Gain equalization in metropolitan and wide area optical networks using optical amplifiers

Li, C.-S.; Tong, F.; Georgiou, C.J.; Chen, M.

doi:10.1109/infcom.1994.337624

Cited by 27 publications

(51 citation statements)

References 15 publications

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“…In wireless sensor networks it may correspond to the maximum distance a signal can be transmitted from the sensors and relays [93]; in optical networks it may represent a bound on the maximum distance between optical amplifiers [253,319]; while in networks in microchips the bound may correspond to a maximum permitted distance between buffers [269].…”

Section: Minimum Steiner Point Tree Problem In the Planementioning

confidence: 99%

Optimal Interconnection Trees in the Plane

Brazil

Zachariasen

2015

Algorithms and Combinatorics

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Section: Minimum Steiner Point Tree Problem In the Planementioning

confidence: 99%

Optimal Interconnection Trees in the Plane

Brazil

Zachariasen

2015

Algorithms and Combinatorics

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“…Optical amplifiers do not have a flat gain spectrum and have potential problems with gain saturation. Although there exist methods to equalize the gain spectrum and place the amplifiers so that all channels are received with approximately equal powers [25], such techniques require monitoring of the received power in each WDM channel, but no simple means has been proposed to perform this monitoring without demultiplexing to individual wavelengths. As shown in Fig.…”

Section: Other Applications Of Identification Tonesmentioning

confidence: 99%

Methods for crosstalk measurement and reduction in dense WDM systems

Kahn

1996

J. Lightwave Technol.

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We propose a scheme for the monitoring and reduction of crosstalk arising from the limited stop-band rejection of optical bandpass filters in dense WDM systems. The optical carrier at each wavelength is modulated with a subcarrier tone unique to that wavelength. The level of crosstalk from a given channel cain be determined by measuring the power of the corresponding; tone. Crosstalk from other channels can be cancelled in a linear fashion by weighting and summing the photocurrents of the desired channel and several adjacent interfering channels. Alternatively, in nonlinear crosstalk cancellation, decisions are made on the interfering signals, and these decision are weighted and summed with the photocurrent of the desired channel. For example, assuming an optical filter having a Gaussian passband, the channel density can be increased from 20 to 30%, depending on the number of adjacent channels ' detected. The signal-tointerference ratio can be increased by 10-20 dB and the system can achieve a BER < low9 under conditions where, without interference cancellation, the signal-to-interference ratio would be less then 10 dB.

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“…The length of an edge of the multicast tree represents the transmission distance, building or routing costs between two devices in the network. In the wavelength‐division multiplexing (WDM) optical network, due to the limited transmission power, signals can be delivered only over a limited distance, otherwise signals may be lost . Hence, if the length of any two devices in the multicast tree is greater than the limited distance in a WDM optical network, we need to arrange some amplifiers (devices) between the two devices such that the correct transmission can be guaranteed.…”

Section: Introductionmentioning

confidence: 99%

“…Of course, we would like to have the transmission distance between two devices in a multicast tree as small as possible. This reason caused us to construct a multicast tree with minimum length of a bottleneck edge . For more details on these applications, see .…”

Section: Introductionmentioning

confidence: 99%

The bottleneck selected‐internal and partial terminal Steiner tree problems

Chen

2016

Networks

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Given a complete graph G = (V , E ), a positive length function on edges, and two subsets R of V and R of R, the selected-internal Steiner tree is defined to be an acyclic subgraph of G spanning all vertices in R such that no vertex in R is a leaf of the subgraph. The bottleneck selected-internal Steiner tree problem is to find a selected-internal Steiner tree T for R and R in G such that the length of the largest edge in T is minimized. The partial terminal Steiner tree is defined to be an acyclic subgraph of G spanning all vertices in R such that each vertex in R is a leaf of the subgraph. The bottleneck partial terminal Steiner tree problem is to find a partial terminal Steiner tree T for R and R in G such that the length of the largest edge in T is minimized. In this article, we show that the bottleneck selected-internal Steiner tree problem is NP-complete. We also show that if there is a (2− )-approximation algorithm, > 0, for the bottleneck selected-internal Steiner tree problem on metric graphs (i.e., a complete graph and the lengths of edges satisfy the triangle inequality), then P=NP. Then we extend to show that if there is an (α(|V |) − )-approximation algorithm, > 0, for the bottleneck selected-internal Steiner tree problem, then P=NP, where α(|V |) is any computable function of |V |. Moreover, we present an approximation algorithm with performance ratio of 3 for the bottleneck selected-internal Steiner tree problem on metric graphs. Finally, we present an exact algorithm of O(|V | 2 log |V |) time for the bottleneck partial terminal Steiner tree problem.

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Gain equalization in metropolitan and wide area optical networks using optical amplifiers

Cited by 27 publications

References 15 publications

Optimal Interconnection Trees in the Plane

Optimal Interconnection Trees in the Plane

Methods for crosstalk measurement and reduction in dense WDM systems

The bottleneck selected‐internal and partial terminal Steiner tree problems

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