Instantaneous Channel Oblivious Phase Shift Design for an IRS-Assisted SIMO System with Quantized Phase Shift

TL;DR

This paper proposes a phase shift design for IRS-assisted SIMO systems that relies on statistical channel information and quantized phase values, reducing signaling overhead while maintaining performance.

Contribution

It introduces a novel phase shift design method using statistical CSI and quantized phases, with closed-form expressions and optimization algorithms for outage probability and ergodic rate.

Findings

Significant reduction in signaling overhead (up to 99.69%)

Effective phase shift design with only 5-bit quantization

Closed-form expressions for outage probability and ergodic rate

Abstract

We design the phase shifts of an intelligent reflecting surface (IRS)-assisted single-input-multiple-output communication system to minimize the outage probability (OP) and to maximize the ergodic rate. Our phase shifts design uses only statistical channel state information since these depend only on the large-scale fading coefficients; the obtained phase shift design remains valid for a longer time frame. We further assume that one has access to only quantized phase values. The closed-form expressions for OP and ergodic rate are derived for the considered system. Next, two optimization problems are formulated to choose the phase shifts of IRS such that (i) OP is minimized and (ii) the ergodic rate is maximized. We used the multi-valued particle swarm optimization (MPSO) and particle swarm optimization (PSO) algorithms to solve the optimization problems. Numerical simulations are performed to study the impact of various parameters on the OP and ergodic rate. We also discuss signaling overhead between BS and IRS controller. It is shown that the overhead can be reduced up to $99.69 \%$ by using statistical CSI for phase shift design and $5$ bits to represent the phase shifts without significantly compromising on the performance.