S. Mumtaz and Govind P. Agrawal, Institute of Optics, University of Rochester

R. J. Essiambre, Alcatel-Lucent Bell Labs

Spatially Multiplexed Transmission in Multicore Fibers:

Role of Core Coupling on System Performance

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Optical fiber communication systems

Data traffic has been growing exponentially every year.

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[Essiambre and Tkach: Capacity Trends and Limits of Optical Communication Networks, IEEE proceedings, May 2012]

North American Internet traffic. Single channel systems (circles) WDM systems (squares).

System capacity must follow this growth to avoid a capacity crunch

Capacity increase through multiplexing

WDM: wavelength-division multiplexing

PDM: Polarization-division multiplexing

I/Q modulation (QPSK, 16-QAM)

?? SDM: Space-division multiplexing

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[Essiambre and Tkach: Capacity Trends and Limits of Optical Communication Networks, IEEE proceedings, May 2012]

Single channel systems (circles) WDM systems (squares).

Space Division multiplexing

Multicore fiber

…LP01 LP11a LP11b LP02 LP21a LP21b

Multimode fiber

QPSK

QPSK

•Tx

•Tx

•DSP

Space division multiplexing

Performance of an SDM system limited by nonlinearities

Important to understand the nonlinear propagation

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SDM increases capacity with reduced energy consumption

Digital signal processing

Nonlinear propagation in multicore fiber

Both linear and nonlinear couplings occur among the fields propagating in different fiber cores.

Electric field

Propagation equation

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Linear core coupling

y

x

y

x

Coupling is a function of the distance among fiber cores.

Coupling length

Linear coupling coefficient

Core a Core b

Distance between cores

r

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Nonlinear core coupling

Nonlinear coupling coefficients

: intra-core nonlinear effects (SPM)

: inter-core XPM effects

Inter-core nonlinear effects decrease exponentially with increasing distance between cores.

XPM nonlinear effects are several orders of magnitude smaller than intra-core SPM effects.

They can be neglected in most cases.

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SPM: self-phase modulationXPM: cross-phase modulation

Nonlinear propagation equation for multicore fibers

We used this set of equations for numerical modeling.

We considered multicore fibers with up to 19 cores.

Two orthogonally polarized 112-Gb/s channel launched into each core using PDM.

Linear core coupling included through qmp parameters.

All intra-core nonlinear effects included through .

Birefringence and dispersion effects fully included.

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Numerical simulations and Results

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Simulation details

Two 28 Gbaud PDM-QPSK symbol streams launched into each core.

Propagation through fiber by the split-step Fourier method.

Least square equalizer (LSE): non-adaptive, based on training sequence.

Actual bit error rate (BER) calculated using 20,000 bits during simulation.

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100km MCF

…

1000km

QPSK

QPSK RC filter

RC filter

MUX DEMUX

EDFA

•LSE

EqualizerDemod.

…0110101

BER0111010

Performance as a function of coupling length

Lc = 100m Lc = 1kmLc = 1m Lc = 10km

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OSNR penalties Vs Injected power

1000km Trans. Lc=100m

Comparison between 1-core and 3-core fibers

Linear coupling reduces the impact of SPM effects better performance

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Performance in function of the core number

1-Core 2-Core 3-Core 5-Core 6-Core4-Core 7-Core

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Nonlinear noise

NL noise after 100 km for and input power of 12 dBm

1-core 3-core

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Conclusions

SDM may be an important new technology in near future.SDM will make use of nulticore or multimode fibers.

We have derived a nonlinear propagation equation for multicore fibers.

We used it to study the impact of linear coupling on the performance PDM-QPSK systems.

Most experiments keep cores far apart to reduce linear coupling.

Our results show that strong coupling actually helps to improve system performance if DSP is used at the receiver.

More cores can be packed together when core spacing is reduced.

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Questions ?

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