A Multiple Access Scheme Based on Multi-Dimensional Compressed Sensing

Compressed sensing can be utilized in multiple access to save channel resource and power consumption to realize green communications. This paper considers the application of compressed sensing to a wireless sensor network for data measurement reconstruction collected in a natural environment. We consider a network with N sensor nodes, sharing a wireless channel with M degrees of freedom, and compete for medium access to a single receiver. A multiple access scheme based on multi-dimensional compressed sensing is proposed, which exploits spatial and time correlations that exist in natural signals. The proposed scheme further removes the necessity of conveying identity information, which improves system power efficiency and enhances system security. Simulation results validate the effectiveness of the proposed method in utilizing the sensed signal's time and spatial correlations to obtain enhanced performances.