# Energy Harvesting Networks with General Utility Functions: Near Optimal Online Policies

## TL;DR

This paper develops near-optimal online scheduling policies for energy harvesting communication systems with general utility functions, demonstrating their effectiveness across various energy arrival distributions and system parameters.

## Contribution

It characterizes the optimal policies for Bernoulli arrivals and shows fixed fraction policies are near-optimal for general i.i.d. energy arrivals, extending previous results.

## Key findings

- Fixed fraction policies are within a constant multiplicative gap of optimal for all energy arrivals.
- Under certain utility function conditions, fixed fraction policies are within a constant additive gap of optimal.
- The analysis applies to systems with finite battery sizes and i.i.d. energy arrivals.

## Abstract

We consider online scheduling policies for single-user energy harvesting communication systems, where the goal is to characterize online policies that maximize the long term average utility, for some general concave and monotonically increasing utility function. In our setting, the transmitter relies on energy harvested from nature to send its messages to the receiver, and is equipped with a finite-sized battery to store its energy. Energy packets are independent and identically distributed (i.i.d.) over time slots, and are revealed causally to the transmitter. Only the average arrival rate is known a priori. We first characterize the optimal solution for the case of Bernoulli arrivals. Then, for general i.i.d. arrivals, we first show that fixed fraction policies [Shaviv-Ozgur] are within a constant multiplicative gap from the optimal solution for all energy arrivals and battery sizes. We then derive a set of sufficient conditions on the utility function to guarantee that fixed fraction policies are within a constant additive gap as well from the optimal solution.