Cluster-based energy-efficient transmission using a new hybrid compressed sensing in WSN

Abstract

Compressive sensing (CS) can reduce the energy consumption and balance the traffic load throughout the wireless sensor networks (WSN). Due to the fault tolerance and traffic load balancing of the clustering method, CS is always combined with clustering for further improvement. And hexagon clustering has some advantages over other clustering methods such as its special structure. However, the total energy consumption for data collection by using pure CS is still large. Then the hybrid CS method was proposed to obtain further energy saving, but the performance will decrease and a large amount of redundancy will be produced with the network scale increasing so that the data compression does not work well. In this paper, an analytical model of cellular clustering is put forward to study how the special hexagon structure can be combined with CS for a better performance. Then, on the basis of hexagon clustering model, a new method of hybrid CS is presented, which performs better on power consumption than other hybrid CS. Extensive simulations confirm that our method can reduce energy consumption significantly.