This Ph.D. thesis investigates the resilient and cost-efficient design of both C-RAN and Xhaul architectures. Minimization of network resources as well as reuse of already deployed infrastructure, either based on fiber, wavelength, bandwidth or Processing Units (PU), is investigated and shown to be effective to reduce the overall cost. Moreover, the design of a survivable network against a single node (Baseband Unit hotel (BBU), Centralized/Distributed Unit (CU/DU) or link failure proposed. The novel function location algorithm, which adopts dynamic function chaining in relation to the evolution of the traffic estimation also proposed and showed remarkable improvement in terms of bandwidth saving and multiplexing gain with respect to conventional C-RAN. Finally, the adoption of Ethernet-based fronthaul and the introduction of hybrid switches is pursued to further decrease network cost by increasing optical resource usage.

Architecture and algorithm for reliable 5G network design

2020

Abstract

This Ph.D. thesis investigates the resilient and cost-efficient design of both C-RAN and Xhaul architectures. Minimization of network resources as well as reuse of already deployed infrastructure, either based on fiber, wavelength, bandwidth or Processing Units (PU), is investigated and shown to be effective to reduce the overall cost. Moreover, the design of a survivable network against a single node (Baseband Unit hotel (BBU), Centralized/Distributed Unit (CU/DU) or link failure proposed. The novel function location algorithm, which adopts dynamic function chaining in relation to the evolution of the traffic estimation also proposed and showed remarkable improvement in terms of bandwidth saving and multiplexing gain with respect to conventional C-RAN. Finally, the adoption of Ethernet-based fronthaul and the introduction of hybrid switches is pursued to further decrease network cost by increasing optical resource usage.
1-apr-2020
Università degli Studi di Bologna
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14242/145497
Il codice NBN di questa tesi è urn:nbn:it:unibo-26108