Closed-Form Delay-Optimal Power Control for Energy Harvesting Wireless System with Finite Energy Storage

TL;DR

This paper develops a delay-optimal power control strategy for energy harvesting wireless systems with finite energy storage, using a novel approximation approach to derive a practical online solution.

Contribution

It introduces a closed-form approximate priority function for an MDP, enabling an adaptive, multi-level water-filling power control scheme for energy harvesting systems.

Findings

Significant performance improvements over baseline schemes

Effective adaptation to channel, data, and energy states

Closed-form solution reduces computational complexity

Abstract

In this paper, we consider delay-optimal power control for an energy harvesting wireless system with finite energy storage. The wireless system is powered solely by a renewable energy source with bursty data arrivals, and is characterized by a data queue and an energy queue. We consider a delay-optimal power control problem and formulate an infinite horizon average cost Markov Decision Process (MDP). To deal with the curse of dimensionality, we introduce a virtual continuous time system and derive closed-form approximate priority functions for the discrete time MDP at various operating regimes. Based on the approximation, we obtain an online power control solution which is adaptive to the channel state information as well as the data and energy queue state information. The derived power control solution has a multi-level water-filling structure, where the water level is determined jointly by the data and energy queue lengths. We show through simulations that the proposed scheme has significant performance gain compared with various baselines.