On the Properties of Next Generation Wireless Backhaul

With the advent of 5G, cellular networks require a high number of base stations, possibly interconnected with wireless links, an evolution introduced in the last revision of 5G as the Integrated Access and Backhaul (IAB). Researchers are now working to optimize the complex topologies of the backhaul network, using synthetic models for the underlying visibility graph, i.e., the graph of possible connections between the base stations. The goal of this paper is to provide a novel methodology to generate visibility graphs starting from real data (and the data sets themselves together with the source code for their manipulation), in order to base the IAB design and optimization on assumptions that are as close as possible to reality. We introduce a GPU-based method to create visibility graphs from open data, we analyze the properties of the realistic visibility graphs, and we show that different geographic areas produce very different graphs. We run state-of-the-art algorithms to create wireless backhaul networks on top of visibility graphs, and we show that the results that exploit synthetic models are far from those that use our realistic graphs. Our conclusion is that the data-based approach we propose is essential to design mobile networks that work in a variety of real-world situations.

Automated summary

The paper aims to provide a novel methodology for generating visibility graphs based on real data to design and optimize wireless backhaul networks. Researchers use GPU-accelerated method with open data to create visibility graphs, analyze their properties, and show significant differences in graphs generated from different geographic areas. The results using realistic graphs are found to be closer to reality compared to those using synthetic models. Therefore, the data-based approach is essential for designing mobile networks that work in a variety of real-world situations.