Practical Non-Linear Energy Harvesting Model and Resource Allocation in SWIPT Systems

TL;DR

This paper introduces a practical non-linear energy harvesting model for SWIPT systems and develops an efficient resource allocation algorithm that significantly improves total harvested power over traditional linear models.

Contribution

It proposes a novel non-linear EH model and an iterative algorithm for optimal resource allocation in SWIPT, addressing non-convex optimization challenges.

Findings

Significant increase in harvested power with the non-linear model

Efficient algorithm achieves globally optimal solutions

Non-linear model outperforms traditional linear models

Abstract

Simultaneous wireless information and power transfer (SWIPT) is a promising solution for enabling long-life, and self-sustainable wireless networks. In this thesis, we propose a practical non-linear energy harvesting (EH) model and design a resource allocation algorithm for SWIPT systems. In particular, the algorithm design is formulated as a non-convex optimization problem for the maximization of the total harvested power at the EH receivers subject to quality of service (QoS) constraints for the information decoding (ID) receivers. To circumvent the non-convexity of the problem, we transform the corresponding non-convex sum-of-ratios objective function into an equivalent objective function in parametric subtractive form. Furthermore, we design a computationally efficient iterative resource allocation algorithm to obtain the globally optimal solution. Numerical results illustrate significant performance gain in terms of average total harvested power for the proposed non-linear EH receiver model, when compared to the traditional linear model.\