A method for receiving data by a terminal in a wireless communication system according to the present document comprises: receiving a channel signal and a reference signal (RS) from a base station; and generating a sequence by filtering the RS, and decoding the channel signal on the basis of the generated sequence, wherein the filtering is zero forcing (ZF) filtering, and the decoding of the channel signal is a selection of one parameter from among parameter sets generated in accordance with a colored-noise machine learning process.

A plurality of control signals transmitted in individual frequency bands by a moving transmission station via a plurality of transmission antennas and a plurality of data signals transmitted in a common frequency band by the transmission station via the plurality of transmission antennas in synchronization with the control signals are received by each of a plurality of antennas disposed at different positions. Based on symbol timings of the control signals received by the antenna, a sampling rate error between the plurality of control signals transmitted by the plurality of transmission antennas, respectively, is compensated for. Based on the control signals subjected to the sampling rate error compensation, frame timings of the plurality of data signals transmitted by the transmission station via the plurality of transmission antennas are synchronized. Based on the control signals subjected to the sampling rate error compensation, channels for the plurality of data signals transmitted by the transmission station via the plurality of transmission antennas are estimated. The plurality of data signals with the frame timings synchronized, for the estimated channels are equalized.

According to the present document, a method by which a terminal receives data in a wireless communication system comprises: receiving a channel signal and a reference signal (RS) from a base station; generating a sequence by performing an operation of equalizing the RS to a channel RS; and decoding the received channel signal on the basis of the generated sequence, wherein the operation of equalizing the RS to the channel RS is based on a parameter determined according to a machine learning process.

An uplink transmission method performed by a terminal includes: receiving, from a base station, at least one DCI for allocating first uplink transmission and second uplink transmission; performing a first LBT procedure for the first uplink transmission, and performing the first uplink transmission when the first LBT procedure is successful; and performing a second LBT procedure for the second uplink transmission, and performing the second uplink transmission when the second LBT procedure is successful, wherein the first uplink transmission and the second uplink transmission are consecutively performed with a time interval longer than a predetermined time.

An electronic device is provided. The electronic device includes a communication processor, at least one radio frequency integrated circuit (RFIC), a first radio frequency front end (RFFE) circuit, a second FRRE circuit, a first antenna group including a plurality of antennas each connected through the first RFFE circuit to transmit a signal corresponding to at least one communication network, and a second antenna group including a plurality of antennas each connected through the second RFFE circuit to transmit a signal corresponding to at least one communication network, wherein the communication processor is configured to control to transmit a reference signal referenced for channel estimation in a base station of a first communication network to at least one of the plurality of antennas of the first antenna group through the first REEF circuit, and control to transmit the reference signal to at least one of the plurality of antennas of the second antenna group through the second RFFE circuit.

An operating method of a user equipment (UE) includes receiving channel state information-reference signal (CSI-RS) configuration information from a base station including time and frequency location information of a first CSI-RS, the first CSI-RS corresponding to a first density value of 0.5, 1 or 3, determining whether to request a second CSI-RS having a second density value based on a channel characteristic, the second density value being different from the first density value, and the channel characteristic corresponding to a channel between the UE and the base station, transmitting a request message to the base station in response to determining to request the second CSI-RS, receiving the second CSI-RS from the base station based on the CSI-RS configuration information, the second CSI-RS being based on the request message, estimating the channel based on the second CSI-RS, and transmitting a CSI-RS report to the base station based on the channel estimate.

Methods, systems, and devices for wireless communications are described. A user equipment (UE) configured for a periodic channel stat information (CSI) reference signal (CSI-RS) configuration may request an update for one or more parameters of the periodic CSI-RS configuration. For example, the UE may transmit request to a base station for a longer periodicity based on detecting a low Doppler scenario or little variance to wireless channel conditions, or the UE may request a shorter periodicity based on detecting a high Doppler scenario or high variance to wireless channel conditions. The base station may update a configuration for CSI or for CSI-RS based on the request. For example, the base station may update a periodicity for the periodic CSI-RS configuration based on the requested periodicity.

Apparatuses, methods, and systems are disclosed for supporting JED model selection and training. One apparatus includes a processor and a transceiver that receives a configuration from a network device, said configuration indicating at least one of: a set of resources for model training, a type of intended model training, and combinations thereof. The processor selects a Joint Channel Equalization and Decoding (“JED”) model from a set of models based on the received configuration. The processor trains the selected JED model using the received configuration.

A method includes storing multiple signals received from a user equipment (UE) in a queue. The method also includes estimating a sounding reference signal (SRS) signal-to-noise-ratio (SNR) and determining a filtered SNR based on the received signals. The method also includes computing one or more features based on the filtered SNR and at least some of the received signals in the queue. The method also includes determining (i) a channel condition of the UE and (ii) a speed range of the UE based on the one or more computed features, wherein the channel condition of the UE comprises line-of-sight (LoS) or non-line-of-sight (NLoS). The method also includes determining a transmission configuration based on the channel condition of the UE and the speed range of the UE.

A method for channel prediction for uplink (UL) and downlink (DL) massive Multiple Input Multiple Output (MIMO) systems for Open Radio Access Network (0-RAN) fronthaul Split 7.2 networks enables prediction of a channel that is seen by the UL slot. The pre-processing matrix is computed by the distributed unit (DU) based on this predicted channel and sent to the radio unit (RU) for minimizing the effects of channel aging. A channel corresponding to sounding reference signal (SRS) symbol closest to uplink slot being decoded can be predicted from previous SRS symbols and can be used as a combining matrix. Alternatively, the channel of the uplink slot itself can be predicted from past SRS symbols, and a combining matrix can be generated based on the predicted channel.