outputting, accessing (e.g., accessing data in memory), etc., as situations where "judgment (decision)" is performed.

[0955] Furthermore, "judgment (decision)" can also refer to situations where resolving, selecting, choosing, establishing, or comparing are considered as making a "judgment (decision)". That is, "judgment (decision)" can also refer to certain operations as making a "judgment (decision)". In this disclosure, "judgment (decision)" can also be rewritten in relation to the operations described above.

[0956] Furthermore, in this disclosure, "determine / determining" can also be interchanged with "assume / assuming," "expect / expecting," "consider / considering," etc. Additionally, in this disclosure, "not assuming to proceed..." can also be interchanged with "assuming not to proceed..."

[0957] In this disclosure, "expect" can also be interchanged with "be expected." For example, "expect(s)..." (where "..." can also be expressed using a that-clause, a to-infinitive, etc.) can also be interchanged with "be expected..." or "perform..." (where "..." is a to-infinitive, and the verb after "to" is removed). "Does not expect..." can also be interchanged with "be not expected..." or "does not perform..." (where "..." is a to-infinitive, and the verb after "to" is removed). Furthermore, "An apparatus A is not expected..." can also be interchanged with "Apparatus B other than apparatus A does not expect..." (for example, if apparatus A is a UE, apparatus B can also be a base station).

[0958] The term "maximum transmit power" as used in this disclosure may refer to the maximum value of the transmit power, the nominal maximum transmit power (the nominal UE maximum transmit power), or the rated maximum transmit power (the rated UE maximum transmit power).

[0959] As used in this disclosure, the terms “connected,” “coupled,” or all variations thereof, refer to all direct or indirect connections or combinations between two or more elements, and can include cases where there is one or more intermediate elements between two mutually “connected” or “coupled” elements. The connections or combinations between elements can be physical, logical, or a combination thereof. For example, “connection” can also be rewritten as “access.”

[0960] In this disclosure, when two elements are connected, it is possible to consider using more than one wire, cable, printed electrical connection, etc. to be "connected" or "combined" with each other, and as several non-limiting and non-exclusive examples, to use electromagnetic energy with wavelengths having wireless frequency domain, microwave region, light (both visible and invisible) region to be "connected" or "combined" with each other.

[0961] In this disclosure, the term "A is different from B" can also mean "A and B are different from each other." Additionally, the term can also mean "A and B are each different from C." Terms such as "separate" and "combined" can also be interpreted in the same way as "different."

[0962] When the terms "include," "including," and variations thereof are used in this disclosure, these terms, like the term "comprising," mean inclusive. Furthermore, the term "or" as used in this disclosure does not mean XOR.

[0963] In this disclosure, for example, in cases where articles are added through translation, such as a, an, and the in English, the disclosure may also include cases where the noun following these articles is in a plural form.

[0964] In this disclosure, words such as "below," "less than," "above," "more than," and "equal to" can be interchanged. Furthermore, in this disclosure, words meaning "good," "bad," "large," "small," "high," "low," "early," "slow," "wide," and "narrow," etc., are not limited to the positive, comparative, and superlative degrees, and can be interchanged. Additionally, in this disclosure, words meaning "good," "bad," "large," "small," "high," "low," "early," "slow," "wide," and "narrow," etc., as expressions with "i" appended (i being any integer), are not limited to the positive, comparative, and superlative degrees, and can be interchanged (for example, "highest" can also be interchanged with "i-th highest").

[0965] In this disclosure, "of", "for", "regarding", "related to", "associated with", etc., can also be rewritten interchangeably.

[0966] In this disclosure, phrases such as "when A, B", "if A, then B", "B upon A", "B in response to A", "based on A", "B during / while A", "before A", "at the same time as / on A", "after A", "since A", and "until A" can be rewritten interchangeably. Furthermore, A and B can be replaced with nouns, gerunds, or ordinary sentences, depending on the context. Additionally, the time difference between A and B can be approximately 0 (immediately following or immediately preceding). Moreover, a time offset can be applied to the time A occurs. For example, "A" can be rewritten interchangeably with "before / after the time A occurs". This time offset (e.g., more than one symbol / slot) can be predetermined or determined by the UE based on the information it is notified of.

[0967] In this disclosure, timing, moment, time, time instance, arbitrary time unit (e.g., time slot, sub-time slot, symbol, subframe), period, opportunity, resource, etc., can also be overridden.

[0968] The inventions disclosed herein have been described in detail above. However, it will be apparent to those skilled in the art that the inventions disclosed herein are not limited to the embodiments described herein. The description herein is for illustrative purposes only and is not intended to be restrictive in any way.

Claims

1. A terminal, comprising: The receiving unit receives information related to consistency used for model recognition; and The control unit, based on the presence or absence of specific parameters contained in the information, applies specific assumptions related to consistency. When the specific parameter is set or activated, the control unit assumes that the characteristics of the reference signal, i.e., RS or channel, corresponding to the specific parameter are consistent.

2. The terminal as described in claim 1, wherein, The control unit is envisioned to be consistent in at least one of the following as characteristics of the RS or the channel: spatial transmission filter, line-of-sight direction, relative pointing direction, beam shape, relative power, and quasi-co-addressable (QCL).

3. The terminal as described in claim 1, wherein, The control unit is envisioned to be consistent in at least one of the following characteristics associated with a resource or resource set: Doppler offset, transmit / receive point (TRP), relative position between multiple panels, carrier, frame, and transmit / receive layout.

4. The terminal as described in claim 1, wherein, The specific parameters include at least one of the following: dataset ID, model ID, data collection ID, report setting ID, resource setting ID, and resource set setting ID.

5. A wireless communication method for a terminal, comprising: The steps of receiving information related to consistency used for model identification; and Based on the presence or absence of specific parameters contained in the information, specific assumptions related to consistency are applied as steps. When the specific parameter is set or activated, the terminal assumes that the characteristics of the reference signal, i.e., RS or channel, corresponding to the specific parameter are consistent.

6. A base station, comprising: The transmitting unit transmits information related to consistency used for model recognition; and The control unit controls the generation of the information so that the terminal applies a specific assumption related to consistency based on specific parameters contained in the information. When the specific parameter is set or activated, the control unit controls the reception of reports from a terminal whose characteristics are assumed to be consistent with those of a reference signal, i.e., RS or channel, corresponding to the specific parameter.

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