Universite de Sfax
Compressive Sensing (CS) intends to recover signals at a sampling rate significantly (much) lower than that classically used according to the Nyquist theorem. This allows avoiding unnecessary sampling and complexity. In this paper, a Three-Dimensional Compressive Sensing (3D-CS) approach is proposed for nodes localization in wireless networks. In 3D-CS-R2S2 approach, which is based on the ratio of Received Signal Strength (RSS), a 3D sparsity basis and a 3D measurement matrix are used as radio map and noisy measurements respectively in order to recover the target position. A specific multi-linear algebra procedure was developed using N-way array products, together with an adequate decomposition.