Manifold-Based Optimizations for RIS-Aided Massive MIMO Systems

TL;DR

This paper introduces manifold optimization as an effective framework for enhancing RIS-aided massive MIMO systems, demonstrating its advantages through five application examples in wireless communications.

Contribution

It provides a tutorial on manifold optimization and applies it to solve complex problems in RIS-aided massive MIMO systems, showcasing its effectiveness.

Findings

Improved fairness and energy efficiency in RIS-aided mMIMO systems.

Effective mitigation of intracell pilot reuse interference.

Enhanced grant-free random access performance.

Abstract

Manifold optimization (MO) is a powerful mathematical framework that can be applied to optimize functions over complex geometric structures, which is particularly useful in advanced wireless communication systems, such as reconfigurable intelligent surface (RIS)-aided massive MIMO (mMIMO) and extra-large scale massive MIMO (XL-MIMO) systems. MO provides a structured approach to tackling complex optimization problems. By leveraging the geometric properties of the manifold, more efficient and effective solutions can be found compared to conventional optimization methods. This paper provides a tutorial on MO technique and provides some applications of MO in the context of wireless communications systems. In particular, to corroborate the effectiveness of MO methodology, we explore five application examples in RIS-aided mMIMO system, focusing on fairness, energy efficiency (EE) maximization, intracell pilot reuse interference mitigation, and grant-free (GF) random access (RA).