Semi-Markov Modeling for Body Area Networks
Signal variation in Body Area Networks (BANs) is dominated by slow, macroscopic fading. The quantized (state) channel has long, and variable state-holding times. We motivate the use of a semi-Markov approach to model the quantized channel gain and show that for everyday activities and on-body (real-world) measurements this approach leads to tractable limits for state holding times and transition probability. We show that while activity does influence the parameters of the semi-Markov model, the...[Show more]
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|Source:||Blind Timing and Carrier Synchronization in Decode and Forward Cooperative Systems|
|01_Chaganti_Semi-Markov_Modeling_for_Body_2011.pdf||492.67 kB||Adobe PDF||Request a copy|
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