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arXiv · 1506.00540

Joint Sparsity Pattern Recovery with 1-bit Compressive Sensing in Sensor Networks

Vipul Gupta·Bhavya Kailkhura·Thakshila Wimalajeewa·Pramod K. Varshney
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Abstract

We study the problem of jointly sparse support recovery with 1-bit compressive measurements in a sensor network. Sensors are assumed to observe sparse signals having the same but unknown sparse support. 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 $l_{1,\infty}$ norm. We observe that even with noisy 1-bit measurements, jointly sparse support can be recovered accurately with multiple sensors each collecting only a small number of measurements.

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Vipul Gupta, Bhavya Kailkhura, Thakshila Wimalajeewa, Pramod K. Varshney. 2015-06-01. Joint Sparsity Pattern Recovery with 1-bit Compressive Sensing in Sensor Networks. https://arxiv.org/abs/1506.00540

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