Practical Non-linear Energy Harvesting Model and Resource Allocation for SWIPT Systems

TL;DR

This paper introduces a practical non-linear energy harvesting model and an iterative resource allocation algorithm for SWIPT systems, demonstrating significant performance improvements over traditional linear models.

Contribution

It proposes a novel non-linear energy harvesting model and an efficient iterative resource allocation algorithm for SWIPT systems, transforming a non-convex problem into a solvable form.

Findings

Significant performance gain using the non-linear model

Efficient iterative algorithm based on SDP relaxation

Improved energy harvesting efficiency

Abstract

In this letter, we propose a practical non-linear energy harvesting model and design a resource allocation algorithm for simultaneous wireless information and power transfer (SWIPT) systems. The algorithm design is formulated as a non-convex optimization problem for the maximization of the total harvested power at energy harvesting receivers subject to minimum required signal-to-interference-plus-noise ratios (SINRs) at multiple information receivers. We transform the considered non-convex objective function from sum-of-ratios form into an equivalent objective function in subtractive form, which enables the derivation of an efficient iterative resource allocation algorithm. In each iteration, a rank-constrained semidefinite program (SDP) is solved optimally by SDP relaxation. Numerical results unveil a substantial performance gain that can be achieved if the resource allocation design is based on the proposed non-linear energy harvesting model instead of the traditional linear model.