Atps: Adaptive Transmission Power Selection For Communication In Wireless Body Area Networks

Since radio links in wireless body area networks (WBANs) commonly experience highly time-varying attenuation due to topology instability, communication protocols with fixed transmission power cannot produce a very good performance in terms of energy consumption, interference range, and communication reliability. We explain that how channel behaviour can be modelled using Markov Chain. Then, a power-adaptive communication protocol for WBANs is developed in which each sensor node can self-learn its channel and dynamically adjust its transmission power. We evaluate our scheme through implementing the idea using the TelosB motes. The results demonstrate that our scheme can self-learn the channel behaviours, and reduce energy consumption and interference.