Limited Feedback in RIS-Assisted Wireless Communications: Use Cases, Challenges, and Future Directions

TL;DR

This paper reviews the importance of limited CSI feedback in RIS-assisted wireless systems, discussing unique channel features, feedback design challenges, and future research directions involving advanced techniques like autoencoders and AI.

Contribution

It provides a comprehensive overview of RIS channel features, challenges in feedback design, and proposes leveraging modern techniques for efficient feedback schemes and future research directions.

Findings

RIS channel features include position-dependent fluctuations and structured sparsity.

Techniques like autoencoders can reduce feedback overhead.

Future directions involve integrating AI and new RIS architectures.

Abstract

Channel state information (CSI) is essential to unlock the potential of reconfigurable intelligent surfaces (RISs) in wireless communication systems. Since massive RIS elements are typically implemented without baseband signal processing capabilities, limited CSI feedback is necessary when designing the reflection/refraction coefficients of the RIS. In this article, the unique RIS-assisted channel features, such as the RIS position-dependent channel fluctuation, the ultra-high dimensional sub-channel matrix, and the structured sparsity, are distilled from recent advances in limited feedback and used as guidelines for designing feedback schemes. We begin by illustrating the use cases and the corresponding challenges associated with RIS feedback. We then discuss how to leverage techniques such as channel customization, structured-sparsity, autoencoders, and others to reduce feedback overhead and complexity when devising feedback schemes. Finally, we identify potential research directions by considering the unresolved challenges, the new RIS architecture, and the integration with multi-modal information and artificial intelligence.