Distributed SNIR Optimization Based on the Verhulst Model in Optical Code Path Routed Networks With Physical Constraints

Durand, Fábio Renan; Abrão, Taufik

doi:10.1364/jocn.3.000683

Cited by 19 publications

(43 citation statements)

References 30 publications

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“…The channel error estimation of = 0.2 represents the maximum uncertainty when there are OPMs of OSNR, power, CD and PMD measurements in all links with acceptable accuracy of the measurements. For this case, the NMSE is approximately 10 -2 , which is adequate to the dynamical adjustment of the transmitted power [8]. However, if there are available only the OPM of power meter in all links of the lightpath, the channel error estimation will increase to 0.4 and the NMSE is approximately 6  10 -2 .…”

Section: Numerical Resultsmentioning

confidence: 97%

“…The quality of solution achieved by any iterative resource allocation procedure could be measured by how close to the optimum solution the found solution is, and can be quantified by the normalized mean squared error (NMSE) when equilibrium is reached after n iterations. For power allocation problem, the NMSE definition is given by [8],…”

Section: Optical Signal Noise Ratio Optimizationmentioning

confidence: 99%

“…, where I is an identity matrix, H is the normalized interference matrix, whose elements can be evaluated by , = Γ , Γ , ⁄ for i  j and zero for other case [8]. The matrix inversion is equivalent to a centralized power control strategy, i.e.…”

Section: Optical Signal Noise Ratio Optimizationmentioning

confidence: 99%

“…the existence of a central node able to proceed with power control calculation. The central node storages information about all physical network architecture like link length between nodes and regular update about link establishment and dynamic of traffic [8]. These observations justify the need for on-line OSNR optimization algorithms, which have provable convergence properties for general network configurations [7], [9].…”

Section: Optical Signal Noise Ratio Optimizationmentioning

confidence: 99%

“…The establishment of lightpaths with a higher OSNR enables us to minimize the number of retransmissions by higher layers, thus increasing network throughput and energy efficiency [7] [8]. For a dynamic traffic requests the objective is to minimize the blocking probability of the lightpaths established by routing, assigning channels while maintain an acceptable level of optical power and suitable OSNR all over the network [7] [9].…”

mentioning

confidence: 99%

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Estimation Uncertainties in the Optical Signal-to-Noise Ratio Network Optimization

Durand

Lopes

Spagolla

et al. 2016

J. Microw. Optoelectron. Electromagn. Appl.

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Abstract-In this work, we investigate the effects of estimation uncertainties in the optimization of the optical signal-to-noise ratio (OSNR) at the wavelength division multiplexing (WDM) optical networks. The OSNR optimization increases the network throughput and energy efficiency and it enables to minimize the number of retransmissions by higher layers. The OSNR optimization algorithms are related to the optical channel estimation performed by the combinations of optical performance monitors (OPM) measurements, analytical models and numerical simulations. Furthermore, the estimation uncertainties are introduced by several factors such as the availability of monitoring information, monitoring accuracy, imperfection of physical layer and dynamic of channel allocation. Our numerical results have demonstrated the relation between the uncertainties in the channel error estimation, normalized mean squared error (NMSE) and power penalty. The developed methodology can be utilized to determinate the maxim level of acceptable uncertainties in the channel error estimation according the power penalty permitted in the OSNR optimization.

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Section: Numerical Resultsmentioning

confidence: 97%

Section: Optical Signal Noise Ratio Optimizationmentioning

confidence: 99%

Section: Optical Signal Noise Ratio Optimizationmentioning

confidence: 99%

Section: Optical Signal Noise Ratio Optimizationmentioning

confidence: 99%

mentioning

confidence: 99%

See 3 more Smart Citations

Estimation Uncertainties in the Optical Signal-to-Noise Ratio Network Optimization

Durand

Lopes

Spagolla

et al. 2016

J. Microw. Optoelectron. Electromagn. Appl.

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Time-delay and estimation uncertainty impact on the heuristic-based power control of optical networks

Durand

Abrão

2015

Opt Quant Electron

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Energy efficiency in optical CDMA networks with forward error correction

Durand

Abrão

2015

Photon Netw Commun

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In this work, we investigate the energy efficiency in optical code division multiplexing access (OCDMA) networks with forward error correction (FEC). We have modeled the energy efficiency considering the capacity of information transmitted and the network power consumption. The proposed network power consumption model considers the optical transmitter, receiver, optical amplifiers, FEC and network infrastructure as encoders, decoders, star coupler and network control in the overall optical power network consumption balance. Furthermore, an expression relating the signal-to-noise-plus-interference ratio gain for forward error correction with low-density parity-check code scheme considering the power consumption and bandwidth occupancy has been derived. Numerical results for OCDMA networks with aggregated FEC procedure have revealed the viability of the FEC deployment aiming to increase the overall energy efficiency of OCDMA networks.

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Distributed SNIR Optimization Based on the Verhulst Model in Optical Code Path Routed Networks With Physical Constraints

Cited by 19 publications

References 30 publications

Estimation Uncertainties in the Optical Signal-to-Noise Ratio Network Optimization

Estimation Uncertainties in the Optical Signal-to-Noise Ratio Network Optimization

Time-delay and estimation uncertainty impact on the heuristic-based power control of optical networks

Energy efficiency in optical CDMA networks with forward error correction

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