Nonlinear signal transformations: path to capacity above the linear AWGN Shannon limit

Sorokina, Mariia; Turitsyn, Sergei K.

doi:10.1109/sum.2014.77

Cited by 2 publications

(2 citation statements)

References 15 publications

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“…93 Sorokina further argues that the Extraordinary State Commission, tasked with investigating the damage done by Nazi Germany to the Soviet Union, was '[o] ne of the immediate participants in the creation of the Stalinist war myth'. 94 Th e same can no doubt be said about the war crimes trials conducted in the Soviet Union. Perhaps one of the most successful individual components of this myth-creation was the shifting of the blame for the Katyn massacre to the Germans.…”

Section: (V) By Way Of Conclusionmentioning

confidence: 98%

Competing Histories

Liivoja¹

2013

The Hidden Histories of War Crimes Trials

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Most contributions to this volume tell untold stories about war crimes trials. Th is chapter, however, focuses on a few trials that attempt to tell untold stories. In other words, it is not the trials themselves that have been hidden in the mist of history, but rather the off ences that they deal with. My aim here is to provide a brief comment on the eff orts that the three Baltic states-Estonia, Latvia and Lithuania-have made to prosecute off ences against international law committed in their territories by the Soviet authorities during and after World War II. Th is discussion highlights the storytelling or history-writing function that trials of international crimes often have. Th e situation of the Baltic states illustrates particularly vividly what happens if the historical record produced by such trials is in confl ict with existing historical paradigms. * I am grateful to Lauri Mälksoo and Gerry Simpson for helpful comments on an earlier draft. Th e responsibility for the fi nal text, however, is mine alone.

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Section: (V) By Way Of Conclusionmentioning

confidence: 98%

Competing Histories

Liivoja¹

2013

The Hidden Histories of War Crimes Trials

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“…traffic type, system bandwidth, polarization mode dispersion values [25]; methods used, e.g. factor graphs [26], nonlinear Fourier transform [27], regenerative transformations [28], channel memory [29] etc. However, it has been established that the nonlinear performance bound is defined by the nonlinear interactions between signal and non-deterministic noise effects [23].…”

Section: Fiber Nonlinearity Compensationmentioning

confidence: 99%

Fiber Nonlinearity Compensation: Commercial Applications and Complexity Analysis

Rafique

2016

J. Lightwave Technol.

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Abstract-Fiber nonlinearities define the ultimate performance bound for optical communication systems. Today's 100Gb/s commercial products employ advanced digital signal processing (DSP) algorithms, capable to adequately address linear channel impairments, leaving fiber nonlinearity compensation (NLC) as the next logical step to improve transmission performance, and consequently diminish the need for signal regeneration. Over the last few decades, several techniques have been presented to minimize or mitigate channel nonlinearities, ranging from specialized link designs in direct-detect legacy networks to advanced DSP algorithms in coherent systems. However, specifically in the coherent age, NLC has always been perceived as an extremely complex approach, allowing insignificant gains when practical implementations are considered. In this article, we focus on the real-world commercial use cases and complexity tradeoffs for NLC, and review several application scenarios, including homogeneous and heterogeneous networks, dispersion unmanaged and dispersion managed link infrastructures, flexgrid networks, and short reach to ultra long-haul transmission applications. We establish that in various practical use cases, NLC may enable substantial performance gains, well beyond conventionally acknowledged bounds.

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Nonlinear signal transformations: path to capacity above the linear AWGN Shannon limit

Cited by 2 publications

References 15 publications

Competing Histories

Competing Histories

Fiber Nonlinearity Compensation: Commercial Applications and Complexity Analysis

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