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Award Abstract # 1704240
CIF: Medium: Collaborative Research: Low-Resolution Sampling with Generalized Thresholds

NSF Org: CCF
Division of Computing and Communication Foundations
Recipient: UNIVERSITY OF FLORIDA
Initial Amendment Date: May 15, 2017
Latest Amendment Date: March 10, 2021
Award Number: 1704240
Award Instrument: Continuing Grant
Program Manager: Phillip Regalia
pregalia@nsf.gov
 (703)292-2981
CCF
 Division of Computing and Communication Foundations
CSE
 Directorate for Computer and Information Science and Engineering
Start Date: May 1, 2017
End Date: February 28, 2021 (Estimated)
Total Intended Award Amount: $400,000.00
Total Awarded Amount to Date: $176,441.00
Funds Obligated to Date: FY 2017 = $92,922.00
FY 2018 = $83,518.00

FY 2019 = $0.00

FY 2020 = $0.00
History of Investigator:
  • Jian Li (Principal Investigator)
    li@dsp.ufl.edu
Recipient Sponsored Research Office: University of Florida
1523 UNION RD RM 207
GAINESVILLE
FL  US  32611-1941
(352)392-3516
Sponsor Congressional District: 03
Primary Place of Performance: University of Florida
1 University of Florida
Gainesville
FL  US  32611-2002
Primary Place of Performance
Congressional District:
03
Unique Entity Identifier (UEI): NNFQH1JAPEP3
Parent UEI:
NSF Program(s): Comm & Information Foundations
Primary Program Source: 01001718DB NSF RESEARCH & RELATED ACTIVIT
01001819DB NSF RESEARCH & RELATED ACTIVIT

01001920DB NSF RESEARCH & RELATED ACTIVIT

01002021DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 7924, 7936
Program Element Code(s): 779700
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.070

ABSTRACT

CIF: Medium: Collaborative Research:
Low-Resolution Sampling with Generalized Thresholds

Jian Li, Lee Swindlehurst, and Mojtaba Soltanalian

Abstract

Quantization of signals of interest is a necessary first step in digital signal processing applications. When signals across a wide frequency band are of interest, a fundamental tradeoff between sampling rate, amplitude quantization precision, cost, and power consumption is encountered. The investigators study low resolution sampling techniques with general thresholds, which are affordable, technically feasible, easy to apply, energy-efficient, and consistent with technological trends. The enormous gains in capacity and spectral efficiency, for example, that could be provided by a successful millimeter wave (mm-wave) massive multiple-input multiple output implementation could have a revolutionary effect on the performance of wireless systems nearly everywhere we use them: at home, at work, at school, commuting via public transportation or by plane, shopping, at restaurants, recreational venues, sporting events, and so on. Besides consumer applications, there are many military- and security-related scenarios where our systems could be used.

This project involves advancing fundamental knowledge in developing dynamic energy-efficient and cost-effective sampling techniques and applies engineering principles to address the critical needs of several important and related applications. Specifically, this project involves addressing significant open questions, including deterministic identifiability, performance bounds, and impact of thresholding pattern on spectrum sensing and array processing, radio frequency interference mitigation, and mm-wave communications to gain fundamental insights into the novel paradigm of low resolution sampling with general thresholds, devising novel signal processing algorithms, including effective and efficient sparse signal recovery techniques and parametric maximum likelihood methods for enhanced performance, and evaluating and demonstrating the performance using measured data. This project also involves preparing students for engineering in the 21st century through the incorporation of practical design and problem-solving techniques into both the education curriculum.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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Ameri, Aria and Bose, Arindam and Li, Jian and Soltanalian, Mojtaba "One-Bit Radar Processing With Time-Varying Sampling Thresholds" IEEE Transactions on Signal Processing , v.67 , 2019 10.1109/TSP.2019.2939086 Citation Details
Ameri, Aria and Li, Jian and Soltanalian, Mojtaba "One-Bit Radar Processing and Estimation with Time-Varying Sampling Thresholds" 2018 IEEE 10th Sensor Array and Multichannel Signal Processing Workshop (SAM) , 2018 10.1109/SAM.2018.8448917 Citation Details
Gianelli, Christopher and Xu, Luzhou and Li, Jian and Stoica, Petre "One-Bit compressive sampling with time-varying thresholds for multiple sinusoids" Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2017 IEEE 7th International Workshop on , 2017 10.1109/CAMSAP.2017.8313172 Citation Details
Ren, Jiaying and Zhang, Tianyi and Li, Jian and Nguyen, Lam H. and Stoica, Petre "RFI Mitigation for UWB Radar Via Hyperparameter-Free Sparse SPICE Methods" IEEE Transactions on Geoscience and Remote Sensing , v.57 , 2019 10.1109/TGRS.2018.2880758 Citation Details
Ren, Jiaying and Zhang, Tianyi and Li, Jian and Stoica, Petre "Sinusoidal Parameter Estimation from Signed Measurements Obtained via Time-Varying Thresholds" Asilomar Conference on Signals, Systems, and Computers , 2018 10.1109/ACSSC.2018.8645123 Citation Details
Ren, Jiaying and Zhang, Tianyi and Li, Jian and Stoica, Petre "Sinusoidal Parameter Estimation From Signed Measurements Via MajorizationMinimization Based RELAX" IEEE Transactions on Signal Processing , v.67 , 2019 10.1109/TSP.2019.2899804 Citation Details
Zahabi, Sayed Jalal and Naghsh, Mohammad Mahdi and Modarres-Hashemi, Mahmoud and Li, Jian "One-Bit Compressive Radar Sensing in the Presence of Clutter" IEEE Transactions on Aerospace and Electronic Systems , v.56 , 2020 10.1109/TAES.2019.2916532 Citation Details
Zhang, Tianyi and Ren, Jiaying and Gianelli, Christopher and Li, Jian "RFI Mitigation for One-Bit UWB Radar Systems" 2019 53rd Asilomar Conference on Signals, Systems, and Computers , 2019 10.1109/IEEECONF44664.2019.9048982 Citation Details

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