Spatially-Localized Compressed Sensing and Routing in Multi-hop Sensor Networks

  • Authors:

  • Sungwon Lee;Sundeep Pattem;Maheswaran Sathiamoorthy;Bhaskar Krishnamachari;Antonio Ortega

  • Affiliations:

  • Dept. of Electrical Engineering, University of Southern California, Los Angeles, USA CA 90089;Dept. of Electrical Engineering, University of Southern California, Los Angeles, USA CA 90089;Dept. of Electrical Engineering, University of Southern California, Los Angeles, USA CA 90089;Dept. of Electrical Engineering, University of Southern California, Los Angeles, USA CA 90089;Dept. of Electrical Engineering, University of Southern California, Los Angeles, USA CA 90089

  • Venue:
  • GSN '09 Proceedings of the 3rd International Conference on GeoSensor Networks
  • Year:
  • 2009

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Abstract

We propose energy-efficient compressed sensing for wireless sensor networks using spatially-localized sparse projections. To keep the transmission cost for each measurement low, we obtain measurements from clusters of adjacent sensors. With localized projection, we show that joint reconstruction provides significantly better reconstruction than independent reconstruction. We also propose a metric of energy overlap between clusters and basis functions that allows us to characterize the gains of joint reconstruction for different basis functions. Compared with state of the art compressed sensing techniques for sensor network, our simulation results demonstrate significant gains in reconstruction accuracy and transmission cost.