Stochastic Online Control for Energy-Harvesting Wireless Networks with Battery Imperfections

TL;DR

This paper develops a stochastic online control algorithm for energy-harvesting wireless networks that accounts for battery imperfections, optimizing data rates without prior statistical knowledge of the environment.

Contribution

It introduces a practical battery model into the Lyapunov optimization framework for energy-harvesting networks, enabling efficient control under realistic battery conditions.

Findings

The proposed scheme achieves feasible data admission, power allocation, routing, and scheduling.

It performs well without requiring prior knowledge of stochastic processes.

Numerical results validate the effectiveness of the control scheme.

Abstract

In energy harvesting (EH) network, the energy storage devices (i.e., batteries) are usually not perfect. In this paper, we consider a practical battery model with finite battery capacity, energy (dis-)charging loss, and energy dissipation. Taking into account such battery imperfections, we rely on the Lyapunov optimization technique to develop a stochastic online control scheme that aims to maximize the utility of data rates for EH multi-hop wireless networks. It is established that the proposed algorithm can provide a feasible and efficient data admission, power allocation, routing and scheduling solution, without requiring any statistical knowledge of the stochastic channel, data-traffic, and EH processes. Numerical results demonstrate the merit of the proposed scheme.