Energy and Transmission Efficiency Enhancement in Passive Optical Network Enabled Reconfigurable Fronthaul Supporting Smart Homes

Smart home technologies are growing actively all around the world. As a result, great pressures are imposed on internet of things networks by dynamic traffic and plenty of devices. The passive optical network is considered one of the most promising fronthaul technologies. In particular, the time and...

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Veröffentlicht in:Sensors (Basel, Switzerland) Jg. 20; H. 21; S. 6245
Hauptverfasser: Gu, Rentao, Wang, Gang, Li, Zhekang, Ji, Yuefeng
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Basel MDPI AG 02.11.2020
MDPI
Schlagworte:
Algorithms
Artificial intelligence
cloud radio access networks
Design
Energy consumption
Energy efficiency
Internet of Things
Linear programming
Machine learning
mobile networks
network algorithms
network resources allocation
Optimization
Signal processing
Smart houses
Wave division multiplexing
ISSN:1424-8220, 1424-8220
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Zusammenfassung:Smart home technologies are growing actively all around the world. As a result, great pressures are imposed on internet of things networks by dynamic traffic and plenty of devices. The passive optical network is considered one of the most promising fronthaul technologies. In particular, the time and wavelength division multiplexing passive optical network has shown the advantage of high capacity and received attention recently. In support of internet of things networks, the energy and transmission efficiency has emerged as an important issue on the time and wavelength division multiplexing passive optical network enabled fronthaul networks. In this paper, we try to enhance the energy and transmission efficiency of the time and wavelength division multiplexing passive optical network enabled reconfigurable fronthaul. Fronthaul links’ load balancing is also taken into consideration. An integer non-linear programming model is employed to formulate the joint optimization problem. We also provide an adaptive genetic algorithm-based approach with fast convergence. The simulation results show that the active units of fronthaul can be dynamically switched on/off with the traffic variation and a significant energy saving is achieved. In addition, the maximum transmission efficiency increases by 87% with integer non-linear programming method in off-peak periods.
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ISSN:1424-8220
1424-8220
DOI:10.3390/s20216245