Abstract: A method of resource selection by a user equipment (UE) is provided. The method includes detecting a need of an uplink transmission having a plurality of transmission parameters for at least one application from a plurality of applications having an associated transmission requirement. The method includes determining a set of configured grant resources available to the UE along with the associated plurality of grant resource parameters. The method includes determining transmission capability for the set of configured grant resources by analyzing the grant resource parameters. The method includes selecting at least one configured grant resource from the set of configured grant resources satisfying at least one transmission requirement of the at least one application.

Abstract: The disclosure relates to a method and system for adaptive antenna configuration in a user equipment comprising one or more antenna modules, each of the one or more antenna modules comprising a plurality of patch elements. The method comprises: determining whether a signal strength of the UE is above a signal threshold, determining whether a mobility of the UE is below a mobility threshold based on determining that the signal strength is above the signal threshold, determining at least one active antenna module based on determining that the mobility of the UE is below the mobility threshold, and deactivating at least one patch element in the at least one antenna module.

Abstract: Embodiments herein provide a method for channel state information (CSI) prediction by a user equipment (UE) in a wireless network. The method comprises determining a CSI; inputting the determined CSI to at least one machine learning (ML) based CSI prediction model to obtain at least one predicted precoder; encoding the at least one predicted precoder into at least one bit stream using at least one ML based CSI encoding model or at least one non-ML based CSI encoding model; and transmitting the at least one encoded bit stream to a network apparatus in the wireless network for the ML based CSI prediction at the network apparatus.

Abstract: A method of beam failure recovery managed by a transmitter of a communication system, includes: detecting a first occurrence of a beam failure between the transmitter and a receiver; based on the detection of the first occurrence of the beam failure, identifying at least one first reconfigurable intelligent surface (RIS) for transmitting at least one reference signal; transmitting the at least one reference signal to the at least one first RIS; receiving, from the at least one first RIS, a receiver feedback for the at least one of reference signal; generating an RIS candidate beam list based on the receiver feedback; and transmitting, to the receiver via the at least one first RIS, a radio resource control (RRC) message including the RIS candidate beam list as a beam failure recovery configuration.

Abstract: A method for managing beam alignment by a user equipment is provided. The method comprises receiving beam width information and base station location information from a base station, calculating a displacement of location of the UE based on location coordinates of the UE, measuring a change in a signal strength of the UE due to the displacement, and determining whether the UE is moving towards or away from the base station using at least one of the beam width information, base station location information, the displacement, and the measured change in the signal strength, determining whether a beam re-alignment is required based on the determination of the movement of UE, and transmitting a realignment request to the base station for a re-aligned beam width and a new transmission beam based on determining that the beam re-alignment is required.

Abstract: Embodiments herein provide a method for predicting iterations for decoding an encoded data at an electronic device. The method includes: receiving, by the electronic device, the encoded data; detecting, by the electronic device, signal parameters associated with the encoded data; predicting, by the electronic device, one of a cyclic redundancy check (CRC) failure, CRC success, and a CRC uncertainty in iterations for decoding the encoded data based on the signal parameters using a Neural Network (NN) model.

Abstract: Disclosed is a method and device for beam training for an IRS assisted cellular system. The method performed by BS in the IRS assisted cellular system includes configuring the IRS in a retro-reflection mode to reflect a received beam in same direction of reception of the beam and determining a BS optimal Tx-Rx beam pair for a BS-IRS link. The method includes: configuring the IRS to receive a beam from the UE; configuring the IRS to determine an IRS optimal Tx-Rx beam pair for an IRS-UE link and receiving signalling information from the UE indicating the IRS optimal Tx-Rx beam pair; and transmitting to the UE, a beam through the BS optimal Tx-Rx beam pair which is received at the UE through the UE optimal Tx-Rx beam pair, wherein the IRS reflects the beam transmitted by the BS to the UE through the IRS optimal Tx-Rx beam pair.

Abstract: A method of distributing throughput intelligently amongst a plurality of applications residing at a User Equipment (UE) is provided. The method includes receiving, at the UE, recommended bit rate (RBR) information from a network node, the RBR information indicating a throughput value allocated to the UE, allocating a codec rate from the allocated throughput value to at least one voice over internet protocol (VoIP) application from the plurality of applications, and allocating, from remaining throughput value of the allocated throughput value, a bit rate to each of a plurality of non-VoIP applications from the plurality of applications, based on corresponding throughput requirement associated with the plurality of non-VoIP applications.

Abstract: Embodiments herein disclose a method for controlling a non-linear effect of a power amplifier by an apparatus. The method includes acquiring an input data of the power amplifier of the apparatus and an output data of the power amplifier. Further, the method includes determining an inverse function using a neural network. The inverse function maps normalized output data of the PA to the input data of the PA, where the neural network comprises at least one sub-network for at least one memory tap from a plurality of memory taps in the neural network. Further, the method includes modifying the input data based on the determined inverse function value by dynamically changing a usage of the at least one memory tap from the plurality of memory taps. Further, the method includes compensating the non-linear effect in the output data of the power amplifier.

Abstract: A method for enhancing receiving signal power at a receiver is provided. The method includes estimating a channel gain by transmitting a pilot signal to the receiver through each antenna from a plurality of antennas of a transmitter and an IRS, determining an antenna selection metric based on the channel gain in transmitting the pilot signal to the receiver through each antenna of the transmitter and the IRS, identifying an antenna from the plurality of antennas that causes to provide the largest antenna selection metric, determining a reflection coefficient for each reflector of the IRS based on the identified antenna, configuring the reflectors of the IRS with the reflection coefficient, and transmitting the signal to the receiver through the identified antenna and the configured reflectors.

Abstract: A method of resource selection by a user equipment (UE) is provided. The method includes detecting a need of an uplink transmission having a plurality of transmission parameters for at least one application from a plurality of applications having an associated transmission requirement. The method includes determining a set of configured grant resources available to the UE along with the associated plurality of grant resource parameters. The method includes determining transmission capability for the set of configured grant resources by analyzing the grant resource parameters. The method includes selecting at least one configured grant resource from the set of configured grant resources satisfying at least one transmission requirement of the at least one application.

Abstract: The embodiments herein disclose methods and systems for configuring an reflecting surface. A method by a base station comprises: receiving at least one discovery signal from the reflecting surface; estimating a direction of a panel of the reflecting surface for transmission and reception using at least one spatial information based on the received at least one discovery signal; identifying a set of beam formed reference signals transmitted in the direction of the panel of the reflecting surface; and configuring at least one reference signal to the reflecting surface based on the identified set of beam formed reference signals.

Abstract: A method of resource selection by a user equipment (UE) is provided. The method includes detecting a need of an uplink transmission having a plurality of transmission parameters for at least one application from a plurality of applications having an associated transmission requirement. The method includes determining a set of configured grant resources available to the UE along with the associated plurality of grant resource parameters. The method includes determining transmission capability for the set of configured grant resources by analyzing the grant resource parameters. The method includes selecting at least one configured grant resource from the set of configured grant resources satisfying at least one transmission requirement of the at least one application.

Abstract: The disclosure refers to a method and a base station for communication in a high frequency network are provided. The method includes generating a first beam having a first beamwidth in a first area of a cell, determining a plurality of second beamwidth levels for a plurality of second beams possible in the first beamwidth of the first beam, wherein a second beamwidth associated with each of the plurality of second beams is narrower than the first beamwidth, generating the plurality of second beams having the plurality of determined second beamwidth levels, and transmitting at least one synchronization message to a plurality of user equipments via the first beam and the plurality of second beams.

Abstract: A method for managing beam alignment by a user equipment is provided. The method comprises receiving beam width information and base station location information from a base station, calculating a displacement of location of the UE based on location coordinates of the UE, measuring a change in a signal strength of the UE due to the displacement, and determining whether the UE is moving towards or away from the base station using at least one of the beam width information, base station location information, the displacement, and the measured change in the signal strength, determining whether a a beam re-alignment is required based on the determination of the movement of UE, and transmitting a realignment request to the base station for a re-aligned beam width and a new transmission beam based on determining that the beam re-alignment is required.

Abstract: Embodiments herein disclose a method for selecting a pilot pattern for an optimal channel estimation in a wireless network by a UE. The method includes: receiving a specified pilot pattern from a base station (BS); determining at least one channel parameter from the received specified pilot pattern, wherein the at least one channel parameter comprises a delay, a Doppler, a Demodulation Reference Signal (DMRS), a sounding reference signal (SRS), and a signal to noise ratio (SNR); estimating a minimum number of pilots required using the at least one determined channel parameter; and determining an optimal pilot pattern using a channel coefficient and the estimated minimum number of pilots, wherein the optimal pilot pattern is used for the optimal channel estimation.

Abstract: Embodiments herein provide a method for predicting iterations for decoding an encoded data at an electronic device. The method includes: receiving, by the electronic device, the encoded data; detecting, by the electronic device, signal parameters associated with the encoded data; predicting, by the electronic device, one of a cyclic redundancy check (CRC) failure, CRC success, and a CRC uncertainty in iterations for decoding the encoded data based on the signal parameters using a Neural Network (NN) model.

Abstract: In an embodiment, a method of a base station (BS) for managing an ISI in a cellular network is disclosed. The method includes receiving at least one UE-Capability information element from a UE comprising a list of CP lengths and a list of SCSs, determining a plurality of parameters associated with the UE based on the list of CP lengths and the list of SCSs, calculating at least one of a first custom CP length and a first SCS based on the plurality of parameters from the list of CP lengths and the list of SCSs, and transmitting, to the UE, a response message indicating that at least one of the first custom CP length and the first SCS is selected for managing the ISI.

Abstract: A method for handling beam blockage in a wireless communication system by a user equipment (UE), a method for handling beam blockage in a wireless communication system by a base station, a UE, and a base station are provided. The method for handling beam blockage in a wireless communication system by a UE includes detecting, by a user equipment (UE), a blockage of at least one beam; determining, by the UE, a duration of the blockage of the at least one beam, wherein the duration of the blockage is determined at a time period at which the blockage is detected; and indicating, by the UE, the blockage.

Abstract: Disclosed is a method for determining beam search space by a user equipment (UE), including determining a geo-location of a base station and a geo-location of the UE at a current time instance, determining a relative angle of reception from the base station based on the geo-location of the base station and the geo-location of the UE at the current time instance, determining a beam search space comprising a plurality of beams, for measurement, centered at the relative angle of reception, and determining an optimal beam from within the beam search space based on the measurement of the plurality of beams in the beam search space.