RIS-Aided Mobile Network Design

2026-03-18

AI Summary

This study addresses the challenge of insufficient 5G/6G signal coverage in complex urban environments by systematically investigating optimal deployment strategies for Reconfigurable Intelligent Surfaces (RIS) under both line-of-sight (LOS) and non-line-of-sight (NLOS) conditions. Leveraging a realistic three-dimensional urban model of Poznań, Poland, the research integrates ray-tracing simulations with SISO and MIMO antenna configurations to evaluate RIS performance. The proposed approach effectively mitigates path loss and significantly enhances signal coverage and quality in high-density urban areas. By reducing reliance on additional base stations while maintaining high service quality, this work presents a cost-effective and efficient deployment paradigm for future 5G/6G radio access networks.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Intelligent Robots: Multi-Robot Systems
• Search and Optimization: Combinatorial Optimization

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

In this paper, we examine the distribution of radio signal propagation within the city of Poznan (Poland) to determine optimal locations for deploying Reconfigurable Intelligent Surfaces (RIS). The study focuses on designing a 5G/6G Radio Access Network (RAN), incorporating eight Base Stations (BSs) that utilize either Single Input Single Output (SISO), or Multiple Input Multiple Output (MIMO) antenna technologies, depending on the network cell configuration. Through detailed simulations and analyses, we explore various propagation scenarios in both Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) conditions, considering the complex urban landscape characterized by high-rise buildings. The results demonstrate the potential of using RISs in mobile networks to enhance radio signal quality in urban environments through strategic placements. Our findings suggest that RISs can significantly mitigate Path Loss (PL) and improve signal coverage in challenging urban environments, particularly in areas where traditional base station deployment alone would be insufficient. Furthermore, the study highlights the role of RISs in reducing the need for additional base stations, thereby optimizing network costs and infrastructure while maintaining high-quality service delivery. The insights gained from this research provide valuable guidelines for network planners and engineers seeking to implement RIS technology in future 5G and beyond networks, ensuring more efficient and robust urban communication systems.

Problem

• Reconfigurable Intelligent Surfaces
• Path Loss
• Urban Propagation
• 5G/6G RAN
• Signal Coverage

Innovation

• Reconfigurable Intelligent Surfaces (RIS)
• 5G/6G RAN
• Path Loss Mitigation
• Urban Propagation Modeling
• RIS Deployment Optimization