Reinforcement Learning Based Energy Management in Wireless Body Area Network: A Survey

Abstract

In modern life, personal health-care awareness is a fast-growing revolution. In which, Wireless Body Area Network (WBAN) allows inexpensive health-care services with the evaluation of modern devices. In particular, WBAN devices such as in-body sensors and coordinator become more decentralized and autonomous. Moreover, Reinforcement Learning (RL) type of machine learning is formulated to lead the WBAN devices to make an autonomous decision such as sensor access control, transmit power control, security against attack to improve the network performance, quality of service (QoS) and increase the overall utility of the network in an optimized way. In this paper, we provide a literature survey about WBAN and its application, challenges and issues. Finally, we present the application of RL has appeared with the sophisticated solution in the WBAN.