Samsung Electronics Co., Ltd.

Seungil Yoon

Satya Kumar Vankayala

Dongwook Kim

Jaemyung Hur

Eungsik Yoon

Kwanyoung Kim

Jungseop Kim

Suhwan Jin

Kunsok Kang

Hojune Yoo

Taedon Hwang

Minsup Kim

Eunseok Choi

Ashvin Kaithara Joseph

Hyunkyu Yun

Swaraj Kumar

Daeyeon Yun

Anshuman Nigam

Avinash Bhat

Joonhyun Yang

Abhay Kumar Sah

Issaac Kommineni

Wonjae Lee

Shweta Madhurapantula

Satish Kumar

Satya Venkata Uma Kishore Godavarti

Sungho Chae

Suman Kumar

Rajesh Challa

Pankaj Bhimrao Thorat

Sukhdeep Singh

Byungseok Soh

Naman Gupta

Raviteja Gundeti

Sukhmeet Singh

Tirthankar Mittra

Venkateswarlu Yarramala

Samuel Ignatius Kanakaraj

Sudharsan Parthasarathy

Rahul Banerji

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

An operating method of the display device includes detecting, through at least one sensor, at least one sensing value corresponding to the at least one sensor, identifying a touch area on the display device that is touched by a mobile device, based on the at least one sensing value, receiving status information about an operation that is being executed by the mobile device, from the mobile device, and performing a function corresponding to the identified touch area, based on the received status information.

Display device and operating method thereof

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

A projector device comprises: an image projection unit for projecting a guide image including a plurality of first objects; a camera; and a processor for obtaining a captured image acquired by the camera, the captured image including a guide image projected through the image projection unit. The processor identifies first location information corresponding to a location of each of a plurality of first objects included in the obtained captured image, identifies second location information corresponding to a location of each of a plurality of second objects related to the plurality of first objects, respectively, on the basis of the obtained captured image, and acquires image correction information on the basis of the first location information and the second location information.

Projector and control method therefor

Provided is a control apparatus including a key input interface including a plurality of keys, a communication interface configured to communicate with an electronic device, a memory storing store one or more instructions, and a processor configured to execute the one or more instructions stored in the memory to detect whether a power of the electronic device is turned on or turned off, and control the control apparatus to operate in a first mode, based on detecting that the power of the electronic device is turned off, wherein the operating in the first mode includes operating a pre-determined first key from among the plurality of keys in an interrupt mode, and not operating a second key other than the first key from among the plurality of keys.

Control apparatus and operating method thereof

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 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

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

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 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.

Method and device for decoding data

An electronic apparatus including at least one interface; and at least one processor configured to: register a first user account with a first server configured to provide a first service, through the at least one interface, identify a second server corresponding to an external apparatus connectable through the at least one interface, wherein the second server is configured to provide a second service different from the first service, register the first user account with the second server through the at least one interface to link the first user account to a second user account corresponding to the second service, and perform a linkage service operation based on the first service and the second service, using the first user account and the second user account.

Electronic apparatus and control method thereof

Disclosed are a display apparatus and a method of controlling the same. a display apparatus including: a display; an optical sensor; and a processor configured to: identify an operation cycle shorter than an idle section of an infrared (IR) signal and including at least a part of a section for a detection operation of the optical sensor, based on the IR signal of which a signal section corresponding to a user key input and the idle section are repeated on a predetermined cycle, control the optical sensor to repetitively perform the detection operation on the identified operation cycle, and perform a predetermined operation based on a detection value obtained by the detection operation of the optical sensor.

Growing community of inventors

Suwon-si, South Korea

Seungil Yoon