Reconfigurable Intelligent Surfaces-Assisted Integrated Access and Backhaul

TL;DR

This paper addresses the challenge of maintaining reliable coverage in wide-area IAB networks subjected to seasonal foliage and weather-induced losses. It develops a finite stochastic geometry framework incorporating RIS-assisted backhaul and compares IAB-only, RIS-assisted, and NCR-assisted deployments, modeling backhaul and access channels with RIS phase optimization to maximize the effective gain and the backhaul rate ${R}$. The key finding is that RIS-assisted backhaul significantly improves the service coverage probability ${\rho = \Pr(R_u \ge \beta)}$ under dense foliage and rain, maintaining higher performance across frequencies (notably ${f_c = 28\,\text{GHz}}$) and user densities, with NCRs offering complementary gains in low-gain scenarios; together with optimized antenna configurations, RIS-enabled IAB networks exhibit robust, year-round performance. These results provide practical guidelines for deploying resilient, energy-efficient wide-area IAB networks in future 6G architectures, leveraging RIS to counter environmental impairments and balance backhaul/access resource allocation. ${\rho}$ and ${R_u}$ are central performance metrics in the analysis, framing design choices around backhaul pathways, frequency, and environmental variability.

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.

Figures (5)

• Figure 1: Illustration of the wide-area IAB assisted with RIS for backhaul links amidst seasonal tree foliage changes.
• Figure 2: Network service coverage probability as a function of total tree depth.
• Figure 3: Network service coverage probability for different carrier frequencies as a function of number of UEs, $N$.
• Figure 4: Network service coverage probability as a function of rain intensity in the presence of tree foliage.
• Figure 5: Network service coverage probability as a function of main lobe antenna gain.