Power Adaptive Localization Algorithm for Wireless Sensor Networks Using Particle Filter

Power scheduling and localization play important roles in network topology management. Distributed power scheduling is an efficient way to construct a reliable and energy-efficient network topology. Localization provides geographical information for topology management. However, during the course of transmission power control, localization based on the received signal strength (RSS) is a challenging problem because of the inconsistent RSS indication (RSSI) measurements in wireless sensor networks. This paper presents an algorithm that takes advantage of the information from the ongoing wireless communication links to calculate the estimated position of sensor nodes. Considering the existing transmit-power-aware medium access control (MAC) protocols, we propose a localization algorithm based on particle filtering for sensor networks assisted by multiple transmit-power information. Therefore, the primary contribution of this paper is the elegant strategy on how to incorporate the practical multiple transmit-power information into the process of particle filtering. Furthermore, a general message-passing framework of the transmit-power-aware MAC is seamlessly integrated with the tracking service. The proposed particle-filtering-based localization algorithm uses the RSS information from the beacons or the neighboring nodes to infer the position of the concerned node without the requirement of any additional hardware instruments. Theoretical analysis and simulation results are presented to demonstrate the performance of the proposed localization method. The simulation results show that the proposed algorithm outperforms the existing algorithms that do not utilize multiple power information.