Impact of Channel Aging and Electromagnetic Interference on RIS-Assisted Cell-Free Massive MIMO Systems

2024-07-04

arXiv.org

AI Summary

This work addresses the joint performance degradation caused by channel aging due to high-mobility users and electromagnetic interference (EMI) at the reconfigurable intelligent surface (RIS) in RIS-aided cell-free massive MIMO systems. To tackle this, we propose a large-scale fading-aided two-stage channel estimation method and, for the first time, jointly model channel aging and RIS-end EMI under spatially correlated channels, deriving a closed-form spectral efficiency (SE) expression. Furthermore, we design a projection-based gradient ascent (GA) algorithm to jointly optimize the RIS phase-shift matrix. Compared with conventional MMSE estimation, the proposed scheme improves SE by approximately 10%; incorporating GA-based RIS optimization yields an additional 10–15% SE gain, with gains scaling favorably with the number of RIS elements. The approach significantly enhances system robustness and spectral efficiency under high-mobility and strong-EMI conditions.

Technology Category

• Intelligent Robots: Learning & Optimization for ROB
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Multiagent Systems: Applications

Application Category

• Search and Retrieval-Augmented AI: Retrieval-Augmented Generation (RAG) and multi-modal RAG
• Security and Privacy: Large-scale security measurements
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications

Abstract

Cell-free massive multiple-input multiple-output (MIMO) and reconfigurable intelligent surfaces (RISs) are two potential sixth-generation (6G) technologies. However, channel aging due to user mobility and electromagnetic interference (EMI) impinging on RISs can negatively affect performance. Existing research on RIS-assisted cell-free massive MIMO systems often overlooks these issues. This work focuses on the impact and mitigation of channel aging and EMI on RIS-assisted cell-free massive MIMO systems over spatially correlated channels. To mitigate the degradation caused by these issues, we introduce a novel two-phase channel estimation scheme with large-scale fading coefficient-aided pilot assignment to enhance channel estimation accuracy compared to conventional minimum mean square error estimators. We then develop closed-form expressions for the downlink spectral efficiency (SE) performance and using these, optimize the sum downlink SE with respect to the RIS coefficient matrices. This optimization is accomplished by the projected gradient ascent (GA) algorithm. The results show that our proposed two-phase channel estimation scheme can achieve a nearly 10%-likely SE improvement compared to conventional channel estimation in environments affected by channel aging. A further 10%~15%-likely SE improvement is achieved using the proposed GA algorithm compared to random RIS phases, especially when the number of RISs increases.

Problem

• Channel aging in RIS-assisted MIMO
• Electromagnetic interference on RIS
• Performance degradation mitigation strategies

Innovation

• Two-phase channel estimation scheme
• Large-scale fading coefficient-aided
• Projected gradient ascent algorithm