On the Performance of IRS-Assisted Relay Systems
Diluka Galappaththige, Alan Devkota, Gayan Amarasuriya
Abstract
This paper investigates the performance of intelligence reflective surface (IRS)-assisted relay systems. To this end, we quantify the optimal signal-to-noise ratio (SNR) attained by smartly controlling the phase-shifts of impinging electromagnetic waves upon an IRS. Thereby, a tightly approximated cumulative distribution function is derived to probabilistically characterize this optimal SNR. Then, we derive tight approximations/bounds for the achievable rate, outage probability, and average symbol error rate. Monte-Carlo simulations are used to validate our performance analysis. We present numerical results to reveal that the IRS-assisted relay system can boost the performance of end-to-end wireless transmissions.