Digital inter-symbol interference mitigation method for Nyquist OTDM signal detection with coherent sampling and KNN classifier

We propose and experimentally demonstrate a digital method to mitigate inter-symbol interference (ISI) in demultiplexing Nyquist optical time-division multiplexing (N-OTDM) signal using a simple but powerfully serviceable k-nearest neighbors (KNN) classifier. The proposed method is evaluated under four types of sampling pulse-width corresponding to various extents of ISI distortion in 160 Gbaud down to 40 Gbaud demultiplexing experiments, and the mitigation performance is found to be better along with the increasement of sampling pulse-width. Compared with the traditional decision-directed least mean square (DD-LMS) equalization method, a 3.9 dB required-OSNR (at a BER of 10−4) improvement is observed under the pulse-width of 5.3 ps. Demultiplexing performance is investigated under the pulse-widths of 3.2 ps and 3.9 ps as well, in which the improvement of required-OSNR are found to be 1.33 dB and 2.95 dB, respectively. The performance improvement clearly indicates the strong ISI mitigation ability of the KNN classifier for N-OTDM signal demultiplexing. In addition, experimental results also confirm that the proposed digital ISI mitigation method could release the pulse-width requirement of the N-OTDM demultiplexing, which paves the way for future practical application of N-OTDM technique.