Capacity Limits of Optical Fiber Networks

By René-Jean Essiambre, Gerhard Kramer, Peter J. Winzer, Gerard J. Foschini, Bernhard Goebel. Journal of Lightwave Technology, 2010

2,243 citations recorded by the source corpus.

We describe a method to estimate the capacity limit of fiber-optic communication systems (or ¿fiber channels¿) based on information theory. This paper is divided into two parts. Part 1 reviews fundamental concepts of digital communications and information theory. We treat digitization and modulation followed by information theory for channels both without and with memory. We provide explicit relationships between the commonly used signal-to-noise ratio and the optical signal-to-noise ratio. We further evaluate the performance of modulation constellations such as quadrature-amplitude modulation, combinations of amplitude-shift keying and phase-shift keying, exotic constellations, and concentric rings for an additive white Gaussian noise channel using coherent detection. Part 2 is devoted specifically to the "fiber channel.'' We review the physical phenomena present in transmission over optical fiber networks, including sources of noise, the need for optical filtering in optically-routed networks, and, most critically, the presence of fiber Kerr nonlinearity. We describe various transmission scenarios and impairment mitigation techniques, and define a fiber channel deemed to be the most relevant for communication over optically-routed networks. We proceed to evaluate a capacity limit estimate for this fiber channel using ring constellations. Several scenarios are considered, including uniform and optimized ring constellations, different fiber dispersion maps, and varying transmission distances. We further present evidences that point to the physical origin of the fiber capacity limitations and provide a comparison of recent record experiments with our capacity limit estimation.

Subfields: Electrical and Electronic Engineering, Signal Processing

View Paper: https://www.semanticscholar.org/paper/a6e9528391ee823879a204857f47b6b490744755

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In Electrical and Electronic Engineering

  1. Peter J. Winzer
  2. Pierluigi Poggiolini
  3. Robert Schober
  4. H. Vincent Poor
  5. Rui Zhang
  6. Bruno Clerckx
  7. Roberto Morandotti
  8. Dong In Kim

In Signal Processing

  1. Peter J. Winzer
  2. Antonio Mecozzi
  3. René-Jean Essiambre
  4. Robert W. Tkach
  5. Rui Zhang
  6. Fabrizio Forghieri
  7. H. Vincent Poor
  8. Vittorio Curri

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