Probabilistically Robust Optimization of IRS-aided SWIPT Under Coordinated Spectrum Underlay

TL;DR

This paper develops robust optimization algorithms for IRS-assisted SWIPT in spectrum underlay, minimizing transmit energy while satisfying QoS and interference constraints, with performance validated through simulations.

Contribution

It introduces novel iterative algorithms for joint beamforming and power splitting in IRS-aided SWIPT under spectrum underlay, including robust design under imperfect CSI.

Findings

Proposed algorithms outperform benchmarks in simulations.

IRS significantly enhances SWIPT performance.

Robust design effectively manages CSI imperfections.

Abstract

This study considers the Joint Transmit/Reflect Beamforming and Power Splitting (JTRBPS) optimization problem in a spectrum underlay setting, such that the transmit sum-energy of the intelligent reflecting surface (IRS)-aided secondary transmitter (ST) is minimized subject to the quality-of-service requirements of the PS-simultaneous wireless information and power transfer (SWIPT) secondary receivers and the interference constraints of the primary receivers (PR). The interference at the PRs caused by the reception of IRS-reflected signals sent by the primary transmitter is taken into account. A coordinated channel state information (CSI) acquisition protocol is proposed. Next, assuming availability at the ST of perfect CSI for all direct and IRS-cascaded transmitter--receiver channels, two penalty-based iterative algorithms are developed: an alternating minimization algorithm that involves semi-definite relaxation in JTBPS design and successive convex approximation in RB optimization, and a block coordinate descent algorithm that employs the Riemannian conjugate gradient algorithm in RB updates. Finally, an outage-constrained robust design under imperfect CSI is devised. Numerical simulations highlight the performance gains of the proposed strategies over benchmarks, corroborate the benefits of using an IRS, and provide valuable insights.