Method and apparatus for beam reporting

Abstract

A method according to embodiments of the present specification comprises the steps of: receiving a reporting configuration related to CSI; and reporting the CSI. The CSI includes one or more RSRPs. The CSI includes: i) first information indicating a first group to which a first RS resource index having the highest RSRP among groups based on RS resource indices configured for measurement belongs; and ii) second information indicating the first RS resource index among RS resource indices within the first group.

Description

Method and device for beam reporting

[0001] The present specification relates to a method and apparatus for beam reporting.

[0002] Mobile communication systems were developed to provide voice services while ensuring user activity. However, they have expanded beyond voice to include data services. Currently, explosive growth in traffic is leading to resource shortages and users are demanding faster services, necessitating a more advanced mobile communication system.

[0003] Next-generation mobile communication systems must support explosive data traffic growth, dramatically increasing data rates per user, a vastly increased number of connected devices, ultra-low end-to-end latency, and high energy efficiency. To achieve these goals, various technologies are being studied, including dual connectivity, massive multiple input multiple output (MIMO), in-band full duplex, non-orthogonal multiple access (NOMA), super wideband support, and device networking.

[0004] In Rel-18 AI / ML SI, studies were conducted on how to utilize AI / ML technologies in three areas: CSI prediction, beam prediction, and positioning. In Rel-19 AI / ML WI, standardization is being discussed in the areas of beam management and positioning. In particular, in beam management, sub-use cases were defined for spatial domain DL Tx beam prediction and temporal DL Tx beam prediction. Both NW-side AI / ML and UE-side AI / ML are considered for each sub-use case.

[0005] Meanwhile, according to the existing method related to beam reporting, i) the highest RSRP (e.g., L1-RSRP with largest measured value quantized to a 7-bit value), ii) differential RSRPs based on the highest RSRP (e.g., differential L1-RSRP quantized to a 4-bit value), and iii) beam IDs related to each RSRP (e.g., CSI-RS Resource Indicator (CRI), SS / PBCH Block Resource indicator (SSBRI)) can be reported.

[0006] For each of the beam management sub-use cases described above, methods for reducing reporting overhead in Set B measurement and reporting operations for NW-side AI / ML are being discussed. Specifically, discussions are underway on omitting the beam ID from existing report contents, which include beam IDs and L1-RSRP values, and reporting only the L1-RSRP values. However, if the beam ID is omitted from the beam report, the criteria for determining the beam ID(s) associated with the reported RSRP(s) may be ambiguous.

[0007] Specifically, if only RSRP value(s) are reported, only the number of beam ID(s) can be determined from the reported RSRP value(s). That is, among the beam IDs set for measurement, the beam ID(s) associated with the reported RSRP value(s) cannot be determined / identified.

[0008] The purpose of this specification is to propose a method to solve the above-mentioned problems.

[0009] The technical problems to be achieved in this specification are not limited to the technical problems mentioned above, and other technical problems not mentioned can be clearly understood by a person having ordinary skill in the technical field to which this specification pertains from the description below.

[0010] A method according to an embodiment of the present disclosure for solving the above-described technical problem includes the steps of receiving a report configuration related to channel state information (CSI) and reporting the CSI. The CSI includes one or more reference signal received powers (RSRPs). The CSI is characterized in that it includes i) first information indicating a first group to which a first RS resource index having a highest RSRP (highest RSRP) among groups based on RS resource indices set for measurement belongs, and second information indicating the first RS resource index among RS resource indices within the first group, or ii) third information indicating the first RS resource index having the highest RSRP.

[0011] Even if the beam ID (CRI / SSBRI) associated with the RSRP(s) is omitted in the beam report, the beam ID(s) associated with the reported RSRP(s) can be clearly determined based on the first / second information or third information described above.

[0012] According to embodiments of the present specification, reporting can be performed excluding beam IDs, while utilizing only minimal additional payload to indicate beam ID(s) associated with reported RSRP(s). Therefore, the reporting overhead required to transmit input data (Set B beam measurement) for beam prediction via the NW-side AI / ML model can be reduced.

[0013] If reporting is performed by simply excluding only beam IDs to reduce reporting overhead, beam IDs unrelated to the reported RSRPs may be utilized as input data for beam prediction through the NW-side AI / ML model. Therefore, the accuracy of the NW-side AI / ML model-based reasoning operation performed after the reporting excluding beam IDs may deteriorate. On the other hand, according to the embodiment of the present specification, beam IDs related to the reported RSRPs among the beam IDs set for measurement can be more clearly identified / determined. Therefore, beam IDs unrelated to the reported RSRPs can be prevented from being utilized as input data. In addition, the accuracy of the NW-side AI / ML model-based reasoning operation performed after the reporting excluding beam IDs can be guaranteed.

[0014] According to an embodiment of the present specification, the first / second information or the third information is mapped first in the CSI, and RSRPs are mapped based on a defined order. Accordingly, it is possible to prevent cases where RS resource indices interpreted as being related to RSRPs based on the mapping order in the CSI are different from RS resource indices related to RSRPs reported by the terminal. Specifically, it is possible to prevent RS resource index(es) different from those measured by the terminal from being utilized as input data for the NW-side model. It is possible to prevent degradation of the inference performance of the NW-side model.

[0015] The effects that can be obtained from this specification are not limited to the effects mentioned above, and other effects that are not mentioned can be clearly understood by a person having ordinary skill in the technical field to which this specification belongs from the description below.

[0016] Figure 1 is a diagram to explain overall functions from an AI / ML model perspective.

[0017] Figure 2 illustrates a general form of AI / ML related procedures performed between a network and a terminal.

[0018] Figure 3 illustrates an example of AI / ML-based beam management operations.

[0019] Figure 4 illustrates an example of AI / ML-based CSI measurement / reporting operations.

[0020] Figure 5 illustrates an example of AI / ML-based positioning operation.

[0021] Figure 6 is a flowchart showing an example of a CSI-related procedure.

[0022] Figure 7 is a flowchart showing an example of a DL BM procedure.

[0023] Figure 8 is a flowchart illustrating a method according to one embodiment of the present specification.

[0024] FIG. 9 is a flowchart illustrating a method according to another embodiment of the present specification.

[0025] FIG. 10 is a drawing showing the configuration of a first device and a second device according to an embodiment of the present specification.

[0026] As used herein, "A or B" can mean "only A," "only B," or "both A and B." In other words, as used herein, "A or B" can be interpreted as "A and / or B." For example, as used herein, "A, B or C" can mean "only A," "only B," "only C," or "any combination of A, B and C."

[0027] As used herein, a slash ( / ) or a comma can mean "and / or." For example, "A / B" can mean "A and / or B." Accordingly, "A / B" can mean "only A," "only B," or "both A and B." For example, "A, B, C" can mean "A, B, or C."

[0028] In this specification, "at least one of A and B" may mean "only A", "only B" or "both A and B". Additionally, in this specification, the expressions "at least one of A or B" or "at least one of A and / or B" may be interpreted identically to "at least one of A and B".

[0029] Additionally, in this specification, “at least one of A, B and C” can mean “only A,” “only B,” “only C,” or “any combination of A, B and C.” Additionally, “at least one of A, B or C” or “at least one of A, B and / or C” can mean “at least one of A, B and C.”

[0030] Additionally, parentheses used herein may mean "for example." Specifically, when indicated as "control information (PDCCH)", "PDCCH" may be proposed as an example of "control information." In other words, "control information" in this specification is not limited to "PDCCH," and "PDCCH" may be proposed as an example of "control information." Furthermore, even when indicated as "control information (i.e., PDCCH)", "PDCCH" may be proposed as an example of "control information."

[0031] In the following explanation, ‘when, if, in case of’ can be replaced with ‘based on’.

[0032] Technical features individually described in a single drawing in this specification may be implemented individually or simultaneously.

[0033] Hereinafter, preferred embodiments according to the present disclosure will be described in detail with reference to the accompanying drawings. The detailed description set forth below, together with the accompanying drawings, is intended to illustrate exemplary embodiments of the present disclosure and is not intended to represent the only embodiments in which the present disclosure may be implemented. The following detailed description includes specific details to provide a thorough understanding of the present disclosure.

[0034] Hereinafter, downlink (DL) refers to communication from a base station to a terminal, and uplink (UL) refers to communication from a terminal to a base station. In downlink, a transmitter may be part of a base station, and a receiver may be part of a terminal. In uplink, a transmitter may be part of a terminal, and a receiver may be part of a base station. A base station may be expressed as a first communication device, and a terminal may be expressed as a second communication device. A base station (BS) may be replaced by terms such as a fixed station, Node B, eNB (evolved-NodeB), gNB (Next Generation NodeB), BTS (base transceiver system), access point (AP: Access Point), network (5G network), AI system, RSU (road side unit), vehicle, robot, drone (Unmanned Aerial Vehicle, UAV), AR (Augmented Reality) device, VR (Virtual Reality) device, etc. In addition, the terminal may be fixed or mobile, and may be replaced with terms such as UE (User Equipment), MS (Mobile Station), UT (user terminal), MSS (Mobile Subscriber Station), SS (Subscriber Station), AMS (Advanced Mobile Station), WT (Wireless terminal), MTC (Machine-Type Communication) device, M2M (Machine-to-Machine) device, D2D (Device-to-Device) device, vehicle, robot, AI module, drone (Unmanned Aerial Vehicle, UAV), AR (Augmented Reality) device, VR (Virtual Reality) device, etc.

[0035] < AI / ML for Wireless Communication >

[0036] With the advancement of computing technology, artificial intelligence (AI) and machine learning (ML) are being adopted in various industries and technical fields. In the field of wireless communications, various discussions are underway to apply AI models trained based on ML, and the 3GPP standardization process refers to this as AI / ML. This specification describes "AI / ML" according to the terminology used in the 3GPP standardization process. However, "AI / ML" may be referred to by various other terms depending on the progress and implementation of future standards. For example, it may be referred to as "transmission / reception mode" or "signal / channel / operation / transmission / reception configuration" configured for AI / ML, but is not limited thereto. The meanings of the terms currently used in the 3GPP standardization process are briefly summarized as follows.

[0037] - AI / ML model: A data-driven algorithm that applies AI / ML technology to generate a set of outputs containing prediction information and / or decision parameters based on a set of inputs.

[0038] - Data collection: The process of collecting data required for AI / ML model training, data analysis, and inference from network nodes, management entities, or terminals.

[0039] - AI / ML Training: An online or offline process of training an AI model by learning features and patterns that best represent the data and obtain a trained AI / ML model for inference.

[0040] - Offline training: The process of training a model based on a previously collected data set, and the trained model is used or provided for future inference.

[0041] - Online training: This is a method in which the model is trained in real time when new training sample data is acquired and used for inference.

[0042] - AI / ML Inference: This is the process of making predictions or inducing decisions based on collected data and the AI ​​model using a trained AI model. Meanwhile, depending on whether the AI / ML model is set up on both the transmitting and receiving devices or only on one of them, it can be divided into (i) a two-sided model and (ii) a one-sided model. (i) In the case of the two-sided model, collaborative inference is performed through paired AI / ML models. Collaborative inference refers to cooperation between the network and the UE, in which one party performs part of the inference and the other party performs the rest of the inference. (ii) The one-sided model is divided into a UE-side model and a network-side model. In the one-sided model, inference is performed entirely by the UE / network-side model.

[0043] 1. Life Cycle Management (LCM) for AI / ML models

[0044] LCM for AI / ML models is a concept that encompasses all the overall procedures for AI / ML models, including data collection, model training, model deployment, model inference, model monitoring, and model updates.

[0045] LCM for AI / ML models can be broadly categorized into functionality-based LCM and model ID-based LCM. In functionality-based LCM, the network can instruct the activation / deactivation / fallback / switching of specific functions, even if the target AI / ML model may not be identified by the network. In model ID-based LCM, the network can instruct the activation / deactivation / selection / switching of AI / ML models identified by their AI / ML model ID.

[0046] Figure 1 is a diagram to explain overall functions from an AI / ML model perspective.

[0047] Referring to Fig. 1, a general AI / ML functional framework can be configured to include a data collection function (10), a model training function (20), a management function (30), an inference function (40), and a model storage function (50).

[0048] The Data Collection function (10) is a function that provides input data to the Model Training function (20), Management function (30), and Inference function (40). The Data Collection function (10) can perform data preparation and provide input data processed through data preparation.

[0049] Here, training data (11) refers to data required as input for the AI / ML Model Training function (20). Monitoring data (12) refers to data required as input for the Management (30) of the AI / ML model or AI / ML function. Inference data (13) refers to data required as input for the AI / ML Inference function (30).

[0050] The Model Training function (20) is a function that performs AI / ML model training, validation, and testing, and can generate model performance metrics that can be used as part of the AI / ML model testing procedure. If necessary, the Model Training function (20) can perform data preparation (e.g., data pre-processing and cleaning, forming, and transformation) based on the Training Data (11) transmitted from the Data Collection function (10).

[0051] Trained / Updated Model (21): If there is a Model Storage function (50), it is used to pass a trained, validated and tested AI / ML model to the Model Storage function (50) or to pass an updated version of the model to the Model Storage function (50).

[0052] The Management function (30) is a function that monitors the operation of the AI / ML model or AI / ML function. In addition, the Management function (30) may perform a decision to ensure appropriate inference operation based on data received from the Data Collection function (10) (i.e., Monitoring Data (12)) and / or data received from the Inference function (40) (i.e., Inference Output (41)).

[0053] Management Instruction (32) is information required as input to manage the Inference function (40). The relevant information may include selection / (de)activation / switching of an AI / ML model or AI / ML-based function, and may also include fallback to non-AI / ML operations (i.e., not relying on the inference process).

[0054] A Model Transfer / Delivery Request (33) can be used to request model(s) from Model Storage (50).

[0055] A Performance Feedback / Retraining Request (31) refers to information required as input to the Model Training function (20) (e.g., for the purpose of (re)training or updating the model).

[0056] The Inference function (40) is a function that provides output from the process of applying an AI / ML model or AI / ML function using data (i.e., Inference Data (13)) provided by Data Collection (10) as input. Data preparation (e.g., data preprocessing and cleaning, formatting, and transformation) may also be performed based on the Inference Data (13) delivered by Data Collection (10). If necessary, the Inference function (40) may also perform data preparation (e.g., data preprocessing and cleaning, forming, and transformation) based on the Inference Data (13) provided by Data Collection function (10).

[0057] Inference Output (41) is data used in the Management function (30) to monitor the performance of an AI / ML model or AI / ML function. Inference Output (41) may include the inference output of the AI / ML model generated by the Inference function (30), and the details of the inference output may vary depending on the use case.

[0058] The Model Storage function (50) stores a learned / updated model that can be used to perform the Inference function (40). The Model Storage function (50) illustrated in Fig. 1 can be used as a reference point (if any) when applicable to protocol termination, model transmission / delivery, and related processes. Furthermore, the Model Storage function (50) is merely an example and is not intended to limit the storage location of actual AI / ML models, and may be omitted.

[0059] Model Transfer / Delivery (51) is used to transfer AI / ML models to inference functions.

[0060] 2. General AI / ML-related procedures between networks and terminals

[0061] Figure 2 illustrates the general form of AI / ML-related procedures performed between a network and a terminal. While Figure 1 examined LCM from an AI / ML model perspective, Figure 2 describes the general form of procedures performed from a signaling / protocol perspective between a terminal and the network.

[0062] (1) Setting procedures related to AI / ML

[0063] Referring to FIG. 2, an AI / ML-related configuration procedure may be performed between the network and the terminal (B05). The AI / ML-related configuration procedure may include information exchange between the terminal and the network via at least one upper-layer signaling, and / or preparatory / follow-up operations at the terminal / network, respectively, before / after the upper-layer signaling.

[0064] Specifically, the AI / ML-related configuration procedure may include, but is not limited to, at least one of (i) AI / ML-related terminal capability reporting, (ii) data collection, (iii) model training, (iv) model transfer / transfer, (v) AI / ML function / model selection, and (vi) configuration for various operations performed based on AI / ML models (e.g., AI / ML-based CSI / Positioning / Beam Management).

[0065] (i) A terminal can report to the network its capabilities, such as models / functionalities supported by the terminal in relation to AI / ML, through UE Capability Reporting. The network can provide AI / ML-related settings to the terminal based on the AI / ML-related capabilities reported by the terminal.

[0066] (ii) AI / ML-related configuration procedures may include data collection and / or provision of configuration information related to AI / ML model training / inference, etc. Configuration information related to data collection may relate to how to configure the method / action of data collection, etc.

[0067] (iii) AI / ML-related configuration procedures may include online or offline AI / ML model training and / or providing configuration information for AI / ML model training. Configuration information for AI / ML model training may relate to how to configure the method / operation of training the AI / ML model, etc.

[0068] (iv) The AI / ML-related configuration procedure may include transmitting / delivering configuration information for the model. The configuration information for the model may include parameters configuring the AI / ML model and / or an identifier (ID) for the AI / ML model.

[0069] The AI / ML model provided can be either a network-trained model or a model that requires self-training on the terminal. Even if a network-trained model is provided, the terminal can perform fine-tuning / retraining processes as needed. Meanwhile, if a network-trained model is provided, the terminal can provide training data to the network.

[0070] Meanwhile, AI / ML models can be categorized into Type A models, which can be identified without over-the-air (OTA) signaling, and Type B models, which are identified through OTA signaling. A model ID can be assigned during the model identification process, which can be further subdivided into terminal-initiated and network-initiated methods.

[0071] (v) The AI / ML-related configuration procedure may include a configuration of how to select an AI / ML Functionality / model and / or a selection process for the AI / ML Functionality / model. Selection of the UE part in a UE-side AI / ML model or a two-sided AI / ML model may be performed through instructions / signaling from the network or may be performed by the UE itself. Selection of the AI / ML Functionality / model may be performed when multiple AI / ML Functionality / models are configured / provided.

[0072] (vi) The AI / ML-related setup procedure may include setup information for various inference operations performed based on AI / ML models, for example, AI / ML-based CSI measurement / reporting, AI / ML-based Positioning, and / or AI / ML-based Beam Management.

[0073] (2) Actions based on inference from AI / ML models

[0074] Referring back to FIG. 2, the network and / or the terminal may perform inference of the AI / ML model through the trained AI / ML model, and perform various operations based on the inference of the AI / ML model (B10). If the AI / ML model is a one-sided model, the inference of the AI / ML model may be performed on either the network or the terminal where the AI / ML model is configured. If the AI / ML model is a two-sided model, each part of the inference of the AI / ML model may be performed on the network and the terminal, and such inference may be performed cooperatively between the network and the terminal depending on the implementation.

[0075] (i) Actions performed based on the inference of the AI / ML model may include AI / ML-based CSI measurement / reporting. The AI / ML-based CSI measurement / reporting may be for improving CSI feedback, and may be related to overhead reduction / CSI compression, accuracy improvement, and / or CSI prediction.

[0076] (ii) The actions performed based on the inference of the AI / ML model may include AI / ML-based beam management. The AI / ML-based beam management may be related to beam prediction in the time domain, reducing overhead / delay in the spatial domain, and / or improving beam selection accuracy.

[0077] (iii) Actions performed based on the inference of the AI / ML model may include AI / ML-based positioning. AI / ML-based positioning may be relevant to improving positioning accuracy in various scenarios, such as non-line-of-sight environments.

[0078] (3) Procedures for AI / ML management

[0079] The network and / or terminal can perform procedures for managing AI / ML Functionality / model or its settings (B15).

[0080] The network and / or terminal may perform monitoring of AI / ML Functionality / model during the process of AI / ML model inference or operation based thereon (B10) for management procedures (B15).

[0081] Management procedures may include, for example, at least one of activation / deactivation, switching, model update, and / or fallback operations for AI / ML Functionality / models. Signaling for management procedures may use various 3GPP signaling methods, such as RRC, MAC-CE, and DCI.

[0082] As an example of model switching, multiple model groups are formed, and switching between them, groups can be performed based on models having a common model structure or partially common sub-structures, and models within the same group can be related to different input / output formats or processing.

[0083] Model updating is the process of changing the parameters used by the model to adapt them to changing channel conditions over time, and fine-tuning is an example of model updating.

[0084] fallback: In a wireless communication system using an AI / ML model, when the reliability of the AI / ML model is reduced due to internal / external environmental factors, it can mean not using the AI / ML model or operating in a default operation mode that is set / defined in advance.

[0085] For example, the decision to perform a management procedure may be made by the network. For example, the network may decide to perform a management procedure upon network initiation, or upon terminal initiation and request.

[0086] As another example, the decision to perform a management procedure can be made by the terminal. For example, the terminal's decision to perform a management procedure can be triggered by the satisfaction of an event condition set by the network, by reporting the terminal's decision to the network, or by the terminal performing the decision autonomously.

[0087] 3. Specific examples of actions based on AI / ML model inference

[0088] (1) Beam management

[0089] Figure 3 illustrates an example of AI / ML-based beam management operations.

[0090] Referring to FIG. 3, the network / terminal can perform a configuration procedure related to AI / ML-based beam management (C05). The network / terminal can exchange configuration information for upper layer signaling for AI / ML-based beam management and perform a configuration procedure for an AI / ML model to be used for AI / ML-based beam management. For example, at least one of information related to model inference, configuration for the first set / second set of beams, monitoring performance, data collection, and assistance information for beam measurement can be signaled.

[0091] The network / terminal can perform measurements on the first set of beams (C10). The beam measurements can be related to RSRP measurements.

[0092] The network / terminal can obtain information about the second set of beams based on the measurement results for the first set of beams (C15). For example, the network / terminal can perform AI / ML inference using the measurement results for the first set of beams as AI / ML input data. Beam ID information may be additionally provided as AI / ML input data. The information about the second set of beams may correspond to AI / ML output data. The AI / ML output data may be related to prediction of future beam quality, such as, but not limited to, the probability that each beam will become a top-N beam, and the predicted RSRP.

[0093] In some embodiments, the network / terminal may transmit and receive information about the acquired second set of beams.

[0094] Specifically, the AI / ML-based beam management operation may include at least one of the following BM-Case 1 and BM-Case 2.

[0095] - BM-Case 1: Prediction of the second set of DL beams in the spatial domain using the first set of beam measurements.

[0096] - BM-Case 2: Prediction of the second set of DL beams in the time domain using the first set of beam measurements.

[0097] In BM-Case 1 and / or 2, both AI / ML model training and inference can be performed in the network or at the terminal. The first set of beams and the second set of beams can be different beams. Alternatively, the first set of beams can be a subset of the second set of beams. Alternatively, particularly in BM-Case 2, the first set of beams and the second set of beams can be the same beams.

[0098] The report corresponding to the inference of the UE-side model for BM-Case 1 may relate to the predicted RSRP for the upper N beams. The report may include, for example, the predicted RSRP value, and for example, the predicted RSRP value may be reported together with the actually measured RSRP.

[0099] UE-side AI / ML model inference for BM-Case 2 can report inference results for N future time points in a single report. Each time point report can correspond to the report for BM-Case 1.

[0100] For performance monitoring of the UE-side model for BM-Case 1 / 2, (i) network side performance monitoring and / or (ii) UE-assisted performance monitoring may be supported. (i) For network side performance monitoring, the UE may report information necessary for the network to calculate performance metrics, for example, measurement results (e.g., RSRP) and / or RS index for a resource set for monitoring. (ii) For UE-assisted performance monitoring, the UE may also calculate performance metrics.

[0101] Regarding the NW-side model for BM-Case 1 / 2, quantization of reported RSRPs may be supported, e.g., differential RSRP reporting may be supported along with existing quantization steps and ranges. The reported content may include information about the RSRP and the corresponding upper N beams, where N may be configured by the network.

[0102] Regarding the configuration of the first set of beams and the second set of beams in the UE-side model of BM Case-1, two resource sets may be separately configured for each of the first set and the second set, and the corresponding resource sets may be provided through the CSI reporting configuration. The terminal may perform inference / measurement for the resource set of the first set of beams. The terminal may not be expected to perform measurement / inference for the resource set of the second set of beams. The beam information of the inference report may include resource set information for the first set.

[0103] In relation to the UE-side model, relevant IDs can be provided via the CSI framework. UEs can assume identical / similar characteristics for DL ​​transmission beams / sets (lists) with the same relevant ID.

[0104] Regarding UE-assisted performance monitoring for the UE-side models of BM-Case 1 and 2, the following methods can be considered.

[0105] i) Compare prediction results based on resources for monitoring and use the top 1 or top K beam prediction accuracy.

[0106] ii) Use RSRP difference information based on RSRP measurements of resources for monitoring and actual RSRP measurements for at least one of the top N predicted beams.

[0107] iii) Use the difference information between the measured RSRP and the predicted RSRP for the corresponding beam of the resources for monitoring.

[0108] iv) Probability information about the predicted beam being one of the top 1 or N beams.

[0109] Quantization of RSRP can be supported for reporting inference results for UE-side models, and differential RSRP with existing quantization steps can be supported. The scope of RSRP reporting is that differential RSRP can be supported among multiple beams in the case of BM-case 1, and differential RSRP can be supported among multiple beams at multiple viewpoints in the case of BM-case 2.

[0110] For BM-Case 2 of the UE-side model, the network can be configured to report inferences for N future time points to the terminal.

[0111] (2) CSI prediction and / or compression (CSI prediction / compression)

[0112] Figure 4 illustrates an example of AI / ML-based CSI measurement / reporting operations.

[0113] Referring to FIG. 4, the network / terminal may perform a configuration procedure related to AI / ML-based CSI (D05). The network / terminal may exchange configuration information for upper-layer signaling for AI / ML-based CSI measurement / reporting, and perform a configuration procedure for an AI / ML model to be used for AI / ML-based CSI. For example, at least one of information related to model inference, configuration of RS / resources to be used for CSI measurement, monitoring performance, data collection, and conditions / resources for CSI reporting may be signaled.

[0114] The terminal can perform CSI measurements based on AI / ML model inference (D10). The AI / ML model used by the terminal for CSI measurements may be a UE-side AI / ML model corresponding to a one-side AI / ML model, or an AI / ML model corresponding to the terminal portion of a two-side AI / ML model.

[0115] A terminal may report CSI to the network based on the CSI measurement results (D15). CSI reporting may be performed periodically or aperiodically depending on the configuration, and in the case of aperiodic CSI reporting, a network instruction (not shown) such as DCI that triggers it may be additionally signaled. CSI reporting may include AI / ML-based CSI content, and additionally (depending on the configuration / scheduling) may further include legacy CSI content (e.g., non-AI / ML-based RI, PMI, CQI, etc.). AI / ML-based CSI content may be related to at least one of 1) CSI compression to reduce the overhead of CSI reporting, and 2) CSI prediction for future time points in the time domain.

[0116] The network can obtain CSI based on the CSI report of the terminal.

[0117] If a two-sided AI / ML model is configured, the network can reconstruct CSI using the terminal's CSI report as input data to the network-configured AI / ML model (D20). The inference (output) of the network-configured AI / ML model can be the reconstructed CSI. In such a two-sided AI / ML model, the terminal-side AI / ML model can be understood as a CSI encoder, while the network-side AI / ML model can be understood as a concept similar to a CSI decoder.

[0118] CSI compression is a spatial-frequency domain CSI compression, which can be primarily based on two-sided AI / ML models. CSI prediction can primarily be based on one-sided, specifically, UE-side AI / ML models.

[0119] In CSI compression based on two-side AI / ML models, AI / ML model training may include at least one of (i) Type 1, in which either the terminal or the network jointly trains two-side AI / ML models, (ii) Type 2, in which the terminal and the network each jointly train their respective two-side AI / ML model parts, and (iii) Type 3, in which the terminal and the network each separately train their respective two-side AI / ML model parts, with the terminal training being primarily related to CSI generation and the network training being primarily related to CSI reconstruction. Joint training means that the CSI generation / reconstruction model is trained in the same loop for forward / backward delays, and separate training may mean a sequential method in which either the terminal or the network starts training first and then the other performs training.

[0120] (3) Positioning

[0121] Figure 5 illustrates an example of AI / ML-based positioning operation.

[0122] Referring to FIG. 5, the network / terminal may perform a configuration procedure related to AI / ML-based positioning (E05). The network / terminal may exchange configuration information for upper-layer signaling for AI / ML-based positioning and perform a configuration procedure for an AI / ML model to be used for AI / ML-based positioning. For example, at least one of information related to model inference, positioning configuration for RS, monitoring performance, data collection, and assistance information for positioning measurement may be signaled.

[0123] The network / terminal can perform measurements for positioning (E10). The measurements for positioning may be related to PRS and / or SRS measurements.

[0124] Based on the measurement results, the network / terminal can obtain information about terminal positioning (E15). For example, the network / terminal can use the PRS / SRS measurement results as AI / ML input data to perform AI / ML inference. Information about terminal positioning may correspond to AI / ML output data. The AI / ML output data may be, for example, terminal location or assistance information that serves as the basis for determining terminal location, but is not limited thereto.

[0125] Depending on the embodiment, the network / terminal may transmit and receive information about the acquired terminal positioning.

[0126] Specifically, the AI / ML-based positioning may include at least one of (i) direct AI / ML positioning and / or (ii) AI / ML-assisted positioning. (i) In direct AI / ML positioning, the output of the AI / ML model includes the UE location. (ii) In AI / ML-assisted positioning, the output of the AI / ML model may be a new measurement result and / or an improvement to an existing measurement (e.g., LoS / NLoS identification, timing and / or angle of the measurement, likelihood of the measurement, etc.).

[0127] The data sample collected for training data collection may include at least one of the following Parts:

[0128] - Part A: Channel measurements, quality indicators of channel measurements, timestamps of channel measurements

[0129] - Part B: ground truth label (or its approximation), label quality indicator, label timestamp

[0130] The training data samples for Part A and Part B may be for the same terminal (e.g., PRU or Non-PRU UE) and for the same location associated with Part B.

[0131] Measurements for positioning can be divided into sample-based measurements and path-based measurements.

[0132] - In sample-based measurements, the measurement consists of Nt' samples of the estimated channel response in the time domain. Timing information for the Nt' samples is reported with a timing granularity T, where T = 2k x Tc. k denotes a timing reporting granularity factor, and Tc denotes the fundamental time unit of the wireless communication system. Nt' and k can be signaled parameters. Timing information can be defined as a value relative to a reference time.

[0133] - Path-based measurement refers to the measurement defined in existing wireless communication systems.

[0134] AI / ML-based positioning may relate to at least one of the following specific cases:

[0135] - (i) Case 1: UE-based positioning using a UE-side model, in the case of direct AI / ML or AI / ML assisted positioning.

[0136] - (ii) Case 2a: UE-assisted / LMF-based positioning using the UE-side model, in the case of AI / ML assisted positioning

[0137] - (iii) Case 2b: UE-assisted / LMF-based positioning using the LMF-side model, in the case of direct AI / ML positioning

[0138] - (iv) Case 3a: NG-RAN node assisted positioning using the gNB-side model, in the case of AI / ML assisted positioning

[0139] - (v) Case 3b: NG-RAN node assisted positioning using LMF-side model, in case of direct AI / ML positioning

[0140] (i) In relation to model performance monitoring in Case 1, the following options may be considered for calculating model performance metrics in label-based model monitoring.

[0141] 1) Option A. Calculate monitoring metrics on the target terminal side.

[0142] - Option A-1: ​​At least some of the information about the target terminal's ground truth label is generated by the LMF and provided to the target terminal. For example, the target terminal and / or base station may send measurement results to the LMF, which may then derive information about the ground truth label.

[0143] - Option A-2: At least part of the information for position calculation assistance data is provided from the LMF to the target UE.

[0144] - Option A-3: This is a method of reusing assistance data previously provided from the LMF to the target terminal, in which PRU measurement results and corresponding PRU location information are provided from the LMF to the target terminal.

[0145] - Option A-4: PRU measurements and PRU locations are provided from the PRU to the target UE.

[0146] 2) Option B. LMF calculates monitoring metrics

[0147] - Option B-1: At least the inference results of the target terminal (i.e., the model output corresponding to the channel measurements of the target terminal) can be transmitted to the LMF by the target terminal.

[0148] - Option B-2: The channel measurement of the PRU is provided to the target terminal through the LMF, and the inference result (i.e., the model output corresponding to the channel measurement of the PRU) can be transmitted from the target terminal to the LMF.

[0149] (iv) With regard to generating training data in Case 3a, at least LMF can generate labels and data related to them (e.g., timestamps).

[0150] (iv) For calculating model performance monitoring metrics in label-based model monitoring in Case 3a, the following options A and B may be considered.

[0151] - Option A: NG-RAN nodes perform monitoring metric calculations for their own models.

[0152] - Option B: LMF performs monitoring metric calculations for models located on NG-RAN nodes.

[0153] (iv) For generating training data for Case 3a and (v) Case 3b, measurements and related data (e.g., timestamp) can be generated at the TRP / base station.

[0154] (v) For base station channel measurements reported to the LMF (location management server) in Case 3b, timing information can be expressed as a relative value to the UL RTOA reference time T0+tSRS.

[0155] (iii) Time domain channel measurements supported for reporting in Case 2b and (v) Case 3b may include timing information and / or power information corresponding to timing information.

[0156] For the definition of a sample-based measurement, Nt' samples can be selected from a list of consecutive Nt samples, and the Nt samples can have a time granularity of T.

[0157] In relation to sample-based measurements, the Nt' samples selected for measurement of the network may be those having the highest power.

[0158] For positioning based on Case 3b, for sample-based measurements, LMF can signal parameter values ​​such as Nt, Nt', k, etc. to the base station.

[0159] < CSI-related actions >

[0160] Figure 6 is a flowchart showing an example of a CSI-related procedure.

[0161] Referring to FIG. 6, in order to perform one of the purposes of CSI-RS, a terminal (e.g., user equipment, UE) receives configuration information related to CSI from a base station (e.g., general Node B, gNB) through RRC (radio resource control) signaling (S610).

[0162] The configuration information related to the above CSI may include at least one of CSI-IM (interference management) resource related information, CSI measurement configuration related information, CSI resource configuration related information, CSI-RS resource related information, or CSI report configuration related information.

[0163] CSI resource configuration related information can be expressed as CSI-ResourceConfig IE. The CSI resource configuration related information defines a group including at least one of a non-zero power (NZP) CSI-RS resource set, a CSI-IM resource set, or a CSI-SSB resource set. That is, the CSI resource configuration related information includes a CSI-RS resource set list, and the CSI-RS resource set list can include at least one of an NZP CSI-RS resource set list, a CSI-IM resource set list, or a CSI-SSB resource set list. A CSI-RS resource set is identified by a CSI-RS resource set ID, and one resource set includes at least one CSI-RS resource. Each CSI-RS resource is identified by a CSI-RS resource ID.

[0164] Information related to the CSI report configuration includes a reportConfigType parameter indicating a time domain behavior and a reportQuantity parameter indicating a CSI-related quantity to be reported. The time domain behavior may be periodic, aperiodic, or semi-persistent.

[0165] The above reportQuantity parameter may be related to at least one of a channel quality indicator (CQI), a precoding matrix indicator (PMI), a CSI-RS resource indicator (CRI), an SSB resource block indicator (SSBRI), a layer indicator (LI), a rank indicator (RI), and a layer 1-reference signal received strength (L1-Reference Signal Received Strength (RSRP).

[0166] Measurement resources may include configurations for downlink signals and / or downlink resources on which a terminal will perform measurements to determine feedback information. Measurement resources may be configured as ZP and / or NZP CSI-RS resource sets associated with CSI reporting configurations. The NZP CSI-RS resource set may include a CSI-RS set or an SSB set. For example, L1-RSRP may be measured for a CSI-RS set or an SSB set.

[0167] The terminal measures CSI based on configuration information related to the CSI (S620). The CSI measurement may include (1) a process of receiving a CSI-RS by the terminal (S621) and (2) a process of computing CSI using the received CSI-RS (S622). The terminal reports the CSI to the base station (S630).

[0168] Resource setting

[0169] Each CSI resource setting 'CSI-ResourceConfig' contains a configuration for S≥1 CSI resource sets (given by the higher layer parameter csi-RS-ResourceSetList). A CSI resource setting corresponds to a CSI-RS-resourcesetlist, where S represents the number of configured CSI-RS resource sets. Wherein, the list of S≥1 CSI resource sets contains either or both of NZP CSI-RS resource set(s) and SS / PBCH block (SSB) set(s) used for L1-RSRP computation, or contains CSI-IM resource set(s).

[0170] One or more CSI resource settings for channel measurement (CM) and interference measurement (IM) are configured via higher layer signaling.

[0171] - CSI-IM resource for interference measurement.

[0172] - NZP CSI-RS resources for interference measurement.

[0173] - NZP CSI-RS resources for channel measurement.

[0174] That is, the CMR (channel measurement resource) can be NZP CSI-RS for CSI acquisition, and the IMR (Interference measurement resource) can be NZP CSI-RS for CSI-IM and IM.

[0175] Here, CSI-IM (or ZP CSI-RS for IM) is mainly used for inter-cell interference measurement.

[0176] And, NZP CSI-RS for IM is mainly used for intra-cell interference measurement from multi-user.

[0177] A UE may assume that the CSI-RS resource(s) configured for channel measurement for one CSI reporting and the CSI-IM / NZP CSI-RS resource(s) for interference measurement (when NZP CSI-RS resource(s) are used for interference measurement) are in a QCL relationship with respect to 'QCL-TypeD' per resource.

[0178] As we have seen, resource setting can mean a resource set list.

[0179] For aperiodic CSI, each trigger state set using the higher layer parameter CSI-AperiodicTriggerState is associated with one or more CSI-ReportConfigs, and each CSI-ReportConfig is linked to a periodic or semi-persistent or aperiodic resource setting.

[0180] One reporting setting can be linked to up to three resource settings.

[0181] < Beam Management (BM) >

[0182] BM procedures are L1 (layer 1) / L2 (layer 2) procedures for acquiring and maintaining a set of base station (e.g., gNB, TRP, etc.) and / or terminal (e.g., UE) beams that can be used for downlink (DL) and uplink (UL) transmission / reception, and may include the following procedures and terminology.

[0183] - Beam measurement: An operation in which a base station or UE measures the characteristics of a received beam-forming signal.

[0184] - Beam determination: An operation in which a base station or UE selects its own transmit beam (Tx beam) / receive beam (Rx beam).

[0185] - Beam sweeping: The operation of covering a spatial area using a transmit and / or receive beam over a predetermined time interval in a predetermined manner.

[0186] - Beam report: An operation in which a UE reports information about a beam-formed signal based on beam measurement.

[0187] The BM procedure can be divided into (1) a DL BM procedure using SS (synchronization signal) / PBCH (physical broadcast channel) Block or CSI-RS, and (2) a UL BM procedure using SRS (sounding reference signal).

[0188] Additionally, each BM procedure may include Tx beam sweeping to determine the Tx beam and Rx beam sweeping to determine the Rx beam.

[0189] DL BM

[0190] The DL BM procedure may include (1) transmission of beamformed DL RSs (reference signals) (e.g., CSI-RS or SS Block (SSB)) of the base station and (2) beam reporting of the terminal.

[0191] Here, beam reporting may include preferred DL RS ID(identifier)(s) and corresponding L1-RSRP (Reference Signal Received Power).

[0192] The above DL RS ID may be an SSBRI (SSB Resource Indicator) or a CRI (CSI-RS Resource Indicator).

[0193] An example of beamforming using SSB and CSI-RS is described in detail below.

[0194] Both SSB and CSI-RS beams can be used for beam measurement. The measurement metric is L1-RSRP per resource / block. SSB is used for coarse beam measurement, and CSI-RS can be used for fine beam measurement. SSB can be used for both Tx beam sweeping and Rx beam sweeping.

[0195] Rx beam sweeping using SSB can be performed by the UE changing the Rx beam for the same SSBRI across multiple SSB bursts, where one SS burst contains one or more SSBs, and one SS burst set contains one or more SSB bursts.

[0196] Below we will look at the DL BM procedure.

[0197] Figure 7 is a flowchart showing an example of a DL BM procedure.

[0198] The configuration for beam report using SSB is performed during CSI / beam configuration in RRC connected state (or RRC connected mode).

[0199] - The terminal receives configuration information from the base station. As a specific example, the terminal receives a CSI-ResourceConfig IE including a CSI-SSB-ResourceSetList including SSB resources used for BM from the base station (S710).

[0200] Table 1 shows an example of the CSI-ResourceConfig IE. As shown in Table 1, BM configuration using SSB is not defined separately, and SSB is configured as a CSI-RS resource.

[0201]

[0202] In Table 1, the csi-SSB-ResourceSetList parameter indicates a list of SSB resources used for beam management and reporting in a single CSI-RS resource set. Here, the SSB resource set can be set to {SSBx1, SSBx2, SSBx3, SSBx4, …}. For example, the SSB index can be defined from 0 to 63.

[0203] - The terminal receives a downlink reference signal (DL RS) from the base station. As a specific example, the terminal receives an SSB from the base station based on the CSI-SSB-ResourceSetList (S720).

[0204] - The terminal transmits a beam report to the base station. For example, if CSI-ReportConfig related to reporting on SSBRI (SSB Resource Indicator) and L1-RSRP is set, the terminal reports the best SSBRI and its corresponding L1-RSRP to the base station (S730).

[0205] That is, when the reportQuantity of the above CSI-ReportConfig IE is set to 'ssb-Index-RSRP', the terminal reports the best SSBRI and the corresponding L1-RSRP to the base station.

[0206] And, if the terminal sets the CSI-RS resource in the same OFDM symbol(s) as the SSB (SS / PBCH Block) and 'QCL-TypeD' is applicable, the terminal can assume that the CSI-RS and SSB are quasi co-located from the 'QCL-TypeD' perspective.

[0207] Here, the QCL TypeD may mean that the antenna ports are QCL-connected from a spatial Rx parameter perspective. When a terminal receives multiple DL antenna ports in a QCL Type D relationship, the same reception beam may be applied. In addition, the terminal does not expect the CSI-RS to be configured in an RE that overlaps with the SSB RE.

[0208] < Description of Rel-17 / 18 beam management >

[0209] In Rel-17, both the DL TCI state and the UL TCI state can be indicated through DL DCI (e.g., DCI format 1-1 or 1-2), or only the UL TCI state can be indicated without indicating the DL TCI state. Therefore, the methods used for UL beam and power control (PC) configuration in the existing R15 / R16 are replaced in Rel-17 with the above UL TCI state indication method. More specifically, in R17, one UL TCI state can be indicated through the TCI field of DL DCI, and the UL TCI state is applied to all PUSCHs and all PUCCHs after a certain time called the beam application time, and can be applied to some or all of the indicated SRS resource sets. In addition, the base station can perform a terminal common beam update by using DCI and / or MAC-CE to perform indication / update with one beam in common (using a joint or separate TCI state) for specific DL / UL channel / RS combinations of multiple terminals. The target channels / RS of common beam update include UE-dedicated CORESET, UE-dedicated reception on PDSCH for DL, DG / CG-PUSCH, all or a subset of dedicated PUCCH for UL, and additionally, AP CSI-RS for tracking / BM, SRS can be set as target channels / RS.In Rel-18, considering the M-TRP environment, the method of indicating multiple UL TCI states (and / or DL ​​TCI states) through the TCI field of DL DCI has been standardized, and the uplink / downlink resources to which multiple indicated TCIs are applied can be defined / configured depending on the S-DCI based M-TRP environment and the M-DCI based M-TRP environment.

[0210] In this document, ' / ' means 'and', 'or', or 'and / or' depending on the context.

[0211] In this specification, 'beam' may mean a source RS for a 'spatial filter' or a 'spatial relation', and may be interpreted as a QCL (type-D) RS or a TCI state or (in the case of uplink) a spatial relation RS.

[0212] For example, in this specification, 'beam' may mean a spatial filter determined based on the reference RS or the source RS. The spatial filter may include a spatial domain filter, a spatial domain transmission filter, and a spatial domain receive filter. For example, in this specification, 'beam' may be interpreted / replaced with a reference signal index (RS index), a reference signal resource index (RS resource index), and / or a resource indicator (e.g., RS index, SSB index, CSI-RS resource index, SRS resource index, SSB Resource Indicator (SSBRI), CSI-RS Resource Indicator (CRI), etc.).

[0213] For example, a beam associated with UL may be referred to as i) a spatial filter (for uplink transmission or uplink reception), ii) a spatial domain filter (for uplink transmission or uplink reception), iii) an uplink spatial domain transmission filter, iv) an uplink spatial domain receive filter, v) an uplink transmit spatial filter (UL Tx spatial filter), or vi) an uplink receive spatial filter (UL Rx spatial filter).

[0214] For example, a beam associated with DL may be referred to as i) a spatial filter (for downlink transmission or downlink reception), ii) a spatial domain filter (for downlink transmission or downlink reception), iii) a downlink spatial domain transmission filter, iv) a downlink spatial domain receive filter, v) a downlink transmit spatial filter (DL Tx spatial filter) or vi) a downlink receive spatial filter (DL Rx spatial filter).

[0215] In the NR standard, QCL setting and spatialRelation setting by TCI state setting are utilized to set the UL / DL transmission / reception beam of the terminal. In the Rel-15 NR standard, RRC and MAC CE signaling are mainly used for UL / DL number / transmission beam. Dynamic signaling was allowed only for the reception beam of the PDSCH using the TCI state field of the DL grant DCI. The Rel-17 / 18 NR standard introduced a unified TCI framework. Specifically, a method was introduced to dynamically manage the common beam by indicating the reception / transmission beam using the indicated TCI using DCI. Meanwhile, in the Rel-18 AI / ML study item, a study was conducted on performance evaluation and specification impact in the spatial beam prediction and temporal beam prediction sub-use cases in the beam management field. The study discussed the NW / UE-side AI / ML operation that predicts the best beam of Set A based on Set B measurements. For UE-side AI / ML, the terminal is required to measure Set B and report the predicted Set A beam. In the latter case, standardization discussions are underway regarding what beam-related information (e.g., beam ID, RSRP, beam pattern ID, beam group ID, and bitmap information) should be included when the terminal performs Set B measurement / report.

[0216] In this specification, we propose a method for setting up beam measurement / reporting for base station-side AI / ML, and propose a beam reporting operation for subsequent terminals.

[0217] < UE initiated BM related background >

[0218] In existing LTE / NR systems, the reporting of CSI / beam information from a UE is determined / controlled by the base station / network (except in the case of BFR). These NW (network)-initiated / triggered reports have limitations in that they require UEs to be configured / instructed to frequently send CSI / beam information in environments where the wireless channel is likely to change rapidly. In such environments, the UL resource overhead for CSI / beam reporting and the related DL measurement RS overhead increase, and the UE's power consumption also increases due to frequent uplink transmission. Furthermore, the more UEs within cell / TRP coverage, the greater the UL resource overhead, as each UE must be allocated UL resources. To overcome these limitations of NW-initiated / triggered reports, recently emerging approaches are UE-initiated / triggered reports or event-based / triggered reports.

[0219] In the UE-initiated / triggered report method or event-based / triggered report method, the UE determines whether and when to report. By performing the report only when necessary (e.g., when a specific event occurs), UL resource overhead and UE power consumption can be reduced. With the above motivation, standardization of UE-initiated / triggered beam reports is expected in NR Rel-19. Furthermore, in 6G communication systems, UE-initiated / triggered or event-based transmission methods can be more actively expanded and adopted to efficiently manage uplink resources.

[0220] In the NR system, there are two representative reporting methods for event-based or UE-initiated / triggered information: SR (scheduling request) and BFR (beam failure recovery). SR reports whether PUSCH allocation is required for UL-SCH transmission, and BFR reports whether BF occurs and new beam-related information. This information is conveyed / transmitted to the base station in an explicit or implicit manner (e.g., conveying a new beam index as PRACH resource selection information). The above-mentioned SR / BFR-related information is conveyed simultaneously or separately through one or two UL resources (e.g., BFRQ on PUCCH + beam information via MAC-CE on PUSCH).

[0221] In this specification, information transmitted to the network based on a terminal event and / or via a UE-initiated / triggered transmission method (e.g., SR, BFRQ, new beam information, etc.) as described above is referred to as “event information” for convenience of explanation. Event information is composed of one or more information parts / blocks, and encoding / rate matching / RE mapping can be performed for each part / block unit. Each information part / unit can also be transmitted via different transmission methods (e.g., BFRQ via UCI as an L1 message, new beam information via MAC-CE as an L2 message).

[0222] < Background related to AI / ML beam management >

[0223] In the Rel-18 AI / ML study item, we conducted a study on performance analysis and potential specification impact through evaluation when NW and / or UE-side AI / ML models operate in three use cases: CSI compression / prediction, beam management, and positioning. In particular, in the beam management use case, we divided the sub-use cases into BM-case1 and BM-case2, and studied performance analysis and potential specification impact for spatial domain beam prediction and temporal beam prediction. The WID goals of AI / ML BM, BM-case1, and BM-case2 are summarized in Tables 2 to 4 below.

[0224] - AI / ML BM's WID goals

[0225]

[0226] - BM-case1: Spatial domain downlink beam prediction for beam set A based on measurement results for beam set B.

[0227]

[0228] - BM-case2: Temporal downlink beam prediction for beam set A based on past measurement results for beam set B.

[0229]

[0230] Additionally, an example of the operation for data collection of AI / ML models in the Beam management use case is shown in Table 5 below.

[0231]

[0232] Additionally, an example of the operation for inference of AI / ML model in Beam management use case is as shown in Table 6 below.

[0233]

[0234] As cited above, the Rel-18 AI / ML study discussed NW / UE sided AI / ML operations that predict the best beam of Set A based on Set B measurements. For UE sided AI / ML, the terminal is required to measure Set B and report the predicted Set A beam. For NW sided AI / ML, the terminal is required to report Set B measurements. In the latter case, standardization discussions are underway regarding what information (e.g., beam ID, RSRP, beam pattern ID, beam group ID, and bitmap information) should be included in the beam-related information to be reported when the terminal performs Set B measurement / report.

[0235] The standardization agreements reached to date are as shown in Table 7 below.

[0236]

[0237] The first agreement above concerns the Set B beam report for the NW-sided AI / ML model. Referring to Table 7, further study points regarding the content are described, such as the FFS (Fast-forward Structure) on the report content for beam-related information. The related proposals are shown in Table 8 below.

[0238]

[0239] For reference, the content of the existing NR beam report is SSBRI / CRI + L1-RSRP / SINR. According to the above proposals, since more than 4 beams (e.g., 5 or more beams) are reported as report content related to Set B, one of the following operations i) to iii) is performed to reduce reporting overhead.

[0240] i) beam ID is not reported.

[0241] ii) The beam pattern ID is reported.

[0242] iii) Bitmap information indicating the beam IDs to be reported is reported.

[0243] Discussions were held regarding the possibility of excluding beam IDs from reporting, or reporting other information instead of beam IDs. The specific details of the discussion are as follows.

[0244] At the last meeting, it was agreed to support L1 reporting for information related to 4 or more beams. Regarding the FFS for reporting the beam-related information, RSRP must be reported for measuring and reporting Set B beams. Regarding the beam ID reporting, there is still an ongoing discussion on whether to report beam ID-related information. Three alternatives were proposed to avoid reporting beam IDs in L1 reporting for information related to 4 or more beams. The first alternative is for the UE to report only the RSRP value and implicitly indicate the beam ID through the order of the reported RSRP values. The second alternative is for the UE to report beam pattern IDs of multiple Set B patterns that vary over time [R1-2400232]. In this case, the beam ID can still be implicitly inferred because the reported beam pattern ID represents a subset of Set B beams with a specific time variation. Finally, the third alternative is for the UE to report bitmap information indicating the beam ID reported within Set B [R1-2401002], which takes into account the possibility of missing some low-quality RSRP values. The network (NW) can infer the beam ID using the reported bitmap information. (In the last meeting, it was agreed to support L1 reporting for more than 4 beam related information. Regarding the FFS on report content for beam related information, RSRP should be reported for Set B beam measurement and report. Regarding the corresponding beam ID reporting, it is still controversial whether to report beam ID related information or not.There are three different alternatives not to report beam ID on L1 reporting for more than 4 beam related information. The first is for UE to report only RSRP values where beam IDs can be implicitly reported by order of reported RSRP values. And, the second is for UE to report beam pattern ID from time-varying multiple Set B patterns [R1-2400232], where beam IDs can also be implicitly reported by the reported beam pattern ID which represents specific time-varying subset of Set B beams, similar as the first alternative. Lastly, the third is for UE to report bitmap for beam ID information to indicate which beam IDs within a Set B is reported considering potential omission of low-quality RSRP(s) [R1-2401002], and beam IDs can be gathered from NW via reported bitmap information.).

[0245] 이러한 배경을 바탕으로, 본 명세서에서는 기지국 측 AI / ML을 위한 beam measurement / reporting 설정방법을 제안하고, 후속하는 단말의 beam reporting 동작에 대해 제안한다.

[0246] In this specification, ' / ' can be interpreted as 'and', 'or', or 'and / or' depending on the context.

[0247] Problem 1

[0248] In the case where beam ID is omitted to reduce overhead when reporting beams related to Set B as described above, a method of reporting only RSRP values ​​in ascending / descending order of ID based on the lowest / highest SSBRI / CRI in Set B (or the lowest / highest SSBRI / CRI in the CMR set corresponding to Set B) connected to CSI-reportConfig may be considered. In this case, the following problems may occur.

[0249] As described above, when only RSRP values ​​are reported, it is difficult to apply the existing method (see Table 9) of sorting and listing SSBRIs / CRIs and their corresponding RSRP values ​​in the reporting payload starting with the highest RSRP value. Specifically, it is impossible to determine which SSBRI / CRI among the ascending / descending SSBRIs / CRIs the highest RSRP value is related to. Consequently, ambiguity arises in the method of expressing RSRP values ​​(e.g., absolute RSRP in step size 1 dB, differential RSRP in step size 2 dB, etc.). Proposal 1 below proposes a method to resolve this problem 1.

[0250] Table 9 below provides examples of information included in beam reporting according to the existing method.

[0251]

[0252] Specifically, Table 9 illustrates the mapping order of CSI fields of one report for CRI / RSRP or SSBRI / RSRP or CRI / RSRP / CapabilityIndex or SSBRI / RSRP / CapabilityIndex reporting, or mapping order of CSI fields of one report for inter-cell SSBRI / RSRP reporting.

[0253] Proposal 1

[0254] (For NW sided AI / ML inference) It may be assumed that the base station configures / instructs the terminal to perform L1 reporting for more than 4 beam related information for Set B (or the CMR set corresponding to Set B). The terminal may perform beam related information reporting (omitting beam ID) based on at least one of the following embodiments.

[0255] In other words, based on the fact that the terminal is configured / instructed to report more than 4 beams, the terminal may omit the beam ID and report only the RSRP value. Specifically, the terminal may report the RSRP value in ascending / descending order of ID based on the lowest / highest SSBRI / CRI in Set B (or the CMR set corresponding to Set B). In this case, the terminal may perform the reporting based on at least one of the detailed embodiments 1) to 3) of the following embodiment 1) and / or the detailed embodiments 1) to 3) of the following embodiment 2.

[0256] Example 1 of Proposal 1)

[0257] The terminal may report an indicator indicating the SSBRI / CRI corresponding to the highest RSRP value. Specifically, the terminal may first configure the indicator within the reporting payload. More specifically, the terminal may configure the indicator as the MSB(s) of the reporting payload. In other words, the MSB(s) within the payload of a CSI report related to more than 4 beams may indicate the SSBRI / CRI corresponding to the highest RSRP value.

[0258] This allows reporting of RSRP values ​​of CMRs within Set B (e.g., SSB resources and / or CSI-RS resources within Set B) without ambiguity in the beam ID (SSBRI / CRI) associated with the RSRP value.

[0259] For example, the indicator can be expressed as ceil(log2(N)) bits when the number of CMRs in Set B is N, or as N bits which is a full bitmap. Specifically, when there are 16 CMRs from CRI 1 to 16 in Set B, the number of bits of the indicator can be ceil(log2(16)) = 4 bits (4 MSBs) or 16 bits (16 MSBs). As an example of 4 bits, if "0010" is indicated (in the case of ascending order), it can mean that CRI 3 has the highest RSRP value. As an example of 16 bits, if "0010000000000000" is indicated, it can mean that CRI 3 has the highest RSRP value. In the above example, CRI 3 may mean a CRI representing the third CMR among 16 CMRs (e.g., CSI-RS resources) in ascending order.

[0260] In the example of the case where CRIs 1 to 16 exist in Set B in the above embodiment 1, when CRI 3 is indicated to have the highest RSRP value, a detailed embodiment of the reporting payload configuration method is described below in detail. The detailed embodiments 1) to 3) below can indicate the mapping order of fields in one report as in Table 9. Specifically, the highest RSRP value (RSRP of CRI 3) is expressed as an absolute value as before (7 bits), but the order in which RSRP values ​​are mapped in the corresponding report may change. Each detailed embodiment is described below.

[0261] Detailed Example 1 of Example 1)

[0262] [indicator(4 bit or 16 bit), RSRP of CRI 1(differential value 4 bit), RSRP of CRI 2(differential value 4 bit), RSRP of CRI 3(absolute value 7 bit), RSRP of CRI 4(differential value 4 bit), RSRP of CRI 5(differential value 4 bit), ..., RSRP of CRI 16(differential value 4 bit)]

[0263] According to the above detailed embodiment 1), RSRP values ​​can be mapped in CRI order. In this case, the highest RSRP value (RSRP of CRI 3) can be placed / mapped third among the RSRP values.

[0264] Detailed Example 2 of Example 1)

[0265] [indicator(4 bit or 16 bit), RSRP of CRI 3(absolute value 7 bit), RSRP of CRI 1(differential value 4 bit), RSRP of CRI 2(differential value 4 bit), RSRP of CRI 4(differential value 4 bit), RSRP of CRI 5(differential value 4 bit),..., RSRP of CRI 16(differential value 4 bit)]

[0266] According to the above detailed embodiment 2), the highest RSRP value (RSRP of CRI 3) is placed / mapped at the front, and subsequent RSRP values ​​can be mapped in CRI order.

[0267] Detailed Example 3 of Example 1)

[0268] [indicator(4 bit or 16 bit), RSRP of CRI 3(absolute value 7 bit), RSRP of CRI 4(differential value 4 bit), RSRP of CRI 5(differential value 4 bit), ..., RSRP of CRI 16(differential value 4 bit), RSRP of CRI 1(differential value 4 bit), RSRP of CRI 2(differential value 4 bit)] (CRI is placed in round robin / cyclic form)

[0269] According to the above detailed embodiment 3), RSRP values ​​can be mapped in the order of CRI, and the highest RSRP value (RSRP of CRI 3) can be mapped first. In this case, RSRPs (RSRP of CRI 1, RSRP of CRI 2) before the highest RSRP value (RSRP of CRI 3) are placed after the RSRP of the last CRI (CRI 16).

[0270] In the embodiment 1 of the above proposal 1, the full bitmap indicator (e.g., a 16-bit indicator for 16 CRIs) can be extended to indicate multiple SSBRIs / CRIs expressed as absolute RSRP values. As an example of a 16-bit indicator, "0010000010000000" can indicate that the RSRP of CRI 3 and the RSRP of CRI 9 are expressed as absolute RSRP values ​​(7 bits).

[0271] Example 2 of Proposal 1)

[0272] The terminal can divide the N CMRs in Set B into M groups. The terminal can report an indicator indicating a group to which the SSBRI / CRI corresponding to the highest RSRP value among the M groups belongs and an indicator indicating the SSBRI / CRI having the highest RSRP value within the indicated group.

[0273] Specifically, the terminal may first configure in the reporting payload an indicator for the group containing the SSBRI / CRI corresponding to the highest RSRP value and an indicator indicating the SSBRI / CRI with the highest RSRP value within the indicated group.

[0274] More specifically, the terminal can configure the two indicators described above as the MSB(s) of the reporting payload. In other words, the MSB(s) in the payload of a CSI report related to more than 4 beams can indicate the group to which the SSBRI / CRI corresponding to the highest RSRP value among the M groups belongs and the SSBRI / CRI with the highest RSRP value within the indicated group. This allows reporting of the RSRP values ​​of CMRs within Set B without ambiguity in the beam ID (SSBRI / CRI) associated with the RSRP value.

[0275] For example, a group indicator containing an SSBRI / CRI corresponding to the highest RSRP value can be expressed as ceil(log2(M)) bits or as a full bitmap of M bits. An SSBRI / CRI indicator with the highest RSRP value within the indicated group can be expressed as ceil(log2(ceil(N / M))) bits or as a full bitmap of ceil(N / M) bits. In this case, the number of CMRs within the group can be assumed to be ceil(N / M).

[0276] Examples of grouping methods in Example 2 are as follows.

[0277] i) Group composition by ascending / descending order of SSBRI / CRI

[0278] ii) Odd (local) indexed beam and even (local) indexed beam configuration

[0279] iii) Composition of M groups by base station signaling

[0280] iv) (local) Beams are composed of beams that have the same remainder when the index is divided by M.

[0281] The above i) to iv) are only examples and are not intended to limit the grouping method based on Example 2 to one of the above-described i) to iv). The grouping based on Example 2 may be performed based on definitions / rules other than the examples described above.

[0282] In the above embodiment 2, in an example where CRIs 1 to 16 exist in Set B, it can be assumed that CRI 7 has the highest RSRP value (e.g., group 1={CRI 1~CRI 4}, group 2={CRI 5~CRI 8}(highest group), group 3={CRI 9~CRI 12}, group 4={CRI 13~CRI 16}). A detailed embodiment of the reporting payload configuration method at this time is described below. The detailed embodiments 1) to 3) below can represent the mapping order of fields in one report, as shown in Table 9.

[0283] Detailed Example 1 of Example 2)

[0284] [highest group indicator (2 bit or 4 bit), highest SSBRI / CRI indicator (2 bit or 4 bit) within group, group 1 (all RSRP=differential value 4 bit), group 2 (RSRP of CRI 5 (differential value 4 bit), RSRP of CRI 6 (differential value 4 bit), RSRP of CRI 7 (absolute value 7 bit), RSRP of CRI 8 (differential value 4 bit) bit)), group 3(all RSRP=differential value 4 bit), group 4(all RSRP=differential value 4 bit)]

[0285] According to the above detailed embodiment 1), groups can be mapped in the order of group index. In this case, the group to which the highest RSRP value belongs (group 2 to which CRI 7 belongs) can be placed / mapped second.

[0286] For example, in the above example, all RSRP values ​​within group 2 may be expressed as absolute values ​​(7 bits). For example, in the above example, the ordering of CRIs within group 2 may be based on detailed embodiments 1 to 3 of embodiment 1.

[0287] Detailed Example 2 of Example 2)

[0288] [highest group indicator (2 bit or 4 bit), highest SSBRI / CRI indicator (2 bit or 4 bit) within group, group 2 (RSRP of CRI 5(differential value 4 bit), RSRP of CRI 6(differential value 4 bit), RSRP of CRI 7(absolute value 7 bit), RSRP of CRI 8(differential value 4 bit)), group 1(all RSRP=differential value 4 bit) bit), group 3(all RSRP=differential value 4 bit), group 4(all RSRP=differential value 4 bit)]

[0289] According to the above detailed embodiment 2), the group to which the highest RSRP value belongs (group 2 to which CRI 7 belongs) is placed / mapped at the front, and subsequent groups can be mapped in the order of group index.

[0290] For example, in the above example, all RSRP values ​​within group 2 may be expressed as absolute values ​​(7 bits). For example, in the above example, the ordering of CRIs within group 2 may be based on detailed embodiments 1 to 3 of embodiment 1.

[0291] Detailed Example 3 of Example 2)

[0292] [highest group indicator (2 bit or 4 bit), highest SSBRI / CRI indicator (2 bit or 4 bit) within group, group 2 (RSRP of CRI 5(differential value 4 bit), RSRP of CRI 6(differential value 4 bit), RSRP of CRI 7(absolute value 7 bit), RSRP of CRI 8(differential value 4 bit)), group 3(all RSRP=differential value 4 bit) bit), group 4(all RSRP=differential value 4 bit), group 1(all RSRP=differential value 4 bit)] (groups are arranged in round robin / cyclic form)

[0293] According to the above detailed embodiment 3), groups are mapped in the order of group index, and the group to which the highest RSRP value belongs (group 2 to which CRI 7 belongs) can be mapped so that it comes first. In this case, the group (group 1) before the group to which the highest RSRP value belongs (group 2 to which CRI 7 belongs) is placed after the last group (group 4).

[0294] For example, in the above example, all RSRP values ​​within group 2 may be expressed as absolute values ​​(7 bits). For example, in the above example, the ordering of CRIs within group 2 may be based on detailed embodiments 1 to 3 of embodiment 1.

[0295] Embodiment 2 of the above proposal 1 can be extended to the following operation.

[0296] For example, a full bitmap indicator for the highest group may represent multiple groups expressed by absolute RSRP values.

[0297] For example, a full bitmap indicator for the highest CRI / SSBRI may represent multiple SSBRIs / CRIs expressed as absolute RSRP values.

[0298] In the case of differential RSRP values ​​for non-best groups in Example 2 of Proposal 1, different step sizes can be set / defined for each group. As you move toward the group with the lowest RSRP, coarse differential RSRP values ​​can be utilized to reduce reporting payload.

[0299] For example, RSRPs within a group containing the highest RSRP can be expressed as differential values ​​based on a smaller step size. RSRPs within other groups (other than the group containing the highest RSRP) can be expressed more coarsely. Specifically, RSRPs within other groups (other than the group containing the highest RSRP) can be expressed as differential values ​​based on a larger step size.

[0300] In another embodiment, the reported RSRP values ​​can be divided into two groups. The RSRP of the dominant group, which includes good beams (SSBRIs / CRIs with high RSRP), can be expressed as a differential value based on a small step size. The RSRP of the remaining groups can be expressed coarsely as a differential value based on a larger step size. Here, as many full bitmaps as the number of SSBRIs / CRIs can be used to express the dominant beams. For example, the full bitmap indicator can indicate RSRP values ​​that are finely expressed with a smaller step size. For example, the full bitmap indicator can indicate RSRP values ​​that are coarsely expressed with a larger step size.

[0301] Embodiment 2 of the above proposal 1 has the advantage of saving the number of bits when configuring a full bitmap compared to Embodiment 1.

[0302] In the embodiments of Proposal 1 above, the indicator indicating the SSBRI / CRI with the highest RSRP value can be extended to indicators indicating the SSBRI / CRI with the second / third / ... / K-th highest RSRP value. In this case, the following two methods can be considered when configuring the reporting payload.

[0303] i) [highest RSRP indicator, second-highest RSRP indicator, ..., K-th highest RSRP indicator, highest RSRP value, second-highest RSRP value, ..., K-th highest RSRP value, remaining RSRP values..]

[0304] ii) [highest RSRP indicator, highest RSRP value, second-highest RSRP indicator, second-highest RSRP value, ..., K-th highest RSRP indicator, K-th highest RSRP value, remaining RSRP values..]

[0305] Additionally, the indicator for a group containing an SSBRI / CRI corresponding to the highest RSRP value can be expanded to include indicators that compare the highest RSRP values ​​within each group and provide an indication for K groups containing the K highest RSRP values. In this case, the following two methods can be considered when configuring the reporting payload.

[0306] i) [highest RSRP group indicator, second-highest RSRP group indicator, ..., K-th highest group RSRP indicator, highest RSRP group, second-highest RSRP group, ..., K-th highest RSRP group, remaining RSRP groups..]

[0307] ii) [highest RSRP group indicator, highest RSRP group, second-highest RSRP group indicator, second-highest RSRP group, ..., K-th highest RSRP group indicator, K-th highest RSRP group, remaining RSRP groups..]

[0308] As described above, the embodiments of Proposal 1 were described assuming that the beam ID is not included in the report content. However, the embodiments of Proposal 1 can be extended to cases where the beam ID is expressed implicitly.

[0309] The embodiments of Proposal 1 can also be extended and applied even when the beam ID is implicitly expressed through the beam pattern / group ID. For example, an indicator based on the embodiments of Proposal 1 can be interpreted / replaced with the beam pattern / group ID.

[0310] The embodiments of Proposal 1 can also be extended to configure an omitted payload (omission of reporting RSRP values ​​of beam IDs having RSRP values ​​lower than or equal to the lowest threshold) by indicating information about non-omitted / omitted beam IDs in the form of a full bitmap. For example, an indicator based on the embodiments of Proposal 1 can be interpreted / replaced with a full bitmap indicating information about non-omitted / omitted beam IDs.

[0311] Problem 2

[0312] When configuring report content as in Proposal 1 above, information on more than 4 beams is reported, which may result in the reporting payload size becoming larger than the maximum payload size. For example, the maximum payload size may be based on the time / frequency domain resource allocation of PUCCH resources set / instructed by the base station for beam reports.

[0313] A method to solve this problem is described in Proposal 2 below.

[0314] Proposal 2

[0315] (For NW sided AI / ML inference) It can be assumed that the base station configures / instructs the terminal to perform L1 reporting for more than 4 beam related information for Set B (or the CMR set corresponding to Set B). When the reporting payload size exceeds the maximum payload size of the configured / instructed PUCCH resource, the terminal can configure the PUCCH payload so as not to exceed the PUCCH maximum payload size by performing omission / partial drop on low priority contents. Specific embodiments are described below. The embodiments described below can also be extended to a case where the PUCCH resource for reporting collides with another PUCCH or PUSCH. For example, when the PUCCH resource collides with another (A / N and / or SR and / or CSI) PUCCH or PUSCH and piggy-back (multiplexing) is performed on one of them, there may be a case where there is insufficient payload to perform the piggy-back (multiplexing). In this case, too, omission / partial drop can be expanded and performed based on the embodiments described below.

[0316] Example 1 of Proposal 2)

[0317] (Related to Example 1 of Proposal 1) When expressing non-highest RSRP values ​​based on differential RSRP values, a step size can be utilized to reduce the reporting payload size.

[0318] For example, the step size may be greater than 2 dB. Specifically, the differential RSRP value may be expressed based on a step size greater than 2 dB (e.g., 4 dB, 6 dB, 8 dB, or 10 dB, etc.).

[0319] For example, the step size may be changed / determined based on the number of reported beams. Specifically, as the number of reported beams increases, the differential RSRP value may be expressed as a coarse value based on a larger step size.

[0320] For example, the step size may be adjusted / determined / changed based on signaling from the base station. As a specific example, the step size may be adjusted / determined / changed based on signaling such as RRC / MAC CE.

[0321] Example 2 of Proposal 2)

[0322] (Related to Example 2 of Proposal 1) When expressing the RSRP value for SSBRI / CRI within a group based on the differential RSRP value for group(s) that do not include the highest RSRP value, a step size can be utilized to reduce the reporting payload size.

[0323] For example, the step size may be greater than 2 dB. Specifically, the differential RSRP value may be expressed based on a step size greater than 2 dB (e.g., 4 dB, 6 dB, 8 dB, or 10 dB, etc.).

[0324] For example, the step size may be changed / determined based on the number of reported beams (within a group). As a specific example, the more reported beams (the number of beams in a group), the more the differential RSRP value may be expressed as a coarse value based on a large step size.

[0325] For example, the step size may be adjusted / determined / changed based on signaling from the base station. As a specific example, the step size may be adjusted / determined / changed based on signaling such as RRC / MAC CE.

[0326] For example, a terminal can drop the RSRP value for groups other than the group with the highest RSRP value.

[0327] For example, the terminal can compare the highest RSRP values ​​within each group and drop the RSRP value for groups other than the K groups that contain the K highest RSRPs.

[0328] For example, it may be assumed that i) in the embodiments of the above proposal 2, the indicator indicating the SSBRI / CRI having the highest RSRP value is extended to indicators indicating the SSBRI / CRI having the second / third / ... / K-th highest RSRP value, and / or ii) the indicator for a group including the SSBRI / CRI corresponding to the highest RSRP value is extended to indicators that compare the highest RSRP values ​​within each group and perform an indication for K groups including K highest RSRPs. Based on the above i) and / or ii), the following operations may be performed to reduce the reporting payload size.

[0329] A terminal can send absolute / differential RSRP values ​​for K RSRPs or / and K RSRP groups.

[0330] The terminal may send a coarse RSRP value (with a larger step size) to the remaining RSRPs or / and the remaining RSRP groups. Alternatively, the terminal may drop the remaining RSRPs or / and the remaining RSRP groups.

[0331] The operation of the above proposal 2 is also applicable when SSBRI / CRI is not omitted but reported explicitly (similar to legacy NR beam reporting) along with the corresponding RSRP value. For example, grouping can be performed as in embodiment 2 of proposal 1 even in the configuration of legacy NR beam reporting contents. In this case, the terminal can operate as follows. For example, the terminal can report a coarse RSRP value for specific group(s) as in embodiment 2 of proposal 2. For example, the terminal can drop RSRP reporting for specific group(s).

[0332] As a concrete example, when configuring sub-band CSI, the dropping rule can be extended to create a group for beams with even (local) IDs within Set B and a group for beams with odd (local) IDs. The terminal can report a coarse RSRP value for the even or odd beam, or drop RSRP reports for specific even or odd beams.

[0333] Additionally, when multiple groups are configured within Set B, reporting can be performed based on groups with even IDs and groups with odd IDs. The terminal can report a coarse RSRP value for the even or odd group, or drop RSRP reporting for the even or odd group.

[0334] In the operation of reporting a coarse RSRP value with a larger step size than the embodiments of the above proposal 2, the step size for the coarse (differential) RSRP value may be set / indicated by the base station or reported by the terminal. For example, the step size for the coarse (differential) RSRP value may be set / indicated to the terminal based on the signaling (RRC / MAC CE / DCI) of the base station. As another example, step size information may be included in the payload when the terminal transmits a report.

[0335] The following effects can be derived from Proposal 2.

[0336] The operation of Proposal 2 above allows the terminal to configure the UCI payload so that it does not exceed the maximum PUCCH payload when configuring the PUCCH payload. This allows the PUCCH for beam reporting to be transmitted in its entirety. In other words, this prevents the loss of information that serves as a critical reference for interpreting beam IDs associated with reported RSRPs due to the PUCCH payload for beam reporting exceeding the maximum PUCCH payload.

[0337] The above embodiments are only examples of operations between base station terminals and are not limited to the above embodiments, and extensions of the above embodiments may also be based on this specification.

[0338] The above embodiments may be operated by a combination of one or more embodiments.

[0339] An example of a terminal (or base station) operation based on at least one of the embodiments described above (e.g., at least one of the embodiments of Proposals 1 and 2) is as follows.

[0340] 1) The terminal (base station) receives (transmits) settings related to beam measurement / reporting.

[0341] The above settings may include settings related to Set A and Set B of Proposal 1.

[0342] 2) The terminal (base station) receives (transmits) a message scheduling the transmission of beam measurement reports.

[0343] The transmission of reports scheduled by the base station above can have periodic / semi-persistent / dynamic time domain behavior.

[0344] 3) The terminal (base station) transmits (receives) a beam measurement report based on the above message.

[0345] The content of the above report may be based on the embodiments of the above proposals 1 and 2.

[0346] The above terminal / base station operations are only an example, and each operation (or step) is not necessarily essential, and the beam measurement / reporting operations of the terminal according to the above-described embodiments may be omitted or added depending on the terminal / base station implementation method.

[0347] In terms of implementation, the operations of the base station / terminal according to the embodiments described above (e.g., operations based on at least one of Proposals 1 and 2) can be processed by the device of FIG. 10 (e.g., the processor (110, 210) of FIG. 10).

[0348] In addition, the operations of the base station / terminal according to the above-described embodiment (e.g., operations based on at least one of proposals 1 and 2) may be stored in a memory (e.g., 140, 240 of FIG. 10) in the form of commands / programs (e.g., instructions, executable codes) for driving at least one processor (e.g., 110, 210 of FIG. 10).

[0349] The embodiments described below are specifically described with reference to FIGS. 8 and 9 in terms of the operation of the terminal and base station. The methods described below are distinguished for convenience of explanation, and it is understood that some components of one method may be substituted for or combined with some components of another method.

[0350] Figure 8 is a flowchart illustrating a method according to one embodiment of the present specification.

[0351] Referring to FIG. 8, a method according to one embodiment of the present specification includes a step of receiving a report setting related to CSI (S810) and a step of reporting CSI (S820).

[0352] In S810, the terminal receives report configuration related to channel state information (CSI) from the base station.

[0353] For example, the reporting settings may include information based on at least one of Proposals 1 and 2.

[0354] In S820, the terminal reports the CSI to the base station.

[0355] For example, the CSI may be related to a report for the BM-Case 1 and / or BM-Case 2 described above (see Tables 2 to 6). The report may include a measurement result report. The information / parameters included in the CSI may be related to the input of a network-side model (NW-sided model). The information / parameters included in the CSI are described in detail below.

[0356] Hereinafter, the above CSI can be interpreted / replaced with a CSI report.

[0357] For example, the CSI includes one or more Reference Signal Received Powers (RSRPs). In this case, the embodiment of Proposal 1 may be applied to resolve ambiguity in determining one or more RS resource indices related to the one or more RSRPs. Specifically, the CSI may include information based on at least one of the above-described Proposals 1 and 2. The CSI may include i) information based on Embodiment 2 of Proposal 1 (e.g., first information and second information) or ii) information based on Embodiment 1 of Proposal 1 (e.g., third information). This will be described in detail below.

[0358] In one embodiment, the CSI may include i) first information indicating a first group to which a first RS resource index having a highest RSRP (highest RSRP) among groups based on RS resource indices (e.g., CRIs / SSBRIs) set for measurement belongs, and ii) second information indicating the first RS resource index among RS resource indices within the first group. The present embodiment may be based on embodiment 2 of proposal 1. The first information may be based on the highest group indicator described above, and the second information may be based on the highest SSBRI / CRI indicator within the group.

[0359] In one embodiment, the bitwidth for the first information may be determined based on the number of groups. This embodiment may be based on Embodiment 2 of Proposal 1.

[0360] For example, the bit width for the first information is It could be. is a ceiling function, and M may be the number of the groups. The first information may be based on a group indicator, which is ceil(log2(M)) bits in embodiment 2 of proposal 1.

[0361] For example, the bit width of the first information may be M. M may be the number of groups. The first information may be based on a group indicator, which is a full bitmap (M bits) in Example 2 of Proposal 1.

[0362] In one embodiment, the bitwidth for the second information may be determined based on the number of RS resource indices within each group. This embodiment may be based on Embodiment 2 of Proposal 1.

[0363] For example, the bit width for the second information is It could be. is the number of RS resource indices in each group above, is a ceiling function. N may be the number of RS resource indices set for the measurement, and M may be the number of groups. The second information may be based on the SSBRI / CRI indicator, which is ceil(log2(ceil(N / M))) bit in embodiment 2 of proposal 1.

[0364] For example, the bit width for the second information is It could be. is the number of RS resource indices in each group above, is a ceiling function. N may be the number of RS resource indices set for the measurement, and M may be the number of groups. The second information may be based on the SSBRI / CRI indicator, which is a ceil(N / M) bit in embodiment 2 of proposal 1.

[0365] As described above, the CSI may include information based on Embodiment 2 of Proposal 1 (e.g., first / second information) or information based on Embodiment 1 of Proposal 1 (e.g., third information). In one embodiment, the CSI may include i) the first information and the second information or ii) third information indicating the first RS resource index with the highest RSRP. The third information may be based on an indicator indicating an SSBRI / CRI corresponding to the highest RSRP value in Embodiment 1 of Proposal 1.

[0366] For example, the bit width for the third information may be determined based on the number of RS resource indices set for the measurement.

[0367] As a specific example, the bit width for the third information is It could be. is a ceiling function, and N may be the number of RS resource indices set for the measurement. The third information may be based on an indicator of ceil(log2(N)) bits.

[0368] As a specific example, the bit width for the third information may be N. N may be the number of RS resource indices set for the measurement. The third information may be based on a full bitmap of N bits.

[0369] Even when information indicating the RS resource index with the highest RSRP as described above is reported, the CSI (CSI report) may be interpreted differently depending on the order in which the remaining RSRPs are mapped within the CSI (CSI report). In other words, if it is not clearly defined in advance whether the highest RSRP will be mapped first or simply based on the order of the RS resource index when RSRPs are mapped within the CSI (CSI report), the following problem may occur. The RS resource indices interpreted as being related to RSRPs based on the mapping order within the CSI may be different from the RS resource indices related to the RSRPs reported by the terminal. In this case, RS resource index(es) different from those measured by the terminal may be utilized as input data for the NW-side model, which may degrade the inference performance. To solve the above-described problem, detailed embodiments of Embodiment 1 / Embodiment 2 of Proposal 1 may be considered. They will be described in detail below.

[0370] In one embodiment, the third information may be mapped first in the CSI. This embodiment may be based on one of the detailed embodiments 1) to 3) in embodiment 1 of proposal 1. Hereinafter, when specific information (e.g., third information or first / second information) is mapped first in the CSI, it may mean that the specific information is mapped to a first field among fields based on the CSI. As a specific example, the third information may be mapped to one or more MSBs (Most Significant Bits) among bits based on the CSI. For example, when the third information is 4 bits, the third information (4 bits) may be mapped to four MSBs among bits based on the CSI. In other words, the third information (4 bits) may be mapped to a first field among fields of the CSI.

[0371] In one embodiment, the one or more RSRPs in the CSI may be mapped based on an order related to the RS resource indices. This embodiment may be based on detailed embodiment 1) in embodiment 1 of proposal 1. When 16 RS resource indices (CRIs) are set for the measurement, and the third RS resource index (CRI 3) has the highest RSRP, the mapping order in the CSI may be expressed as follows.

[0372] 1) indicator (4 bit or 16 bit): 3rd information

[0373] 2) RSRP of CRI 1(differential value 4 bit)

[0374] 3) RSRP of CRI 2(differential value 4 bit)

[0375] 4) RSRP of CRI 3(absolute value 7 bit)

[0376] 5) RSRP of CRI 4(differential value 4 bit)

[0377] 6) RSRP of CRI 5(differential value 4 bit)

[0378] ...

[0379] 17) RSRP of CRI 16 (differential value 4 bit)

[0380] Referring to the above example, the highest RSRP (e.g., RSRP value quantized to 7 bits with 1 dB step size) based on the third RS resource index (CRI 3) is mapped to the third RSRP (fourth among all fields). In the above example and the examples described below, it is assumed that RSRPs for all 16 RS resource indices are reported. This is for convenience of explanation, and the number of RSRPs reported may vary depending on the set value / set number.

[0381] In one embodiment, the highest RSRP among the one or more RSRPs in the CSI may be mapped first, and the remaining RSRPs may be mapped starting from the RSRP associated with the lowest RS resource index based on the order associated with the RS resource indices. This embodiment may be based on detailed embodiment 2) in embodiment 1 of proposal 1. When 16 RS resource indices (CRIs) are set for the measurement, and the third RS resource index (CRI 3) has the highest RSRP, the mapping order in the CSI may be expressed as follows.

[0382] 1) indicator (4 bit or 16 bit): 3rd information

[0383] 2)RSRP of CRI 3(absolute value 7 bit)

[0384] 3) RSRP of CRI 1(differential value 4 bit)

[0385] 4) RSRP of CRI 2(differential value 4 bit)

[0386] 5) RSRP of CRI 4(differential value 4 bit)

[0387] 6) RSRP of CRI 5(differential value 4 bit)

[0388] ...

[0389] 17) RSRP of CRI 16 (differential value 4 bit)]

[0390] Referring to the above example, the highest RSRP (e.g., RSRP value quantized to 7 bits with 1 dB step size) based on the third RS resource index (CRI 3) is mapped to the first RSRP (second among all fields). After that, the RSRP associated with the lowest RS resource index (CRI 1) is mapped in order of RS resource index.

[0391] In one embodiment, the highest RSRP among the one or more RSRPs in the CSI may be mapped first, and the remaining RSRPs may be mapped starting from the RSRP associated with the next RS resource index of the first RS resource index based on the order associated with the RS resource indices. This embodiment may be based on detailed embodiment 3) in embodiment 1 of proposal 1. When 16 RS resource indices (CRIs) are set for the measurement, and the third RS resource index (CRI 3) has the highest RSRP, the mapping order in the CSI may be expressed as follows.

[0392] 1) indicator (4 bit or 16 bit): 3rd information

[0393] 2)RSRP of CRI 3(absolute value 7 bit)

[0394] 3) RSRP of CRI 4(differential value 4 bit)

[0395] 4) RSRP of CRI 5(differential value 4 bit)

[0396] ...

[0397] 15) RSRP of CRI 16 (differential value 4 bit)

[0398] 16) RSRP of CRI 1(differential value 4 bit)

[0399] 17) RSRP of CRI 2(differential value 4 bit)

[0400] Referring to the above example, the highest RSRP (e.g., RSRP value quantized to 7 bits with 1 dB step size) based on the third RS resource index (CRI 3) is mapped to the first (second among all fields) among the RSRPs. Then, the RSRP associated with the next RS resource index (CRI 4) of the third RS resource index (CRI 3) is mapped based on the order of the RS resource indexes. At this time, the RSRPs are mapped in a cyclic manner. For example, when mapping up to the RSRP of the last RS resource index (CRI 16), the RSRPs are mapped in order from the lowest RS resource index (CRI 1) among the RS resource indexes (CRI 1, CRI 2) before the third RS resource index (CRI 3).

[0401] In one embodiment, the first information and the second information may be mapped first within the CSI. This embodiment may be based on one of detailed embodiments 1) to 3) in embodiment 2 of proposal 1.

[0402] In one embodiment, the one or more RSRPs in the CSI may be mapped based on the order of group indices associated with the groups. This embodiment may be based on detailed embodiment 1) in embodiment 2 of proposal 1. For the measurement, 16 RS resource indices (CRIs) are set, and 4 groups (e.g., group 1 (e.g., CRI 1 to CRI 4), group 2 (e.g., CRI 5 to CRI 8), group 3 (e.g., CRI 9 to CRI 12), group 4 (e.g., CRI 13 to CRI 16)) are determined based on the 16 RS resource indices, and when the 7th RS resource index (CRI 7) (=the first RS resource index) belonging to the second group (=the first group) has the highest RSRP, the mapping order in the CSI may be expressed as follows.

[0403] 1) Highest group indicator (2 bits or 4 bits): First information

[0404] 2) Highest SSBRI / CRI indicator (2 bits or 4 bits) within the group: Second information

[0405] 3) group 1 (all RSRP=differential value 4 bit)

[0406] 4-1) group 2 (RSRP of CRI 5(differential value 4 bit))

[0407] 4-2) group 2 (RSRP of CRI 6(differential value 4 bit))

[0408] 4-3) group 2 (RSRP of CRI 7(absolute value 7 bit))

[0409] 4-4) group 2 (RSRP of CRI 8(differential value 4 bit))

[0410] 5) group 3 (all RSRP=differential value 4 bit)

[0411] 6) group 4 (all RSRP=differential value 4 bit)

[0412] Referring to the above example, 16 RSRPs based on 4 groups are mapped based on the order of the group indexes. The second group, to which the 7th RS resource index with the highest RSRP belongs, is mapped to the second of the 4 groups. At this time, the mapping order of RSRPs within each group (or the second group) may be based on one of the detailed embodiments 1) to 3) of Embodiment 1 of Proposal 1 described above.

[0413] In one embodiment, within the CSI, the RSRPs of the first group to which the highest RSRP among the one or more RSRPs belongs may be mapped first, and the remaining RSRPs may be mapped starting from the RSRPs belonging to the group with the lowest group index based on the order of the group indices associated with the groups. This embodiment may be based on detailed embodiment 2) in embodiment 2 of proposal 1. For the above measurement, 16 RS resource indices (CRIs) are set, and based on the 16 RS resource indices, 4 groups (e.g., group 1 (e.g., CRI 1 to CRI 4), group 2 (e.g., CRI 5 to CRI 8), group 3 (e.g., CRI 9 to CRI 12), group 4 (e.g., CRI 13 to CRI 16)) are determined, and when the 7th RS resource index (CRI 7) (=the first RS resource index) belonging to the second group (=the first group) has the highest RSRP, the mapping order within the CSI can be expressed as follows.

[0414] 1) Highest group indicator (2 bits or 4 bits): First information

[0415] 2) Highest SSBRI / CRI indicator (2 bits or 4 bits) within the group: Second information

[0416] 3-1) group 2 (RSRP of CRI 5(differential value 4 bit))

[0417] 3-2) group 2 (RSRP of CRI 6(differential value 4 bit))

[0418] 3-3) group 2 (RSRP of CRI 7(absolute value 7 bit))

[0419] 3-4) group 2 (RSRP of CRI 8(differential value 4 bit))

[0420] 4) group 1 (all RSRP=differential value 4 bit)

[0421] 5) group 3 (all RSRP=differential value 4 bit)

[0422] 6) group 4 (all RSRP=differential value 4 bit)

[0423] Referring to the above example, among the 16 RSRPs based on the 4 groups, the RSRPs of the second group, which includes the 7th RS resource index with the highest RSRP, are mapped first. Then, among the remaining groups, the RSRPs belonging to the group (group 1) with the lowest group index are mapped based on the order of the group indices. At this time, the mapping order of the RSRPs within each group (or the second group) may be based on one of the detailed embodiments 1) to 3) of embodiment 1 of the above-described proposal 1.

[0424] In one embodiment, within the CSI, RSRPs of the first group to which the highest RSRP among the one or more RSRPs belongs may be mapped first, and the remaining RSRPs may be mapped starting from RSRPs belonging to the next group of the first group based on the order of group indices associated with the groups. This embodiment may be based on detailed embodiment 3) in embodiment 2 of proposal 1. For the above measurement, 16 RS resource indices (CRIs) are set, and based on the 16 RS resource indices, 4 groups (e.g., group 1 (e.g., CRI 1 to CRI 4), group 2 (e.g., CRI 5 to CRI 8), group 3 (e.g., CRI 9 to CRI 12), group 4 (e.g., CRI 13 to CRI 16)) are determined, and when the 7th RS resource index (CRI 7) (=the first RS resource index) belonging to the second group (=the first group) has the highest RSRP, the mapping order within the CSI can be expressed as follows.

[0425] 1) highest group indicator (2 bit or 4 bit)

[0426] 2) highest SSBRI / CRI indicator (2 bit or 4 bit) within the group

[0427] 3-1)group 2 (RSRP of CRI 5(differential value 4 bit))

[0428] 3-2)group 2 (RSRP of CRI 6(differential value 4 bit))

[0429] 3-3)group 2 (RSRP of CRI 7(absolute value 7 bit))

[0430] 3-4)group 2 (RSRP of CRI 8(differential value 4 bit))

[0431] 4) group 3 (all RSRP=differential value 4 bit)

[0432] 5) group 4 (all RSRP=differential value 4 bit)

[0433] 6) group 1 (all RSRP=differential value 4 bit)

[0434] Referring to the above example, among the 16 RSRPs based on the 4 groups, the RSRPs of the second group, which has the 7th RS resource index with the highest RSRP, are mapped first. After that, among the remaining groups, the RSRPs belonging to the next group (group 3) of the second group are mapped based on the order of the group indexes. At this time, the RSRPs of each group are mapped in a cyclical manner. For example, when the RSRPs of the last group (group 4) are mapped, the RSRPs of the group (e.g., group 1) with the lowest group index among the group(s) before the second group are mapped in order.

[0435] According to embodiment 2 of proposal 1, RSRPs belonging to the first group can be mapped based on one of detailed embodiments 1) to 3) of embodiment 1 of proposal 1 described above. The mapping order of RSRPs within the group to which the highest RSRP belongs is described in detail below.

[0436] In one embodiment, RSRPs belonging to the first group within the CSI may be mapped based on an order related to the RS resource indices. This embodiment may be based on detailed embodiment 1) of embodiment 1 of proposal 1. When the 7th RS resource index belonging to the second group among 4 groups based on 16 RS resource indices has the highest RSRP, the mapping order of the RSRPs of the second group may be expressed as follows.

[0437] 1) RSRP of CRI 5(differential value 4 bit)

[0438] 2) RSRP of CRI 6(differential value 4 bit)

[0439] 3) RSRP of CRI 7 (absolute value 7 bit)

[0440] 4) RSRP of CRI 8(differential value 4 bit)

[0441] In one embodiment, within the CSI, the highest RSRP among the RSRPs belonging to the first group may be mapped first, and the remaining RSRPs belonging to the first group may be mapped starting from the RSRP associated with the lowest RS resource index based on the order associated with the RS resource indices. This embodiment may be based on detailed embodiment 2) of embodiment 1 of proposal 1. When the 7th RS resource index belonging to the second group among 4 groups based on 16 RS resource indices has the highest RSRP, the mapping order of the RSRPs of the second group may be expressed as follows.

[0442] 1) RSRP of CRI 7 (absolute value 7 bit)

[0443] 2) RSRP of CRI 5(differential value 4 bit)

[0444] 3) RSRP of CRI 6(differential value 4 bit)

[0445] 4) RSRP of CRI 8(differential value 4 bit)

[0446] In one embodiment, among the RSRPs belonging to the first group in the CSI, the highest RSRP may be mapped first, and the remaining RSRPs belonging to the first group may be mapped starting from the RSRP associated with the next RS resource index of the first RS resource index based on the order associated with the RS resource indices. This embodiment may be based on the detailed embodiment 3) of embodiment 1 of proposal 1. When the 7th RS resource index belonging to the second group among the 4 groups based on the 16 RS resource indices has the highest RSRP, the mapping order of the RSRPs of the second group may be expressed as follows.

[0447] 1) RSRP of CRI 7 (absolute value 7 bit)

[0448] 2) RSRP of CRI 8(differential value 4 bit)

[0449] 3) RSRP of CRI 5(differential value 4 bit)

[0450] 4) RSRP of CRI 6(differential value 4 bit)

[0451] In one embodiment, among the one or more RSRPs, the remaining RSRPs other than the highest RSRP may be expressed based on a differential value. The step size associated with the differential value may vary for each group. This embodiment may be based on Embodiment 2 of Proposal 1.

[0452] For example, a step size associated with one of the remaining groups, excluding the first group, among the above groups may be larger than a step size associated with the first group. As a specific example, the step size for the first group may be 2 dB, and the step size for one of the remaining groups may be 4 dB, 6 dB, 8 dB, etc., which are larger than 2 dB.

[0453] In one embodiment, the CSI may be transmitted based on a Physical Uplink Control Channel (PUCCH) resource. Based on the number of bits of Uplink Control Information (UCI) associated with the CSI (e.g., the number of UCI bits) being greater than a maximum payload size associated with the PUCCH resource: the remaining RSRPs other than the highest RSRP may be expressed based on a second step size greater than a first step size defined for a differential value. This embodiment may be based on Proposal 2.

[0454] For example, the first step size may be 2 dB. The second step size may be determined based on i) the number of one or more RSRPs or ii) the number of RSRPs belonging to each group. This embodiment may be based on embodiment 1) or embodiment 2) of proposal 2.

[0455] The operations based on S810 to S820 described above can be implemented by the device of FIG. 10. For example, referring to FIG. 10, the terminal (200) can control one or more transceivers (230) and / or one or more memories (240) to perform the operations based on S810 to S820.

[0456] The embodiments described below are specifically described in terms of base station operation.

[0457] S910 to S920 described below correspond to S810 to S820 described in FIG. 8. Considering the above correspondence, redundant descriptions are omitted. That is, the specific description of the base station operation described below may be replaced with the description / example of FIG. 8 corresponding to the corresponding operation.

[0458] FIG. 9 is a flowchart illustrating a method according to another embodiment of the present specification.

[0459] Referring to FIG. 9, a method according to another embodiment of the present specification includes a step of transmitting a report setting related to CSI (S910) and a step of receiving CSI (S920).

[0460] In S910, the base station transmits report configuration related to channel state information (CSI) to the terminal.

[0461] For example, the reporting settings may include information based on at least one of Proposals 1 and 2.

[0462] In S920, the base station receives the CSI from the terminal.

[0463] Hereinafter, the above CSI can be interpreted / replaced with a CSI report.

[0464] For example, the CSI includes one or more Reference Signal Received Powers (RSRPs). In this case, the embodiment of Proposal 1 may be applied to resolve ambiguity in determining one or more RS resource indices related to the one or more RSRPs. Specifically, the CSI may include information based on at least one of the above-described Proposals 1 and 2. The CSI may include i) information based on Embodiment 2 of Proposal 1 (e.g., first information and second information) or ii) information based on Embodiment 1 of Proposal 1 (e.g., third information). This will be described in detail below.

[0465] In one embodiment, the CSI may include i) first information indicating a first group to which a first RS resource index having a highest RSRP (highest RSRP) among groups based on RS resource indices (e.g., CRIs / SSBRIs) set for measurement belongs, and ii) second information indicating the first RS resource index among RS resource indices within the first group. The present embodiment may be based on Embodiment 2 of Proposal 1.

[0466] The operations based on S910 to S920 described above can be implemented by the device of FIG. 10. For example, referring to FIG. 10, the base station (100) can control one or more transceivers (130) and / or one or more memories (140) to perform the operations based on S910 to S920.

[0467] The operations / terms based on the embodiments described above have been described assuming a 5G system. However, this is for convenience of explanation and is not intended to limit the scope of application of the technical problems and problem-solving means to be solved by this specification to a specific system. That is, the technical problems / technical issues / problems mentioned in this specification may equally exist in other systems (e.g., 6G systems). It is self-evident that the embodiments of this specification can be expanded and applied to solve problems equally existing in the other systems. Therefore, for the expanded application of the embodiments of this specification to other systems, the terms defined / described based on the 5G system may be replaced / changed with terms defined in the other systems (or generalized terms not specific to a system). For example, PRACH, PUSCH, PUCCH, or SRS may be replaced / changed with uplink signals (or uplink channels). For example, SSB, CSI-RS, PDSCH, and PDCCH may be replaced / changed with downlink signals (or downlink channels).

[0468] Hereinafter, a device to which an embodiment of the present specification can be applied (a device that implements a method / operation according to an embodiment of the present specification) is described with reference to FIG. 10.

[0469] FIG. 10 is a drawing showing the configuration of a first device and a second device according to an embodiment of the present specification.

[0470] The first device (100) may include a processor (110), an antenna unit (120), a transceiver (130), and a memory (140).

[0471] The processor (110) performs baseband-related signal processing and may include a higher layer processing unit (111) and a physical layer processing unit (115). The higher layer processing unit (111) may process operations of a MAC layer, an RRC layer, or higher layers. The physical layer processing unit (115) may process operations of a PHY layer. For example, when the first device (100) is a base station device in base station-terminal communication, the physical layer processing unit (115) may perform uplink reception signal processing, downlink transmission signal processing, etc. For example, when the first device (100) is a first terminal device in terminal-to-terminal communication, the physical layer processing unit (115) may perform downlink reception signal processing, uplink transmission signal processing, sidelink transmission signal processing, etc. In addition to performing baseband-related signal processing, the processor (110) may also control the overall operation of the first device (100).

[0472] The antenna unit (120) may include one or more physical antennas, and when it includes multiple antennas, it may support MIMO transmission and reception. The transceiver (130) may include an RF (Radio Frequency) transmitter and an RF receiver. The memory (140) may store information processed by the processor (110), and software, an operating system, applications, etc. related to the operation of the first device (100), and may also include components such as a buffer.

[0473] The processor (110) of the first device (100) may be configured to implement the operation of the base station in the base station-to-terminal communication (or the operation of the first terminal device in the terminal-to-terminal communication) in the embodiments described in the present disclosure.

[0474] The second device (200) may include a processor (210), an antenna unit (220), a transceiver (230), and a memory (240).

[0475] The processor (210) performs baseband-related signal processing and may include a higher layer processing unit (211) and a physical layer processing unit (215). The higher layer processing unit (211) may process operations of a MAC layer, an RRC layer, or higher layers. The physical layer processing unit (215) may process operations of a PHY layer. For example, when the second device (200) is a terminal device in base station-terminal communication, the physical layer processing unit (215) may perform downlink reception signal processing, uplink transmission signal processing, etc. For example, when the second device (200) is a second terminal device in terminal-to-terminal communication, the physical layer processing unit (215) may perform downlink reception signal processing, uplink transmission signal processing, sidelink reception signal processing, etc. In addition to performing baseband-related signal processing, the processor (210) may also control the overall operation of the second device (210).

[0476] The antenna unit (220) may include one or more physical antennas, and when it includes multiple antennas, it may support MIMO transmission and reception. The transceiver (230) may include an RF transmitter and an RF receiver. The memory (240) may store information processed by the processor (210), software, an operating system, applications, etc. related to the operation of the second device (200), and may also include components such as a buffer.

[0477] The processor (210) of the second device (200) may be configured to implement operations of the terminal in base station-to-terminal communication (or operations of the second terminal device in terminal-to-terminal communication) in the embodiments described in the present disclosure.

[0478] In the operation of the first device (100) and the second device (200), the same explanations given for the base station and the terminal (or the first terminal and the second terminal in the terminal-to-terminal communication) in the examples of the present disclosure may be applied, and redundant explanations are omitted.

[0479] Here, the wireless communication technology implemented in the device of the present disclosure may include LTE, NR, and 6G, as well as Narrowband Internet of Things (NB-IoT) for low-power communication. For example, NB-IoT technology may be an example of LPWAN (Low Power Wide Area Network) technology and may be implemented in standards such as LTE Cat NB1 and / or LTE Cat NB2, and is not limited to the above-described names.

[0480] Additionally or alternatively, the wireless communication technology implemented in the device of the present disclosure may perform communication based on LTE-M technology. For example, LTE-M technology may be an example of LPWAN technology and may be called by various names such as eMTC (enhanced Machine Type Communication). For example, LTE-M technology may be implemented by at least one of various standards such as 1) LTE CAT 0, 2) LTE Cat M1, 3) LTE Cat M2, 4) LTE non-BL (non-Bandwidth Limited), 5) LTE-MTC, 6) LTE Machine Type Communication, and / or 7) LTE M, and is not limited to the above-described names.

[0481] Additionally or alternatively, the wireless communication technology implemented in the device of the present disclosure may include at least one of ZigBee, Bluetooth, and Low Power Wide Area Network (LPWAN), which take low-power communication into account, and is not limited to the above-described names. For example, ZigBee technology can create personal area networks (PANs) related to small / low-power digital communication based on various standards such as IEEE 802.15.4, and may be called by various names.

Claims

1. In the method, A step of receiving a report configuration related to channel state information (CSI); and A step of reporting the above CSI; including: The above CSI includes one or more Reference Signal Received Powers (RSRPs), A method characterized in that the CSI includes i) first information indicating a first group to which a first RS resource index having a highest RSRP (highest RSRP) among groups based on RS resource indices set for measurement belongs, and ii) second information indicating the first RS resource index among RS resource indices within the first group.

2. In paragraph 1, A method characterized in that the bitwidth for the first information is determined based on the number of groups.

3. In paragraph 2, The bit width for the above first information is and, A method characterized in that is a ceiling function and M is the number of said groups.

4. In paragraph 2, A method characterized in that the bit width of the first information is M, and M is the number of the groups.

5. In paragraph 1, A method characterized in that the bitwidth for the second information is determined based on the number of RS resource indexes in each group.

6. In paragraph 5, The bit width for the above second information is and, is the number of RS resource indices in each group above, A method characterized in that is a ceiling function, N is the number of RS resource indices set for the measurement, and M is the number of groups.

7. In paragraph 5, The bit width for the above second information is And, is the number of RS resource indices in each group above, A method characterized in that is a ceiling function, N is the number of RS resource indices set for the measurement, and M is the number of groups.

8. In paragraph 1, A method characterized in that the CSI comprises i) the first information and the second information or ii) third information indicating the first RS resource index having the highest RSRP.

9. In paragraph 8, A method characterized in that the third information is mapped first within the CSI.

10. In paragraph 9, A method characterized in that the one or more RSRPs within the CSI are mapped based on an order related to the RS resource indices.

11. In paragraph 9, A method characterized in that among the one or more RSRPs within the CSI, the highest RSRP is mapped first, and the remaining RSRPs are mapped starting from the RSRP associated with the lowest RS resource index based on the order associated with the RS resource indices.

12. In paragraph 9, A method characterized in that the highest RSRP among the one or more RSRPs within the CSI is mapped first, and the remaining RSRPs are mapped starting from the RSRP associated with the next RS resource index of the first RS resource index based on the order associated with the RS resource indices.

13. In paragraph 1, A method characterized in that the first information and the second information are mapped first within the CSI.

14. In paragraph 13, A method characterized in that the one or more RSRPs within the CSI are mapped based on the order of group indices associated with the groups.

15. In paragraph 13, A method characterized in that, within the CSI, RSRPs of the first group to which the highest RSRP among the one or more RSRPs belongs are mapped first, and the remaining RSRPs are mapped starting from RSRPs belonging to the group having the lowest group index based on the order of group indices associated with the groups.

16. In paragraph 13, A method characterized in that, within the CSI, RSRPs of the first group to which the highest RSRP among the one or more RSRPs belongs are mapped first, and the remaining RSRPs are mapped starting from RSRPs belonging to the next group of the first group based on the order of group indexes associated with the groups.

17. In paragraph 13, A method characterized in that RSRPs belonging to the first group within the CSI are mapped based on the order related to the RS resource indices.

18. In paragraph 13, A method characterized in that, within the CSI, the highest RSRP among the RSRPs belonging to the first group is mapped first, and the remaining RSRPs belonging to the first group are mapped starting from the RSRP associated with the lowest RS resource index based on the order related to the RS resource indices.

19. In paragraph 13, A method characterized in that among the RSRPs belonging to the first group within the CSI, the highest RSRP is mapped first, and the remaining RSRPs belonging to the first group are mapped starting from the RSRP associated with the next RS resource index of the first RS resource index based on the order associated with the RS resource indices.

20. In paragraph 1, Among the above one or more RSRPs, the remaining RSRPs other than the highest RSRP are expressed based on differential values, A method characterized in that the step size associated with the above difference value is different for each group.

21. In paragraph 20, A method characterized in that a step size associated with one of the remaining groups excluding the first group among the above groups is larger than a step size associated with the first group.

22. In paragraph 8, The above CSI is transmitted based on physical uplink control channel (PUCCH) resources, Based on the number of bits of the uplink control information (UCI) related to the CSI being greater than the maximum payload size related to the PUCCH resource: A method characterized in that the remaining RSRPs other than the highest RSRP are expressed based on a second step size larger than a first step size defined for a differential value.

23. In paragraph 22, The above first step size is 2 dB, A method characterized in that the second step size is determined based on i) the number of one or more RSRPs or ii) the number of RSRPs belonging to each group.

24. At the terminal, One or more transmitters and receivers; one or more processors; and One or more memories connected to said one or more processors and storing instructions, A terminal characterized in that the instructions, based on being executed by the one or more processors, cause the terminal to perform all steps of the method according to any one of claims 1 to 23.

25. In a device comprising one or more memories and one or more processors connected to the one or more memories, A device characterized in that said one or more memories store instructions that cause said device to perform all steps of a method according to any one of claims 1 to 23, based on being executed by said one or more processors.

26. In a non-transitory computer-readable storage medium storing instructions, A non-transitory computer-readable storage medium characterized in that the instructions executable by one or more processors cause a terminal to perform all steps of a method according to any one of claims 1 to 23.

27. In the method, A step of transmitting report configuration related to channel state information (CSI); and A step of receiving the above CSI; including: The above reporting configuration includes i) information about a first CSI resource configuration related to prediction and ii) information about a second CSI resource configuration related to measurement, A method characterized in that the CSI includes i) information on at least one RS resource index among RS resource indices based on the first CSI resource configuration and / or ii) at least one Reference Signal Received Power (RSRP) associated with the at least one RS resource index.

28. At the base station, One or more transmitters and receivers; one or more processors; and One or more memories connected to said one or more processors and storing instructions, A base station characterized in that the instructions, based on being executed by the one or more processors, cause the base station to perform all steps of the method according to claim 27.

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