TU Darmstadt / ULB / TUbiblio

RadiOrchestra: Proactive Management of Millimeter-wave Self-backhauled Small Cells via Joint Optimization of Beamforming, User Association, Rate Selection, and Admission Control

Abanto-Leon, Luis F. ; Garcia-Saavedra, Andres ; Asadi, Arash ; Sim, Gek Hong ; Hollick, Matthias (2022)
RadiOrchestra: Proactive Management of Millimeter-wave Self-backhauled Small Cells via Joint Optimization of Beamforming, User Association, Rate Selection, and Admission Control.
In: IEEE Transactions on Wireless Communications, (Early Access)
doi: 10.1109/TWC.2022.3191744
Artikel, Bibliographie

Kurzbeschreibung (Abstract)

Millimeter-wave self-backhauled small cells are a key component of next-generation wireless networks. Their dense deployment will increase data rates, reduce latency, and enable efficient data transport between the access and backhaul networks, providing greater flexibility not previously possible with optical fiber. Despite their high potential, operating dense self-backhauled networks optimally is an open challenge, particularly for radio resource management (RRM). This paper presents, RadiOrchestra, a holistic RRM framework that models and optimizes beamforming, rate selection as well as user association and admission control for self-backhauled networks. The framework is designed to account for practical challenges such as hardware limitations of base stations (e.g., computational capacity, discrete rates), the need for adaptability of backhaul links, and the presence of interference. Our framework is formulated as a nonconvex mixed-integer nonlinear program, which is challenging to solve. To approach this problem, we propose three algorithms that provide a trade-off between complexity and optimality. Furthermore, we derive upper and lower bounds to characterize the performance limits of the system. We evaluate the developed strategies in various scenarios, showing the feasibility of deploying practical self-backhauling in future networks.

Typ des Eintrags: Artikel
Erschienen: 2022
Autor(en): Abanto-Leon, Luis F. ; Garcia-Saavedra, Andres ; Asadi, Arash ; Sim, Gek Hong ; Hollick, Matthias
Art des Eintrags: Bibliographie
Titel: RadiOrchestra: Proactive Management of Millimeter-wave Self-backhauled Small Cells via Joint Optimization of Beamforming, User Association, Rate Selection, and Admission Control
Sprache: Englisch
Publikationsjahr: 25 Juli 2022
Verlag: IEEE
Titel der Zeitschrift, Zeitung oder Schriftenreihe: IEEE Transactions on Wireless Communications
(Heft-)Nummer: Early Access
DOI: 10.1109/TWC.2022.3191744
Kurzbeschreibung (Abstract):

Millimeter-wave self-backhauled small cells are a key component of next-generation wireless networks. Their dense deployment will increase data rates, reduce latency, and enable efficient data transport between the access and backhaul networks, providing greater flexibility not previously possible with optical fiber. Despite their high potential, operating dense self-backhauled networks optimally is an open challenge, particularly for radio resource management (RRM). This paper presents, RadiOrchestra, a holistic RRM framework that models and optimizes beamforming, rate selection as well as user association and admission control for self-backhauled networks. The framework is designed to account for practical challenges such as hardware limitations of base stations (e.g., computational capacity, discrete rates), the need for adaptability of backhaul links, and the presence of interference. Our framework is formulated as a nonconvex mixed-integer nonlinear program, which is challenging to solve. To approach this problem, we propose three algorithms that provide a trade-off between complexity and optimality. Furthermore, we derive upper and lower bounds to characterize the performance limits of the system. We evaluate the developed strategies in various scenarios, showing the feasibility of deploying practical self-backhauling in future networks.

Fachbereich(e)/-gebiet(e): DFG-Sonderforschungsbereiche (inkl. Transregio)
DFG-Sonderforschungsbereiche (inkl. Transregio) > Sonderforschungsbereiche
DFG-Sonderforschungsbereiche (inkl. Transregio) > Sonderforschungsbereiche > SFB 1053: MAKI – Multi-Mechanismen-Adaption für das künftige Internet
DFG-Sonderforschungsbereiche (inkl. Transregio) > Sonderforschungsbereiche > SFB 1053: MAKI – Multi-Mechanismen-Adaption für das künftige Internet > T: Transferprojekte
DFG-Sonderforschungsbereiche (inkl. Transregio) > Sonderforschungsbereiche > SFB 1053: MAKI – Multi-Mechanismen-Adaption für das künftige Internet > T: Transferprojekte > Transferprojekt T1: Adaptivität im Mobilfunk
Hinterlegungsdatum: 15 Aug 2022 07:51
Letzte Änderung: 15 Aug 2022 07:51
PPN:
Export:
Suche nach Titel in: TUfind oder in Google
Frage zum Eintrag Frage zum Eintrag

Optionen (nur für Redakteure)
Redaktionelle Details anzeigen Redaktionelle Details anzeigen