Samsung Electronics Co., Ltd.

Caleb K Lo

Jeongho Jeon

Jianzhong Zhang

Joonyoung Cho

Gilwon Lee

Qiaoyang Ye

Junhyuk Song

Shiyang Leng

Pranav Madadi

Methods and devices for transmission symbol modulation that accounts for distortion introduced by a power amplifier (PA). A user equipment (UE) comprises a transceiver and a processor. The transceiver is configured to transmit, to a base station (BS), UE capability information that indicates support for adjusted symbol constellations, wherein the adjusted symbol constellations are adjusted to pre-compensate for distortion effects of a power amplifier (PA) in the transceiver, and receive, from the BS, a modulation and coding scheme (MCS) indication. The processor is configured to determine, based on the MCS indication, an adjusted symbol constellation, and generate modulation symbols from input bits according to the determined adjusted symbol constellation. The transceiver is further configured to transmit, to the BS, the modulation symbols.

Support of power amplifier-aware modulation

Machine learning (ML) adaptation of any one of reference signal (RS) temporal density, RS frequency density, RS spatial density, or number of transmission/reception points (TRPs) that transmit RS provides configuration of lower RS densities or fewer TRPs that transmit RS without significant loss of throughput in appropriate circumstances. Determinations to switch from high density transmission to low density transmission, to reduce the number of antenna ports or TRPs that transmit RS, or to fallback to high density transmission may be made by the ML model, optionally with UE assistance information.

Method and apparatus for reference symbol pattern adaptation

Capability of a user equipment to support machine learning adaptation by a base station of a reference signal pattern is signaled between the base station and the user equipment. Configuration information from the base station indicates one or more of enabling or disabling of machine learning adaptation of the reference signal pattern, a machine learning model used for machine learning adaptation of the reference signal pattern, updated model parameters for the machine learning model, or whether model parameters received from the user equipment will be used for machine learning adaptation of the reference signal pattern. Model training may be performed or model parameters received, and reference signals are received from the base station. Information on a reference signal pattern may be transmitted by the user equipment to the serving base station. Assistance information may be transmitted by the user equipment to the base station, which configures a reference signal pattern.

A service management and orchestration (SMO) entity enabling a functional split between a non-real-time (RT) radio access network (RAN) intelligent controller (RIC) and an external artificial intelligence (AI)/machine learning (ML) server will, during a data collection phase, utilize the SMO entity and the non-RT RIC to collect and process RAN data and non-RAN data and, during a data transfer phase, transfer processed RAN and non-RAN data from the SMO entity to an external AI/ML server via an interface. During a training model input phase, the SMO entity receives a trained AI/ML model, metadata, and training results from the external AI/ML server via an interface and, during a configuration phase, the SMO entity uses the trained AI/ML model within the SMO entity and the non-RT RIC to transfer configuration parameters to a near-RT RIC.

Functional architecture and interface for non-real-time ran intelligent controller

Methods and apparatuses for uplink timing and frequency synchronization in a wireless communication system. A method for operating a user equipment (UE) includes receiving, from a base station (BS), information indicating satellite ephemeris information of a communication satellite associated with the BS, a common timing advance (TA), and a compensated frequency offset (FO). The method further includes transmitting a physical random access channel (PRACH) based on the common TA and the compensated FO and receiving a random access response (RAR) indicating a UE-specific TA and FO. The method further includes, for transmission of an uplink (UL) channel, adjusting a TA and pre-compensating a FO based on the UE-specific TA and FO, respectively.

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San Jose, CA, United States of America

Caleb K Lo