Greedy localization approach in Wireless Sensors Network

In this paper, we propose a greedy localization approach in Wireless Sensors Network (WSN) which has received much attention in the emerging area of Internet of Things (IoT). The proposed method is based on Compressive Sensing (CS) formulation and uses the inherent sparsity of the localization problem. While this is not the first work on applying CS to localize targets, in this paper, we propose a simple and novel formulation and deduce an algorithm to solve this problem, more suitable to the time and complexity constraints of IoT context. Moreover, we propose a Denoising - Greedy Recovery Algorithm (D-GRA) to deal with noise measurement affecting the received signal strength used to the sensor localization. The proposed algorithm has been compared to the classical trilateration method by performing different simulations. The obtained results demonstrate that the proposed algorithms outperform the trilateration method in a noisy environment.