@inproceedings{69903aba954b4f6ea4acb313d8f0ee9f,
title = "Joint sparsity pattern recovery with 1-bit compressive sensing in sensor networks",
abstract = "We study the problem of joint sparsity pattern recovery with 1-bit compressive measurements in a sensor network. Sensors are assumed to observe sparse signals having the same but unknown sparsity pattern. Each sensor quantizes its measurement vector element-wise to 1-bit and transmits the quantized observations to a fusion center. We develop a computationally tractable support recovery algorithm which minimizes a cost function defined in terms of the likelihood function and the ℓ1,∞ norm. We observe that even with noisy 1-bit measurements, joint sparsity pattern can be recovered accurately with multiple sensors each collecting only a small number of measurements.",
keywords = "Compressed sensing, maximum-likelihood estimation, quantization, support recovery",
author = "Vipul Gupta and Bhavya Kailkhura and Thakshila Wimalajeewa and Sijia Liu and Varshney, {Pramod K.}",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015 ; Conference date: 08-11-2015 Through 11-11-2015",
year = "2016",
month = feb,
day = "26",
doi = "10.1109/ACSSC.2015.7421389",
language = "English (US)",
series = "Conference Record - Asilomar Conference on Signals, Systems and Computers",
publisher = "IEEE Computer Society",
pages = "1472--1476",
editor = "Matthews, {Michael B.}",
booktitle = "Conference Record of the 49th Asilomar Conference on Signals, Systems and Computers, ACSSC 2015",
address = "United States",
}