Cooperative Bayesian Self-Tracking for Wireless Networks

Abstract

Self-tracking of mobile nodes in wireless networks has the potential to revolutionize the wireless communications industry. This letter presents a cooperative self-tracking algorithm for mobile nodes in wireless networks. The presented algorithm is fully distributed and cooperative. It is derived using network factor graphs (Net-FGs) and results in the sum-product algorithm over a wireless network (SPAWN). Numerical results show that it is robust and can significantly outperform conventional non- cooperative self-tracking techniques.