Samsung Electronics Co., Ltd.

Nokia Corporation

Parion Sciences, Inc.

E.i. Dupont De Nemours and Company

Siemens Medical Solutions Usa, Inc.

Intrexon Corporation

Qualcomm Incorporated

Other

Google Inc.

Motorola Mobility LLC

Jianzhong Zhang

Young-Han Nam

Boon Loong Ng

Farooq Khan

Zhouyue Pi

Lingjia Liu

Jin-Kyu Han

Aris Papasakellariou

Joonyoung Cho

Juho Lee

Yang Li

Krishna Kamal Sayana

Hao Chen

Yeqing Hu

Ju-Ho Lee

Michael Ross Johnson

Young-Bum Kim

Bruce Francis Molino

Gary Xu

Eko Nugroho Onggosanusi

Cornelius Van Rensburg

Hwan-Joon Kwon

Thomas David Novlan

Jianhua Mo

Joon-Young Cho

Ying Li

Ahmed Atef Ibrahim Ibrahim

Rui Wang

Christian Peter Lenges

Richard C Ebersole

Hartmuth C Kolb

Yan Xin

Arkadij M Elizarov

Mario W Chen

Jiann-An Tsai

Vishnu Vardhan Ratnam

Gang Xu

Younsun Kim

Hyojin Lee

Won Suk Choi

Sridhar Rajagopal

Shadi Abu-Surra

Subba Reddy Palli

Himke Van Der Velde

Dean Ervin Cress

Yingyang Li

Md Saifur Rahman

Jeongho Jeon

Joon Young Cho

Jin Kyu Han

Li Guo

Vikram Chandrasekhar

Giridhar Dhati Mandyam

Gilwon Lee

Young Han Nam

Youn-Sun Kim

Yan E Wang

Ju Ho Lee

Balaji B Raghothaman

Bruno Clerckx

Namjeong Lee

Sudhir Ramakrishna

Yuming Zhu

Tejas Maheshbhai Bhatt

Yinong Ding

Rubayet Shafin

Jinkyu Han

Youn Hyoung Heo

Robert W Monroe

Hoondong Noh

Kenneth Anderson Stewart

Raja Sekhar Bachu

Wenxun Qiu

Zinan Lin

R Michael Van Dam

Abhishek Sehgal

Sean Ford

Zhijun Cai

Taeyoung Kim

Soeng-hun Kim

Hongbo Si

Ji-Yun Seol

Qiong Cheng

Richard Stirling-Gallacher

Youn Sun Kim

Richard C Boucher

Saidhiraj Amuru

Kaushik Morapakkam Josiam

Haihong Zheng

Kiran Bynam

Yousuf Saifullah

Michael Royce Johnson

Stephen R Fahnestock

Aditya V Padaki

Sangkyu Park

Yongseok Park

Myung Hoon Yeon

Joseph R Cavallaro

Tanja Maria Gruber

Error-correcting performance of polar codes is improved by assigning parity check bits to small, reliable indices. Zeros are assigned to message indices not among a most-reliable set of the message indices, information bits and parity check bits are assigned to the most-reliable set of the message indices, with the parity check bits generated on the information bits assigned to the smallest of the most-reliable set and then assigned to the smallest indices of the most-reliable set that follow the information bits on which the parity check pits are generated. During successive cancellation list decoding, the parity check bits allow error events to be promptly corrected during decoding.

Method for polar code design with parity check bits

A method includes obtaining Wi-Fi channel state information (CSI) parameters measured at an anchor and a target device from Wi-Fi frames transmitted between the anchor and the target device, the CSI parameters comprising, for each of the anchor and the target device, frame transmission and reception times, a carrier phase of the CSI, a crystal offset factor, and a packet detection time error. The method also includes determining a round trip time (RTT) estimate or a relative change in the RTT estimate as a function of the CSI parameters. The method further includes estimating a range between the anchor and the target device as a function of the RTT estimate, or estimating a change in the range between the anchor and the target device as a function of the relative change in the RTT estimate.

Wi-Fi based fine ranging using carrier phase information

A hybrid MIMO system comprises N digital transceiver chains and N analog beamformers, each coupled to one of the digital transceiver chains and comprising M analog transmitter (TX) chains and M analog receiver (RX) chains. One of the analog RX chains is an RX reference node and one of the analog TX chains is a TX reference node. A processor is coupled to a calibration transceiver, the transceiver chains, and the beamformers. For each beamformer the processor measures, using the corresponding transceiver chain and the calibration transceiver, TX and RX phase responses and TX and RX magnitude responses of the TX and RX reference nodes, respectively, determines a reciprocity calibration based on a phase difference between the TX and RX phase responses and a magnitude difference between the TX and RX magnitude responses, and applies the reciprocity calibration to stored beam definitions to correct for the phase and magnitude differences.

Hierarchical beamforming and reciprocity calibration for hybrid MIMO systems

Methods and apparatuses in a wireless communication system. A base station (BS) includes a transceiver and a processor. The processor is configured to receive, via the transceiver, a channel state information (CSI) report from at least one user equipment (UE). The processor is also configured to configure CSI-reference signal (RS) resources for the at least one UE. The processor is further configured to, based on the CSI report from the at least one UE, perform one of: set a transmission power to full power for transmission in a physical downlink shared channel (PDSCH); or apply a back-off percentage to the transmission power in the PDSCH.

Hybrid PDSCH for out-of-band earth station interference cancelation

A two-dimensional constellation for data signals having improved bitwise mutual information of data points is based on a signal-to-noise ratio (SNR) and a code rate where, based on the SNR, data bits are mapped to pre-defined in-phase and quadrature values. The in-phase and quadrature values denote points in the two-dimensional space such that the efficiency of bitwise mutual information is adapted based on the SNR. The mapping is preferably subject to a constraint selected from one of quadrant symmetry Lagrangian (QSL), quadrant symmetry constraint (QSC), or rectangular structure constraint (RSC).

AI/ML empowered high order modulation

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.

Low complexity machine learning based channel classifier

Methods and apparatuses for uplink (UL) coverage enhancements with joint phase-time arrays (JPTAs). A method for operating a base station (BS) includes identifying criteria associated with a set of user equipments (UEs) in a cell of the BS and determining, based on the criteria, a first subset of the set of UEs to use a JPTA beamforming. The method further includes using the JPTA beamforming for signaling with the first subset of UEs and using an analog beamforming for signaling with a second subset of UEs in the set of UEs.

Uplink coverage using joint phase-time arrays

A system and method for an indoor position localization of a target device is provided. A network comprising a server and a plurality of anchors is configured to fuse two radio technologies to estimate a location of the target device within an indoor facility. The method includes obtaining, via a first radio technology, a first candidate location of a target device. The method also includes obtaining, via a second radio technology, a plurality of second candidate locations of the target device. The method further includes selecting one of the second candidate locations as an estimated position of the target device based on a proximity of each of the second candidate locations to the first candidate location.

Method and apparatus for positioning system with multiple radio access technologies

Methods and apparatuses for canonical model (CM) based channel status information enhancement. A base station includes a transceiver configured to receive a reference signal from a user equipment (UE) and a processor operably coupled to the transceiver. The processor is configured to perform a linear transformation based on the received reference signal, select a basis set based on the linear transformation, select a set of kernels based on the selected basis set and the linear transformation, and reconstruct a channel based on the selected set of kernels.

CM based channel status information enhancement

A method includes, when a handheld device is in motion within a service area to be traversed by a robot: obtaining ultra-wideband (UWB) ranging measurements between the handheld device and multiple anchors located in the service area; and obtaining image data and inertial measurement unit (IMU) data. The method also includes determining a trajectory of motion of the handheld device based on the UWB ranging measurements. The method also includes adjusting the trajectory based on image features obtained from the image data and motion estimates obtained from the IMU data. The method also includes identifying the adjusted trajectory as a boundary of the service area.

System and method for RF based robot localization

A method and device for self-tuning scales of variables for processing in fixed-point hardware. The device includes a sequence of fixed-point arithmetic circuits configured to receive at least one input signal and output at least one output signal. The circuits are preconfigured with control scales associated with each of the input and output signals. A first circuit in the sequence is configured to receive a first input signal having a dynamic true scale that is different from the control scale associated with the first input signal. Each of the circuits is further configured to determine, for each of the output signals, an adaptive scale from the control scale associated with the output signal based on the true scale of the first input signal and the control scale associated with the first input signal, and generate, from the input signal, the output signal having the associated adaptive scale.

Self-tuning fixed-point least-squares solver

A method includes partitioning a set of configuration management (CM) data for one or more cellular network devices into multiple distinct time intervals, each time interval associated with a distinct set of CM settings at the one or more cellular network devices, the CM data comprising multiple CM parameters. The method also includes determining a regression model based on the set of CM data. The method also includes applying the regression model to compute a distinct set of scores and compare the set of scores to estimate whether a performance of the one or more cellular network devices has changed during a second time interval relative to a first time interval.

Automatically using configuration management analytics in cellular networks

A method includes identifying ACF information by: obtaining channel information including multiple channels of expected operation scenarios; and based on the channel information for each of the channels, determining MMSE channel estimation (CE) weights expressed in a form of ACFs and an SNR, and covariance matrices. The method includes clustering the MMSE CE weights into K clusters. A center ACF weight of each of the K clusters represents a codeword. The method includes determining a distance metric based on a cluster distance after a re-clustering. The method includes, in response to a determination that cluster distances before and after the clustering differ from each other by a non-negligibly, iteratively re-clustering the ACF information thereby updating the center ACF weights and cluster distances. The method includes generating the codebook to include an index k of each of the K clusters and the center ACF weight of each of the K clusters.

Codebook for AI-assisted channel estimation

Capability of a user equipment to support machine learning adaptation by a base station of a reference signal pattern is signaled between the base station and the user equipment. Configuration information from the base station indicates one or more of enabling or disabling of machine learning adaptation of the reference signal pattern, a machine learning model used for machine learning adaptation of the reference signal pattern, updated model parameters for the machine learning model, or whether model parameters received from the user equipment will be used for machine learning adaptation of the reference signal pattern. Model training may be performed or model parameters received, and reference signals are received from the base station. Information on a reference signal pattern may be transmitted by the user equipment to the serving base station. Assistance information may be transmitted by the user equipment to the base station, which configures a reference signal pattern.

Method and apparatus for reference symbol pattern adaptation

A method includes determining one or more delay values and one or more phase shift values for generation of multiple desired frequency-dependent analog beams. The method also includes configuring one or more true-time delay (TTD) elements and one or more phase shifters of a transceiver based on the one or more delay values and the one or more phase shift values, the transceiver having one or more radio-frequency (RF) chains connected to multiple antennas via the one or more TTD elements and the one or more phase shifters. The method also includes operating the transceiver to generate the multiple desired frequency-dependent analog beams.

System and method for time-delay based hybrid beamforming

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Plano, TX, United States of America

Jianzhong Zhang