Energy Harvesting for Throughput Enhancement of Cooperative Wireless Sensor Networks

Abstract

We consider an energy harvesting for cooperative wireless sensor networks with a nonlinear power consumption model. The information transmission from the source node to the destination node is assumed to occur via several clusters of decode-and-forward relay nodes. We assume that all the source and relay nodes have the ability to harvest energy from the environment and use that harvested energy to transmit and forward the information to the next hop. Under such assumption, the objective of our design is to improve the total throughput of the end-to-end link over a number of transmission blocks subject to constraints on energy causality, battery overflow, and time duration for energy harvesting. The optimization problem is found to be a nonconvex maximin fractional program, which is difficult to solve in general. We present an efficient iterative algorithm to solve the optimization problem. Specifically, by introducing novel transformations, we apply an approximate convex technique to obtain a convex problem at each iteration. We then propose an iterative power allocation algorithm which converges to a locally optimal solution at a Karush-Kuhn-Tucker point. Numerical results are provided to evaluate the proposed scheme.