Robust Faster-than-Nyquist PDM-mQAM Systems with Tomlinson-Harashima Precoding
Deyuan Chang, Oluyemi Omomukuyo, Xiang Lin, Shu Zhang, Octavia A., Dobre, and Ramachandran Venkatesan
TL;DR
This paper introduces a robust training-based channel estimation algorithm for faster-than-Nyquist PDM-mQAM systems with Tomlinson-Harashima precoding, improving OSNR requirements under dispersion and phase noise.
Contribution
It presents a new channel estimation algorithm that is robust to convergence issues and remains format-transparent in faster-than-Nyquist PDM-mQAM systems with THP.
Findings
Reduces OSNR needed for target BER under dispersion and phase noise
Robust to convergence failures of previous algorithms
Applicable to 4, 16, 64-QAM systems
Abstract
A training-based channel estimation algorithm is proposed for the faster-than-Nyquist PDM-mQAM (m = 4, 16, 64) systems with Tomlinson-Harashima precoding (THP). This is robust to the convergence failure phenomenon suffered by the existing algorithm, yet remaining format-transparent. Simulation results show that the proposed algorithm requires a reduced optical signal-to-noise ratio (OSNR) to achieve a certain bit error rate (BER) in the presence of first-order polarization mode dispersion and phase noise introduced by the laser linewidth.
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