MIMO Assisted Networks Relying on Intelligent Reflective Surfaces

TL;DR

This paper analyzes IRS-assisted MIMO networks using stochastic geometry, deriving performance metrics like outage probability and ergodic rate, and shows that increasing IRS elements improves spectral and energy efficiency.

Contribution

It introduces a joint passive beamforming and detection design for IRS-assisted MIMO networks, deriving closed-form performance expressions and insights into high-SNR behavior.

Findings

High-SNR slope of ergodic rate is one.

SE and EE increase with more IRS elements.

Zero-forcing design suppresses intra-cell interference.

Abstract

Intelligent reflective surfaces (IRSs) are invoked for improving both spectral efficiency (SE) and energy efficiency (EE). Specifically, an IRS-aided multiple-input multiple-output network is considered, where the performance of randomly roaming users is analyzed by utilizing stochastic geometry tools. As such, to distinguish the superposed signals at each user, the passive beamforming weight at the IRSs and detection weight vectors at the users are jointly designed. As a benefit, by adopting a zero-forcing-based design, the intra-cell interference imposed by the IRS can be suppressed. In order to evaluate the performance of the proposed network, we first derive the approximated channel statistics in the high signal-to-noise-ratio (SNR) regime. Then, we derive the closed-form expressions both for the outage probability and for the ergodic rate of users. Both the high-SNR slopes of ergodic rate and the diversity orders of outage probability are derived for gleaning further insights. The network's SE and EE are also derived. Our numerical results are provided to confirm that: i) the high-SNR slope of the proposed network is one; ii) the SE and EE can be significantly enhanced by increasing the number of IRS elements.