Optical performance monitoring in transparent and configurable DWDM networks

Richter, A.; Fischler, W.; Bock, H.; Bach, R.; Grupp, Wolfgang

doi:10.1049/ip-opt:20020349

Cited by 19 publications

(4 citation statements)

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“…Extensive research [23]- [26] has been carried out on developing fast and accurate Q monitoring techniques for fault management in WDM networks. The feasibility and effectiveness of Q monitoring have been verified by field trials simulating realistic networks [27], [24]. Thus, it is reasonable to expect that Q meters will be more and more deployed in wavelength-routed networks for performance monitoring purpose.…”

Section: B Qos Metric: Estimation-based Vs Detection-basedmentioning

confidence: 89%

Adaptive QoS routing in dynamic wavelength-routed optical networks

Deng

Subramaniam

2005

2nd International Conference on Broadband Networks, 2005.

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In transparent DWDM (Dense Wavelength Division Multiplexing) networks, high blocking rate of lightpaths due to unsatisfactory BERs (Bit Error Rates) can become a major traffic bottleneck. Most of the existing routing schemes have focused on reducing the call rejection rate that is caused by wavelength exhaustion on the assigned routes, without considering the inferior network BER performance that these schemes often produce. In this paper, we propose a dynamic AQoS (Adaptive Quality of Service) routing algorithm, which assigns routes based on real-time Q factor measurements collected from devices. Not only is it BER-friendly, the incorporated CLC (Constrained Least Congested) approach in route selection makes our algorithm wavelength-efficient as well. AQoS routing can work seamlessly with variable data rates and heterogeneous device characteristics. More importantly, it handles non-uniform networks and state changes in a much more flexible way than traditional schemes. Simulation results show that our routing algorithm gives the best overall performance in all tested scenarios.

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Section: B Qos Metric: Estimation-based Vs Detection-basedmentioning

confidence: 89%

Adaptive QoS routing in dynamic wavelength-routed optical networks

Deng

Subramaniam

2005

2nd International Conference on Broadband Networks, 2005.

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“…OPM can be used to optimize network elements, locate and manage faults, and provide an approximate signal measure to assess the optical signal health [1][2][3][4]. In order to support network transparency, OPM techniques should be based on analog optical signal and thus, protocol or data format independent.…”

Section: Introductionmentioning

confidence: 99%

“…The electrical signal is then amplified and sampled synchronously or asynchronously and by assuming Gaussian statistics, the data is processed to obtain an estimate for Q-factor and BER. Synchronous sampling [3][4][5][6] requires clock recovery and timing information which makes it relatively more complicated to implement. Asynchronous sampling [7][8][9][10] received more attention because it does not require timing and thus uses simpler electronic circuitry.…”

Section: Introductionmentioning

confidence: 99%

Analog post amplifier effect on signal sampling and monitoring systems

Belhadj-Yahya

2008

2008 15th IEEE International Conference on Electronics, Circuits and Systems

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Synchronous and asynchronous sampling of analog signals have been established as important methods in performance monitoring of optical communication systems. The effect of analog front end amplifiers on the sampling method accuracy have been investigated using experimental measurements. The results show that post amplifiers, with automatic gain control, have a strong influence on the estimated signal quality measure (Q). When these amplifiers are operated in linear mode with optimized gain ranges the sampling method gave more accurate Q values.

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“…Therefore, despite its limitations, the Gaussian model is widely used, mostly due to its simplicity, as it is enough to measure the means and variances of the mark and space levels to estimate the BER. This information can be obtained using a variable decision threshold method (Richter et al 2002;Bergano et al 1993) or from the histograms, obtained using some kind of sampling (being it either optical (Shake et al 1998) or electrical (Weinert et al 2000;Hanik et al 1999) sampling, among them both asynchronous and synchronous methods are used).…”

mentioning

confidence: 99%

Optical signal quality metric based on statistical moments and Laguerre expansion

2008

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A new and straightforward optical signal quality metric, which is based on the approximation of the analytical probability density function by its Laguerre expansion, is proposed. This expansion uses statistical moments to approximate the true statistics, but, unlike the well-known Gaussian approximation, higher order moments can be used as well. The quality of the proposed metric is discussed and the metric is compared with the Gaussian approximation. It is shown that the new metric provides not only a good estimation of the bit error rate in the range of practical interest but, contrary to the Gaussian approximation, correctly estimates optimum decision threshold and accurately pictures the shape of the noise distribution.

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Optical performance monitoring in transparent and configurable DWDM networks

Cited by 19 publications

References 1 publication

Adaptive QoS routing in dynamic wavelength-routed optical networks

Adaptive QoS routing in dynamic wavelength-routed optical networks

Analog post amplifier effect on signal sampling and monitoring systems

Optical signal quality metric based on statistical moments and Laguerre expansion

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