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.

On the Properties of Next Generation Wireless Backhaul

Gemmi, Gabriele
;
Maccari, Leonardo
2023-01-01

Abstract

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.
File in questo prodotto:
File Dimensione Formato  
On_the_Properties_of_Next_Generation_Wireless_Backhaul.pdf

accesso aperto

Tipologia: Versione dell'editore
Licenza: Creative commons
Dimensione 1.86 MB
Formato Adobe PDF
1.86 MB Adobe PDF Visualizza/Apri

I documenti in ARCA sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/5012889
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 6
  • ???jsp.display-item.citation.isi??? 4
social impact