A Scheme for Joint Signal Reconstruction in Wireless Multimedia Sensor Networks

In context aware wireless multimedia sensor networks, scenarios are usually such that signals of multiple distributed sensors contain a common sparse component and each individual signal owns an innovation sparse component. So distributed compressive sensing based on joint sparsity of a signal ensemble concept exploits both these intraand intersignal correlation structures and compress signals to the extent possible. This paper proposes an optimized reconstruction scheme based on joint sparsity model which is derived from the distributed compressive sensing. In this regard, based on distributed compressive sensing, a joint reconstruction scheme is proposed to compress and reconstruct ensemble of signals even in large scale data transmission. Furthermore, simulation results show the effectiveness of the proposed method in diverse compression ratios and processing times in comparison with the joint sparsity model and individual compressive sensing reconstruction methods.