Physically Consistent Models for Intelligent Reflective Surface-assisted Communications under Mutual Coupling and Element Size Constraint

TL;DR

This paper models the electromagnetic mutual coupling effects in intelligent reflective surfaces with finite-sized dipole elements, demonstrating that accounting for mutual coupling is essential to optimize the achievable rate in IoT networks.

Contribution

It introduces a novel EM coupling model for IRSs with finite-sized dipole elements, incorporating mutual impedance and element size constraints for improved rate maximization.

Findings

Mutual coupling significantly impacts IRS performance.

Proper modeling prevents achievable rate degradation.

Gradient ascent effectively optimizes IRS phase shifts.

Abstract

We investigate the benefits of mutual coupling effects between the passive elements of intelligent reconfigurable surfaces (IRSs) on maximizing the achievable rate of downlink Internet-of-Things (IoT) networks. In this paper, we present an electromagnetic (EM) coupling model for IRSs whose elements are connected minimum scattering antennas (i.e., dipoles). Using Chu's theory, we incorporate the finite antenna size constraint on each element of the IRS to obtain the IRS mutual impedance matrix. By maximizing the IRS phase shiters using the gradient ascent procedure, our numerical results show that mutual coupling is indeed crucial to avoid the achievable rate degradation when the spacing between IRS elements is down to a fraction of the wavelength.