Abstract: This disclosure provides methods for channel state information (CSI) feedback. In one method, at a user equipment (UE), CSI data of a communication channel between the UE and a base station (BS) is collected. The UE is configured with an encoder model to compress CSI and the BS is configured with a decoder model to decompress CSI. Based on the collected CSI data, online training is performed at the UE on a previously trained encoder-decoder model pair including the encoder model and the decoder model to generate updated models for the encoder model and the decoder model, respectively. In another method, the CSI data is collected at the BS and the online training is performed at the BS based on the collected CSI data.

Abstract: First processing circuitry of a first apparatus for compressing channel state information (CSI) classifies a CSI element into one of multiple classes of CSI elements. Each class is associated with a different one of multiple encoders. The first processing circuitry compresses the CSI element based on one of the multiple encoders associated with the one of the multiple classes of CSI elements, and sends, to a second apparatus, the compressed CSI element and a class index of the one of the multiple classes of CSI elements. Second processing circuitry of the second apparatus for decompressing CSI receives the compressed CSI element and the class index. Each class of CSI elements is associated with a different one of multiple decoders. The second processing circuitry determines one of the multiple decoders based on the class index, and decompresses the CSI element based on the determined decoder to obtain a decompressed CSI element.

Abstract: Aspects of the disclosure provide a method, an apparatus, and a non-transitory computer-readable medium for compressing channel state information (CSI). Under the method, a CSI matrix is decomposed, at a first device, into a first vector including a plurality of significant numbers extracted from the CSI matrix. A second vector is generated by multiplying the first vector with a linear operator. A length of the second vector is less than a length of the first vector. The second vector is sent from the first device to a second device along with a number of the plurality of significant numbers in the first vector. The method is implemented in software instructions, and when processing circuitry of the apparatus executes the software instructions, the processing circuitry of the apparatus performs the method. The software instructions are stored in the non-transitory computer-readable medium.

Abstract: In an aspect of the disclosure, a method, a computer-readable medium, and an apparatus are provided. The apparatus may be a UE. The UE receives a first configuration for activating a first number of sets of TC states. Each set of the first number of sets includes at least a TCI state configured for communicating with a first TRP. The UE determines, based on an indication contained in the first configuration, that the first number of sets of TC states are activated for communicating with the first TRP or a second TRP in a first direction selected from an uplink direction and a downlink direction. The UE activates the first number of sets of TC states for communicating with the first TRP or the second TRP in the first direction.

Abstract: Examples pertaining to beam management in mobile communications are described. A user equipment (UE) determines a beam pattern according to at least one of an optimal beam in a previous inference, a beam in use, a previous measurement result and a condition of a channel between the apparatus and a network node. The UE provides information regarding the beam pattern to the network node.

Abstract: A UE receives, from a base station, a first monitoring configuration for monitoring an artificial intelligence/machine learning (AI/ML) model for managing a set of beams. The UE measures a first subset of the set of beams. The UE performs inference using the AI/ML model based on measurements of the first subset to determine predication values of a second subset of the set of beams. The second subset is selected based on the first monitoring configuration. The UE measures the second subset of the set of beams to determine measured values of the second subset. The UE calculates one or more performance metrics based on the predication values and the measured values of the second subset. The one or more performance metrics are selected based on the first monitoring configuration.

Abstract: In an aspect of the disclosure, a method, a computer-readable medium, and an apparatus are provided. The apparatus may be a user equipment (UE). The UE generates metadata for channel state information (CSI) samples. The UE uses the generated metadata to categorize the CSI samples into one or more subsets. The UE uses each subset of the one or more subsets to train a machine learning model or a part of a machine learning model.

Abstract: Techniques pertaining to channeling state information (CSI) pre-processing are described. A user equipment (UE) that is in wireless communication with a base station node extracts eigenvectors (EVs) from CSI acquired by the UE. The UE generates pre-processed CSI for compression by a machine-learning (ML)-based encoder of the UE into CSI feedback for the base station node by at least performing one or more of a phase discontinuity compensation (PDC), a one-step polarization separation with re-ordering, or a two-step polarization separation that includes separation based on polarization type and separation by position on the EVs.

Abstract: Techniques pertaining to training artificial intelligence (AI)/machine learning (ML) models in wireless communications are described. An apparatus participates in training of a two-sided AI/ML model. The apparatus also performs a wireless communication by utilizing the two-sided AI/ML model.

Abstract: In an aspect of the disclosure, a method, a computer-readable medium, and an apparatus are provided. The apparatus may be wireless equipment. The wireless equipment selects a first subset of beams to be utilized for beam management. The beams are from a set of first type of beams used for communication with a base station or a UE. The wireless equipment measures signals transmitted on a second subset of beams. The beams are from the set of first type of beams or from a set of second type of beams. The wireless equipment measures the signals over a time window. The wireless equipment inputs the measurements to a computational model. The wireless equipment receives predictions of channel measurements on the first subset of beams from the computational model.

Abstract: Techniques pertaining to generalization of an artificial intelligence (AI)/machine learning (ML) model in wireless communications are described. A user equipment (UE) receives, from a network, an indicator related to a network environment surrounding the UE. The UE utilizes the indicator as an additional input with respect to an AI/(ML model.

Abstract: A method pertaining to channel state information (CSI) reporting for multiple transmission/reception-points (multi-TRP) in next-generation mobile communications involves a user equipment (UE) generating a CSI report for multiple TRPs in communications with the UE. Additionally, the method also involves the UE transmitting the CSI report to one or more of the multiple TRPs using one or multiple CSI reporting resources.

Abstract: Techniques pertaining to channeling state information (CSI) compression are described. A user equipment (UE) that is in wireless communication with a base station node acquires channel state information (CSI) at least associated with the wireless communication. The UE further compresses the CSI into CSI feedback for the base station node via an artificial intelligence (AI)/machine-learning (ML)-based encoder that implements at least one of convolutional projection, expandable kernels, or multi-head re-attention (MHRA).

Abstract: A unified solution to support all PCell, SCell, and per-TRP based beam failure recovery (BFR) procedure is proposed, with less standard impact and reduced latency. In a first novel aspect, a set of reference signals (RSs) for BFD is configured for each BWP of a serving cell, and a maximum number of BFD RSs (N) per TRP for each BWP of a serving cell is configured. In a second novel aspect, for single DCI multi-TRP, the BFD RSs can be updated via MAC CE to reduce latency. In a third novel aspect, new RRC parameters for BFD RSs and candidate beam RSs are configured, with different sets of SSB/CSI-RS resources associated to each TRP. Specifically, an additional lists of SSB/CSI-RS resource set is defined for each corresponding TRP.

Abstract: User equipment (UE) for sounding reference signal (SRS) triggering is provided. The UE may include a radio frequency (RF) signal processing device and a processor. The RF signal processing device receives first slot offset information and second slot offset information from a network node. The first slot offset information is configured through a radio resource control (RRC) information element (IE) to indicate a first time difference between the down link control information (DCI) and a resource reference slot. The second slot offset information indicates the second time difference between the reference slot and an SRS resource. The processor is coupled to the RF signal processing device. When the RF signal processing device receives the DCI, the processor triggers an SRS transmission for the SRS resource according to the first slot offset information and the second slot offset information.

Abstract: A user equipment (UE) in wireless communication receives a configuration of search space (SS) sets that include a first SS set in a first control resource set (CORESET) and a second SS set in a second CORESET. The first CORESET and the second CORESET have different transmission configuration indication (TCI) states. The UE repeatedly receives downlink control information (DCI) via a first physical downlink control channel (PDCCH) and a second PDCCH. The first PDCCH is allocated with a first set of time-and-frequency resources configured for first SS set and the second PDCCH is allocated with a second set of time-and-frequency resources configured for the second SS set. The UE then parses the DCI to obtain control information for the wireless communication. Alternatively, the configuration of SS sets received by the UE is in one CORESET that has at least a TCI state and a second TCI state activated.

Abstract: User equipment (UE) for sounding reference signal (SRS) triggering is provided. The UE may include a radio frequency (RF) signal processing device and a processor. The RF signal processing device receives first slot offset information and second slot offset information from a network node. The first slot offset information is configured through a radio resource control (RRC) information element (IE) to indicate a first time difference between the down link control information (DCI) and a resource reference slot. The second slot offset information indicates the second time difference between the reference slot and an SRS resource. The processor is coupled to the RF signal processing device. When the RF signal processing device receives the DCI, the processor triggers an SRS transmission for the SRS resource according to the first slot offset information and the second slot offset information.

Abstract: In an aspect of the disclosure, a method, a computer-readable medium, and an apparatus are provided. The apparatus may be a UE. The UE receives, at a time point, DCI scheduling two or more downlink data channels. The UE receives, within a threshold processing time from the time point, a first control signal in a first CORESET according to a first TCI state. The threshold processing time is allocated for the UE to decode the downlink control information. The UE receives, subsequent to the first CORESET, data according to the first TCI state (a) until an end of the threshold processing time when a second CORESET in which the UE is configured to receive a second control signal does not exist in the threshold processing time or (b) until the second CORESET when the second CORESET exists in the threshold processing time.

Abstract: A unified solution to support all PCell, SCell, and per-TRP based beam failure recovery (BFR) procedure is proposed, with less standard impact and reduced latency. In a first novel aspect, a set of reference signals (RSs) for BFD is configured for each BWP of a serving cell, and a maximum number of BFD RSs (N) per TRP for each BWP of a serving cell is configured. In a second novel aspect, for single DCI multi-TRP, the BFD RSs can be updated via MAC CE to reduce latency. In a third novel aspect, new RRC parameters for BFD RSs and candidate beam RSs are configured, with different sets of SSB/CSI-RS resources associated to each TRP. Specifically, an additional lists of SSB/CSI-RS resource set is defined for each corresponding TRP.

Abstract: A method for beam management for a communications apparatus communicating with a network device in a wireless network, comprising: determining whether there is any component carrier (CC) recorded in a predetermined CC list with a predetermined resource identifier upon receiving information regarding a Transmission Configuration Indicator (TCI) state of a reference signal (RS) resource in a target CC; and when there is one or more CCs recorded in the predetermined CC list with the predetermined resource identifier, applying a setting of a predetermined Quasi Co-Location (QCL) type indicated by the TCI state of the RS resource in the target CC to the one or more CCs recorded in the predetermined CC list with the predetermined resource identifier.