Hierarchical Distributed Compressed Sensing for Wireless Sensor Network

Distributed Compressed Sensing (DCS) is an effective means to reduce the amount of data transmission and energy consumption in Wireless Sensor Network (WSN). Hierarchical Distributed Compressed Sensing (HDCS) is proposed for clustering WSN. It eliminates the temporal-spatial redundancies among data collected by the cluster members with the intra-cluster DCS, and eliminates the spatial redundancies among clusters with the inter-cluster DCS. According to the signal's structured sparsity, a block-sparse intra-cluster joint sparsity model and a block-sparse inter-cluster joint sparsity model are constructed. Then, a hierarchical measurement scheme and a hierarchical joint reconstruction scheme are proposed for HDCS. Experimental results show that compared to general DCS, HDCS can relieve the transmission burden in the network effectively, without lowering the quality of the reconstructed signal. Moreover, it can reduce the signal reconstruction time at the Sink observably.