Information Acquisition with Compressed Sensing Multiuser Detection in Underwater Sensor Networks

Abstract

Underwater sensor network is a typically energy limited and bandwidth-limited system, the technical bottleneck of which is the asymmetry between the demand for large-scale and high-resolution information gathering and the limited network resource. In order to realize accurate information acquisition of the large-scale underwater sensor networks in an energy-efficient way, a compressed sensing (CS) multi-user detection (MUD) scheme is proposed and evaluated in this paper. The proposed scheme consists of three main components: (1) Data sampling with random selected nodes, (2) Quasi-orthogonal multiple access with MUD, such as CDMA and its particular case IDMA, (3) Information recovery. Exploiting the sparse property of the monitored objects, only a subset of sensors is required to measure and transmit to the monitoring center for accurate information reconstruction, reducing the energy consumption and prolonging the network lifetime significantly. Furthermore, by taking advantage of compressed sensing theory, this scheme has sufficient capability to resist packet error during multi-user detection. Simulation results with real ocean monitoring data validate the efficiency of the proposed scheme.