A Modified Compressed Sensing-Based Recovery Algorithm for Wireless Sensor Networks

Abstract

In this paper, a novel compressed sensing (CS) acquisition and joint recovery of spatiotemporal correlated signals algorithm is presented for effective data collection and precise sensors data streams reconstruction in wireless sensor networks. The CS-based proposed method utilizes~an iterative re-weighted l1-minimization and a l2 regularization to increase the reconstruction accuracy with a small number of required data transmission. Moreover, we develop~an alternating direction method of multipliers based algorithm to efficiently solve the resulting optimization problem. Numerical experiments are conducted on several test signals with~a variety of sampling ratios. The experimental results verify the effectiveness of the proposed scheme in terms of reconstruction accuracy and consumption time compared with the state of the art algorithms.