Coverage Probability of Distributed IRS Systems Under Spatially Correlated Channels

TL;DR

This paper analyzes the coverage probability of distributed IRS systems considering spatially correlated channels, comparing different IRS deployment strategies and deriving closed-form expressions for coverage probability.

Contribution

It provides the first closed-form coverage probability analysis for distributed IRS systems with correlated Rayleigh fading, considering different IRS deployment scenarios.

Findings

Adding more IRS surfaces improves coverage probability.

Correlated fading impacts the effectiveness of IRS optimization.

Uncorrelated Rayleigh fading limits coverage probability optimization.

Abstract

This paper suggests the use of multiple distributed intelligent reflecting surfaces (IRSs) towards a smarter control of the propagation environment. Notably, we also take into account the inevitable correlated Rayleigh fading in IRS-assisted systems. In particular, in a single-input and single-output (SISO) system, we consider and compare two insightful scenarios, namely, a finite number of large IRSs and a large number of finite size IRSs to show which implementation method is more advantageous. In this direction, we derive the coverage probability in closed-form for both cases contingent on statistical channel state information (CSI) by using the deterministic equivalent (DE) analysis. Next, we obtain the optimal coverage probability. Among others, numerical results reveal that the addition of more surfaces outperforms the design scheme of adding more elements per surface. Moreover, in the case of uncorrelated Rayleigh fading, statistical CSI-based IRS systems do not allow the optimization of the coverage probability.