Abstract

Background: Cell-Free Massive MIMO (CF-mMIMO) is a key enabling technology for 6G networks, but its performance degrades significantly under user mobility due to outdated clustering and pilot assignment decisions. Static resource management fails in mobile environments, while fixed periodic updates apply a uniform update rate that incurs unnecessary overhead for slow-moving users and remains insufficiently responsive for fast-moving users.

Methods: To address this limitation, this paper presents an enhanced Event-Triggered Mobility-Adaptive Clustering and Pilot Assignment (ET-MAC-PA) framework for CF-mMIMO systems with heterogeneous mobility. The proposed framework adapts AP-UE clusters and pilot assignments on a per-user basis and triggers reconfiguration only when a significant topological change is detected through variations in large-scale channel conditions. A time-resolved simulation platform, with data modeled and analyzed during 2024-2025, incorporating realistic pedestrian and vehicular mobility, spatially correlated shadow fading, and channel aging is developed to evaluate performance.

Results: Comprehensive uplink and downlink results demonstrate that ET-MAC-PA achieves higher spectral efficiency and improved user fairness compared to static and fixed periodic schemes. Moreover, the proposed approach attains a more favorable performance-overhead trade-off by dynamically adapting the update rate to user mobility. Scalability analysis further shows that the performance advantages of ET-MAC-PA increase with user density, particularly in the downlink.

Conclusion: These results indicate that event-triggered resource management is a practical and effective mechanism for CF-mMIMO operation in mobile environments.

Key words: Cell-Free Massive MIMO, Mobility, Dynamic Clustering, Heterogeneous Mobility, Resource Management, Scalability, 6G