Origin Wireless, Inc.

Apple Inc.

Origin Research Wireless, Inc.

Qualcomm Incorporated

University System of Maryland

Beibei Wang

K J Ray Liu

Oscar Chi-Lim Au

Zhu Ji

Johnson O Sebeni

Jia Tang

Chenshu Wu

Hung-Quoc Duc Lai

Dawei Zhang

Feng Zhang

Yang Li

Wei Zeng

Wei Zhang

Sami M Almalfouh

Tianyan Pu

Yuchul Kim

Yi Han

Haitong Sun

Chen Chen

Qinyi Xu

Haijing Hu

Dan Bugos

Xiangying Yang

Min Wu

Chao-Lun Mai

Sai Deepika Regani

Yuqian Hu

Vijay Venkataraman

Pengkai Zhao

Zhung-Han Wu

David N Claffey

Hangfang Zhang

Christian W Mucke

Chau-Wai Wong

Muhammed Zahid Ozturk

Yan Chen

Zoltan Safar

Fangli Xu

Yuqin Chen

Srinivasan Nimmala

Sethuraman Gurumoorthy

Longda Xing

Srirang Ashok Lovlekar

Sree Ram Kodali

Muthukumaran Dhanapal

Lele Cui

Xiantao Sun

Li Su

Murtaza A Shikari

Ping Wang

Zhiwei Wang

Swaminathan Balakrishnan

Sachin J Sane

Sai Sravan Bharadwaj Karri

Yaoqi Yan

Yu-Lin Wang

Yu-Han Yang

Manish G Vemulapalli

Bilal Sadiq

Saurabha Rangrao Tavildar

Zheng Zhang

Sunny Arora

Shreeshankar Ravishankar Bodas

Qiao Li

Hsi-Jung Wu

Sharad Deepak Sambhwani

Jianxiong Shi

Xiaosong Zhou

Xin Ru Wang

Rohit Kapoor

Farouk Belghoul

Lakshmi N Kavuri

Yongle Wu

Dazhong Zhang

Xiaowen Wang

Christopher M Garrido

Thanigaivelu Elangovan

Yifan Zhu

Karthick Santhanam

Karthik Anantharaman

Ming Jin

Hang Yuan

Vijay Kumar Ramamurthi

Eric L Chien

Xiaohua Yang

Peikang Song

Xiangpeng Jing

Sang Ho Baek

Feng Han

Adesh Kumar

Albert E Keinath

Hang Ma

Xueting Liu

Erdogan Dede

Vikrant Kasarabada

Zhao Wang

David R Conrad

Hailong Yang

Apparatuses, systems, and methods for a wireless device to perform beam management procedures with a base station. A wireless device in communication with a 5G base station may perform measurements and determine constraints relevant to beam selection. The device may select a recommended beam based on the measurements and constraint(s) and indicate the recommended beam to the base station. A recommended uplink beam may not correspond to a recommended downlink beam.

Beam management without beam correspondence

Wireless sensing using classifier probing and refinement is described. In one example, a described method comprises: computing output analytics by a classifier based on input data constructed based on raw measurement data; mapping each output analytics to a respective mapped outcome; identifying at least one reference input data each associated with a reference output analytics and a reference mapped outcome; each reference input data being one of the input data for the classifier for which a respective reference outcome is available and is different from the reference mapped outcome; and for each reference input data for the classifier: computing a respective plurality of perturbed output analytics by the classifier, generating selected perturbed input data based on the plurality of perturbed output analytics; and re-training the classifier based on the selected perturbed input data and the associated reference outcome.

Wireless sensing using classifier probing and refinement

Methods, apparatus and systems for wireless sensing are described. In one example, a described system in a wireless data communication network comprises: a transmitter configured to transmit a time series of at least one wireless sounding signal (WSS) based on a standard wireless network protocol associated with the wireless data communication network, and a receiver. The wireless data communication network comprises a physical (PHY) layer, a medium access control (MAC) layer, and at least one higher layer. The receiver is configured to: receive the time series of at least one WSS (TSWSS) based on the standard wireless network protocol through a wireless channel of a venue, and perform a plurality of wireless sensing measurements based on the received TSWSS to obtain sensing measurement results based on the standard wireless network protocol. The PHY layer or the MAC layer of the receiver provides the sensing measurement results locally to the at least one higher layer of the receiver based on the standard wireless network protocol. The sensing measurement results are available to the at least one higher layer of the receiver for performing a sensing-based task based on the sensing measurement results.

Method, apparatus, and system for wireless sensing measurement and reporting

Devices and associated methods for operating a dual-subscriber identity module (SIM) dual-standby (DSDS) user equipment device (UE) configured with a first SIM and a second SIM. The UE performs communications with a first cellular network using the first SIM and a first radio resource control (RRC) connection, and receives a request to perform a higher priority communication using the second SIM. In response to the request to perform the higher priority communication, the UE transmits a request to the first network to suspend the first RRC connection. After transmission of the request to suspend the first RRC connection, the UE receives a message from the first network to place the first RRC connection in an inactive state, and initiates a timer, wherein the timer is used to determine whether the first RRC connection remains in the inactive state or transitions to an idle state.

User equipment having multiple subscriber identity modules with improved suspend / resume operation

Apparatuses, systems, and methods for a user equipment device (UE) to perform a method using a status change of a timer associated with a connected mode discontinuous reception (CDRX) communication session with a base station to trigger a switch from using a first bandwidth part (BWP) to a second BWP as the active BWP for the CDRX communication session. The timer may be an on-duration timer, an inactivity timer, or a retransmission timer. The UE may also alter a monitoring schedule of a physical downlink control channel (PDCCH) in response to detecting the status change of the timer. The second BWP may have a wider or narrower bandwidth than the first BWP, depending on the type of timer and the type of status change.

Joint optimization of bandwidth part, search space and connected mode discontinuous reception operation in 5G new radio

A process for dual subscriber identity module (SIM) dual standby (DR-DSDS) operation including receiving event data indicating a trigger event configuring radio frequency (RF) hardware; identifying a conflict between a communication band of a first SIM and a communication band of a second SIM for DR-DSDS operation; determining a type of the conflict; determining, a first priority value for a component carrier (CC) corresponding to the first SIM, and a second priority value for a CC corresponding to the second SIM, the first and second priority values based at least on the type of the conflict; determining a timing scenario for configuring the RF hardware; searching for a RF hardware configuration to resolve the conflict based on the first and second priority values; and generating RF handle data, corresponding to the conflict resolution, specifying a RF hardware configuration for the DR-DSDS operation.

Band conflict resolution for dual receive dual sim dual standby scenarios

A device, system and method for a user equipment (UE) to report a network resource and capability state to a network for coordinating network resource allocations. The UE is configured to establish a first connection to a first network based on a first subscriber identity module (SIM) of the UE and further configured to establish a second connection to a second network based on a second SIM of the UE. The method includes determining an upcoming first change of a state of the UE with respect to the first connection and transmitting, to the first network, an indication of the first change of state of the UE. The method further includes changing the state of the UE with respect to the first connection.

Reporting framework for dynamic UE capabilities

Methods, apparatus and systems for radio-assisted signal estimation are described. In one example, a described system comprises: a sensor configured to obtain a baseband mixture signal in a venue; a transmitter configured to transmit a first radio signal through a wireless channel of the venue; a receiver configured to receive a second radio signal through the wireless channel; and a processor. The baseband mixture signal comprises a mixture of a first source signal and an additional signal. The first source signal is generated by a first motion of a first object in the venue. The second radio signal differs from the first radio signal due to the wireless channel and at least the first motion of the first object in the venue. The processor is configured for: obtaining a radio feature of the second radio signal, constructing a first adaptive filter for the baseband mixture signal based on the radio feature, filtering the baseband mixture signal using the first adaptive filter to obtain a first output signal, and generating an estimation of the first source signal based on the first output signal.

Method, apparatus, and system for speech enhancement and separation based on audio and radio signals

Methods, apparatus and systems for wireless sensing based on deep learning are described. For example, a described method comprises: transmitting a wireless signal through a wireless multipath channel of a venue, wherein the wireless multipath channel is impacted by a motion of an object in the venue; receiving the wireless signal through the wireless multipath channel of the venue, wherein the received wireless signal differs from the transmitted wireless signal due to the wireless multipath channel and the motion of the object; obtaining a time series of channel information (TSCI) of the wireless multipath channel based on the received wireless signal; computing a plurality of autocorrelation functions based on the TSCI, each autocorrelation function (ACF) computed based on CI of the TSCI in a respective sliding time window; constructing at least one ACF vector, wherein each respective ACF vector is a vector associated with a respective ACF comprising multiple vector elements each associated with a respective time lag, each vector element being a value of the respective ACF evaluated at the respective time lag; rearranging the at least one ACF vector into rearranged ACF data, wherein each ACF vector is a one-dimensional (1D) ACF-block; and performing a wireless sensing task based on a task engine to do a processing using the rearranged ACF data as an input.

Method, apparatus, and system for wireless sensing based on deep learning

Wireless sensing for in-vehicle child presence detection is described. In one example, a described method comprises: obtaining a time series of channel information (TSCI) of a wireless channel in a vehicle; computing a motion statistics (MS) based on channel information (CI) of the TSCI in a time period; detecting a motion of a user in the time period by comparing the motion statistics with a first threshold, wherein the motion of the user is detected when the motion statistics exceed the first threshold; constructing a 2-dimensional (2D) transform matrix based on 1-dimensional (D) transforms of CI of TSCI in sliding time windows in the time period; detecting a number of horizontal streaks of the 2D transform matrix; detecting a breathing motion of the user in the time period based on the number of detected horizontal streaks of the 2D transform matrix and an associated criterion.

Wireless sensing for in-vehicle child presence detection

Methods, apparatus and systems for enhanced wireless monitoring of vital signs are described. In one example, a described system comprises: a transmitter configured to transmit a wireless signal through a wireless channel of a venue; a receiver configured to receive the wireless signal through the wireless channel; and a processor. The received wireless signal differs from the transmitted wireless signal due to the wireless channel that is impacted by a periodic motion of a vital sign of an object in the venue. The processor is configured for: obtaining a time series of channel information (CI) of the wireless channel based on the received wireless signal, computing a two dimensional (2D) decomposition of the time series of CI (TSCI), enhancing the 2D decomposition, and monitoring the periodic motion of the vital sign based on the enhanced 2D decomposition.

Method, apparatus, and system for enhanced wireless monitoring of vital signs

Methods, apparatus and systems for wireless monitoring and tracking are described. In one example, a described method of a wireless monitoring system comprises: transmitting a wireless signal that is impacted by a wireless multipath channel in a venue and a modulation of an object undergoing a motion in the venue, to obtain a set of channel information (CI) of the wireless multipath channel; performing a monitoring task by monitoring the object and the motion; determining a plurality of admissible system states of the wireless monitoring system, wherein each admissible system state is associated with a respective setting of at least one of: the wireless signal, a series of sounding signals in the wireless signal, or the monitoring task; choosing one of the admissible system states to be a system state of the wireless monitoring system based on the monitoring task; and applying a setting associated with the chosen admissible system state to the wireless monitoring system.

Method, apparatus, and system for automatic and adaptive wireless monitoring and tracking

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Cupertino, CA, United States of America

Beibei Wang