Abstract
In body area networks, sustainable energy supply and reliable data transmission are important to prolong the service cycle and guarantee the quality of service. In this article, we build a system model to capture the stochastic processes in body area networks, including energy harvesting process, spectrum pricing process, and data sampling process. In the system model, energy harvesting technology and cognitive radio technology are adopted to provide green energy and improve transmission environment for body area networks. Based on the proposed model, we formulate an optimization problem of system utility maximization. Since this problem is a multi-objective mixed-integer problem under multiple restrictions, we decompose the problem into several subproblems by Lyapunov optimization theory. Based on this, we design an efficient online energy and channel transmission management algorithm to solve these subproblems and achieve a close-to-optimal system utility without any priori knowledge. We analyze the optimality of proposed algorithm and derive the required battery capacity and the size of data buffer. Simulation results demonstrate the effectiveness of the proposed algorithm.
Highlights
The phenomenon of aging population has became an inescapable issue that the government, medicine, and academic must face
Motivated by the challenges above, we develop a framework based on Lyapunov optimization in a single-hop resource harvesting body area networks (RHBANs) consisting of a personal device (PD) and a few medical sensors, by jointly considering three stochastic processes: energy harvesting (EH), spectrum pricing, and data sampling
We develop a framework based on Lyapunov optimization to decompose the system optimization problem into three subproblems, that is, energy control optimization (ECO), sampling optimization (SO), and channel transmission optimization (CTO)
Summary
The phenomenon of aging population has became an inescapable issue that the government, medicine, and academic must face. Changing the battery is unrealistic for the medical application that embeds sensors inside human body In this condition, energy harvesting (EH) technology is studied and developed,[5] and already deployed into BANs, known as energy harvesting body area networks (EHBANs). The problems of energy supply and channel transmission can be solved by EH technology and CR technology, there are still some new challenges to face.[11] First of all, the EH process is dynamic and stochastic, which makes a challenge to balance energy consumption and supply.[12] Second, the price of licensed spectrum is dynamic, which makes providing stable, fast access to licensed spectrum challenging.[13] Since the aim of EH technology and CR technology is harvesting resource, the BANs equipped with the two technologies above are referred to as resource harvesting body area networks (RHBANs). We compute the required battery capacity to support the channel trading and data transmission; we compute the upper bound of data queue and debt queue to guarantee the stability of system; and we compute the optimality of ECTM algorithm to compare the gap between time-average system utility and optimal system utility
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