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SDN-Enabled Resource Management for Converged Fi-Wi 5G Fronthaul

Authors :
Kostas Ramantas
Christos Verikoukis
Luiz Anet Neto
Eftychia Datsika
John S. Vardakas
Prodromos-Vasileios Mekikis
Idelfonso Tafur Monroy
Terahertz Photonic Systems
Terahertz Systems
Center for Quantum Materials and Technology Eindhoven
Center for Terahertz Science and Technology Eindhoven
Source :
IEEE Journal on Selected Areas in Communications, IEEE Journal on Selected Areas in Communications, 39(9):9373366, 2772-2788. Institute of Electrical and Electronics Engineers

Abstract

Future mobile networks will offer high data rates based on high-capacity fronthaul. Current fronthaul design has two main components that communicate via the common public radio interface and fiber links, i.e., remote units (RUs) that implement simple signal processing and centralized baseband units (CBBUs) in high power-consuming data centers that perform complex network functions. Various functional splits between CBBUs and RUs are feasible, inducing trade-offs between centralization gains and bandwidth demands. This design lacks in capacity and flexibility, motivating the use of converged fiber-wireless (Fi-Wi) fronthaul with high-bandwidth fiber and millimeter-wave links, and splits that move functionalities to RUs reducing the delay demands. Further flexibility is offered by analog radio-over-fiber fronthaul that supports dynamic functional splitting via software-defined networking (SDN). Ensuring acceptable delay for all RUs, i.e., minimizing fronthaul grade-of-service (GoS), requires selection of CBBUs, channel bandwidth and functional splits of RUs. The split type affects fronthaul power consumption determining which fronthaul components are active and their processing power. Using a simulated annealing-based dynamic fronthaul resource allocation (DFRA) scheme, we jointly optimize GoS and power consumption in a novel SDN Fi-Wi fronthaul. Our results show that DFRA minimizes GoS and power consumption for all load levels outperforming baseline approaches.

Details

Language :
English
ISSN :
15580008 and 07338716
Volume :
39
Issue :
9
Database :
OpenAIRE
Journal :
IEEE Journal on Selected Areas in Communications
Accession number :
edsair.doi.dedup.....302db5e88186eff1eb5256ee51642c93
Full Text :
https://doi.org/10.1109/jsac.2021.3064651