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Cooperative Bayesian Self-Tracking for Wireless Networks

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3 Author(s)
Wymeersch, H. ; Lab. for Inf. & Decision Syst., Massachusetts Inst. of Technol., Cambridge, MA ; Ferner, U. ; Win, M.Z.

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.

Published in:

Communications Letters, IEEE  (Volume:12 ,  Issue: 7 )