Optimizing and Managing Wireless Backhaul for Resilient Next-Generation Cellular Networks

TL;DR

This paper implements and prototype the solution as a dynamic IAB control framework based on the Open Radio Access Network (RAN) architecture, and demonstrates its functionality in Colosseum, a large-scale wireless network emulator with hardware in the loop.

Abstract

Next-generation wireless networks target high network availability, ubiquitous coverage, and extremely high data rates for mobile users. This requires exploring new frequency bands, e.g., mmWaves, moving toward ultra-dense deployments in urban locations, and providing ad hoc, resilient connectivity in rural scenarios. The design of the backhaul network plays a key role in advancing how the access part of the wireless system supports next-generation use cases. Wireless backhauling, such as the newly introduced Integrated Access and Backhaul (IAB) concept in 5G, provides a promising solution, also leveraging the mmWave technology and steerable beams to mitigate interference and scalability issues. At the same time, however, managing and optimizing a complex wireless backhaul introduces additional challenges for the operation of cellular systems. This paper presents a strategy for the optimal creation of the backhaul network considering various constraints related to network topology, robustness, and flow management. We evaluate its feasibility and efficiency using synthetic and realistic network scenarios based on 3D modeling of buildings and ray tracing. We implement and prototype our solution as a dynamic IAB control framework based on the Open Radio Access Network (RAN) architecture, and demonstrate its functionality in Colosseum, a large-scale wireless network emulator with hardware in the loop.

Figures (7)

• Figure 1: System model of the closed-loop management optimization using the (i) realistic topologies representations; (ii) graph-based optimization; and (iii) the O-RAN infrastructure.
• Figure 2: An example realization of the backhaul graph with $R\xspace=2$. Circles are -nodes, squares are -donors, orange/blue edges are backhaul links in two disjoint edge-set, gray edges are all the potential edges. Every gray node has two incoming edges.
• Figure 3: Map showing one of the four realistic networks in Milan, with density 45 /km$^2$. -nodes are in black, and feasible backhaul links have a color gradient corresponding to their capacity (yellow for low capacity and green for high capacity).
• Figure 4: Box-plots of the fraction of donors $\rho$ for the synthetic topologies, with different MIMO configuration ($\Lambda=1$, $\Lambda=2$), the single tree model ($R=1$) and the failure resistant model ($R=2$). The box plot show the median, 25% and 75% quartile and 1.5*IQR (inter quantile range) whiskers.
• Figure 5: Fraction of donors $\rho$ for the realistic topologies, with different MIMO configuration ($\Lambda=1$, $\Lambda=2$), the single tree model ($R=1$) and the failure resilient model ($R=2$).