A Maximin Optimal Online Power Control Policy for Energy Harvesting Communications

TL;DR

This paper introduces a maximin optimal online power control policy for energy harvesting communications that maximizes worst-case expected throughput using only the mean energy arrival, outperforming existing fixed fraction policies.

Contribution

It develops a universal, explicit maximin optimal policy based solely on the mean energy arrival, improving worst-case performance over prior methods.

Findings

The policy is universally near optimal across all energy arrival distributions.

It outperforms the fixed fraction policy in worst-case scenarios.

Numerical examples demonstrate the policy's superior competitiveness.

Abstract

A general theory of online power control for discrete-time battery limited energy harvesting communications is developed, which leads to, among other things, an explicit characterization of a maximin optimal policy. This policy only requires the knowledge of the (effective) mean of the energy arrival process and maximizes the minimum asymptotic expected average reward (with the minimization taken over all energy arrival distributions of a given (effective) mean). Moreover, it is universally near optimal and has a strictly better worst-case performance as well as a strictly improved lower multiplicative factor in comparison with the fixed fraction policy proposed by Shaviv and \"{O}zg\"{u}r when the objective is to maximize the throughput over an additive white Gaussian noise channel. The competitiveness of this maximin optimal policy is also demonstrated via numerical examples.