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Auto-Regressive Modeling of the Shadowing for RSS Mobile Tracking

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4 Author(s)
Hadi Noureddine ; Mitsubishi Electr. R&D Centre Eur., France ; Nicolas Gresset ; Damien Castelain ; Ramesh Pyndiah

In this paper, we consider the tracking of mobile terminals based on the received signal strength (RSS) measured from several base stations. The spatial correlation of the random shadowing is exploited in order to improve the position tracking. We define an auto-regressive (AR) model of the temporal evolution of the shadowing. This model allows for performing a joint tracking of the position and the shadowing by applying a Rao- Blackwellized (RB) particle filter approximating the posterior probability distributions numerically. The simulation results show that the tracking can be improved by considering sufficiently high auto-regressive orders.

Published in:

2011 IEEE International Conference on Communications (ICC)

Date of Conference:

5-9 June 2011