Compressed sensing based random routing for multi-hop wireless sensor networks

Abstract

Compressed sensing (CS) is an emerging theory based on the fact that the salient information of a signal can be preserved in a relatively small number of linear projections. Besides its applications in image compression and signal processing in the past few years, compressed sensing has been attracting ever-increasing interests in the areas of wireless communication and sensor networks. According to its advantageous characteristics, compressed sensing is able to play a significant role in the fields like wireless channel estimation, signal detection, data gathering, network monitoring, and so on. This study describes current researches on the applications of CS in wireless communication and sensor networks, and then specially focuses on bringing out a novel random routing scheme for efficient data gathering. Accordingly, we first introduce the basic approach of compressed sensing, and then summarize recent technical advancements of compressed sensing schemes and their applications in wireless communication and sensor networks. Then, we propose a random routing method executed with CS for efficient data gathering in typical wireless sensor networking environment, and analyze the relevant performances comparing with those of the existing data gathering schemes, obtaining the conclusion that the proposed scheme is effective in signal reconstruction and efficient in reducing routing energy consumption.