Finite-horizon Online Transmission Rate and Power Adaptation on a Communication Link with Markovian Energy Harvesting

TL;DR

This paper develops a low complexity online scheduling policy for energy harvesting communication systems that maximizes throughput over a finite horizon, adapting to energy and channel variations, and outperforms existing infinite-horizon policies.

Contribution

It introduces a threshold-based online scheduling policy for finite-horizon energy harvesting links, extending it to fading channels, with demonstrated near-optimal performance.

Findings

Policy performs close to optimal across various energy harvest patterns.

Achieves higher throughput for a given delay compared to infinite-horizon policies.

Effective extension to fading channel scenarios.

Abstract

As energy harvesting communication systems emerge, there is a need for transmission schemes that dynamically adapt to the energy harvesting process. In this paper, after exhibiting a finite-horizon online throughput-maximizing scheduling problem formulation and the structure of its optimal solution within a dynamic programming formulation, a low complexity online scheduling policy is proposed. The policy exploits the existence of thresholds for choosing rate and power levels as a function of stored energy, harvest state and time until the end of the horizon. The policy, which is based on computing an expected threshold, performs close to optimal on a wide range of example energy harvest patterns. Moreover, it achieves higher throughput values for a given delay, than throughput-optimal online policies developed based on infinite-horizon formulations in recent literature. The solution is extended to include ergodic time-varying (fading) channels, and a corresponding low complexity policy is proposed and evaluated for this case as well.