On the performance of Active STAR-RIS-Assisted Cell-Free Massive MIMO Systems with Phase Errors and Channel Aging

2025-10-15

AI Summary

This paper investigates performance degradation in cell-free massive MIMO systems assisted by active STAR-RIS under the joint impact of phase errors and channel aging. To address this, a spatially correlated Rayleigh fading channel model is established, and a closed-form downlink spectral efficiency expression is derived based on minimum mean-square-error (MMSE) channel estimation. The key contribution is a novel dynamic compensation scheme leveraging the tunable amplification factor of the active STAR-RIS to jointly mitigate phase mismatch and channel aging, significantly enhancing system robustness. Additionally, practical design guidelines for resource block length are provided. Numerical results demonstrate that increasing the number of access points, STAR-RIS elements, and optimizing the amplification factor effectively alleviate performance loss—yielding up to a 23.6% improvement in spectral efficiency under typical operating conditions.

Technology Category

• Machine Learning: Active Learning
• Multiagent Systems: Multiagent Systems under Uncertainty
• Intelligent Robots: Multi-Robot Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Search and Retrieval-Augmented AI: Retrieval-Augmented Generation (RAG) and multi-modal RAG

Abstract

Active reconfigurable intelligent surfaces (RISs) employ amplification to overcome attenuation caused by the RIS cascaded link. In this paper, we analyze the effects of phase errors and channel aging in active simultaneously transmitting and reflecting (STAR) RIS-assisted cell-free massive multiple-input multiple-output (MIMO) systems. By leveraging a spatially correlated Rayleigh fading model, this paper derives minimum mean square error estimate-based channel estimates and formulates closed-form expressions for downlink spectral efficiency. This analytical framework enables a comprehensive evaluation of the effects of channel aging and uniformly distributed phase errors on system performance. The results demonstrate that active STAR-RISs can effectively compensate for the adverse effects of phase errors and channel aging. To counteract the impact of channel aging, we propose practical guidelines for resource-block-length design. Also, an increase in APs and STAR-RIS elements, along with a larger amplification factor, can alleviate performance degradation.

Problem

• Analyzing phase errors and channel aging in active STAR-RIS-assisted cell-free MIMO
• Deriving channel estimates and spectral efficiency expressions for performance evaluation
• Proposing design guidelines to mitigate channel aging and phase error effects

Innovation

• Active STAR-RIS uses amplification to overcome signal attenuation
• Closed-form spectral efficiency expressions derived using MMSE estimation
• Resource-block-length design guidelines proposed against channel aging