Coverage Improvement and Reconfigurable Intelligent Surfaces across Indoor Wireless Networks

Abstract

The advent of highly demanding wireless communication standards has necessitated the exploration of novel technologies capable of mitigating signal degradation in complex environments. Among these technologies, Reconfigurable Intelligent Surfaces have emerged as a paradigm-shifting solution for manipulating electromagnetic wave propagation, transforming the wireless environment from a passive medium into an active, controllable entity. This paper presents a comprehensive investigation into the coverage improvement capabilities of Reconfigurable Intelligent Surfaces deployed within indoor wireless networks. By employing an advanced agent-based modeling framework, this study captures the intricate and dynamic interactions between base stations, mobile user equipment, and dynamically adjustable reflecting elements. The simulation environment models a highly obstructed indoor office space where traditional signal propagation suffers from severe multi-path fading, penetration losses, and shadow blockages. Through systematic variation of surface element configurations and user mobility patterns, the agent-based model demonstrates that strategically positioned intelligent surfaces significantly enhance signal-to-noise ratios and drastically reduce the occurrence of communication blind spots. The results indicate that decentralized agent interactions can effectively approximate optimal phase shift adjustments in real-time, providing robust coverage even for highly mobile users. This research underscores the viability of Reconfigurable Intelligent Surfaces as a cost-effective, energy-efficient infrastructure enhancement for future wireless systems, offering critical insights for network planners and engineers.