Modified square timing error detector with large chromatic dispersion tolerance for optical coherent receivers.

Clock recovery plays an important role in the digital signal processing (DSP) chain of modern coherent optical receivers. It references the local sampling clock with the signal baudrate and finds the optimal sampling instances by performing endless timing error corrections. At the core of clock recovery, a timing error detector (TED) is used to provide instantaneous error tracking. However, usual TEDs suffer from effects such as chromatic dispersion (CD) and polarization rotation, thus requiring additional efforts to remove those effects before TED. Here we propose a modified square TED based on the signal's cyclic autocorrelation function (CAF), which generalizes its classical counterpart and exhibits a much larger CD tolerance. It provides a time-domain solution of the CD-tolerant TED. The previously analyzed equivalence among the time-domain and the frequency-domain TEDs is reestablished in the framework of spectral correlation. The modified square TED demands a minimum extra complexity. Both numerical simulation and experiments are performed to study the performance of the proposed TED.

Chromatic dispersion equalization FIR filter design based on discrete least-squares approximation.

Chromatic dispersion (CD) equalization is one of the core tasks of the digital signal processing (DSP) chain in modern optical coherent receivers. A conventional impulse-invariant method for designing the CD equalization filter is revisited, improved by proper weighting, and reinterpreted as a Fourier series. To improve upon a direct evaluation of the passband least-squares (LS) approximation, we propose to design a CD equalization finite impulse response (FIR) filter based on a discrete LS approximation. The proposed method avoids numerical evaluation of nontrivial functions and relies only on Fourier transform. Its flexibility is corroborated by a filter design demonstration of joint matched filtering and CD equalization.

OSNR monitoring based on a low-bandwidth coherent receiver and LSTM classifier.

Optical signal-to-noise ratio (OSNR) monitoring is one of the core tasks of advanced optical performance monitoring (OPM) technology, which plays an essential role in future intelligent optical communication networks. In contrast to many regression-based methods, we convert the continuous OSNR monitoring into a classification problem by restricting the outputs of the neural network-based classifier to discrete OSNR intervals. We also use a low-bandwidth coherent receiver for obtaining the time domain samples and a long short-term memory (LSTM) neural network as the chromatic dispersion-resistant classifier. The proposed scheme is cost efficient and compatible with our previously proposed multi-purpose OPM platform. Both simulation and experimental verification show that the proposed OSNR monitoring technique achieves high classification accuracy and robustness with low computational complexity.