Terminal, wireless communication method and system

Abstract

A terminal according to an embodiment of the present disclosure is characterized by comprising: a transmission unit that transmits information obtained by compressing channel state information (CSI) using an artificial intelligence (AI) / machine learning (ML) model; and a control unit that, for calculation of a channel quality indicator (CQI), presumes a specific precoding matrix is to be applied to physical downlink shared channel (PDSCH) transmission. Appropriate CSI feedback using AI can be achieved with an embodiment of the present disclosure.

Description

Technical Field

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

Background Art

[0002] In a Universal Mobile Telecommunications System (UMTS) network, Long Term Evolution (LTE) was specified for the purpose of further high data rates, low latency, etc. (Non-Patent Document 1). Also, for the purpose of further large capacity and sophistication of LTE (Third Generation Partnership Project (3GPP (registered trademark)) Release (Rel.) 8, 9), LTE-Advanced (3GPP Rel. 10-14) was specified.

[0003] Successor systems to LTE (for example, also referred to as 5th generation mobile communication system (5G), 5G+ (plus), 6th generation mobile communication system (6G), New Radio (NR), 3GPP Rel. 15 and later, etc.) are also under consideration.

Prior Art Documents

Non-Patent Documents

[0004]

Non-Patent Document 1

Summary of the Invention

[0005] Regarding future wireless communication technologies, there is a growing consideration to utilize artificial intelligence (AI) technologies, such as machine learning (ML), for network / device control and management in terminals (user terminals, User Equipment (UE)) and base stations. For example, in future wireless communication technologies, there is a growing consideration to utilize AI technology to improve Channel State Information Reference Signal (CSI) feedback, such as reducing overhead, improving accuracy, and making predictions. AI-based CSI feedback may also be called AI-aided CSI feedback or AI-based CSI feedback.

[0006] However, the method for calculating the Channel Quality Indicator (CQI) when applying AI-assisted CSI feedback has not yet been thoroughly investigated. Without proper definition of these aspects, it may be impossible to perform appropriate CSI feedback using AI. This could prevent the achievement of appropriate overhead reduction, highly accurate channel estimation, and efficient resource utilization, potentially hindering improvements in communication throughput and communication quality.

[0007] Therefore, this disclosure relates to a terminal, wireless communication method, and capable of realizing appropriate CSI feedback using AI. system One of the objectives is to provide [this]. [Means for solving the problem]

[0008] A terminal according to one aspect of this disclosure includes a transmission unit that transmits information obtained by compressing channel status information (CSI) using an Artificial Intelligence (AI) / Machine Learning (ML) model, and a control unit that assumes that a specific precoding matrix is ​​applied to physical downlink shared channel (PDSCH) transmission for the purpose of calculating a channel quality indicator (CQI). The specific precoding matrix is ​​a precoding matrix calculated based on the AI / ML model output at the base station, a precoding matrix derived based on the CSI calculated based on terminal measurements, or a precoding matrix derived based on the expected output for the AI / ML model at the base station. It is characterized by the following: [Effects of the Invention]

[0009] According to one aspect of this disclosure, appropriate CSI feedback using AI can be achieved. [Brief explanation of the drawing]

[0010] [Figure 1] Figure 1 shows an example of a framework for managing AI models. [Figure 2] Figure 2 shows an example of specifying an AI model. [Figure 3] Figure 3 shows an example of AI-based CSI feedback. [Figure 4] Figure 4 shows the relationship between subband difference CQI values ​​and offset levels. [Figure 5] Figure 5 shows an example of CSI feedback according to embodiment 1.4. [Figure 6] Figure 6 shows an example of CSI feedback for Option 1 in the second embodiment. [Figure 7] Figure 7 shows an example of a schematic configuration of a wireless communication system according to one embodiment. [Figure 8] Figure 8 shows an example of the configuration of a base station according to one embodiment. [Figure 9] Figure 9 shows an example of the configuration of a user terminal according to one embodiment. [Figure 10] Figure 10 shows an example of the hardware configuration of a base station and a user terminal according to one embodiment. [Figure 11] FIG. 11 is a diagram showing an example of a vehicle according to an embodiment.

Embodiments for Carrying Out the Invention

[0011] (Application of Artificial Intelligence (AI) Technology to Wireless Communication) Regarding future wireless communication technologies, it has been considered to utilize AI technologies such as Machine Learning (ML) for network / device control, management, etc.

[0012] For example, regarding future wireless communication technologies, it has been considered to utilize AI technologies for improving Channel State Information Reference Signal (CSI) feedback (e.g., overhead reduction, accuracy improvement, prediction), improving beam management (e.g., accuracy improvement, prediction in time / space domains), improving position measurement (e.g., improvement of position estimation / prediction), etc.

[0013] FIG. 1 is a diagram showing an example of a framework for managing an AI model. In this example, each stage related to the AI model is shown as a block. This example is also expressed as the life cycle management of the AI model.

[0014] The Data Collection stage corresponds to the stage of collecting data for generating / updating the AI model. The Data Collection stage may include data sorting (e.g., determination of which data to transfer for model training / model inference), data transfer (e.g., transferring data to an entity (e.g., UE, gNB) that performs model training / model inference), etc.

[0015] In the model training stage, model training is performed based on the data transferred from the collection stage (training data). This stage may include data preparation (such as performing preprocessing, cleaning, formatting, conversion, etc. of the data), model training / validation, model testing (such as checking whether the trained model meets the performance threshold), model exchange (such as transferring the model for distributed learning), model deployment / update (deploying / updating the model to the entity that performs model inference), and the like.

[0016] In the model inference stage, model inference is performed based on the data transferred from the collection stage (inference data). This stage may include data preparation (such as performing preprocessing, cleaning, formatting, conversion, etc. of the data), model inference, model monitoring (such as monitoring the performance of model inference), model performance feedback (providing the model performance as feedback to the entity that performs model training), output (providing the output of the model to the actor), and the like.

[0017] The actor stage may include an action trigger (such as determining whether to trigger an action for other entities), feedback (such as providing the information necessary for training data / inference data / performance feedback), and the like.

[0018] Note that, for example, the training of the model for mobility optimization may be performed, for example, in the operation, administration, and maintenance (management) (OAM) in the network (NW) / gNodeB (gNB). In the former case, interoperability, large-capacity storage, operator manageability, and model flexibility (such as feature engineering) are advantageous. In the latter case, the advantage is that the latency of model update and data exchange for model deployment are not required. The above model inference may be performed, for example, in the gNB.

[0019] Furthermore, the entities used for training / inference may differ depending on the use case.

[0020] For example, in AI-assisted beam management based on measurement reports, OAM / gNB may perform model training and gNB may perform model inference.

[0021] For AI-assisted UE-assisted positioning, a Location Management Function (LMF) may perform model training and model inference.

[0022] For CSI feedback / channel estimation using an autoencoder, the OAM / gNB / UE may perform model training, and the gNB / UE may perform model inference (jointly).

[0023] For AI-assisted beam management or AI-assisted UE-based positioning based on beam measurements, the OAM / gNB / UE may perform model training and the UE may perform model inference.

[0024] Incidentally, it is desirable that data / AI models be treated as proprietary assets. For example, creating highly accurate AI models is extremely costly and time-consuming, so if the contents of an AI model created by one company become known to another company, it can result in significant disadvantages. For this reason, consideration is being given to making some information about AI models unavailable (or making it impossible to infer) for UE / gNBs provided by different vendors.

[0025] An identifier (ID)-based model approach could be one way to manage AI models in such scenarios. For example, a network / gNB might not know the details of an AI model, but only some information about it (e.g., which ML models are being used for what purpose in the UE) for AI model management purposes.

[0026] Figure 2 shows an example of specifying an AI model. In this example, the UE and NW (for example, the base station (BS)) can recognize models #1 and #2 (they do not need to fully understand the details of the models). The UE may report the performance of model #1 and model #2 to the NW, and the NW may instruct the UE on which AI model to use.

[0027] In this disclosure, the UE / BS may input channel status information, reference signal measurements, etc., to the ML model and output high-precision channel status information / measurements / beam selection / position, future channel status information / wireless link quality, etc.

[0028] In this disclosure, AI may be interpreted as an object (also called a subject, object, data, function, program, etc.) having (implementing) at least one of the following characteristics: • Estimation based on observed or collected information • Selection based on observed or collected information. • Predictions based on observed or collected information.

[0029] In this disclosure, an object may be, for example, a device such as a terminal or base station. Furthermore, in this disclosure, an object may refer to a program / model / entity operating on such device.

[0030] Furthermore, in this disclosure, the ML model may be replaced with an object having (implementing) at least one of the following features: • By providing information (feeding), estimates are generated. By providing information, predict the estimated value. By providing information, we can discover features. • By providing information, the user can select an action.

[0031] Furthermore, in this disclosure, AI, AI / ML, AI / ML model, ML model, model, AI model, predictive analytics, predictive analytics model, etc., may be interpreted interchangeably. Also, an ML model may be derived using at least one of the following: regression analysis (e.g., linear regression analysis, multiple regression analysis, logistic regression analysis), support vector machine, random forest, neural network, deep learning, etc. In this disclosure, a model may be interpreted as at least one of the following: encoder, decoder, tool, etc.

[0032] An ML model outputs at least one piece of information based on the input information, such as an estimate, a prediction, a chosen action, or a classification.

[0033] ML models may include supervised learning, unsupervised learning, and reinforcement learning. Supervised learning may be used to learn general rules for mapping inputs to outputs. Unsupervised learning may be used to learn data features. Reinforcement learning may be used to learn actions to maximize an objective (goal).

[0034] In this disclosure, terms such as generation, calculation, and derivation may be interpreted interchangeably. In this disclosure, terms such as implementation, operation, function, and execution may be interpreted interchangeably. In this disclosure, terms such as training, learning, updating, and retraining may be interpreted interchangeably. In this disclosure, terms such as inference, after-training, production use, and actual use may be interpreted interchangeably. Signal may be interpreted interchangeably with signal / channel.

[0035] (CSI report (CSI report or reporting)) In Rel.15 NR, a terminal (also called a user terminal, User Equipment (UE), etc.) generates (determines, calculates, estimates, measures, etc.) channel state information (CSI) based on a reference signal (RS) (or a resource for the RS), and transmits (reports, provides feedback, etc.) the generated CSI to the network (e.g., a base station). The CSI may be transmitted to the base station using, for example, an uplink control channel (e.g., a Physical Uplink Control Channel (PUCCH)) or an uplink shared channel (e.g., a Physical Uplink Shared Channel (PUSCH)).

[0036] The RS used to generate the CSI may be at least one of the following: a Channel State Information Reference Signal (CSI-RS), a Synchronization Signal / Physical Broadcast Channel (SS / PBCH) block, a Synchronization Signal (SS), or a Demodulation Reference Signal (DMRS).

[0037] The CSI-RS may include at least one of Non Zero Power (NZP) CSI-RS and CSI-Interference Management (CSI-IM). The SS / PBCH block is a block that includes SS and PBCH (and the corresponding DMRS), and may be called an SS block (SSB), etc. The SS may also include at least one of a Primary Synchronization Signal (PSS) and a Secondary Synchronization Signal (SSS).

[0038] Furthermore, CSI may include at least one of the following: Channel Quality Indicator (CQI), Precoding Matrix Indicator (PMI), CSI-RS Resource Indicator (CRI), SS / PBCH Block Resource Indicator (SSBRI), Layer Indicator (LI), Rank Indicator (RI), L1-RSRP (Layer 1 Reference Signal Received Power), L1-RSRQ (Reference Signal Received Quality), L1-SINR (Signal to Interference plus Noise Ratio), and L1-SNR (Signal to Noise Ratio).

[0039] The UE may receive information regarding CSI reporting (report configuration information) and control CSI reporting based on said report configuration information. Such report configuration information may be, for example, the "CSI-ReportConfig" information element (IE) of Radio Resource Control (RRC). In this disclosure, RRC IE may be interpreted interchangeably with RRC parameters, higher layer parameters, etc.

[0040] The reporting configuration information (for example, "CSI-ReportConfig" in RRC IE) may include at least one of the following: • Information regarding the type of CSI report (report type information, e.g., "reportConfigType" in RRC IE) • Information regarding one or more CSI quantities (one or more CSI parameters) to be reported (report quantity information, e.g., "reportQuantity" in RRC IE) • Information regarding the RS resource used to generate the quantity (the CSI parameter) in question (resource information, for example, "CSI-ResourceConfigId" in RRC IE). • Information regarding the frequency domain covered by the CSI report (frequency domain information, for example, "reportFreqConfiguration" in RRC IE)

[0041] For example, the reporting type information may indicate a periodic CSI (P-CSI) report, an aperiodic CSI (A-CSI) report, or a semi-persistent CSI (SP-CSI) report.

[0042] Furthermore, the reported quantity information may specify at least one combination of the above CSI parameters (e.g., CRI, RI, PMI, CQI, LI, L1-RSRP, etc.).

[0043] Furthermore, resource information may also be the ID of a resource for RS. Such RS resources may include, for example, a non-zero-power CSI-RS resource or SSB and a CSI-IM resource (for example, a zero-power CSI-RS resource).

[0044] Furthermore, frequency domain information may indicate the frequency granularity of the CSI report. This frequency granularity may include, for example, wideband and subband. The wideband is the entire CSI reporting band. The wideband may be, for example, the entire carrier (component carrier (CC)), cell, serving cell, or the entire bandwidth part (BWP) within a carrier. The wideband may also be referred to as the CSI reporting band, the entire CSI reporting band, etc.

[0045] Furthermore, a subband may be part of the wideband and may consist of one or more resource blocks (RBs) or physical resource blocks (PRBs). The size of the subband may be determined according to the size of the BWP (number of PRBs).

[0046] Frequency domain information may indicate whether to report wideband or subband PMI (frequency domain information may include, for example, the RRC IE's "pmi-FormatIndicator" used to determine whether to report wideband or subband PMI). The UE may determine the frequency granularity of the CSI report (i.e., whether to report wideband or subband PMI) based on at least one of the above reported quantity information and frequency domain information.

[0047] If wideband PMI reporting is established (decided), one wideband PMI may be reported for the entire CSI reporting band. On the other hand, if subband PMI reporting is established, a single wideband indication i1 may be reported for the entire CSI reporting band, and one or more subband indications i2 (e.g., subband indications for each subband) may be reported for each subband within the entire CSI reporting band.

[0048] The UE performs channel estimation using the received RS and estimates the channel matrix H. The UE then feeds back the index (PMI) determined based on the estimated channel matrix.

[0049] PMI may represent a precoder matrix (also simply called a precoder) that the UE considers appropriate for use in downlink (DL) transmissions to the UE. Each value of PMI may correspond to a single precoder matrix. A set of PMI values ​​may correspond to a different set of precoder matrices called a precoder codebook (also simply called a codebook).

[0050] In a spatial domain, a CSI report may include one or more types of CSI. For example, the CSI may include at least one of a first type (Type 1 CSI) used for single-beam selection and a second type (Type 2 CSI) used for multi-beam selection. Single-beam can be rephrased as a single layer, and multi-beam can be rephrased as multiple beams. Furthermore, Type 1 CSI may not assume multi-user multiple input multiple output (MIMO), while Type 2 CSI may assume multi-user MIMO.

[0051] The above codebooks may include a codebook for Type 1 CSI (also called a Type 1 codebook, etc.) and a codebook for Type 2 CSI (also called a Type 2 codebook, etc.). Furthermore, Type 1 CSI may include Type 1 single-panel CSI and Type 1 multi-panel CSI, and different codebooks (Type 1 single-panel codebook and Type 1 multi-panel codebook) may be specified for each.

[0052] In this disclosure, Type 1 and Type I may be interpreted as interchangeable. In this disclosure, Type 2 and Type II may be interpreted as interchangeable.

[0053] The Uphill Control Information (UCI) type may include at least one of the following: Hybrid Automatic Repeat reQuest ACKnowledgement (HARQ-ACK), scheduling request (SR), or CSI. The UCI may be carried by PUCCH or by PUSCH.

[0054] In Rel.15 NR, the UCI may include one CSI part for wideband PMI feedback. CSI report #n will include PMI wideband information if reported.

[0055] In Rel.15 NR, the UCI may include two CSI parts for subband PMI feedback. CSI part 1 contains wideband PMI information. CSI part 2 contains one wideband PMI piece and several subband PMI pieces. CSI parts 1 and 2 are encoded separately.

[0056] (Receiving information) In this disclosure, the UE may receive various types of information (e.g., information regarding configuration / instructions) from the NW (base station, gNB) using upper-layer signaling / physical-layer signaling (e.g., RRC signaling / MAC CE / DCI).

[0057] MAC CE may have a new Logical Channel ID (LCID) in its subheader. Existing MAC CEs (e.g., MAC CEs in Rel.15 / 16) may be extended. For example, a new octet may be introduced.

[0058] DCI may have existing DCI fields (e.g., DCI fields in Rel. 15 / 16) or newly introduced DCI fields. DCI may be scrambled with Cyclic Redundancy Check (CRC) using existing Radio Network Temporary Identifiers (RNTIs) or newly introduced RNTIs. DCI may be in DCI formats to which existing DCI formats (DCI formats 0_0~0_2, 1_0~1_2, 2_0~2_6, 3_0~3_1) or newly introduced DCI formats are applied.

[0059] The UE may receive information from the NW in the following types: periodically, semi-persistent (triggered by instructions from the UE or gNB), or aperiodic (triggered by instructions from the UE or gNB).

[0060] (Reporting information) In this disclosure, the UE may transmit (report) various types of information to the NW (base stations, gNBs) using at least one of the following: higher layer signaling (e.g., RRC messages), MAC CE, or UCI.

[0061] MAC CE may have a new Logical Channel ID (LCID) in its subheader. Existing MAC CE may be extended. For example, a new octet may be introduced.

[0062] UCI may be transmitted via either PUCCH or PUSCH.

[0063] The UE may transmit information to the NW in a periodic, semi-persistent (triggered by instructions from the UE or gNB), or aperiodic (triggered by instructions from the UE or gNB) manner.

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

[0065] Figure 3 shows an example of AI-based CSI feedback. The UE performs preprocessing, AI / ML-based CSI generation, and postprocessing on measurement results related to CSI, and transmits the encoded bits (CSI feedback information) to the NW (base station). CSI compression may be performed during this AI / ML-based CSI generation. The NW (base station) performs preprocessing, AI / ML-based CSI reconstruction, and postprocessing on the received bits to obtain the CSI (channel / precoding matrix).

[0066] In this case, it is desirable to select and adjust AI / ML so that the CSI acquired by the NW (base station) is close to the target CSI. The target CSI may refer to the CSI calculated based on UE measurements, the ideal CSI (simulated CSI, fixed value), or the actual CSI.

[0067] (CQI) The UE derives (calculates) the highest CQI value (reported in UL slot n) that satisfies the following conditions (1) to (4).

[0068] (1) The block error probability of a single PDSCH TB with a CQI index and CSI reference resource shall not exceed the following values: • If the cqi-table of CSI-ReportConfig is set to a predetermined table (table1 or table2), then 0.1. • If the cqi-table in CSI-ReportConfig is set to the specified table (table3), the value is 0.00001.

[0069] (2) In order to derive CQI / PMI / RI, UE makes the following assumptions about PDSCH. • The PDSCH and DMRS have 12 symbols (the first two symbols are occupied by control signals). • The same bandwidth is set for CQI reporting. • Front-loaded symbols and additional DMRS symbols based on DMRS-DownlinkConfig. The PRB band ring size is assumed to be PRB. The UE may assume PDSCH transmission using a precoding matrix corresponding to the reported PMI.

[0070] (3) CQI observation interval. Unless otherwise specified, there is no time limit. • Unlimited in the frequency domain.

[0071] (4) For each subband index s, a 2-bit subband difference CQI is defined as follows (Figure 4). Subband offset level (s) = Subband CQI index (s) - Broadband CQI index.

[0072] (CQI value based on precoding matrix) If configured to report a CQI index, the UE assumes the following in the CSI reference resource to derive the CQI index and (if configured) the PMI and RI:

[0073] For a PDSCH transmission scheme, the UE may assume that PDSCH transmission is performed at up to eight transmission layers. For CQI calculations, the UE assumes that the PDSCH signals on the antenna ports of the set of ν layers [1000, ..., 1000+ν-1] are equivalent to the signals of the corresponding symbols transmitted at the antenna ports [3000, ..., 3000+P-1]. These signals are expressed as shown in equation (1), where x(i) is expressed as shown in equation (2).

[0074]

number

[0075]

number

[0076] In equation (2), x(i) is a vector of PDSCH symbols from the layer mapping. p∈[1,2,4,8,12,16,24,32] is the number of CSI-RS ports. If only one CSI-RS port is configured, W(i) is 1. If the upper layer parameter reportQuantity of the CSI-ReportConfig on which the CQI is reported is either 'cri-RI-PMI-CQI' or 'cri-RI-LI-PMI-CQI', then W(i) is the precoding matrix corresponding to the reported PMI applied to x(i). If the upper layer parameter reportQuantity of the CSI-ReportConfig on which the CQI is reported is set to 'cri-RI-CQI', then W(i) is set to a specific precoding matrix. The corresponding PDSCH signals transmitted on antenna ports [3000,…,3000+P-1] are adjusted so that the ratio of EPRE to CSI-RS EPRE is equal to a specific ratio.

[0077] (analysis) As mentioned above, the application of AI-based CSI feedback is being considered. However, how to calculate the CQI when AI-based CSI feedback is applied has not yet been thoroughly investigated.

[0078] For example, if information about the precoding vector (precoding matrix) is compressed, it is unclear how CQI-related information is calculated and reported. For example, if information about the channel matrix is ​​compressed by the AI / ML model, it is unclear how information about normalization (e.g., amplitude) is reported. For example, it is unclear whether the channel matrix is ​​normalized, and if so, whether the normalization coefficients are transmitted.

[0079] Therefore, the inventors conceived of a terminal that can provide appropriate CSI feedback using AI.

[0080] The embodiments of this disclosure will be described in detail below with reference to the drawings. Each wireless communication method according to the embodiments may be applied individually or in combination.

[0081] In this disclosure, "A / B" and "at least one of A and B" may be interpreted as mutually exclusive. In this disclosure, "A / B / C" may mean "at least one of A, B, and C".

[0082] In this disclosure, terms such as activate, deactivate, indicate, select, configure, update, and determine may be interpreted interchangeably. In this disclosure, terms such as support, control, controllable, operate, and operable may be interpreted interchangeably.

[0083] In this disclosure, Radio Resource Control (RRC), RRC parameters, RRC messages, higher-layer parameters, fields, Information Elements (IE), settings, etc., may be interpreted interchangeably. In this disclosure, Medium Access Control elements (MAC Control Element (CE)), update commands, activation / deactivation commands, etc., may be interpreted interchangeably.

[0084] In this disclosure, the upper-layer signaling may be, for example, Radio Resource Control (RRC) signaling, Medium Access Control (MAC) signaling, broadcast information, or a combination thereof.

[0085] In this disclosure, MAC signaling may include, for example, MAC Control Elements (MAC CEs) and MAC Protocol Data Units (PDUs). Broadcast information may include, for example, Master Information Blocks (MIBs), System Information Blocks (SIBs), Remaining Minimum System Information (RMSIs), and Other System Information (OSIs).

[0086] In this disclosure, physical layer signaling may include, for example, Downlink Control Information (DCI) and Uplink Control Information (UCI).

[0087] In this disclosure, terms such as index, identifier (ID), indicator, and resource ID may be interpreted interchangeably. In this disclosure, terms such as sequence, list, set, group, cluster, and subset may be interpreted interchangeably.

[0088] In this disclosure, CSI-RS, Non Zero Power (NZP) CSI-RS, Zero Power (ZP) CSI-RS, and CSI Interference Measurement (CSI-IM) may be interpreted interchangeably. Furthermore, CSI-RS may include other reference signals.

[0089] Furthermore, in this disclosure, terms such as encoder, encoding, encoding, and modification / change / control by an encoder may be interpreted interchangeably. Also, in this disclosure, terms such as decoder, decoding, decoding, and modification / change / control by a decoder may be interpreted interchangeably.

[0090] In this disclosure, UCI, CSI report, CSI feedback, feedback information, feedback bits, etc., may be interpreted interchangeably. Also, in this disclosure, bits, bit sequences, bit series, sequences, values, information, values ​​obtained from bits, information obtained from bits, etc., may be interpreted interchangeably.

[0091] In this disclosure, the term "layer" (referring to an encoder) may be interpreted interchangeably with the terms "input layer," "hidden layer," etc., used in an AI model. The layers in this disclosure may correspond to at least one of the following: an input layer, a hidden layer, an output layer, a batch normalization layer, a convolutional layer, a dropout layer, a fully connected layer, etc.

[0092] In this disclosure, the layer for the precoding matrix may be interpreted as a Multi Input Multi Output (MIMO) layer, stream, etc.

[0093] In the following embodiments, the relevant entities are the UE and BS to describe an AI model relating to communication between UE and BS, but the application of each embodiment of this disclosure is not limited thereto. For example, for communication between other entities (e.g., UE-UE communication), the UE and BS in the embodiments below may be replaced with a first UE and a second UE. In other words, the UE, BS, etc. in this disclosure may all be replaced with any UE / BS.

[0094] In this disclosure, "model" and "AI / ML model" may be interpreted interchangeably. In this disclosure, "CQI" may be replaced with at least one of the modulation scheme, target coding rate, transport block size, or related information. The modulation scheme, target coding rate, and transport block size may be subject to the condition that they do not exceed the transport block error probability. "Compression," "encoding," and "application of AI / ML model" may be interpreted interchangeably. "Network (NW)," "base station," and "gNB" may be interpreted interchangeably. "CQI" and "CQI index" may be interpreted interchangeably. In this disclosure, "expectation," "assumption," and "prediction" may be interpreted interchangeably.

[0095] (Wireless communication method) <First Embodiment> The first embodiment relates to CSI calculation. When the UE applies CSI compression (e.g., using an AI / ML model), it transmits the information obtained by compressing the CSI (e.g., Encoded bits in Figure 3) to the NW (base station). The UE may then assume that the following precoding matrix is ​​applied to the PDSCH transmission for CQI calculation. The UE may then calculate the CQI based on the following precoding matrix.

[0096] [Aspect 1.1] The UE assumes that, when CSI compression is applied, the precoding matrix calculated at the base station based on the AI / ML model output is applied to PDSCH transmission. In other words, the UE calculates the CQI based on the precoding matrix actually obtained using the AI / ML model. If the UE has an encoder and decoder, it can derive this precoding matrix.

[0097] [Aspect 1.2] The UE assumes that, when CSI compression is applied, the output of an ideal AI / ML model (target CSI), for example, a precoding matrix derived based on a CSI calculated based on the UE's measurements, will be applied to the PDSCH transmission. In this example, the target CSI can be derived even if the UE does not have a decoder. However, the performance difference between the ideal output of the target CSI / model and the actual output (CSI) is ignored.

[0098] [Aspect 1.3] The UE assumes that, when CSI compression is applied, a precoding matrix derived based on the expected output of the AI / ML model at the base station (the expected output for the AI / ML model) will be applied to the PDSCH transmission. The UE may derive the expected output of the model based on the target CSI (the CSI calculated from the measured values) and expected performance information. The expected performance information (information about the AI / ML model) may be calculated by the UE, instructed / set by the base station (gNB), or transmitted from a server, etc. The expected performance information may also be expected estimated error information (such as the expected error variability).

[0099] In this example, even if the UE does not have a decoder, the expected output (CSI) can be derived based on the target CSI and expected performance. However, there is a performance difference between the model's expected output and the actual output.

[0100] [Aspect 1.4] The UE assumes that, when CSI compression is applied, a precoding matrix calculated based on the channel matrix derived from the output of the AI / ML model at the base station is applied to PDSCH transmission for CQI calculation. How the precoding matrix is ​​calculated from the channel matrix may be determined by the UE or specified in the specification. This example can be applied to CSI compression on the channel matrix. Also, since the CQI is calculated based on the actually obtained channel matrix, the UE can derive the resulting channel matrix if it has an encoder and decoder.

[0101] Figure 5 shows an example of CSI feedback in embodiment 1.4. In Figure 5, pre-processing and post-processing are omitted, but pre-processing and post-processing may be performed as in Figure 3. The NW (base station) calculates the precoding matrix based on the channel matrix output from the AI / ML model.

[0102] [Aspect 1.5] The UE assumes that, when CSI compression is applied, a precoding matrix calculated based on the channel matrix derived from the output of an ideal AI / ML model (target CSI), for example, a CSI calculated based on the UE's measurements, will be applied to PDSCH transmission. How the precoding matrix is ​​calculated from the channel matrix may be determined by the UE or specified in the specification. This example can be applied to CSI compression for channel matrices. However, there may be performance differences between the target CSI or the ideal output of the model and the actual model output.

[0103] [Aspect 1.6] The UE assumes that, when CSI compression is applied, the precoding matrix calculated from the channel matrix derived from the expected output of the AI / ML model at the base station (the expected output for the AI / ML model) is applied to PDSCH transmission. How the precoding matrix is ​​calculated from the channel matrix may be determined by the UE or specified in the specification. This example can be applied to CSI compression for the channel matrix. The UE can derive the expected output of the model based on the target CSI and expected performance information. The expected performance information may be calculated by the UE, instructed / set by the base station via upper-layer signaling / physical layer signaling, or transmitted from a server, etc. The expected performance information may also be expected estimated error information (such as the expected error variability).

[0104] <Second Embodiment> The second embodiment relates to CSI reporting. When an AI / ML model is applied for CSI compression, the UE can report at least one of the CQI and CQI-related information as follows:

[0105] [Option 1] The UE may generate compressed information (CSI feedback information) obtained by using an AI / ML model to compress CQI or information related to CQI, and transmit it to the base station. In other words, further data capacity reduction can be achieved by compressing not only CSI but also CQI. When AI-based CSI compression is applied, the UE may report only the wideband CQI index. The reported bits generated through the AI / ML model may include information about subband CQI indexes or subband CQI offset levels.

[0106] Figure 6 shows an example of CSI feedback for Option 1 of the second embodiment. The UE inputs the CSI, including the CQI, into the AI / ML model and transmits the encoded bits to the NW (base station). The NW inputs the received bits into the AI / ML model and obtains the CSI, including the CQI. In Figure 6, the pre-processing and post-processing of the AI / ML model are omitted, but pre-processing and post-processing may be performed as in Figure 3.

[0107] [Option 2] The UE may report both CQI (CQI without applying the AI / ML model) and bits generated through the AI / ML model. This allows for the reuse of existing specifications regarding CQI and reduces the impact on the specifications.

[0108] <Third Embodiment> The UE may normalize the absolute values ​​of the CSI components (e.g., channel matrix) and report the normalization factor (e.g., amplitude) to the base station (gNB). The UE may generate CSI feedback information including the normalization factor using an AI / ML model. This also compresses the normalization factor, thus reducing the amount of data transmitted. The UE may report the normalization factor in the manner described above (reporting information). The normalization factor may be specified in the specifications. Alternatively, the UE may set / instruct the normalization factor via the NW in the manner described above (receiving information).

[0109] <Supplement> At least one of the embodiments described above may apply only to a UE that has reported or supports a particular UE capability.

[0110] The particular UE capability may indicate that it supports specific processing / operation / control / information for at least one of the embodiments described above.

[0111] Furthermore, the above-mentioned specific UE capabilities may be capabilities that apply across all frequencies (commonly regardless of frequency), capabilities per frequency (e.g., cell, band, BWP), capabilities per frequency range (e.g., Frequency Range 1 (FR1), FR2, FR3, FR4, FR5, FR2-1, FR2-2), capabilities per subcarrier spacing (SCS), or capabilities per feature set (FS) or feature set per component-carrier (FSPC).

[0112] Furthermore, the specific UE capabilities described above may be capabilities that apply across all duplexing schemes (common to all duplexing schemes), or they may be capabilities specific to each duplexing scheme (e.g., Time Division Duplex (TDD), Frequency Division Duplex (FDD)).

[0113] Furthermore, at least one of the embodiments described above may apply when the UE is configured with specific information related to the embodiments described above through upper-layer signaling.

[0114] If the UE does not support at least one of the above-mentioned specific UE capabilities or does not have the above-mentioned specific information configured, the behavior of, for example, Rel.15 / 16 may be applied.

[0115] (Note) The following invention is added with respect to one embodiment of this disclosure. [Note 1] A transmission unit that transmits information obtained by compressing channel state information (CSI) using an Artificial Intelligence (AI) / Machine Learning (ML) model, A control unit that assumes a specific precoding matrix is ​​applied to physical downlink shared channel (PDSCH) transmissions for the calculation of channel quality indicators (CQI), A terminal. [Note 2] The aforementioned specific precoding matrix is ​​a precoding matrix calculated based on the AI / ML model output at the base station, a precoding matrix derived based on the CSI calculated based on terminal measurements, or a precoding matrix derived based on the expected output for the AI / ML model at the base station. The terminals listed in Appendix 1. [Note 3] The aforementioned specific precoding matrix is ​​a precoding matrix calculated based on a channel matrix derived from the output of the AI / ML model at the base station, a precoding matrix calculated based on a channel matrix derived from the CSI calculated from the measurement of the UE, or a precoding matrix calculated from a channel matrix derived from the expected output for the AI / ML model at the base station. The terminals listed in Appendix 1. [Note 4] The transmitting unit transmits information obtained by compressing CQI or information related to CQI using the AI / ML model. The terminals listed in any of the appendices 1 through 3.

[0116] (Wireless communication system) The configuration of a wireless communication system according to one embodiment of this disclosure will be described below. In this wireless communication system, communication is performed using any or a combination thereof of the wireless communication methods according to the above embodiments of this disclosure.

[0117] Figure 7 shows an example of a schematic configuration of a wireless communication system according to one embodiment. The wireless communication system 1 (which may also be simply called system 1) may be a system that implements communication using Long Term Evolution (LTE), 5th generation mobile communication system New Radio (5G NR), etc., as specified by the Third Generation Partnership Project (3GPP).

[0118] Furthermore, the wireless communication system 1 may support dual connectivity between multiple Radio Access Technologies (RATs) (Multi-RAT Dual Connectivity (MR-DC)). MR-DC may include dual connectivity between LTE (Evolved Universal Terrestrial Radio Access (E-UTRA)) and NR (E-UTRA-NR Dual Connectivity (EN-DC)), dual connectivity between NR and LTE (NR-E-UTRA Dual Connectivity (NE-DC)), and so on.

[0119] In EN-DC, the LTE (E-UTRA) base station (eNB) is the Master Node (MN), and the NR base station (gNB) is the Secondary Node (SN). In NE-DC, the NR base station (gNB) is the MN, and the LTE (E-UTRA) base station (eNB) is the SN.

[0120] The wireless communication system 1 may support dual connectivity between multiple base stations within the same RAT (for example, dual connectivity where both MN and SN are NR base stations (gNB) (NR-NR Dual Connectivity (NN-DC))).

[0121] The wireless communication system 1 may include a base station 11 that forms a macrocell C1 with relatively wide coverage, and base stations 12 (12a-12c) located within the macrocell C1 that form a small cell C2 that is narrower than the macrocell C1. User terminals 20 may be located within at least one cell. The arrangement and number of each cell and user terminal 20 are not limited to the configuration shown in the figure. Hereinafter, when base stations 11 and 12 are not distinguished, they will be collectively referred to as base station 10.

[0122] The user terminal 20 may be connected to at least one of the multiple base stations 10. The user terminal 20 may utilize at least one of Carrier Aggregation (CA) using multiple Component Carriers (CC) and Dual Connectivity (DC).

[0123] Each CC may be included in at least one of the first frequency band (Frequency Range 1 (FR1)) and the second frequency band (Frequency Range 2 (FR2)). A macrocell C1 may be included in FR1, and a small cell C2 may be included in FR2. For example, FR1 may be a frequency band of 6 GHz or less (sub-6 GHz), and FR2 may be a frequency band above 24 GHz (above-24 GHz). Note that the frequency bands and definitions of FR1 and FR2 are not limited to these, and for example, FR1 may fall in a frequency band higher than FR2.

[0124] Furthermore, the user terminal 20 may communicate using at least one of the following methods at each CC: Time Division Duplex (TDD) and Frequency Division Duplex (FDD).

[0125] Multiple base stations 10 may be connected by wire (e.g., optical fiber compliant with Common Public Radio Interface (CPRI), X2 interface, etc.) or wireless (e.g., NR communication). For example, if NR communication is used as a backhaul between base stations 11 and 12, base station 11, which is the upstream station, may be called an Integrated Access Backhaul (IAB) donor, and base station 12, which is the relay station, may be called an IAB node.

[0126] Base station 10 may be connected to the core network 30 via other base stations 10 or directly. The core network 30 may include at least one of the following: Evolved Packet Core (EPC), 5G Core Network (5GCN), Next Generation Core (NGC), etc.

[0127] The core network 30 may include network functions (NF) such as User Plane Function (UPF), Access and Mobility Management Function (AMF), Session Management Function (SMF), Unified Data Management (UDM), Application Function (AF), Data Network (DN), Location Management Function (LMF), and Operation, Administration and Maintenance (Management) (OAM). Multiple functions may be provided by a single network node. Furthermore, communication with an external network (e.g., the Internet) may occur via the DN.

[0128] The user terminal 20 may be a terminal that supports at least one of the following communication methods: LTE, LTE-A, 5G, etc.

[0129] In the wireless communication system 1, an orthogonal frequency division multiplexing (OFDM)-based wireless access scheme may be used. For example, Cyclic Prefix OFDM (CP-OFDM), Discrete Fourier Transform Spread OFDM (DFT-s-OFDM), Orthogonal Frequency Division Multiple Access (OFDMA), Single Carrier Frequency Division Multiple Access (SC-FDMA), etc., may be used in at least one of the downlink (DL) and uplink (UL).

[0130] The wireless access method may also be called a waveform. In wireless communication system 1, other wireless access methods (for example, other single-carrier transmission methods, other multi-carrier transmission methods) may be used for the UL and DL wireless access methods.

[0131] In the wireless communication system 1, a Physical Downlink Shared Channel (PDSCH), a Broadcast Channel (PBCH), or a Physical Downlink Control Channel (PDCCH) may be used as the downlink channel, shared by each user terminal 20.

[0132] Furthermore, in the wireless communication system 1, the uplink channel may include a Physical Uplink Shared Channel (PUSCH), a Physical Uplink Control Channel (PUCCH), a Physical Random Access Channel (PRACH), or the like, all of which are shared by each user terminal 20.

[0133] User data, higher-layer control information, and System Information Blocks (SIBs) are transmitted via PDSCH. User data and higher-layer control information may also be transmitted via PUSCH. Furthermore, Master Information Blocks (MIBs) may be transmitted via PBCH.

[0134] Lower-layer control information may be transmitted by PDCCH. The lower-layer control information may include, for example, Downlink Control Information (DCI) which includes scheduling information for at least one of PDSCH and PUSCH.

[0135] Furthermore, the DCI that schedules PDSCH may be called a DL assignment or DL ​​DCI, and the DCI that schedules PUSCH may be called a UL grant or UL DCI. Furthermore, PDSCH may be interpreted as DL data, and PUSCH may be interpreted as UL data.

[0136] PDCCH detection may utilize a Control Resource Set (CORESET) and a search space. A CORESET corresponds to the resources used to search for DCIs. A search space corresponds to the search area and search method for PDCCH candidates. A single CORESET may be associated with one or more search spaces. The UE may monitor CORESETs associated with a particular search space based on the search space configuration.

[0137] A single search space may correspond to one or more PDCCH candidates corresponding to aggregation levels. One or more search spaces may be referred to as a search space set. In this disclosure, "search space," "search space set," "search space configuration," "search space set configuration," "CORESET," and "CORESET configuration" may be interpreted interchangeably.

[0138] PUCCH may transmit uplink control information (UCI) which includes at least one of the following: channel state information (CSI), delivery acknowledgment (e.g., Hybrid Automatic Repeat reQuest ACKnowledgement (HARQ-ACK), ACK / NACK, etc.), and scheduling request (SR). PRACH may transmit a random access preamble for establishing a connection with the cell.

[0139] In this disclosure, downlinks, uplinks, etc., may be expressed without the prefix "link." Also, the prefix "physical" may be omitted when describing various channels.

[0140] In the wireless communication system 1, a synchronization signal (SS), a downlink reference signal (DL-RS), etc., may be transmitted. In the wireless communication system 1, as DL-RS, a cell-specific reference signal (CRS), a channel state information reference signal (CSI-RS), a demodulation reference signal (DMRS), a positioning reference signal (PRS), a phase tracking reference signal (PTRS), etc., may be transmitted.

[0141] The synchronization signal may be, for example, at least one of a Primary Synchronization Signal (PSS) and a Secondary Synchronization Signal (SSS). A signal block including SS (PSS, SSS) and PBCH (and DMRS for PBCH) may be called an SS / PBCH block, SS Block (SSB), etc. SS, SSB, etc., may also be called reference signals.

[0142] Furthermore, in the wireless communication system 1, the Uplink Reference Signal (UL-RS) may transmit the Sounding Reference Signal (SRS), Demodulation Reference Signal (DMRS), etc. The DMRS may also be called the User-Specific Reference Signal (UE-specific Reference Signal).

[0143] (base station) Figure 8 shows an example of the configuration of a base station according to one embodiment. The base station 10 includes a control unit 110, a transceiver unit 120, a transceiver antenna 130, and a transmission line interface 140. Note that one or more of the control unit 110, transceiver unit 120, transceiver antenna 130, and transmission line interface 140 may be provided.

[0144] In this example, the functional blocks of the characteristic parts of this embodiment are mainly shown, and it may be assumed that the base station 10 also has other functional blocks necessary for wireless communication. Some of the processing of each part described below may be omitted.

[0145] The control unit 110 controls the entire base station 10. The control unit 110 can be composed of a controller, control circuit, etc., as described based on common understanding in the art relating to this disclosure.

[0146] The control unit 110 may control signal generation, scheduling (e.g., resource allocation, mapping), etc. The control unit 110 may also control transmission and reception, measurement, etc., using the transceiver unit 120, the transceiver antenna 130, and the transmission path interface 140. The control unit 110 may generate data to be transmitted as signals, control information, sequences, etc., and transfer them to the transceiver unit 120. The control unit 110 may also perform call processing of communication channels (setting, releasing, etc.), status management of the base station 10, management of radio resources, etc.

[0147] The transmitting / receiving unit 120 may include a baseband unit 121, a radio frequency (RF) unit 122, and a measurement unit 123. The baseband unit 121 may include a transmission processing unit 1211 and a reception processing unit 1212. The transmitting / receiving unit 120 can be composed of a transmitter / receiver, RF circuit, baseband circuit, filter, phase shifter, measurement circuit, transmitting / receiving circuit, etc., as described based on common understanding in the art relating to this disclosure.

[0148] The transmitting / receiving unit 120 may be configured as an integrated transmitting / receiving unit, or it may be composed of a transmitting unit and a receiving unit. The transmitting unit may consist of a transmitting processing unit 1211 and an RF unit 122. The receiving unit may consist of a receiving processing unit 1212, an RF unit 122 and a measuring unit 123.

[0149] The transmitting and receiving antenna 130 can be composed of an antenna described based on common understanding in the art relating to this disclosure, such as an array antenna.

[0150] The transmitting / receiving unit 120 may transmit the downlink channel, synchronization signal, downlink reference signal, etc. The transmitting / receiving unit 120 may also receive the uplink channel, uplink reference signal, etc.

[0151] The transmitting / receiving unit 120 may form at least one of the transmitting beam and the receiving beam using digital beamforming (e.g., precoding), analog beamforming (e.g., phase rotation), or the like.

[0152] The transmitting / receiving unit 120 (transmission processing unit 1211) may perform processing on data and control information acquired from the control unit 110, for example, at the Packet Data Convergence Protocol (PDCP) layer, the Radio Link Control (RLC) layer (e.g., RLC retransmission control), the Medium Access Control (MAC) layer (e.g., HARQ retransmission control), etc., to generate a bit sequence to be transmitted.

[0153] The transmitting / receiving unit 120 (transmission processing unit 1211) may perform transmission processing on the bit sequence to be transmitted, such as channel coding (which may include error correction coding), modulation, mapping, filtering, discrete Fourier transform (DFT) processing (if necessary), inverse fast Fourier transform (IFFT) processing, precoding, and digital-to-analog conversion, and output a baseband signal.

[0154] The transmitting / receiving unit 120 (RF unit 122) may perform modulation, filtering, amplification, etc., of the baseband signal to the radio frequency band and transmit the signal in the radio frequency band via the transmitting / receiving antenna 130.

[0155] On the other hand, the transmitting / receiving unit 120 (RF unit 122) may perform amplification, filtering, demodulation to a baseband signal, etc., on the radio frequency band signal received by the transmitting / receiving antenna 130.

[0156] The transmitting / receiving unit 120 (receiving processing unit 1212) may apply reception processing to the acquired baseband signal, such as analog-to-digital conversion, Fast Fourier Transform (FFT) processing, Inverse Discrete Fourier Transform (IDFT) processing (if necessary), filtering, demapping, demodulation, decoding (may include error correction decoding), MAC layer processing, RLC layer processing, and PDCP layer processing, to acquire user data, etc.

[0157] The transmitting / receiving unit 120 (measurement unit 123) may perform measurements related to the received signal. For example, the measurement unit 123 may perform Radio Resource Management (RRM) measurements, Channel State Information (CSI) measurements, etc., based on the received signal. The measurement unit 123 may also measure received power (e.g., Reference Signal Received Power (RSRP)), reception quality (e.g., Reference Signal Received Quality (RSRQ), Signal to Interference plus Noise Ratio (SINR), Signal to Noise Ratio (SNR)), signal strength (e.g., Received Signal Strength Indicator (RSSI)), propagation path information (e.g., CSI), etc. The measurement results may be output to the control unit 110.

[0158] The transmission path interface 140 may send and receive signals (backhaul signaling) with devices included in the core network 30 (e.g., network nodes providing NF), other base stations 10, etc., and may acquire and transmit user data (user plane data), control plane data, etc. for the user terminal 20.

[0159] In this disclosure, the transmitting and receiving units of the base station 10 may consist of at least one of a transmitting / receiving unit 120, a transmitting / receiving antenna 130, and a transmission path interface 140.

[0160] The transmitting / receiving unit 120 may receive information obtained by compressing channel state information (CSI) using an Artificial Intelligence (AI) / Machine Learning (ML) model.

[0161] The control unit 110 may apply a specific precoding matrix to the physical downlink shared channel (PDSCH) transmission for the calculation of the channel quality indicator (CQI).

[0162] (User terminal) Figure 9 shows an example of the configuration of a user terminal according to one embodiment. The user terminal 20 includes a control unit 210, a transmitting / receiving unit 220, and a transmitting / receiving antenna 230. Note that one or more of the control unit 210, the transmitting / receiving unit 220, and the transmitting / receiving antenna 230 may be provided.

[0163] In this example, the functional blocks of the characteristic parts of this embodiment are mainly shown, and it may be assumed that the user terminal 20 also has other functional blocks necessary for wireless communication. Some of the processing of each part described below may be omitted.

[0164] The control unit 210 controls the entire user terminal 20. The control unit 210 can be composed of a controller, control circuit, etc., as described based on common understanding in the technical field related to this disclosure.

[0165] The control unit 210 may control signal generation, mapping, etc. The control unit 210 may also control transmission and reception, measurement, etc., using the transmitting / receiving unit 220 and the transmitting / receiving antenna 230. The control unit 210 may generate data to be transmitted as signals, control information, sequences, etc., and transfer them to the transmitting / receiving unit 220.

[0166] The transmitting / receiving unit 220 may include a baseband unit 221, an RF unit 222, and a measurement unit 223. The baseband unit 221 may include a transmission processing unit 2211 and a reception processing unit 2212. The transmitting / receiving unit 220 can be composed of a transmitter / receiver, RF circuit, baseband circuit, filter, phase shifter, measurement circuit, transmitting / receiving circuit, etc., as described based on common understanding in the art relating to this disclosure.

[0167] The transmitting / receiving unit 220 may be configured as an integrated transmitting / receiving unit, or it may be composed of a transmitting unit and a receiving unit. The transmitting unit may consist of a transmitting processing unit 2211 and an RF unit 222. The receiving unit may consist of a receiving processing unit 2212, an RF unit 222 and a measuring unit 223.

[0168] The transmitting and receiving antenna 230 can be composed of an antenna described based on common understanding in the art relating to this disclosure, such as an array antenna.

[0169] The transmitting / receiving unit 220 may receive the downlink channel, synchronization signal, downlink reference signal, etc. The transmitting / receiving unit 220 may also transmit the uplink channel, uplink reference signal, etc.

[0170] The transmitting / receiving unit 220 may form at least one of the transmitting beam and the receiving beam using digital beamforming (e.g., precoding), analog beamforming (e.g., phase rotation), or the like.

[0171] The transmitting / receiving unit 220 (transmission processing unit 2211) may perform PDCP layer processing, RLC layer processing (e.g., RLC retransmission control), MAC layer processing (e.g., HARQ retransmission control), etc., on data and control information acquired from the control unit 210, etc., to generate a bit sequence to be transmitted.

[0172] The transmitting / receiving unit 220 (transmission processing unit 2211) may perform transmission processing on the bit sequence to be transmitted, such as channel coding (which may include error correction coding), modulation, mapping, filtering, DFT processing (if necessary), IFFT processing, precoding, and digital-to-analog conversion, and output a baseband signal.

[0173] Whether or not to apply DFT processing may be based on the transform precoding settings. The transmitting / receiving unit 220 (transmission processing unit 2211) may perform DFT processing as part of the transmission process to transmit a channel (for example, PUSCH) using a DFT-s-OFDM waveform if transform precoding is enabled for that channel, or it may not perform DFT processing as part of the transmission process if transform precoding is not enabled for that channel.

[0174] The transmitting / receiving unit 220 (RF unit 222) may perform modulation, filtering, amplification, etc., of the baseband signal to the radio frequency band and transmit the signal in the radio frequency band via the transmitting / receiving antenna 230.

[0175] On the other hand, the transmitting / receiving unit 220 (RF unit 222) may perform amplification, filtering, demodulation to a baseband signal, etc., on the radio frequency band signal received by the transmitting / receiving antenna 230.

[0176] The transmitting / receiving unit 220 (receiving processing unit 2212) may apply reception processing such as analog-to-digital conversion, FFT processing, IDFT processing (if necessary), filtering, demapping, demodulation, decoding (may include error correction decoding), MAC layer processing, RLC layer processing, and PDCP layer processing to the acquired baseband signal to acquire user data, etc.

[0177] The transmitting / receiving unit 220 (measuring unit 223) may perform measurements related to the received signal. For example, the measuring unit 223 may perform RRM measurement, CSI measurement, etc., based on the received signal. The measuring unit 223 may also measure received power (e.g., RSRP), received quality (e.g., RSRQ, SINR, SNR), signal strength (e.g., RSSI), propagation path information (e.g., CSI), etc. The measurement results may be output to the control unit 210.

[0178] In this disclosure, the transmitting and receiving units of the user terminal 20 may consist of at least one of a transmitting / receiving unit 220 and a transmitting / receiving antenna 230.

[0179] The transmitting / receiving unit 220 may transmit information obtained by compressing channel state information (CSI) using an Artificial Intelligence (AI) / Machine Learning (ML) model.

[0180] The control unit 210 may assume that a specific precoding matrix is ​​applied to the physical downlink shared channel (PDSCH) transmission for the purpose of calculating the channel quality indicator (CQI).

[0181] The aforementioned specific precoding matrix may be a precoding matrix calculated based on the AI / ML model output at the base station, a precoding matrix derived based on the CSI calculated based on terminal measurements, or a precoding matrix derived based on the expected output for the AI / ML model at the base station.

[0182] The aforementioned specific precoding matrix may be a precoding matrix calculated based on a channel matrix derived from the output of the AI / ML model at the base station, a precoding matrix calculated based on a channel matrix derived from the CSI calculated from the measurement of the UE, or a precoding matrix calculated from a channel matrix derived from the expected output for the AI / ML model at the base station.

[0183] The transmitting / receiving unit 220 may transmit information obtained by compressing CQI or information related to CQI using the AI / ML model.

[0184] (Hardware configuration) The block diagrams used in the description of the above embodiments show functional units. These functional blocks (components) are realized by any combination of at least one of hardware and software. Furthermore, the method of realizing each functional block is not particularly limited. That is, each functional block may be realized using one device that is physically or logically coupled, or it may be realized using two or more physically or logically separated devices that are directly or indirectly connected (for example, using wired or wireless connections). A functional block may also be realized by combining the above one device or the above multiple devices with software.

[0185] Here, functions include, but are not limited to, judgment, decision, determination, calculation, calculation, processing, derivation, investigation, search, confirmation, reception, transmission, output, access, resolution, selection, selection, establishment, comparison, assumption, expectation, consideration, broadcasting, notifying, communicating, forwarding, configuring, reconfiguring, allocating (mapping), and assigning. For example, a functional block (configuration part) that enables transmission may be called a transmitting unit or transmitter. In all cases, as mentioned above, the method of implementation is not particularly limited.

[0186] For example, a base station, user terminal, etc. in one embodiment of the present disclosure may function as a computer that processes the wireless communication method of the present disclosure. Figure 10 is a diagram showing an example of the hardware configuration of a base station and user terminal according to one embodiment. The base station 10 and user terminal 20 described above may be physically configured as a computer device including a processor 1001, memory 1002, storage 1003, communication device 1004, input device 1005, output device 1006, bus 1007, etc.

[0187] In this disclosure, terms such as apparatus, circuit, device, section, and unit are interchangeable. The hardware configuration of the base station 10 and the user terminal 20 may include one or more of the devices shown in the figure, or it may be configured to omit some of the devices.

[0188] For example, although only one processor 1001 is shown in the diagram, there may be multiple processors. Furthermore, processing may be performed by one processor, or by two or more processors simultaneously, sequentially, or by other means. Note that processor 1001 may be implemented using one or more chips.

[0189] Each function in the base station 10 and the user terminal 20 is realized, for example, by loading predetermined software (programs) onto hardware such as the processor 1001 and memory 1002, which allows the processor 1001 to perform calculations and control communication via the communication device 1004, or to control at least one of the reading and writing of data in the memory 1002 and storage 1003.

[0190] The processor 1001 controls the entire computer, for example, by running an operating system. The processor 1001 may be composed of a central processing unit (CPU) that includes interfaces with peripheral devices, control units, arithmetic units, registers, etc. For example, at least a part of the control unit 110 (210) and the transmitting / receiving unit 120 (220) described above may be implemented by the processor 1001.

[0191] Furthermore, the processor 1001 reads programs (program code), software modules, data, etc., from at least one of the storage 1003 and the communication device 1004 into the memory 1002 and executes various processes accordingly. The program used is one that causes the computer to execute at least a part of the operations described in the above embodiment. For example, the control unit 110 (210) may be implemented by a control program stored in the memory 1002 and running on the processor 1001, and other functional blocks may be implemented similarly.

[0192] Memory 1002 is a computer-readable recording medium and may consist of at least one of the following: Read Only Memory (ROM), Erasable Programmable ROM (EPROM), Electrically EPROM (EEPROM), Random Access Memory (RAM), or other suitable storage medium. Memory 1002 may also be called a register, cache, or main memory. Memory 1002 can store executable programs (program code), software modules, etc., for carrying out a wireless communication method according to one embodiment of this disclosure.

[0193] Storage 1003 is a computer-readable recording medium and may consist of at least one of the following: a flexible disk, a floppy disk, a magneto-optical disk (e.g., a compact disk (Compact Disc ROM (CD-ROM)), a digital multipurpose disk, a Blu-ray disk), a removable disk, a hard disk drive, a smart card, a flash memory device (e.g., a card, stick, key drive), a magnetic stripe, a database, a server, or other suitable storage medium. Storage 1003 may also be called an auxiliary storage device.

[0194] The communication device 1004 is hardware (transmitting / receiving device) for communicating between computers via at least one of a wired network and a wireless network, and is also referred to as a network device, network controller, network card, communication module, etc. The communication device 1004 may be configured to include, for example, a high-frequency switch, duplexer, filter, frequency synthesizer, etc., in order to implement at least one of frequency division duplex (FDD) and time division duplex (TDD). For example, the above-mentioned transmitting / receiving unit 120 (220), transmitting / receiving antenna 130 (230), etc., may be implemented by the communication device 1004. The transmitting / receiving unit 120 (220) may be implemented with physically or logically separated implementations of a transmitting unit 120a (220a) and a receiving unit 120b (220b).

[0195] The input device 1005 is an input device that accepts input from an external source (e.g., a keyboard, mouse, microphone, switch, button, sensor, etc.). The output device 1006 is an output device that outputs to an external source (e.g., a display, speaker, light-emitting diode (LED) lamp, etc.). The input device 1005 and the output device 1006 may be configured as an integrated unit (e.g., a touch panel).

[0196] Furthermore, each device, such as the processor 1001 and memory 1002, is connected by a bus 1007 for communicating information. The bus 1007 may be configured using a single bus, or different buses may be configured for each device.

[0197] Furthermore, the base station 10 and the user terminal 20 may be configured to include hardware such as a microprocessor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a programmable logic device (PLD), and a field programmable gate array (FPGA), and some or all of each functional block may be implemented using such hardware. For example, the processor 1001 may be implemented using at least one of these hardware components.

[0198] (modified version) In addition, terms used in this disclosure and terms necessary for understanding this disclosure may be replaced with terms having the same or similar meanings. For example, channel, symbol, and signal (signal or signaling) may be used interchangeably. Also, a signal may be a message. A reference signal may be abbreviated as RS and may be called a pilot, pilot signal, etc., depending on the applicable standard. Also, a component carrier (CC) may be called a cell, frequency carrier, carrier frequency, etc.

[0199] A wireless frame may consist of one or more periods (frames) in the time domain. Each of these periods (frames) constituting a wireless frame may be called a subframe. Furthermore, a subframe may consist of one or more slots in the time domain. A subframe may have a fixed time length (e.g., 1 ms) that is independent of numerology.

[0200] Here, the neuralelogy may be communication parameters applied to at least one of the transmission and reception of a signal or channel. The neuralelogy may be, for example, at least one of the following: subcarrier spacing (SCS), bandwidth, symbol length, cyclic prefix length, transmission time interval (TTI), number of symbols per TTI, radio frame configuration, specific filtering processes performed by the transceiver in the frequency domain, or specific windowing processes performed by the transceiver in the time domain.

[0201] A slot may consist of one or more symbols in the time domain (such as Orthogonal Frequency Division Multiplexing (OFDM) symbols or Single Carrier Frequency Division Multiple Access (SC-FDMA) symbols). Alternatively, a slot may be a time unit based on neurology.

[0202] A slot may include multiple mini-slots. Each mini-slot may consist of one or more symbols in the time domain. Mini-slots may also be called sub-slots. Mini-slots may consist of fewer symbols than a slot. A PDSCH (or PUSCH) transmitted in a time unit larger than a mini-slot may be called a PDSCH (PUSCH) mapping type A. A PDSCH (or PUSCH) transmitted using a mini-slot may be called a PDSCH (PUSCH) mapping type B.

[0203] Wireless frames, subframes, slots, minislots, and symbols all represent units of time when transmitting a signal. Wireless frames, subframes, slots, minislots, and symbols may each be referred to by different names. Furthermore, the units of time such as frames, subframes, slots, minislots, and symbols in this disclosure may be interpreted as interchangeable.

[0204] For example, one subframe may be called TTI, multiple consecutive subframes may be called TTI, or one slot or one mini-slot may be called TTI. In other words, at least one of the subframe and TTI may be a subframe (1ms) in existing LTE, a period shorter than 1ms (e.g., 1-13 symbols), or a period longer than 1ms. Note that the unit representing TTI may be called a slot, mini-slot, etc., instead of a subframe.

[0205] Here, TTI refers to, for example, the smallest unit of time for scheduling in wireless communication. For example, in an LTE system, the base station schedules each user terminal to allocate wireless resources (such as the frequency bandwidth and transmission power available to each user terminal) in TTI units. However, the definition of TTI is not limited to this.

[0206] TTI may be a transmission time unit for channel-encoded data packets (transport blocks), code blocks, code words, etc., or it may be a processing unit for scheduling, link adaptation, etc. Given a TTI, the actual time interval (e.g., number of symbols) to which the transport block, code block, code word, etc. are mapped may be shorter than the given TTI.

[0207] Furthermore, if one slot or one mini-slot is referred to as TTI, then one or more TTIs (i.e., one or more slots or one or more mini-slots) may constitute the minimum time unit of scheduling. In addition, the number of slots (number of mini-slots) that constitute the minimum time unit of scheduling may be controlled.

[0208] A TTI with a time length of 1 ms may also be called a normal TTI (TTI in 3GPP Rel.8-12), a long TTI, a normal subframe, a long subframe, or a slot. A TTI shorter than a normal TTI may also be called a shortened TTI, a short TTI, a partial or fractional TTI, a shortened subframe, a short subframe, a mini slot, a sub slot, or a slot.

[0209] Furthermore, long TTIs (e.g., normal TTIs, subframes, etc.) may be interpreted as TTIs with a time length exceeding 1 ms, and short TTIs (e.g., shortened TTIs, etc.) may be interpreted as TTIs with a TTI length less than that of a long TTI but 1 ms or more.

[0210] A Resource Block (RB) is a resource allocation unit in the time domain and frequency domain, and in the frequency domain, it may contain one or more consecutive subcarriers. The number of subcarriers in an RB may be the same regardless of the neurology, for example, 12. The number of subcarriers in an RB may be determined based on the neurology.

[0211] Furthermore, an RB may contain one or more symbols in the time domain and may have the length of one slot, one minislot, one subframe, or one TTI. Each TTI, subframe, etc., may consist of one or more resource blocks.

[0212] One or more RBs may also be called Physical RBs (PRBs), Sub-Carrier Groups (SCGs), Resource Element Groups (REGs), PRB pairs, RB pairs, etc.

[0213] Furthermore, a resource block may consist of one or more resource elements (REs). For example, one RE may be a radio resource area comprising one subcarrier and one symbol.

[0214] A Bandwidth Part (BWP) (also called a partial bandwidth) may represent a subset of consecutive common resource blocks (RBs) for a given neurology in a given carrier. Here, the common RBs may be identified by an index of the RBs relative to the carrier's common reference point. PRBs may be defined and numbered within a BWP.

[0215] A BWP may include UL BWPs (BWPs for UL) and DL BWPs (BWPs for DL). One or more BWPs may be configured within a single carrier for a UE.

[0216] At least one of the configured BWPs may be active, and the UE does not need to assume that it will send or receive a given signal / channel outside of the active BWP. In this disclosure, terms such as "cell" and "carrier" may be read as "BWP".

[0217] The structures described above, such as wireless frames, subframes, slots, minislots, and symbols, are merely illustrative examples. For instance, the number of subframes included in a wireless frame, the number of slots per subframe or wireless frame, the number of minislots within a slot, the number of symbols and RBs included in a slot or minislot, the number of subcarriers included in an RB, and the number of symbols, symbol length, and cyclic prefix (CP) length within a TTI can be varied in various ways.

[0218] Furthermore, the information, parameters, etc., described in this disclosure may be expressed using absolute values, relative values ​​from a predetermined value, or corresponding other information. For example, wireless resources may be indicated by a predetermined index.

[0219] The names used for parameters and other elements in this disclosure are not restrictive in any way. Furthermore, mathematical formulas and other elements that use these parameters may differ from those expressly disclosed in this disclosure. Various channels (PUCCH, PDCCH, etc.) and information elements can be identified by any suitable name, and therefore, the various names assigned to these various channels and information elements are not restrictive in any way.

[0220] The information, signals, etc. described in this disclosure may be represented using any of the various different techniques. For example, the data, instructions, commands, information, signals, bits, symbols, chips, etc. that may be referred to throughout the above description may be represented by voltage, current, electromagnetic waves, magnetic fields or magnetic particles, optical fields or photons, or any combination thereof.

[0221] Furthermore, information, signals, etc., can be output from upper layers to lower layers and from lower layers to upper layers, or to at least one of the two. Information, signals, etc., may also be input and output via multiple network nodes.

[0222] Input and output information and signals may be stored in a specific location (e.g., memory) or managed using a management table. Input and output information and signals may be overwritten, updated, or appended to. Output information and signals may be deleted. Input information and signals may be transmitted to other devices.

[0223] Information notification is not limited to the embodiments described herein and may be carried out by other means. For example, information notification in this disclosure may be carried out by physical layer signaling (e.g., Downlink Control Information (DCI), Uplink Control Information (UCI)), higher layer signaling (e.g., Radio Resource Control (RRC) signaling, broadcast information (Master Information Block (MIB), System Information Block (SIB)), Medium Access Control (MAC) signaling), other signals, or a combination thereof).

[0224] Physical layer signaling may also be called Layer 1 / Layer 2 (L1 / L2) control information (L1 / L2 control signals), L1 control information (L1 control signals), etc. RRC signaling may also be called RRC messages, for example, RRC Connection Setup messages, RRC Connection Reconfiguration messages, etc. MAC signaling may also be communicated using, for example, MAC Control Element (CE).

[0225] Furthermore, notification of the specified information (for example, notification that "X is the case") is not limited to explicit notification, but may also be made implicitly (for example, by not notifying the specified information or by notifying other information).

[0226] The determination may be made by a value represented by 1 bit (0 or 1), by a boolean value represented as true or false, or by a numerical comparison (for example, a comparison with a predetermined value).

[0227] Software should be broadly interpreted to mean instructions, instruction sets, code, code segments, program code, programs, subprograms, software modules, applications, software applications, software packages, routines, subroutines, objects, executable files, execution threads, procedures, functions, and so on, whether they are called software, firmware, middleware, microcode, hardware description languages, or by any other name.

[0228] Furthermore, software, instructions, information, etc., may be transmitted and received via a transmission medium. For example, if software is transmitted from a website, server, or other remote source using at least one of wired technology (such as coaxial cable, fiber optic cable, twisted pair, or Digital Subscriber Line (DSL)) and wireless technology (such as infrared or microwave), then at least one of these wired and wireless technologies is included in the definition of a transmission medium.

[0229] The terms “system” and “network” as used in this disclosure may be used interchangeably. “Network” may also mean the equipment included in the network (e.g., base stations).

[0230] In this disclosure, terms such as "precoding," "precoder," "weight (precoding weight)," "quasi-co-location (QCL)," "transmission configuration indication state (TCI state)," "spatial relation," "spatial domain filter," "transmit power," "phase rotation," "antenna port," "antenna port group," "layer," "number of layers," "rank," "resource," "resource set," "resource group," "beam," "beam width," "beam angle," "antenna," "antenna element," and "panel" may be used interchangeably.

[0231] In this disclosure, terms such as "Base Station (BS)", "wireless base station", "fixed station", "NodeB", "eNB (eNodeB)", "gNB (gNodeB)", "access point", "Transmission Point (TP)", "Reception Point (RP)", "Transmission / Reception Point (TRP)", "panel", "cell", "sector", "cell group", "carrier", and "component carrier" may be used interchangeably. Base stations may also be referred to by terms such as macrocell, small cell, femtocell, and picocell.

[0232] A base station can house one or more (e.g., three) cells. If a base station houses multiple cells, the entire coverage area of ​​the base station can be divided into several smaller areas, each of which may also be provided with communication services by a base station subsystem (e.g., a small indoor base station (Remote Radio Head (RRH))). The terms “cell” or “sector” refer to part or all of the coverage area of ​​at least one of the base station and / or base station subsystems that provide communication services in that coverage.

[0233] In this disclosure, the transmission of information by a base station to a terminal may be interpreted as the base station instructing the terminal to perform a control / operation based on said information.

[0234] In this disclosure, terms such as "Mobile Station (MS)," "user terminal," "User Equipment (UE)," and "terminal" may be used interchangeably.

[0235] A mobile station may also be called a subscriber station, mobile unit, subscriber unit, wireless unit, remote unit, mobile device, wireless device, wireless communication device, remote device, mobile subscriber station, access terminal, mobile terminal, wireless terminal, remote terminal, handset, user agent, mobile client, client, or some other appropriate term.

[0236] At least one of the base station and the mobile station may be called a transmitting device, a receiving device, a wireless communication device, etc. At least one of the base station and the mobile station may also be a device mounted on a moving object, the moving object itself, etc.

[0237] The term "mobile object" refers to any movable object, regardless of its speed, and naturally includes cases where the mobile object is stationary. Examples of such mobile objects include, but are not limited to, vehicles, transport vehicles, automobiles, motorcycles, bicycles, connected cars, excavators, bulldozers, wheel loaders, dump trucks, forklifts, trains, buses, handcarts, rickshaws, ships and other watercraft, airplanes, rockets, satellites, drones, multicopters, quadcopters, balloons, and items carried on them. Furthermore, such mobile objects may be autonomously driven objects operating based on operational commands.

[0238] The mobile entity may be a vehicle (e.g., a car, an airplane), an unmanned mobile entity (e.g., a drone, an autonomous vehicle), or a robot (manned or unmanned). At least one of the base station and the mobile station may be a device that does not necessarily move during communication operations. For example, at least one of the base station and the mobile station may be an Internet of Things (IoT) device such as a sensor.

[0239] Figure 11 shows an example of a vehicle according to one embodiment. The vehicle 40 includes a drive unit 41, a steering unit 42, an accelerator pedal 43, a brake pedal 44, a shift lever 45, left and right front wheels 46, left and right rear wheels 47, an axle 48, an electronic control unit 49, various sensors (including a current sensor 50, a rotation speed sensor 51, a pneumatic pressure sensor 52, a vehicle speed sensor 53, an acceleration sensor 54, an accelerator pedal sensor 55, a brake pedal sensor 56, a shift lever sensor 57, and an object detection sensor 58), an information service unit 59, and a communication module 60.

[0240] The drive unit 41 consists of, for example, at least one of an engine, a motor, or an engine-motor hybrid. The steering unit 42 includes at least a steering wheel (also called a handle) and is configured to steer at least one of the front wheels 46 and the rear wheels 47 based on the operation of the steering wheel operated by the user.

[0241] The electronic control unit 49 consists of a microprocessor 61, memory (ROM, RAM) 62, and communication ports (e.g., input / output (IO) ports) 63. Signals from various sensors 50-58 installed in the vehicle are input to the electronic control unit 49. The electronic control unit 49 may also be called an Electronic Control Unit (ECU).

[0242] Signals from various sensors 50-58 include current signals from current sensor 50 for sensing motor current, rotational speed signals of front wheels 46 / rear wheels 47 acquired by rotational speed sensor 51, air pressure signals of front wheels 46 / rear wheels 47 acquired by air pressure sensor 52, vehicle speed signals acquired by vehicle speed sensor 53, acceleration signals acquired by acceleration sensor 54, accelerator pedal depression signal of accelerator pedal 43 acquired by accelerator pedal sensor 55, brake pedal depression signal of brake pedal 44 acquired by brake pedal sensor 56, operation signals of shift lever 45 acquired by shift lever sensor 57, and detection signals for detecting obstacles, vehicles, pedestrians, etc., acquired by object detection sensor 58.

[0243] The information service unit 59 consists of various devices for providing (outputting) various types of information such as driving information, traffic information, and entertainment information, including a car navigation system, audio system, speakers, displays, television, and radio, and one or more ECUs that control these devices. The information service unit 59 uses information acquired from external devices via a communication module 60 or the like to provide various types of information / services (e.g., multimedia information / multimedia services) to the occupants of the vehicle 40.

[0244] The information service unit 59 may include input devices that accept input from the outside (e.g., keyboard, mouse, microphone, switch, button, sensor, touch panel, etc.) and output devices that perform output to the outside (e.g., display, speaker, LED lamp, touch panel, etc.).

[0245] The driver assistance system unit 64 consists of various devices that provide functions to prevent accidents or reduce the driver's workload, such as millimeter-wave radar, Light Detection and Ranging (LiDAR), cameras, positioning locators (e.g., Global Navigation Satellite System (GNSS)), map information (e.g., High Definition (HD) maps, Autonomous Vehicle (AV) maps), gyro systems (e.g., Inertial Measurement Unit (IMU), Inertial Navigation System (INS)), artificial intelligence (AI) chips, and AI processors, as well as one or more ECUs that control these devices. The driver assistance system unit 64 also transmits and receives various information via the communication module 60 to realize driver assistance functions or autonomous driving functions.

[0246] The communication module 60 can communicate with the microprocessor 61 and components of the vehicle 40 via the communication port 63. For example, the communication module 60 sends and receives data (information) via the communication port 63 to the drive unit 41, steering unit 42, accelerator pedal 43, brake pedal 44, shift lever 45, left and right front wheels 46, left and right rear wheels 47, axle 48, the microprocessor 61 and memory (ROM, RAM) 62 in the electronic control unit 49, and various sensors 50-58 provided in the vehicle 40.

[0247] The communication module 60 is a communication device that can be controlled by the microprocessor 61 of the electronic control unit 49 and can communicate with external devices. For example, it can send and receive various types of information to and from external devices via wireless communication. The communication module 60 may be located either inside or outside the electronic control unit 49. The external device may be, for example, the base station 10 or the user terminal 20 described above. Alternatively, the communication module 60 may be, for example, at least one of the base station 10 and the user terminal 20 (it may function as at least one of the base station 10 and the user terminal 20).

[0248] The communication module 60 may transmit at least one of the following to an external device via wireless communication: signals from the various sensors 50-58 input to the electronic control unit 49, information obtained based on said signals, and information based on input from an external source (user) obtained via the information service unit 59. The electronic control unit 49, the various sensors 50-58, the information service unit 59, etc., may also be called input units that accept input. For example, the PUSCH transmitted by the communication module 60 may include information based on the above input.

[0249] The communication module 60 receives various information (traffic information, signal information, inter-vehicle information, etc.) transmitted from an external device and displays it on the information service unit 59 installed in the vehicle. The information service unit 59 may also be called an output unit, which outputs information (for example, it outputs information to devices such as displays and speakers based on the PDSCH (or data / information decoded from the PDSCH) received by the communication module 60).

[0250] Furthermore, the communication module 60 stores various information received from external devices in a memory 62 that can be used by the microprocessor 61. Based on the information stored in the memory 62, the microprocessor 61 may control the drive unit 41, steering unit 42, accelerator pedal 43, brake pedal 44, shift lever 45, left and right front wheels 46, left and right rear wheels 47, axle 48, various sensors 50-58, etc., which are provided in the vehicle 40.

[0251] Furthermore, the term "base station" in this disclosure may be interpreted as "user terminal." For example, the various aspects / embodiments of this disclosure may be applied to a configuration in which communication between a base station and a user terminal is replaced with communication between multiple user terminals (which may be called, for example, Device-to-Device (D2D), Vehicle-to-Everything (V2X)). In this case, the user terminal 20 may have the functions that the base station 10 has. Also, terms such as "uplink" and "downlink" may be interpreted as terms corresponding to terminal-to-terminal communication (for example, "sidelink"). For example, uplink channel and downlink channel may be interpreted as sidelink channel.

[0252] Similarly, the term "user terminal" in this disclosure may be replaced with "base station." In this case, the base station 10 may be configured to have the same functions as the user terminal 20 described above.

[0253] In this disclosure, operations performed by a base station may, in some cases, be performed by its upper node. In a network including one or more network nodes with base stations, it is clear that various operations performed for communication with terminals may be performed by the base station, one or more network nodes other than the base station (for example, a Mobility Management Entity (MME), a Serving Gateway (S-GW), etc., but not limited to these), or a combination thereof.

[0254] Each aspect / embodiment described in this disclosure may be used individually, in combination, or switched between during execution. Furthermore, the processing procedures, sequences, flowcharts, etc., of each aspect / embodiment described in this disclosure may be rearranged in order, provided they are consistent. For example, the methods described in this disclosure present various step elements in an exemplary order and are not limited to that specific order.

[0255] Each aspect / embodiment described in this disclosure includes Long Term Evolution (LTE), LTE-Advanced (LTE-A), LTE-Beyond (LTE-B), SUPER 3G, IMT-Advanced, 4th generation mobile communication system (4G), 5th generation mobile communication system (5G), 6th generation mobile communication system (6G), xth generation mobile communication system (xG (where x is, for example, an integer or decimal)), Future Radio Access (FRA), New-Radio Access Technology (RAT), New Radio (NR), New radio access (NX), Future generation radio access (FX), Global System for Mobile communications (GSM®), CDMA2000, Ultra Mobile Broadband (UMB), IEEE 802.11 (Wi-Fi®), IEEE 802.16 (WiMAX®), and IEEE This may apply to systems utilizing 802.20, Ultra-WideBand (UWB), Bluetooth®, or other appropriate wireless communication methods, as well as next-generation systems that are extended, modified, created, or defined based on these. It may also apply to combinations of multiple systems (e.g., a combination of LTE or LTE-A and 5G).

[0256] In this disclosure, the phrase "based on" does not mean "based solely on" unless otherwise specified. In other words, the phrase "based on" means both "based solely on" and "based at least on."

[0257] Any reference to elements using the designations “first,” “second,” etc., as used in this disclosure does not generally limit the quantity or order of those elements. These designations may be used in this disclosure as a convenient way to distinguish between two or more elements. Accordingly, the references to the first and second elements do not imply that only two elements may be employed or that the first element must precede the second element in any way.

[0258] The term “determining” as used in this disclosure may encompass a wide variety of actions. For example, “determining” may be considered to include judging, calculating, computing, processing, deriving, investigating, looking up, searching, inquiry (e.g., searching in tables, databases, or other data structures), ascertaining, etc.

[0259] Furthermore, "judgment (decision)" may be considered as "judging (deciding)" things like receiving (e.g., receiving information), transmitting (e.g., sending information), input, output, accessing (e.g., accessing data in memory).

[0260] Also, "judgment (decision)" may be regarded as "resolving", "selecting", "choosing", "establishing", "comparing", etc. That is, "judgment (decision)" may be regarded as making a judgment on some operation.

[0261] Also, "judgment (decision)" may be read as "assuming", "expecting", "considering", etc.

[0262] The "maximum transmit power" described in the present disclosure may mean the maximum value of the transmit power, or the nominal UE maximum transmit power, or the rated UE maximum transmit power.

[0263] As used in the present disclosure, the terms "connected" and "coupled", or any variations thereof, mean any direct or indirect connection or coupling between two or more elements, and may include the presence of one or more intermediate elements between two elements that are "connected" or "coupled" to each other. The coupling or connection between elements may be physical, logical, or a combination thereof. For example, "connected" may be read as "accessed".

[0264] In the present disclosure, when two elements are connected, they can be considered to be "connected" or "coupled" to each other using one or more wires, cables, printed electrical connections, etc., and, as some non-limiting and non-exhaustive examples, electromagnetic energy having wavelengths in the radio frequency region, microwave region, optical (both visible and invisible) region, etc.

[0265] In this disclosure, the term "A and B are different" may mean "A and B are different from each other." The term may also mean "A and B are each different from C." Terms such as "separate" and "combine" may be interpreted similarly to "different."

[0266] Where the terms “include,” “including,” and variations thereof are used in this disclosure, these terms are intended to be inclusive, as is the term “comprising.” Furthermore, the term “or” as used in this disclosure is not intended to mean exclusive OR.

[0267] In this disclosure, if articles are added by translation, such as a, an, and the in English, this disclosure may include the fact that the noun following these articles is plural.

[0268] In this disclosure, terms such as "less than or equal to," "less than," "greater than or equal to," "more than," and "equal to" may be interpreted interchangeably. In addition, in this disclosure, terms meaning "good," "bad," "big," "small," "high," "low," "early," "slow," "wide," and "narrow" may be interpreted interchangeably, not limited to the positive, comparative, and superlative degrees. Furthermore, in this disclosure, terms meaning "good," "bad," "big," "small," "high," "low," "early," "slow," "wide," and "narrow" may be interpreted interchangeably, not limited to the positive, comparative, and superlative degrees, by adding "i-th" (where i is any integer) to the expression (for example, "highest" may be interpreted interchangeably with "i-th highest").

[0269] In this disclosure, "of," "for," "regarding," "related to," and "associated with" may be interpreted as being interchangeable.

[0270] Although the invention described herein has been explained in detail above, it will be clear to those skilled in the art that the invention described herein is not limited to the embodiments described herein. The invention described herein can be implemented in modified and altered forms without departing from the spirit and scope of the invention as defined in the claims. Therefore, the descriptions herein are for illustrative purposes only and do not imply any limitation on the invention described herein.

Claims

1. A transmission unit that transmits information obtained by compressing channel state information (CSI) using an Artificial Intelligence (AI) / Machine Learning (ML) model, A control unit that assumes a specific precoding matrix is ​​applied to a physical downlink shared channel (PDSCH) transmission for the calculation of a channel quality indicator (CQI), It has, The terminal wherein the aforementioned specific precoding matrix is ​​a precoding matrix calculated based on the AI / ML model output at the base station, a precoding matrix derived based on the CSI calculated based on the measurement of the terminal, or a precoding matrix derived based on the output expected for the AI / ML model at the base station.

2. The aforementioned specific precoding matrix is ​​a precoding matrix calculated based on a channel matrix derived from the output of the AI / ML model at the base station, a precoding matrix calculated based on a channel matrix derived from the CSI calculated from terminal measurements, or a precoding matrix calculated from a channel matrix derived from the expected output for the AI / ML model at the base station. The terminal according to claim 1.

3. The transmitting unit transmits information obtained by compressing CQI or information related to CQI using the AI / ML model. The terminal according to claim 1.

4. The process involves transmitting information obtained by compressing channel state information (CSI) using an Artificial Intelligence (AI) / Machine Learning (ML) model, The process involves assuming that a specific precoding matrix is ​​applied to a physical downlink shared channel (PDSCH) transmission in order to calculate the channel quality indicator (CQI), and It has, A wireless communication method for a terminal, wherein the specific precoding matrix is ​​a precoding matrix calculated based on the AI / ML model output at the base station, a precoding matrix derived based on the CSI calculated based on terminal measurements, or a precoding matrix derived based on the output expected for the AI / ML model at the base station.

5. A system including a terminal and a base station, The aforementioned terminal is A transmission unit that transmits information obtained by compressing channel state information (CSI) using an Artificial Intelligence (AI) / Machine Learning (ML) model, A control unit that assumes a specific precoding matrix is ​​applied to a physical downlink shared channel (PDSCH) transmission for the calculation of a channel quality indicator (CQI), It has, The aforementioned specific precoding matrix is ​​a precoding matrix calculated based on the AI / ML model output at the base station, a precoding matrix derived based on the CSI calculated based on terminal measurements, or a precoding matrix derived based on the expected output for the AI / ML model at the base station. The aforementioned base station is A system having a receiving unit that receives the aforementioned information.

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