Distributed Compressive Sensing for Wireless Sensor Networks

This paper presents some key problems of the distributed compressive sensing for wireless sensor network (WSN) in detail. The compressive sensing technique has been becoming a hot spot all over the world because of its excellent performance for signal processing. In this paper, we firstly present the original compressive sensing technique for single signal in brief. Secondly, we discuss the application of compressive sensing in WSN. It analysises the difference between distributed compressive sensing technique and compressive sensing technique for single signal. The Joint sparsity models, distributed source coding and recovery of joint sparsity signals are also discussed in detail for wireless sensor networks. We discusses several popular joint sparsity models for WSN and explains their applications in practice and analyse the performance and efficiency of distributed source coding and recovery of joint sparsity signals. At last, we introduce the future challenges of distributed compressive sensing technique.