Energy-efficient adaptive transmission power control for wireless body area networks

An important constraint in wireless body area network (WBAN) is to maximise the energy-efficiency of wearable devices due to their limited size and light weight. Two experimental scenarios; right wrist to right hip' and chest to right hip' with body posture of walking are considered. It is analyzed through extensive real-time data sets that due to large temporal variations in the wireless channel, a constant transmission power and a typical conventional transmission power control (TPC) methods are not suitable choices for WBAN. To overcome these problems a novel energy-efficient adaptive power control (APC) algorithm is proposed that adaptively adjusts transmission power (TP) level based on the feedback from base station. The main advantages of the proposed algorithm are saving more energy with acceptable packet loss ratio (PLR) and lower complexity in implementation of desired tradeoff between energy savings and link reliability. We adapt, optimise and theoretically analyse the required parameters to enhance the system performance. The proposed algorithm sequentially achieves significant higher energy savings of 40.9%, which is demonstrated by Monte Carlo simulations in MATLAB. However, the only limitation of proposed algorithm is a slightly higher PLR in comparison to conventional TPC such as Gao's and Xiao's methods.