Abstract: The disclosure relates to a 5G or 6G communication system for supporting a higher data transmission rate. The method comprises: receiving a flow index corresponding to a plurality of applications available at an electronic device, wherein the flow index represents a type of the flow, and a priority of the flow; determining whether connection for the data transmission exists between the electronic device and an internet server based on the flow index; performing one of regulating the flow based on the flow index in response to determining that the connection for the data transmission exists between the electronic device and the internet server, and discarding the flow index received from the electronic device for regulation of the flow in response to determining that the connection for the data transmission does not exists.

Abstract: A method for decoding data by an electronic device is provided. The method includes receiving, by the electronic device, encoded data, determining, by the electronic device, a sparsity of a plurality of Machine Learning (ML) models of a turbo decoder of the electronic device for decoding the encoded data based on Quality-of-Service (QoS) parameters, and decoding, by the electronic device, the encoded data using the turbo decoder based on the determined sparsity.

Abstract: A method implemented at one or more base stations for a power management of the one or more base stations in a wireless communication network is disclosed. The method includes transmitting, by the one or more base stations, a plurality of Key Performance Indicator (KPI) parameters associated with the one or more base stations to a federal server controller. The method includes receiving, by the one or more base stations from the federal server controller, a KPI relationship predicting a future load based on the plurality of KPI parameters associated with the one or more base stations. The method includes adjusting, by the one or more base stations, a Central Processing Unit (CPU) frequency associated with the one or more base stations autonomously based on the KPI relationship for managing the future load associated with the one or more base stations.

Abstract: The present disclosure discloses a method and system for traffic shaping for a user equipment (UE) in a wireless communication network. The method comprises: estimating a congestion at each of a plurality of cells in the wireless communication network based on one or more network key performance indicators (KPIs) associated with the wireless communication network, collecting movement data of the UE by monitoring a movement of the UE connected to a first cell, predicting, based on the movement data and at least one of the estimated congestion and a bandwidth delay product (BDP) of the each of the plurality of cells, whether the UE is likely to be handed over from the first cell to a second cell, and transmitting a congestion notification to a core network of the wireless communication network based on the prediction, to perform traffic shaping for the UE upon receiving the congestion notification.

Abstract: The present disclosure relates to a pre-5th-Generation (5G) or 5G communication system to be provided for supporting higher data rates Beyond 4th-Generation (4G) communication system such as long term evolution (LTE). Methods and systems for optimizing computation of log-likelihood ratio (LLR) for decoding modulated symbols. A method disclosed herein involves receiving at least one symbol transmitted from at least one device, wherein the received at least one symbol is encoded and modulated symbol including a plurality of data bits. The method further includes computing a log-likelihood ratio (LLR) of each bit in the received at least one symbol for decoding the received at least one symbol using a centroid method that involves exploiting a symmetry of a constellation of code words and/or a uncertainty region defined on a constellation of code words.

Abstract: The disclosure relates to a 5G or 6G communication system for supporting a higher data transmission rate. The method comprises: receiving a flow index corresponding to a plurality of applications available at an electronic device, wherein the flow index represents a type of the flow, and a priority of the flow; determining whether connection for the data transmission exists between the electronic device and an internet server based on the flow index; performing one of regulating the flow based on the flow index in response to determining that the connection for the data transmission exists between the electronic device and the internet server, and discarding the flow index received from the electronic device for regulation of the flow in response to determining that the connection for the data transmission does not exists.

Abstract: A method for decoding data by an electronic device (100) is provided. The method includes receiving, by the electronic device (100), encoded data. The method includes determining, by the electronic device (100), a sparsity of a plurality of Machine Learning (ML) models (301, 302) of a turbo decoder (150) of the electronic device (100) for decoding the encoded data based on Quality-of-Service (QoS) parameters. The method includes decoding, by the electronic device (100), the encoded data using the turbo decoder (150) based on the determined sparsity.

Abstract: A method for decoding user data by an apparatus in a wireless network is provided. The method includes receiving, by the apparatus, user data associated with a plurality of network parameters. The method includes training, by the apparatus, a neural network using the plurality of received network parameters. Further, the method includes computing, by the apparatus, a Log Likelihood Ratio (LLR) using the trained neural network. Further, the method includes decoding, by the apparatus, the received user data using the computed LLR.