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Ultra-Wideband Real-Time Dynamic Channel Characterization and System-Level Modeling for Radio Links in Body Area Networks

Reliable on-body wireless network design needs to incorporate the natural body movements. However, existing models are static or pseudo-dynamic models. In this work, the lack of a comprehensive channel model for a moving body is addressed. A dynamic radio channel around the human body is statistically analyzed and modeled. Important parameters of the channel are estimated from measured data and compared with the model prediction. Simulations show that the model can predict the parameters of a system working in a dynamic body area network with 92% accuracy.