Samsung Electronics Co., Ltd.

Satya Kumar Vankayala

Seungil Yoon

Anshuman Nigam

Abhay Kumar Sah

Satya Venkata Uma Kishore Godavarti

Ashvin Kaithara Joseph

Pankaj Bhimrao Thorat

Swaraj Kumar

Rajesh Challa

Issaac Kommineni

Ashok Kumar Reddy Chavva

Vivek Soni

Nithin Srinivasan

Satya Venkata Umakishore Godavarti

Vishal Devinder Karira

Raviteja Gundeti

Fasil Abdul Latheef

Anusha Gunturu

Shweta Madhurapantula

Mudit Gupta

Avinash Bhat

Dheeraj Kumar

Uma Kishore Satya Venkata Godavarti

Godavarti Satya Venkata Uma Kishore

Akhil Shukla

Mohan Rao Naga Santha Goli

Mayank Kailash Agrawal

Ravi Teja Gundeti

Shruti Shetty

Samuel Ignatius Kanakaraj

Sudharsan Parthasarathy

Tirthankar Mittra

Gaurav Potnis

Venkateswarlu Yarramala

V V N K Someswara Rao Koduri

Javed Akhtar

Tummala Seshu

Sukhmeet Singh

Saikrishna Pedamalli

Avani Agrawal

Provided is a method of operating a user equipment (UE) in a wireless network for managing physical downlink control channel (PDCCH) data. The method includes: obtaining a plurality of network parameters, predicting at least one aggregation level (AL) used by a base station (BS) associated with the UE to transmit the PDCCH data in the wireless network based on the plurality of received network parameters, and decoding the PDCCH data based on the at least one predicted AL.

System and method to reduce PDCCH blind decoding attempts using artificial intelligence and machine learning

Embodiments of the disclosure provide a method for provisioning mobility management during congestion in a wireless network by a network apparatus. The method includes: detecting a plurality of parameters of a current cell associated with at least one User Equipment (UE) in the wireless network; predicting an uplink (UL) congestion condition with an uplink radio resource of the current cell by applying at least one machine learning model to the plurality of parameters of the current cell; performing a mobility of the at least one UE from the current cell to at least one target cell in the wireless network based on the predicted UL congestion condition with the uplink radio resource of the current cell associated with the at least one UE.

Method and network apparatus for provisioning mobility management during congestion in a wireless network

The present disclosure relates to a pre-5-Generation (5G) or 5G communication system to be provided for supporting higher data rates Beyond 4-Generation (4G) communication system such as Long Term Evolution (LTE). The present disclosure provides methods and systems for reducing fronthaul bandwidth. Embodiments herein relate to the field of wireless networks and more particularly to reducing fronthaul bandwidth during a transfer of data between at least one radio node and at least one centralized node in a wireless network. A method disclosed herein includes determining parameters specific to at least one User Equipment (UE) using a machine learning method. The method further includes transferring data between the at least one radio node and the at least one centralized node over a fronthaul link by compressing the data using the parameters that are determined using the machine learning method. The method further includes decompressing, by at least one of the at least one radio node and the at least one centralized node, the compressed data using the parameters that are determined using the machine learning method.

Methods and systems for reducing fronthaul bandwidth in a wireless communication system

A method of enabling multi-connectivity in a wireless network includes predicting at least one of a RLF, a call drop, and a jitter based on a plurality of Key Performance Indicators (KPIs) associated with the UE and the wireless network, determining whether the UE is in one of a Dual Connectivity (DC) mode and a carrier aggregation (CA) mode, performing one of: adding a new secondary gNodeB (gNB) in response to determining that the UE is not in both the DC mode and the CA mode and converting the new gNB to a master gNB, converting an existing secondary gNodeB to a master gNodeB with one of an existing Master Cell Group (MCG) gNodeB and another gNodeB as the secondary gNodeB, in response to determining that the UE is in the DC mode, and converting an existing secondary cell to a primary cell.

Method and device of enabling multi-connectivity in wireless network for improving QOS of UE

Embodiments herein provide a method for managing a network slice load in a wireless network. The method includes: sending, by a CN device, a request message for network slice load information to a base station of the wireless network; determining, by the base station, the network slice load based on the parameter; sending, by the base station, the response message comprising the network slice load information to the core network device for managing the network slice load; determining, by a CN device, the network slice load at the base station based on the response message; and managing, by a CN device, the network slice load at the base station.

Method and system for managing network slice load in wireless network

The present disclosure relates to a pre-5-Generation (5G) or 5G communication system to be provided for supporting higher data rates Beyond 4-Generation (4G) communication system such as Long Term Evolution (LTE). Embodiments of present disclosure relates to apparatus and method for enabling optimized decoding of data packet in HARQ based communication in wireless communication network. Initially, unsuccessful decoding of instant data packet received from transmitting unit is identified. If number of previous data packets, received preceding the instant data packet, is greater than one, subsequent decoding is enabled in the receiving unit for the instant data packet. The subsequent decoding includes generating sequentially, modified versions of data packets, for decoding. The modified versions comprises all possible weighted combinations of the data packets with at least one of the instant data packet and one or more of the previous data packets. Each of the modified versions is decoded individually and a subsequent modified version from the modified versions is generated when unsuccessful decoding is identified for previously generated modified version from the modified versions.

Method and apparatus for enabling optimized decoding of data packet in HARQ based communication

The disclosure relates to a communication method and system for converging a fifth-generation (5G) communication system for supporting higher data rates beyond a fourth-generation (4G) system with a technology for Internet of Things (IoT). The disclosure may be applied to intelligent services based on the 5G communication technology and the IoT-related technology, such as a smart home, a smart building, a smart city, a smart car, a connected car, health care, digital education, smart retail, security and safety services. A method for predicting channel quality status (CQS) in a wireless network by a base station (BS) is provided. The method includes receiving channel quality indicator (CQI) reports, pre-coding matrix index (PMI) reports, and rank index (RI) reports of first frequency band of a plurality of frequency bands in the wireless network, storing the CQI reports, the PMI reports, and the RI reports of the first frequency band, and predicting the CQI, the PMI and the RI of a second frequency band of the plurality of frequency bands associated with the UE based on the CQI reports, the PMI reports, and the RI reports of the first frequency band.

Method and system for channel quality status prediction in wireless network using machine learning

Embodiments herein provide a method for generating a real-time radio coverage map in a wireless network by a network apparatus. The method includes: receiving real-time geospatial information from one or more geographical sources in the wireless network; determining handover information of at least one user equipment (UE) in the wireless network from a plurality of base stations based on the real-time geospatial information; and generating the real-time radio coverage map based on the handover information of at least one UE and the real-time geospatial information.

Method and network apparatus for generating real-time radio coverage map in wireless network

The present disclosure relates to a pre-5-Generation (5G) or 5G communication system to be provided for supporting higher data rates Beyond 4-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.

Methods and systems for optimizing computation of log-likelihood ratio (LLR) for decoding modulated symbols

Disclosed herein is a method and a network for managing resources in a network. The method comprises determining a predefined number of repetitions of data packets for receiving the data packets from a user equipment (UE) associated with a network node. Further, a minimum number of repetitions, out of the predefined number of repetitions, required for successfully decoding the data packets received from the UE is estimated based on one or more network status parameters. Thereafter, the data packets are decoded within the minimum number of repetitions and one or more resources allocated for remaining number of repetitions are released, thereby optimally managing the resource utilization in the network.

Method and system for optimal resource management in a network

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.

Method and apparatus to decode packets to compute log likelihood ratio in wireless network

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.

Smart decoder

The present disclosure relates to a method and an apparatus for decoding data packets in communication network. The method comprises receiving one or more data packets related to each of one or more data types; and decoding the one or more data packets using a parity check matrix associated with the corresponding data type, wherein the parity check matrix comprises a plurality of layers, arranged according to a combination of layers which is determined using a reinforcement model.

Method and apparatus for decoding data packets in communication network

A Method and a system for securing a SDN controller from denial of service attack are provided. A SDN controller receives, from a networking device, data packets pertaining to a flow in Packet_IN messages, if the flow does not match flow entries in a first flow table of the networking device. A table miss flow entry pertaining to the flow is created in a second flow table of the networking device for sending the Packet_IN. The SDN controller installs a flood prevention flow entry in the second flow table to enable the networking device to drop subsequent data packets pertaining to the flow until the SDN controller installs, in the first flow table, a flow entry matching the flow. The flood prevention flow entry is deleted from the second flow table after the installation of the flow entry matching the flow.

Methods and system for securing a SDN controller from denial of service attack

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.

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Bengaluru, India

Satya Kumar Vankayala