On online energy harvesting in multiple access communication systems

TL;DR

This paper analyzes the performance limits of energy harvesting in multiple access systems, deriving optimal power policies and algorithms to maximize long-term throughput under causal energy arrivals.

Contribution

It introduces a novel continuous-time model with a storage dam for energy harvesting nodes and develops algorithms to optimize power policies in this setting.

Findings

Derived upper bounds on throughput based on battery capacity.

Formulated and solved a non-linear optimization problem for power policies.

Developed iterative algorithms with numerical validation.

Abstract

We investigate performance limits of a multiple access communication system with energy harvesting nodes where the utility function is taken to be the long-term average sum-throughput. We assume a causal structure for energy arrivals and study the problem in the continuous time regime. For this setting, we first characterize a storage dam model that captures the dynamics of a battery with energy harvesting and variable transmission power. Using this model, we next establish an upper bound on the throughput problem as a function of battery capacity. We also formulate a non-linear optimization problem to determine optimal achievable power policies for transmitters. Applying a calculus of variation technique, we then derive Euler-Lagrange equations as necessary conditions for optimum power policies in terms of a system of coupled partial integro-differential equations (PIDEs). Based on a Gauss-Seidel algorithm, we devise an iterative algorithm to solve these equations. We also propose a fixed-point algorithm for the symmetric multiple access setting in which the statistical descriptions of energy harvesters are identical. Along with the analysis and to support our iterative algorithms, comprehensive numerical results are also obtained.