Accurate calculation of eye diagrams and bit error rates in opticaltransmission systems using linearization
Holzlohner, R.
Grigoryan, V.S.
Menyuk, C.R.
Kath, W.L.
Dept. of Comput. Sci. & Electr. Eng., Maryland Univ., Baltimore, MD;
This paper appears in: Lightwave Technology, Journal of
Publication Date: Mar 2002
Volume: 20,
Issue: 3
On page(s): 389-400
ISSN: 0733-8724
References Cited: 38
CODEN: JLTEDG
INSPEC Accession Number: 7206958
Digital Object Identifier: 10.1109/50.988987
Current Version Published: 2002-08-07
Abstract
We present a novel linearization method to calculate accurate eye
diagrams and bit error rates (BERs) for arbitrary optical transmission
systems and apply it to a dispersion-managed soliton (DMS) system. In
this approach, we calculate the full nonlinear evolution using Monte
Carlo methods. However, we analyze the data at the receiver assuming
that the nonlinear interaction of the noise with itself in an
appropriate basis set is negligible during transmission. Noise-noise
beating due to the quadratic nonlinearity in the receiver is kept. We
apply this approach to a highly nonlinear DMS system, which is a
stringent test of our approach. In this case, we cannot simply use a
Fourier basis to linearize, but we must first separate the phase and
timing jitters. Once that is done, the remaining Fourier amplitudes of
the noise obey a multivariate Gaussian distribution, the timing jitter
is Gaussian distributed, and the phase jitter obeys a Jacobi-Θ
distribution, which is the periodic analogue of a Gaussian distribution.
We have carefully validated the linearization assumption through
extensive Monte Carlo simulations. Once the effect of timing jitter is
restored at the receiver, we calculate complete eye diagrams and the
probability density functions for the marks and spaces. This new method
is far more accurate than the currently accepted approach of simply
fitting Gaussian curves to the distributions of the marks and spaces. In
addition, we present a deterministic solution alternative to the Monte
Carlo method
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