Texas Instruments Corporation

Cisco Technology, Inc.

Samsung Electronics Co., Ltd.

Wildfire.exchange, Inc.

Plume Design, Inc.

Facebook, Inc.

Egnyte, Inc.

Apple Inc.

University of Texas System

Vikram Chandrasekhar

Runhua Chen

Eko Nugroho Onggosanusi

Anthony Edet Ekpenyong

Andrea Goldsmith

Ritesh Kumar Madan

Santhosh Krishna

Kedar Shirali

Ritesh Madan

Rohit U Nabar

Qing Zhao

Young-Han Nam

Boon Loong Ng

Rajesh S Pazhyannur

Hao Chen

Jianzhong Zhang

William John McFarland

Amrit Jassal

Qinghai Gao

Andrew Frederick Myles

Balaji Rengarajan

Debjit Bhattacharjee

Willy Lanig Picard

Marcin Artur Zablocki

Tomasz Marek Kaczmarek

Li Guo

James Wesley McCoy

Ahsan Aziz

James Paul Seymour

Russell Douglas Ford

Jeffrey G Andrews

Pranav Madadi

Ralf Matthias Bendlin

Brian Donald Hart

Hongbo Si

Pierre Bertrand

Jaewon Kim

Saidhiraj Amuru

Ahmadreza Hedayat

Yan Xin

Sangkyu Park

Yongseok Park

Yeqing Hu

Hakyung Jung

Chao He

Mandar Narsinh Kulkarni

Pengda Huang

Raymond Yuk Chor Kwan

Eric Earl Johnson

Chance Tarver

Sushanth Chandappa Kulal

Yuqiang Heng

Shan Jin

Kedar Durgadas Shirali

Ritesh K Madan

Rohit Umesh Nabar

A base station selects a subset of at least one geographically separated antennas for each of the plurality of user equipments. The base station forms at least layer of data stream including modulated symbols, precodes the data stream via multiplication with the NT-by-N precoding matrix where N is the number of said layers and NT is the number of transmit antenna elements and transmits the precoded layers of data stream to the user equipment via the selected geographically separated antennas. The base station signals the subset of the plurality of geographically separated antennas via higher layer Radio Resource Control or via a down link grant mechanism. The base station optionally does not signal the subset of the plurality of geographically separated antennas to the corresponding mobile user equipment.

Downlink multiple input multiple output enhancements for single-cell with remote radio heads

A wireless transmission system included at least one user equipment and a base station. The base station is operable to form a downlink control information block, modulate the downlink control information, precode the modulated downlink control information, and transmit the precoded, modulated downlink control information on at least one demodulation reference signal antenna port to the at least one user equipment. The precoded, modulated downlink control information is mapped to a set of N1 physical resource block pairs in a subframe from an orthogonal frequency division multiplexing symbol T1 to and orthogonal frequency division multiplexing symbol T2.

Physical downlink control channel and physical hybrid automatic repeat request indicator channel enhancements

Systems and methods for serving subject access requests (SARs) are disclosed. A network connection is established with a user. An SAR, including at least one piece of personal data corresponding to an entity associated with said user, is received from the user via the network connection. Text data is extracted from a plurality of data objects, the data objects including personal data associated with the user. The text data is then processed to identify instances of names and instances of personal data within the text data. Associations are generated between identified names and identified personal data. A subset of the identified personal data that corresponds to the entity is identified based on the associations. A response to the SAR is provided, based at least in part on the identified personal data corresponding to the entity.

System and method for serving subject access requests

Systems and methods for Wi-Fi network optimization include receiving inputs related to signal strength and interference during operation of the Wi-Fi network; performing an optimization to determine operational parameters of one or more access points in the Wi-Fi network, wherein the optimization is based on the inputs and is configured to address an objective associated with the Wi-Fi network; and providing outputs comprising the operational parameters for configuration of the Wi-Fi network, based on the optimization, wherein the operational parameters include channel and bandwidth selection, and topology of the one or more access points.

Optimization of distributed Wi-Fi networks

A UE includes a transceiver configured to receive, from a base station, a higher layer parameter that is set as enabled or disabled. The higher layer parameter is explicitly or implicitly determined to be disabled by Boolean parameters or DL DCI format types. The UE also includes a controller configured to, based on identifying that the higher layer parameter is set as enabled either on per CORESET basis or on per DCI format basis, assume that, for receiving a PDSCH, an indication state is present in a DL DCI transmitted by a PDCCH on a CORESET, wherein the indication state indicates an associated PDSCH QCL parameter. A transceiver receives the associated PDSCH using the QCL parameter from the base station.

Configuration of beam indication in a next generation mmWave system

A method of a user equipment (UE) for control resource set (CORESET) configuration in a wireless communication system is provided. The method comprises receiving, from a base station (BS), system information, determining whether the system information includes a random access channel (RACH) CORESET configuration, determining a CORSET to use for transmitting data based on whether the RACH CORESET configuration is included in the system information, and receiving, from the BS, the data based on the determined CORESET over an RACH.

Method and apparatus for control resource set configuration for 5G next radio system

A method and user equipment for channel state information (CSI) reporting are described. The method receives a channel quality indicator request. The method determines a channel quality indicator based on a CSI reference resource. The method transmits a CSI report that includes the channel quality indicator via a Physical Uplink Control CHannel (PUCCH) on an uplink subframe. The CSI reference resource belongs to a subframe subset for which the CSI report is sent. The CSI reference resource includes overhead of Demodulation Reference Signals according to a corresponding rank report.

CSI reporting

Apparatuses and methods for identifying network anomalies. A method includes determining a cumulative anomaly score over a predefined time range based on a subset of historical PM samples and determining an anomaly ratio of a first time window and a second time window, based on the cumulative anomaly score. The method also includes determining one or more anomaly events coinciding with CM parameter changes based on the anomaly ratio; collating the PM, alarm, and CM data into a combined data set based on matching fields and timestamps; generating a set of rules linking one or more CM parameter changes and the collated data to anomaly events; and generating root cause explanations for CM parameter changes that are linked to anomaly events.

Configuration management and analytics in cellular networks

An apparatus for performing a wireless communication includes a communication interface configured to measure uplink (UL) Sounding Reference Signals (SRSs) transmitted from a mobile client device, and at least one processor configured to buffer a number of uplink (UL) SRS measurements derived from UL SRS transmissions of the mobile client device, the number of UL SRS measurements exceeding a threshold, extract features from UL SRS measurements, obtain a machine learning (ML) classifier for determining a category to be used for estimating mobility associated with the mobile client device, and determine the category of the mobile client device by applying the extracted features to the ML classifier. Methods and apparatus extract the features of either a set of power spectrum density measurements or a set of pre-processed frequency domain real and imaginary portions of UL SRS measurements and feed the features to an AI classifier for UE speed estimation.

Method and apparatus for AI-based UE speed estimation using uplink SRS measurements

A method for discovering and diagnosing network anomalies. The method includes receiving key performance indicator (KPI) data and alarm data. The method includes extracting features based on samples obtained by discretizing the KPI data and the alarm data. The method includes generating a set of rules based on the features. The method includes identifying a sample as a normal sample or an anomaly sample. In response to identifying the sample as the anomaly sample, the method includes identifying a first rule that corresponds to the sample, wherein the first rule indicates symptoms and root causes of an anomaly included in the sample. The method further includes applying the root causes to derive a root cause explanation of the anomaly and performing a corrective action to resolve the anomaly based on the first rule.

Root cause analysis and automation using machine learning

Growing community of inventors

Mountain View, CA, United States of America

Vikram Chandrasekhar