Second Order Cone Programming based Localization Method for Internet of Things

A novel method for device localization under mixed line-of-sight/non-line-of-sight (LOS/NLOS) conditions based on second order cone programming (SOCP) is presented in this paper. The devices can communicate cooperatively among themselves in a large Internet of things (IoT) network. SOCP methods have, hitherto, not been utilized in the node localization under mixed LOS/NLOS conditions. Unlike semidefinite programming (SDP) formulation, SOCP is computationally efficient for resource constrained IoT network. The proposed method can work seamlessly in mixed LOS/NLOS conditions. The robustness of the method is due to the fair utilization of all measurements obtained under LOS and NLOS conditions. The computational complexity of this method is quadratic in the number of nearest neighbours of the unknown node. Cramer-Rao bound and localization error are analyzed to illustrate the effectiveness of the proposed method. The experimental results of the proposed method indicate a reasonable improvement when compared to recent state of the art methods.