Agile filterless optical networking

Tremblay, Christine; Littlewood, Paul; Bélanger, Michel; Wosinska, Lena; Chen, Jiajia

doi:10.23919/ondm.2017.7958526

Cited by 11 publications

(2 citation statements)

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“…Note that using QPSK instead of 16QAM halves the capacity per SC. Paths between leaf nodes and the hub on the constructed tree are calculated by the constraint (6), where one unit of auxiliary flow is generated by node u and passing through other nodes; only the hub receives it. Constraint (7) confirms that the paths are contained in the trees.…”

Section: Decision Variablesmentioning

confidence: 99%

“…However, it also leads to spectrum waste and potentially higher losses. Therefore, this architecture is only suitable for some network segments, such as metro-aggregation [6], where traffic is not meshed and transmission distances are relatively short. Closed loops must be avoided when designing filterless networks to prevent the same optical signal from crossing the same connection again [7].…”

Section: Introductionmentioning

confidence: 99%

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Multi-period planning in metro-aggregation networks exploiting point-to-multipoint coherent transceivers

Hosseini¹,

Pedro²,

Napoli³

et al. 2023

J. Opt. Commun. Netw.

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This paper proposes an integer linear programming framework to optimize the multi-period planning of metro-aggregation networks exploiting point-to-multipoint coherent pluggable transceivers and a filterless line system architecture. We investigate several planning strategies to minimize capital expenditure caused by transceiver cost based on the predictability horizon of traffic and availability of transceivers during planning while considering operational expenses (OpEx) as well. The results obtained by evaluating a deployed reference network provide evidence of reductions in transceiver cost between 20% and 32% compared to that in the point-to-point approach, and the OpEx can be reduced by around 30% at the expense of a 10% increase in transceiver cost over a five-year planning period.

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Section: Decision Variablesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%