Compressive Sensing Based Data Gathering in Wireless Sensor Networks with Transmit-only Nodes

Abstract

In this paper, we employ compressive sensing (CS) to design a data gathering scheme for wireless sensor networks (WSNs) with transmit-only nodes, where plenty of transmit-only nodes are activated to perform the sensing task and their data are gathered at a sink center to monitor environment using the CS principle. Typically, in the research published methods based on CS and random channel access, authors have used measurement matrix to reconstruct with encouraging results. However, they are limited in processing WSNs with transmit-only nodes.To account for the packet loss that occurs due to collisions, we propose a new approach with dual-measurement matrixreconstruction that minimizes average reconstruction error at the sink center. Simulation results demonstrate that compared with the conventional random channel access models, the proposed dual-measurement matrix model can improved reconstruction performance, and it is more effective in processing compressive WSNs with transmit-only nodes.