Robust Beamforming for SWIPT Systems with Non-linear Energy Harvesting Model

TL;DR

This paper presents a novel resource allocation algorithm for SWIPT systems that maximizes harvested power using a non-linear energy harvesting model, accounting for imperfect CSI and ensuring QoS, with proven global optimality.

Contribution

It introduces a new iterative algorithm that globally optimizes resource allocation in SWIPT systems with a non-linear energy harvesting model under imperfect CSI conditions.

Findings

Significant increase in harvested power compared to baseline.

Enhanced robustness against CSI imperfections.

Effective optimization of resource allocation for SWIPT systems.

Abstract

This paper investigates resource allocation for simultaneous wireless information and power transfer (SWIPT) downlink systems based on a non-linear energy harvesting model. The resource allocation algorithm design is formulated as a non-convex optimization problem for the maximization of the total harvested power. The proposed problem formulation not only takes into account imperfect channel state information (CSI) but also guarantees the quality-of-service (QoS) of information transfer. A novel iterative algorithm is proposed to obtain the globally optimal solution of the considered non-convex optimization problem. In each iteration, a rank-constrained semidefinite program (SDP) is solved optimally by SDP relaxation. Simulation results demonstrate the significant gains in harvested power and the robustness against CSI imperfection for the proposed optimal resource allocation, compared to a baseline scheme designed for perfect CSI and the conventional linear energy harvesting model.