Abstract: Disclosed herein is a method of operating a terminal in a wireless communication system. As an example of the present disclosure, the method may include: receiving information on at least one of a first split point and a second split point from a base station; performing first split inference based on the first split point and generating first intermediate data; transmitting the first intermediate data to the base station; receiving second intermediate data generated based on the second split point from the base station; performing remaining split inference from the second split point based on the second intermediate data; and adjusting the second split point based on the second intermediate data.

Abstract: In order to provide device and method for adjusting split point in wireless communication system, a method of operating a terminal in a wireless communication system may comprise requesting a base station for uplink channel quality information, receiving, from the base station, the uplink channel quality information, determining a first split point based on the channel quality information, performing first split inference based on the determined first split point and transmitting, to the base station, first split inference result information.

Abstract: An intelligent computing device according to an embodiment of the present specification may receive a request for terminal information related to a terminal from a base station, transmit the terminal information to the base station, receive a resource for data transmission or reception, which is allocated by the base station, and transmit or receive data to or from the base station by using the allocated resource, wherein the data is transmitted or received by using a receiver selected from among a normal receiver of the terminal and an artificial intelligence receiver of the terminal on the basis of wireless communication environment information of the terminal, so that the conventional normal receiver and the artificial intelligence receiver provided at the terminal can be efficiently used in a wireless communication environment.

Abstract: A method for performing reinforcement learning by a V2X communication device in an autonomous driving system, specifically, a method for performing reinforcement learning in consideration of a reward application ratio over time, is proposed. Action information is transmitted to a second V2X communication device, reward information is received from the second V2X communication device, and reinforcement learning is performed on the basis of a reward, wherein a reward corresponding to a ratio determined by a first V2X communication device is applied to the reinforcement learning, the ratio is determined on the basis of a time interval from a time point of transmission of the action information to a time point of reception of the reward information, and the ratio is between 0 and 1, both inclusive.

Abstract: A method for performing reinforcement learning by a V2X communication device in an autonomous driving system, specifically, a method for performing reinforcement learning in consideration of an application rate of a reward according to age in terms of the freshness of a reward for an action, is proposed. An agent transmits an action message and controls a reflection rate of a reward through AoI management for a reward message, so that rewards transmitted from a plurality of devices are suitably reflected in an environment of a reinforcement learning-based autonomous driving system, and an optimal policy can be found accordingly.

Abstract: Disclosed is a method for controlling, by a terminal, an operation of a deep neural network in a wireless communication system. The method according to an embodiment of the present disclosure receives a downlink from abase station in a wireless communication system; and preprocesses the downlink on the basis of the result of an operation of a deep neural network of a terminal, wherein at least one reference signal is applied to the downlink while a statistical feature related to noise of the downlink are maintained. The terminal of the present disclosure may be linked to an artificial intelligence module, a drone (unmanned aerial vehicle (UAV)), a robot, an augmented reality (AR) device, a virtual reality (VR) device, a device related to 6G services, and the like.

Abstract: Disclosed is a method by which a terminal controls the calculations of a deep neural network in a wireless communication system. A method according to one embodiment of the present disclosure receives a downlink from a base station of a wireless communication system by using a multi input multi output (MIMO) operation, pre-processes the downlink on the basis of a result of calculations of a deep neural network in a terminal, acquires the number of a plurality of transmission antennas connected to the terminal, acquires the number of a plurality of reception antennas connected to the terminal, and forms a plurality of overlapping neural networks overlapping in the deep neural network, on the basis of a preset number of reference antennas, the number of transmission antennas, and the number of reception antennas.

Abstract: Disclosed is a method for transmitting and receiving data by a terminal in a wireless communication system according to the present document, the method comprising the steps of: receiving configuration information from a base station; and receiving data, on the basis of the configuration information. The configuration information includes information about a first receiver model and a first zone to which the base station belongs, the first zone includes one or more base stations adjacent to the base station, and the first receiver model is generated on the basis of a combination of receiver models that are trained by the base stations within the first zone, according to a machine learning step.

Abstract: Disclosed is a wireless communication method using an on-device learning-based machine learning network. A method according to one embodiment of the present specification comprises the steps of: generating a learning list on the basis of one or more location samples collected while a terminal communicates through a network; when an event associated with any one of one or more first items included in the learning list is detected, obtaining training data for updating, to a second machine learning network, a first machine learning network to be applied to a receiver of the terminal; and updating the first machine learning network by using the training data, and thereby the method provides a wireless communication service adaptive to an actual communication environment.

Abstract: The present disclosure relates to a method for operating a terminal and a base station in a wireless communication system and an apparatus for supporting the same. In an embodiment of the present disclosure, a method for operating a terminal in a wireless communication system may include: transmitting a first message including information related to learning; receiving a second message including configuration information for learning; transmitting an uplink reference signal; and transmitting channel information related to a downlink channel measured based on a downlink reference signal.

Abstract: Provided is a method for transmitting or receiving data, by a user equipment (UE), to or from a base station (BS). The method includes transmitting, by the UE, capability information of the UE to the BS, wherein the capability information includes information related to artificial intelligence (AI) calculation for the data transmission or reception, receiving, by the UE, at least one of a plurality of AI parameters from the BS, and applying the at least one AI parameter to an encoding process for the data transmission or a decoding process for the data reception, wherein the encoding process or the decoding process is performed by information on a network structure in the at least one AI parameter, and wherein the at least one AI parameter comprises a plurality of information for performing the encoding process or the decoding process by the network structure.

Abstract: Provided is a method for transmitting or receiving data, by a user equipment (UE), to or from a base station (BS). The method includes transmitting, by the UE, capability information of the UE to the BS, wherein the capability information includes information related to artificial intelligence (AI) calculation for the data transmission or reception, receiving, by the UE, at least one of a plurality of AI parameters from the BS, and applying the at least one AI parameter to an encoding process for the data transmission or a decoding process for the data reception, wherein the encoding process or the decoding process is performed by information on a network structure in the at least one AI parameter, and wherein the at least one AI parameter comprises a plurality of information for performing the encoding process or the decoding process by the network structure.