Modeling of Nonlinear Signal Distortion in Fiber-Optic Networks

Johannisson, Pontus; Agrell, Erik

doi:10.1109/jlt.2014.2361357

Cited by 120 publications

(136 citation statements)

References 27 publications

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“…Break; 13: end if 14: end for 15: end for 16: I ← I + J ; 17: while there is no valid spectral efficiency value in c 18: remove rounded values of c; 19: while there is an inacceptable spectral efficiency value in c main parameters that affect the amount of NLIs [22], [23]. To simultaneously minimize NLIs and ASE noises, one idea is to add minimization of the number of common links to the SPR goal function:…”

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confidence: 99%

Resource Allocation for Elastic Optical Networks Using Geometric Optimization

Hadi

Pakravan

2017

J. Opt. Commun. Netw.

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Abstract-Resource allocation with quality of service constraints is one of the most challenging problems in elastic optical networks which is normally formulated as a mixed-integer nonlinear optimization program. In this paper, we focus on novel properties of geometric optimization and provide a heuristic approach for resource allocation which is very faster than its mixed-integer nonlinear counterpart. Our heuristic consists of two main parts for routing/traffic ordering and power/spectrum assignment. It aims at minimization of transmitted optical power and spectrum usage constrained to quality of service and physical requirements. We consider three routing/traffic ordering procedures and compare them in terms of total transmitted optical power, total received noise power and total nonlinear interference including self-and cross-channel interferences. We propose a posynomial expression for optical signal to noise ratio in which fiber nonlinearities and spontaneous emission noise have been addressed. We also propose posynomial expressions that relate modulation spectral efficiency to its corresponding minimum required optical signal to noise ratio. We then use the posynomial expressions to develop six geometric formulations for power/spectrum assignment part of the heuristic which are different in run time, complexity and accuracy. Simulation results demonstrate that the proposed solution has a very good accuracy and much lower computational complexity in comparison with mixed-integer nonlinear formulation. As example for European Cost239 optical network with 46 transmit transponders, the geometric formulations can be more than 59 times faster than its mixed-integer nonlinear counterpart. Numerical results also reveal that in long-haul elastic optical networks, considering the product of the number of common fiber spans and the transmission bit rate is a better goal function for routing/traffic ordering sub-problem.

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confidence: 99%

Resource Allocation for Elastic Optical Networks Using Geometric Optimization

Hadi

Pakravan

2017

J. Opt. Commun. Netw.

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“…Considering these four effects are in line with what literature deals with. For this work we will use the physical layer model proposed in [17,18].…”

Section: Physical Layer Impairmentmentioning

confidence: 99%

Performance Evaluation of Survivability Strategies for Elastic Optical Networks under Physical Layer Impairments

Lacerda¹,

Fontinele²,

Moura³

et al. 2017

CLEIej

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This paper carried out a performance evaluation study that compares two survivability strategies (DPP and SM-RSA) for elastic optical networks with and without physical layer impairments. The evaluated scenarios include three representative topologies for elastic optical network, NSFNET, EON and USA. It also analyzes the increase of blocking probability when the survivability strategies are evaluated under the realistic scenario that assumes physical layer impairments. For all studied topologies under physical layer impairments, the survivability strategies achieved blocking probability above 80%.

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“…That's why we follow the algorithm of scheduling used for nonlinear propagation where linear routing and wavelength choice finding are the great problems [5]. As a result, accuracy and simple simulation process are required to obtain the best performance of the link.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Nonlinear Signal Interference to Optimize the Coherent Optical Transmission System

Gafur¹

2017

IOSR JECE

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Modeling of Nonlinear Signal Distortion in Fiber-Optic Networks

Cited by 120 publications

References 27 publications

Resource Allocation for Elastic Optical Networks Using Geometric Optimization

Resource Allocation for Elastic Optical Networks Using Geometric Optimization

Performance Evaluation of Survivability Strategies for Elastic Optical Networks under Physical Layer Impairments

Analysis of Nonlinear Signal Interference to Optimize the Coherent Optical Transmission System

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