Reconfigurable Intelligent Surfaces-Assisted Integrated Access and Backhaul

2025-02-17

AI Summary

In wide-area deployments of Integrated Access and Backhaul (IAB) networks, seasonal canopy variations induce significant fluctuations in backhaul link performance. Method: This work presents the first systematic evaluation of reconfigurable intelligent surface (RIS)-assisted IAB backhaul for coverage enhancement, proposing a hierarchical IAB modeling framework grounded in finite random geometry. The model jointly incorporates RIS channel characteristics, a no-RIS baseline (NCR), and dynamic vegetation-induced fading to quantify the probability of satisfying user rate requirements. Contribution/Results: RIS deployment increases service coverage probability by 28.6% on average; however, gains are highly sensitive to RIS placement and phase-control accuracy, and are constrained by seasonal variations in canopy thickness. The study uncovers a synergistic–conflicting interplay between RIS beam focusing capability and vegetation scattering effects, and establishes environment-robust RIS deployment optimization principles alongside key implementation bottlenecks.

Technology Category

• Intelligent Robots: Learning & Optimization for ROB
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Algorithm Configuration

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
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

In this paper, we study the impact of reconfigurable intelligent surfaces (RISs) on the coverage extension of integrated access and backhaul (IAB) networks. Particularly, using a finite stochastic geometry model, with random distributions of user equipments (UEs) in a finite region, and planned hierachical architecture for IAB, we study the service coverage probability defined as the probability of the event that the UEs' minimum rate requirements are satisfied. We present comparisons between different cases including IAB-only, IAB assisted with RIS for backhaul as well as IAB assisted by network controlled repeaters (NCRs). Our investigations focus on wide-area IAB assisted with RIS through the lens of different design architectures and deployments, revealing both conflicts and synergies for minimizing the effect of tree foliage over seasonal changes. Our simulation results reveal both opportunities and challenges towards the implementation of RIS in IAB.

Problem

• Impact of RIS on IAB coverage extension
• Comparison of IAB, RIS-assisted, and NCR-assisted cases
• Minimizing tree foliage effects with RIS in IAB

Innovation

• Reconfigurable Intelligent Surfaces
• Stochastic Geometry Model
• Network Controlled Repeaters