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Ori Nurit Shental

from Marlboro, NJ
Age ~51
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Related to:
Nurit N Shental, 49Nurit Shental
Connected to:
Andrew D Shenton, 62Ashley Shenton, 31Jamie L Shenton, 31Lee H Shenton, 80Shawn L Shenton, 54Timothy B Shenton, 32Chad Shenuski, 50Ralph J Shenyo, 75Melody Sheodial, 48Rinku Sheoran, 41

Ori Shental Phones & Addresses

  • Marlboro, NJ
  • San Diego, CA

Resumes

Resumes

Ori Shental Photo 1

Principal Engineer

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Location:
Cincinnati, OH
Industry:
Wireless
Work:
Qualcomm
Principal Engineer
Columbia University In the City of New York
Adjunct Associate Professor In the Departments of Electrical Engineering and Statistics
Huawei Technologies Nov 2015 - Jul 2016
Senior Algorithm Researcher
Nokia Bell Labs Nov 2015 - Jul 2016
Member of Technical Staff and Research Scientist at the Communications Theory Department, Bell Labs
Radcom 2003 - 2006
Consultant
Education:
Uc San Diego 2006 - 2008
Bar - Ilan University 2006 - 2006
Tel Aviv University 2003 - 2006
Doctorates, Doctor of Philosophy, Electrical Engineering, Philosophy Tel Aviv University 1992 - 1996
Bachelors, Bachelor of Science, Electrical Engineering, Electronics
Skills:
Signal Processing
Compressed Sensing
Algorithms
Digital Signal Processors
Information Theory
Coding Theory
Machine Learning
Wireless
Phy
Lte
Mimo
Embedded Systems
Fpga
Probabilistic Inference In Graphical Models
Communications Theory
Convex Optimization
Statistical Physics
Communication Theory
R&D
Soc
Asic
Mobile Tv
Personal Area Communications
Cellular
Various Transmission Methods
Ofdm
Non Linear Ic
Rf Impairments Mitigation Via Dsp
Matlab
Rf
Simulations
Research and Development
Field Programmable Gate Arrays
Wireless Technologies
Radio Frequency
Telecommunications
Cellular Communications
Digital Signal Processing
4G
Universal Mobile Telecommunications System
Mobile Communications
Optimization
Statistical Modeling
3Gpp
Noma
Polar Codes
Massive Mimo
Systems Design
Digital Communication
Ieee 802.11
Languages:
Hebrew
English
Ori Shental Photo 2

Researcher At Ucsd

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Location:
Greater San Diego Area
Industry:
Research

Publications

Us Patents

Efficient Compressed Sensing Channel Estimation For Single-Carrier Communication Systems

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US Patent:
20120069914, Mar 22, 2012
Filed:
Sep 22, 2010
Appl. No.:
12/888254
Inventors:
ORI SHENTAL - SAN DIEGO CA, US
ALECSANDER P. EITAN - SAN DIEGO CA, US
Assignee:
QUALCOMM Incorporated - San Diego CA
International Classification:
H04L 27/00
US Classification:
375259
Abstract:
Methods and devices for receiving wireless signals employ compressed sensing-based estimation techniques to receive single-carrier transmissions, exploiting the common sparseness of the wireless channel, enabling signal reception in the presence of significant Delay and Doppler spreads. When implemented for an ATSC or ATSC-M/H mobile TV standard signal, the compressed sensing channel estimation algorithm enables data reception in Delay and Doppler spread conditions beyond the capabilities of conventional channel estimation methods.

Beam Changing For A Repeater Node

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US Patent:
20220311503, Sep 29, 2022
Filed:
Mar 23, 2021
Appl. No.:
17/210105
Inventors:
- San Diego CA, US
Navid Abedini - Basking Ridge NJ, US
Junyi Li - Franklin Park NJ, US
Ori Shental - Marlboro NJ, US
International Classification:
H04B 7/155
H04L 27/26
H04W 72/04
H04B 7/06
H04L 5/00
Abstract:
This disclosure provides systems, apparatus, methods, and computer-readable media for beam switching by a repeater node that forwards communications from one of a first node or a second node to the other of the first node or the second node. For example, after a change of position by the second node, the first node may provide the repeater node an instruction to perform a beam change operation to communicate with the second node. In some aspects, performing the beam change operation by the repeater node may improve reliability of wireless communications, such as by focusing signal energy in a particular direction. Further, a beam change delay time interval or a scheduling of the beam change delay time interval may be selected based on scheduling associated with other nodes, which may reduce a number of messages sent to the repeater node (such as by reducing instructions to change beam directions).

Deep Learning Eigen-Beamforming

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US Patent:
20210384953, Dec 9, 2021
Filed:
Oct 11, 2018
Appl. No.:
17/284526
Inventors:
- Espoo, FI
Ori SHENTAL - Holmdel NJ, US
International Classification:
H04B 7/06
H04B 7/08
H04B 7/0426
G06N 3/02
Abstract:
According to one example embodiment, a method is provided including initializing a first recurrent neural network with a first vector; iteratively training a weight matrix for one or more layers of the first recurrent neural network, wherein W(t) is the weight matrix of the layer of the first recurrent neural network corresponding to iteration t, and wherein W(t) is based at least on a channel covariance matrix; the first vector; and an output from a previous layer of the first recurrent neural network corresponding to iteration, t−1: and determining a first eigenvector based on a converged output from the first recurrent neural network, wherein the first eigenvector is used to perform beamforming for multiple input multiple output reception and/or transmission.

Efficient Linear Detection Implementation For Massive Mimo

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US Patent:
20200021348, Jan 16, 2020
Filed:
Jun 7, 2019
Appl. No.:
16/434377
Inventors:
- Espoo, FI
Ori Shental - Holmdel NJ, US
International Classification:
H04B 7/06
H04B 7/0456
Abstract:
Per given time instance, K samples b are acquired from a signal r, which is based at least on K transmitted symbols x and a transfer matrix H of a communication channel, and a linear detection matrix A of a size K×K is acquired, which is based at least on the transfer matrix H (S). For the K samples b and the linear detection matrix A, at most K(K−1) tentative parameters b and at most K(K−1) tentative parameters A are iteratively calculated (S).It is checked whether or not the tentative parameters b and A have converged (S). If b and A have converged, K estimation values x{circumflex over ( )} are decided for the K transmitted symbols x based on b and A (S). If b and A have not converged, it is returned to the iteratively calculating b and A for the K samples b.
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Ori Nurit Shental from Marlboro, NJ, age ~51 Get Report