  The probability density function of Kerr effect phase noise, often called the
Gordon-Mollenauer effect, is derived analytically. The Kerr effect phase noise
can be accurately modeled as the summation of a Gaussian random variable and a
noncentral chi-square random variable with two degrees of freedom. Using the
received intensity to correct for the phase noise, the residual Kerr effect
phase noise can be modeled as the summation of a Gaussian random variable and
the difference of two noncentral chi-square random variables with two degrees
of freedom. The residual phase noise can be approximated by Gaussian
distribution better than the Kerr effect phase noise without correction.
