Samsung Electronics Co., Ltd.

Hongbing Cheng

Kee-Bong Song

Jungwon Lee

Federico Penna

Yanru Tang

Qi Zhan

Jang Wook Moon

Hyukjoon Kwon

Linbo Li

Xiaoqiang Ma

Binnan Zhuang

Bemini Hennadige Janath Peiris

Bofeng Yuan

Jung Hyun Bae

Inyup Kang

Ruchen Duan

Sili Lu

Soobok Yeo

Kwangman Ok

Mehdi Ganji

Mirette Sadek

A system and a method are disclosed for performing data-aided channel tracking for a subcarrier, including obtaining a reference channel estimate (CE) at a first time instance using a reference signal; determining, based on the obtained reference CE and based on received data symbols, a data-aided CE at a second time instance that is subsequent to the first time instance; and sequentially determining one or more additional data-aided CEs, for one or more time instances subsequent to the second time instance, based on a data-aided CE obtained at a previous time instance and based on the received data symbols.

Data-aided channel tracking for OFDM systems

Methods and systems of obtaining a beamforming matrix, the method comprising inputting PMI feedback from a user equipment (UE), inputting partial channel estimation derived from sounding reference signal (SRS) switching, and composing a precoding matrix using the PMI feedback and partial channel estimation.

Transmitter beamforming at base station with partial channel information and UE feedback

Disclosed is a method for determining whether to trigger of a conditional handover, including estimating, using a line-of-sight (LoS) channel, a received signal power as a function of a blocker used to simulate a human body, determining multiple stages of potential blockage of the received signal power by the blocker, predicting, using long-short-term memory (LTSM), a channel state and the potential blockage, and determining whether to trigger the conditional handover based on the predicted channel state and potential blockage.

Line-of-sight human blockage modeling and prediction

A system and method are provided in which an input including a measurement output of digital channel information is received. The digital channel information includes an estimated digital channel, a beamforming codebook, and quantized angle of arrival (AoA) values. A basis corresponding to one of the quantized AoA values is selected according to a largest projection power of the measurement output. A partial channel is recovered based on the beamforming codebook and the estimated digital channel. An analog channel is recovered based on the partial channel and the basis.

System and method for providing channel recovery for angle domain sparse channels

A wireless communication device includes: a processing circuit configured to: receive, from an antenna array during a previous period, a first directional electromagnetic signal including beam sweeping reference symbols of a previous beam sweeping period; compute an estimated combined channel; estimate a dominant angle-of-arrival (AoA) of the first directional electromagnetic signal based on the estimated combined channel and a previous beamforming codebook including two or more beamforming vectors corresponding to different AoAs; construct an updated beamforming codebook based on the estimated dominant AoA and one or more remaining AoAs spaced apart from the estimated dominant AoA; receive, at the antenna array during a current period, a second directional electromagnetic signal including data symbols; determine a beamforming vector for data reception of the second directional electromagnetic signal based on the updated beamforming codebook; and detect the data symbols in the second directional electromagnetic signal based on the determined beamforming vector.

Systems and methods for updating beamforming codebooks for angle-of-arrival estimation using compressive sensing in wireless communications

A first antenna array includes antenna panels including: first antenna panels arranged on a first circle having a first radius, each of the first antenna panels including antenna elements; and second antenna panels arranged on a second circle having a second radius, each of the second antenna panels including antenna elements, the second circle being concentric with the first circle at a center point, the second antenna panels being arranged at a first angle around the center point with respect to the first antenna panels, the first radius, the second radius, and the first angle being computed in accordance with wireless transmission conditions including: a line-of-sight distance to a second antenna array including third antenna panels arranged on two or more circles; and a carrier frequency of a line-of-sight wireless transmission between the first antenna array and the second antenna array.

Systems and methods for antenna placement for wireless communications

A system and a method are disclosed for estimating antenna misalignments in a line-of-sight wireless communication system and using the estimated antenna misalignments to form an optimal beam that may provide the best performance based on the channel conditions. A receiver determines a rotational estimate and a translational estimate of the receiver with respect to a transmitter, and sends feedback information to the transmitter that is used to determine an optimal beamforming matrix for LOS communications between the receiver and the transmitter. The feedback information includes estimated rotational angles and an estimated translational distance between the receiver and the transmitter, or includes an offset angle between a first plane of antennas of the receiver and a second plane of antennas of the transmitter, a normal vector of the first plane of antennas and the estimated translational distance. The antennas may be antenna arrays or single-element antennas.

Methods and systems for line-of-sight (LOS) multiple-input and multiple-output (MIMO) communications with antenna misalignments

A method for minimizing a time domain mean square error (MSE) of channel estimation (CE) includes estimating, by a processor, a power delay profile (PDP) from a time domain observation of reference signal (RS) channels; estimating, by the processor, a noise variance of the RS channels; and determining, by the processor, a first arrival path (FAP) value and a delay spread estimation (DSE) value based on the estimated PDP and the estimated noise variance for minimizing the MSE of CE.

System and method for providing first arrival path (FAP) and delay spread estimation (DSE) in wireless communication system

A system and method for providing channel recovery for angle domain sparse channels is herein provided. According to one embodiment, a method includes receiving an input including a measurement output, and recovering analog channels utilizing bases derived from the measurement output.

An apparatus is provided. The apparatus includes a processor configured to receive a synchronization signal (SS) and identify timing of the SS based on a primary spreading signal (PSS) in the SS, identify tentative secondary spreading signals (SSSs) based on the identified timing, and group the tentative SSSs; a register configured to receive the SS; and a memory configured to store the tentative SSSs for each group of the tentative SSSs; wherein the processor is further configured to cross correlate the tentative SSSs, combine cross correlated outputs with weights by group, determine an SSS as the tentative SSS with a maximum combined cross correlation outputs, and determine a cell identification based on the determined SSS.

Apparatus and method for cell detection by combining secondary spreading sequences

According to one general aspect, a method may include estimating a combined channel. The method may include estimating a channel correlation based, at least in part upon a measurement of a combined channel for a current beam sweeping interval and a previous beam sweeping interval. The method may include recovering a current channel by employing a compressive sensing-based channel recovery employing estimated channel correlation, a previous measurement, and a current measurement.

Compressive sensing based channel recovery considering time variation of the channel

Compressive sensing (CS) channel recovery using history measurements. Both current and history measurements for AoAs estimation, and only use current measurement for coefficient estimation. The dominant angle of arrival (AoA) is estimated using history and current measurements. In Approach 1, the dominant AoA is invariant and the coefficients are uncorrelated. In Approach 2, the dominant AoA is invariant and the coefficients are fully correlated. The remaining AoAs are estimated. The coefficients corresponding to each estimated dominant AoA are estimated. And the channel is recovered.

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San Diego, CA, United States of America

Hongbing Cheng