RSS-based Cooperative Localization and Transmit Power(s) Estimation using Mixed SDP-SOCP

Received signal strength (RSS)-based localization techniques are widely used to estimate the location of wireless sensor nodes as they utilize minimum bandwidth and do not require additional hardware. However, these techniques typically assume that the nodes' transmit power is known, despite the fact that changes in transmit power, influenced by factors such as antenna orientation and battery level, can significantly impact localization performance. To address this issue, we propose an RSS-based cooperative localization technique that jointly estimates the location and transmit power of the nodes and will refer to it as FCUP (Fast Cooperative localization technique with Unknown transmit Power). The maximum likelihood (ML) estimator for joint estimation of location and transmit power is non-convex, discontinuous, and computationally challenging to solve. So, we reformulate the optimization problem into a mixed semidefinite second-order cone program (SDP-SOCP) using the Taylor expansion, epigraph method, and semidefinite relaxation. FCUP takes advantage of the high accuracy of SDP and the low complexity of SOCP. FCUP is compared to the existing techniques to demonstrate its superior performance based on localization accuracy, computational complexity, and execution time.