Demodulation and Detection Schemes for a Memoryless Optical WDM Channel
Journal article, 2018

It is well known that matched filtering and sampling (MFS) demodulation together with minimum Euclidean distance (MD) detection constitute the optimal receiver for the additive white Gaussian noise channel. However, for a general nonlinear transmission medium, MFS does not provide sufficient statistics, and therefore is suboptimal. Nonetheless, this receiver is widely used in optical systems, where the Kerr nonlinearity is the dominant impairment at high powers. In this paper, we consider a suite of receivers for a two-user channel subject to a type of nonlinear interference that occurs in wavelength-division-multiplexed channels. The asymptotes of the symbol error rate (SER) of the considered receivers at high powers are derived or bounded analytically. Moreover, Monte-Carlo simulations are conducted to evaluate the SER for all the receivers. Our results show that receivers that are based on MFS cannot achieve arbitrary low SERs, whereas the SER goes to zero as the power grows for the optimal receiver. Furthermore, we devise a heuristic demodulator, which together with the MD detector yields a receiver that is simpler than the optimal one and can achieve arbitrary low SERs. The SER performance of the proposed receivers is also evaluated for some single-span fiber-optical channels via split-step Fourier simulations.

nonlinear channel

demodulation

Optical fiber

MAP detector.

nonlinearity compensation

Author

Kamran Keykhosravi

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks

Morteza Esmaeili Tavana

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks

Erik Agrell

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks

Giuseppe Durisi

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks

IEEE Transactions on Communications

0090-6778 (ISSN) 15580857 (eISSN)

Vol. 66 7 2994-3005

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Areas of Advance

Information and Communication Technology

Subject Categories

Telecommunications

Communication Systems

Probability Theory and Statistics

Infrastructure

C3SE (Chalmers Centre for Computational Science and Engineering)

DOI

10.1109/TCOMM.2018.2811811

More information

Latest update

6/30/2023