Apple Inc.

Samsung Electronics Co., Ltd.

Amgen Inc.

Surrozen Operating, Inc.

The University of Texas System

Other

Dialog Semiconductor Gmbh

Hush, Inc.

Google Inc.

Intuit, Inc.

Iwatt Inc.

University of California

Yang Li

Zhu Ji

Johnson O Sebeni

Dawei Zhang

Wei Zeng

Yuchul Kim

Jia Tang

Tianyan Pu

Sami M Almalfouh

Wei Zhang

Beibei Wang

Haitong Sun

Jianzhong Zhang

Young-Han Nam

Eko Nugroho Onggosanusi

Md Saifur Rahman

Haijing Hu

Xiangying Yang

Li Su

Boon Loong Ng

Rui Wang

Ian Nevin Foltz

Chadwick Terence King

Vijay Venkataraman

Christian W Mucke

Aaron Sato

Pengkai Zhao

Yu Zhang

Ping Wang

Sudhir Ramakrishna

Taeyoung Kim

Li Guo

Gang Xu

John William Kesterson

Bin Wu

Gunasekaran Kannan

Kyung-joong Kim

Hoondong Noh

Chaohao Wang

Farouk Belghoul

Dongwook Kim

Zhibing Ge

Sridhar Rajagopal

Michael Andrew Cleron

Xiaowen Wang

Namjeong Lee

Dianne K Hackborn

Shadi Abu-Surra

Jeonghoon Sun

Bei Shan

Wanping Zhang

Yuan Cheng

Hao Lu

Yeqing Hu

Wen-Chen Yeh

Junmo Sung

Junsung Lim

Shaw-Fen Sylvia Hu

Taruna Arora

Robert W Monroe

Jin Yuan

Helene Baribault

Jinming Gao

Young Han Nam

Yu-Lin Wang

Randall J Brezski

Yiguang Wang

Baran D Sumer

Xiaoyan Wang

Yan Xin

John Gordon Allen

Leslie Phillip Miranda

Zheng Zhang

Gary Xu

Junming Yie

Xiaokai Li

Jackie Zeqi Sheng

Mark Leo Michaels

Derek Evan Piper

Xuecheng Jin

YuMei Xiong

Zhulun Wang

Gilwon Lee

Xianwei Zhao

Tharathorn Joy Rimchala

Yi Su

Khadijeh Bayat

Sunny Arora

Xiantao Sun

Jungsuek Oh

Avery P Yuen

Alex H Pai

David T W Wong

Sheng Xu

Young Jae Kim

Khalil Haddad

Alice Bakker

Christopher Murawsky

Wonbin Hong

A method includes determining estimated features comprising second order statistics based on at least one received signal. The method also includes classifying, using a machine learning network, each channel of the at least one received signal into a channel profile based on the estimated features. The method also includes obtaining multiple minimum mean square error (MMSE) channel estimation weights from a database based on the estimated features, the database storing (i) representative MMSE estimation weights and (ii) channel cluster representatives indexed by the estimated features. The method also includes applying a respective MMSE channel estimation weight for each channel.

AI-augmented channel estimation

Calibration in distributed multiple input multiple output (MIMO) networks. A method performed by a first base station (BS) includes receiving a first uplink (UL) reference signal (RS) and determining, based on the first UL RS and a second UL RS, a first phase offset for transmission of a first downlink (DL) RS to a user equipment (UE). The second UL RS is associated with a second BS. The first phase offset of the first DL RS is relative to a second DL RS associated with the second BS. The method further includes transmitting the first DL RS with the first phase offset; receiving UE feedback associated with the first DL RS and the second DL RS; and determining, based on the first phase offset and the received feedback, for a DL data transmission to the UE, a second phase offset between transmissions of the first BS and the second BS.

Method and apparatus for calibration in distributed mimo networks

The present disclosure provides tissue-specific Wnt signal enhancing molecules, and related methods of using these molecules to increase Wnt signaling in liver tissues.

Tissue-specific WNT signal enhancing molecules and uses

A network entity includes a memory and a processor operable coupled to the memory. The processor is configured to determine a hybrid joint transmission (Hybrid-JT) signal for transmission from a wireless network associated with the network entity to a user equipment (UE). The Hybrid-JT signal includes a diversity joint transmission (Div-JT) component and a multiplexing joint transmission (Mux-JT) component. The processor is further configured to instruct the wireless network to transmit the Hybrid-JT signal to the UE.

Hybrid joint transmission for multiple antenna coordinated multipoint systems

A method performed by a network entity includes determining a target timing mismatch for a phase timing slope between first and second channel state information-reference signal (CSI-RS) resources, and determining, based on the target timing mismatch, a first band separation between a first calibrated phase for the first the second CSI-RS resource and a second calibrated phase for the first and the second CSI-RS resource. The method further includes determining a first frequency band for the first calibrated phase, and determining, based on the band separation, a second frequency band for the second calibrated phase. The method further includes determining, based on the band separation between the first calibrated phase the second calibrated phase, a first phase timing slope between the first the second CSI-RS resource, and performing joint transmission from a first TRP and a second TRP based on the first phase timing slope.

Phase-timing calibration algorithm for distributed MIMO using CSI-RS resources

A method of operating a network entity includes receiving, via a first TRP and a second TRP, information associated with a SRS from a UE, and estimating a channel based on the information associated with the SRS. The method further includes, for N iterations: transmitting, via a first CSI-RS port from a CSI-RS resource, from the first TRP, a CSI-RS; transmitting, via a second CSI-RS port from the CSI-RS resource, from the second TRP, the CSI-RS with a controlled phase offset; receiving a PMI report associated with the CSI-RS including a measured phase offset between the first CSI-RS port and the second CSI-RS port; and updating the controlled phase offset, based on the measured phase offset. The method further includes, after the N iterations, based on the controlled phase offset and the measured phase offset, determining a phase mis-match for phase calibration between the first TRP and the second TRP.

Distributed MIMO calibration

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 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 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

The present invention provides Wnt pathway agonists and related compositions, which may be used in any of a variety of therapeutic methods for the treatment of diseases.

Wnt surrogate molecules and uses thereof

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 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

The present disclosure provides liver-specific Wnt signal enhancing molecules, and related methods of using these molecules to increase Wnt signaling in liver tissues and treat liver diseases and disorders.

Liver-specific Wnt signal enhancing molecules and uses thereof

Apparatuses, systems, and methods for a wireless device to perform substantially concurrent communications with a next generation network node and a legacy network node. The wireless device may be configured to stablish a first wireless link with a first cell according to a RAT, where the first cell operates in a first system bandwidth and establish a second wireless link with a second cell according to a RAT, where the second cell operates in a second system bandwidth. Further, the wireless device may be configured to perform uplink activity for both the first RAT and the second RAT by TDM uplink data for the first RAT and uplink data for the second RAT if uplink activity is scheduled according to both the first RAT and the second RAT.

TDM transmission for inter-RAT dual connectivity UE

A downlink control information (DCI), such as a blanking DCI (bDCI) message may be transmitted by a base station (e.g., eNB) and received by a mobile device (e.g., UE). The bDCI may indicate that the eNB will not transmit a subsequent DCI to the UE for a duration of time. The UE may be in continuous reception mode or connected discontinuous reception (C-DRX) mode. The UE may therefore determine to enter a sleep state or take other action. The bDCI may specify an explicit blanking duration, or an index indicating a blanking duration from a lookup table, and/or the blanking duration (and/or a blanking duration offset value) may be determined in advance, e.g., semi-statically. When the UE is in C-DRX mode, the UE may be configured such that either the sleep/wake period of the C-DRX mode or the blanking period of the bDCI may take precedence over the other.

Control channel for UE power saving

Growing community of inventors

Plano, TX, United States of America

Yang Li