Quasi-Passive Reconfigurable Node for 5G Mobile Optical Backhaul Networks

Wang, K, Gowda, A, Yin, S, Bi, Y and Kazovsky, L 2018, 'Quasi-Passive Reconfigurable Node for 5G Mobile Optical Backhaul Networks', Journal of Lightwave Technology, vol. 36, no. 23, pp. 5432-5441.

Document type: Journal Article
Collection: Journal Articles

Title Quasi-Passive Reconfigurable Node for 5G Mobile Optical Backhaul Networks
Author(s) Wang, K
Gowda, A
Yin, S
Bi, Y
Kazovsky, L
Year 2018
Journal name Journal of Lightwave Technology
Volume number 36
Issue number 23
Start page 5432
End page 5441
Total pages 10
Publisher IEEE
Abstract A novel multi-dimensional quasi-passive reconfigurable (MD-QPAR) node for 5G mobile backhaul optical WDM mesh networks is proposed in this paper. The proposed MD-QPAR is capable of providing dynamic power and wavelength allocations for signals from any input port(s) to any output port(s). Each input/output port is connected to one possible direction or the local wireless nodes, and hence, the data rate, flexibility, robustness, and reliability requirements in 5G backhaul networks can be satisfied. In addition, the MD-QPAR is 'quasi-passive,' where it only consumes power during network reconfigurations and there is no power consumption during steady-state operations, to enable high energy efficiency. Three possible MD-QPAR structures are proposed and studied. Simulations under the optical Flow traffic assumption are carried out and the signal blocking probability and the scalability are investigated. Proof-of-concept experiments are also undertaken and the MD-QPAR with Structure II is demonstrated. Results show that dynamic power and wavelength distributions from any input port(s) to any output port(s) can be realized, and the power penalty due to the MD-QPAR is limited to <0.5 dB.
Subject Communications Technologies not elsewhere classified
Keyword(s) 5G mobile backhaul
optical latching switch
optical WDM networks
quasi-passive reconfigurable node
DOI - identifier 10.1109/JLT.2018.2875049
Copyright notice © 2018 IEEE
ISSN 0733-8724
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