Capacity Limits of Fiber-Optic Communication Systems

75 Pages·2010·1.52 MB·English

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René-Jean Essiambre1, Gerard Foschini1, Peter Winzer1 and Gerhard Kramer2
1 Bell Labs, Alcatel-Lucent, Holmdel, NJ, USA
2 Bell Labs, Alcatel-Lucent, Murray Hill, NJ, USA
Email: [email protected]
Presentation at OFC in San Diego, California, USA
Optical Fiber Communication (OFC) Conference (OFC), March 2009
Acknowledgment
Jim Gordon
Andy Chraplyvy
Bob Tkach
Adel Saleh*
Maurizio Magarini
Bert Basch
Torsten Freckmann
Stéphane Colas
Herwig Kogelnik
Seb Savory
* Early part of this work was supported by DARPA under contract HR0011-06-C-0098
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Outline
1. Introduction
2. Information Theory
3. Constellations and Modulation
4. “The Fiber Channel”
5. Fiber Transmission
6. Fiber Nonlinearity Compensation
7. Capacity of the Fiber Channel
8. Predictions based on Capacity Limit Estimates
9. Summary and Outlook
10. Acronyms and References
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IInnttrroodduuccttiioonn
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Historical Evolution of Fiber-Optic Systems Capacity
Record Capacities
100
Optical Amplifier
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1986 1990 1994 1998 2002 2006 2010
Year
What is the ultimate capacity that a
single optical fiber can carry?
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What are We Trying to Determine?
Transmission of information over fiber-optic networks
Impairment Capacity
Additive Noise Information theory
Fiber Kerr nonlinearity How to determine a capacity?
Is there a fundamental limit to fiber capacity
imposed by the Kerr nonlinearity?
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What Technologies Are Considered?
• We are including an array of advanced technologies
(cid:57) Coding
(cid:57) Modulation
(cid:57) Constellations
(cid:57) Electronic signal processing
(cid:57) Optical amplification
• We will also estimate the impact on capacity of
(cid:57)Fiber loss
(cid:57)Fiber effective area
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IInnffoorrmmaattiioonn TThheeoorryy
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The Birth of Information Theory
One paper by C. E. Shannon in two separate issues
of the Bell System Technical Journal (1948)
Claude E. Shannon (1955)
Mathematical theory that calculates the asymptote of the
rates that information can be transmitted at an arbitrarily
low error rate through an additive noise channel
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Definition of the Channel
A “channel” can be defined as that part of a communication
system that we are unable or unwilling to change:
Example of a “channel”
Pulse
Information Source Channel Digital
shaper
source encoder encoder modulator
Waveform
channel
Output Source Channel Digital
Sampler
signal decoder decoder demodulator
• The “waveform channel” is the part of the channel where the
signal assumes a continuous (analog) form
• Shannon paid special attention to the additive white Gaussian
noise (AWGN) memoryless channel
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