Preprint Article Version 1 This version is not peer-reviewed

Coalition Formation Based Compressive Sensing in Wireless Sensor Networks

Version 1 : Received: 13 May 2018 / Approved: 14 May 2018 / Online: 14 May 2018 (11:59:00 CEST)

A peer-reviewed article of this Preprint also exists.

Masoum, A.; Meratnia, N.; Havinga, P.J.M. Coalition Formation Based Compressive Sensing in Wireless Sensor Networks. Sensors 2018, 18, 2331. Masoum, A.; Meratnia, N.; Havinga, P.J.M. Coalition Formation Based Compressive Sensing in Wireless Sensor Networks. Sensors 2018, 18, 2331.

Journal reference: Sensors 2018, 18, 2331
DOI: 10.3390/s18072331

Abstract

Compressive sensing originates in the field of signal processing and has recently become a topic of energy-efficient data gathering in wireless sensor networks. In this paper, we propose an energy efficient distributed compressive sensing solution for sensor networks. Proposed solution utilizes sparsity distribution of signals to group sensor nodes into several coalitions and then implements localized compressive sensing inside coalitions. This solution improves data-gathering performance in terms of both data accuracy and energy consumption. The approach curbs both data-transmission costs and number of measurements. Coalition-based data gathering cuts transmission cost, and the number of measurements is reduced by scheduling sensor nodes and adjusting their sampling frequency. Our simulation showed that our approach enhances network performance by minimizing energy cost and improving data accuracy.

Subject Areas

compressive sensing; coalition; sparsity; belief propagation; joint sparse recovery

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