Two-Timescale Optimization for Intelligent Reflecting Surface-Assisted MIMO Transmission in Fast-Changing Channels

TL;DR

This paper introduces a two-timescale beamforming method for IRS-assisted MIMO systems in fast-changing channels, reducing overhead by combining statistical and instantaneous CSI for improved average achievable rate.

Contribution

It proposes a novel two-timescale optimization framework with a model-driven PSO algorithm that enhances IRS configuration efficiency and performance in dynamic environments.

Findings

The two-timescale approach outperforms existing methods in average achievable rate.

The model-driven PSO effectively reduces the need for channel samples.

Simulations confirm improved efficiency and IRS benefits in fast-changing channels.

Abstract

The application of intelligent reflecting surface (IRS) depends on the knowledge of channel state information (CSI), and has been hindered by the heavy overhead of channel training, estimation, and feedback in fast-changing channels. This paper presents a new two-timescale beamforming approach to maximizing the average achievable rate (AAR) of IRS-assisted MIMO systems, where the IRS is configured relatively infrequently based on statistical CSI (S-CSI) and the base station precoder and power allocation are updated frequently based on quickly outdated instantaneous CSI (I-CSI). The key idea is that we first reveal the optimal small-timescale power allocation based on outdated I-CSI yields a water-filling structure. Given the optimal power allocation, a new mini-batch sampling (mbs)- based particle swarm optimization (PSO) algorithm is developed to optimize the large-timescale IRS configuration with reduced channel samples. Another important aspect is that we develop a model-driven PSO algorithm to optimize the IRS configuration, which maximizes a lower bound of the AAR by only using the S-CSI and eliminates the need of channel samples. The modeldriven PSO serves as a dependable lower bound for the mbs-PSO. Simulations corroborate the superiority of the new two-timescale beamforming strategy to its alternatives in terms of the AAR and efficiency, with the benefits of the IRS demonstrated.