4.6 Article

Blind Adaptive Low-Complexity Time-Domain Equalizer for 100-Gb/s Direct-Detection Optical OFDM Systems Over Long-Reach SSMF

Journal

IEEE SYSTEMS JOURNAL
Volume 15, Issue 3, Pages 3841-3847

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSYST.2020.2996384

Keywords

Cyclic prefix (CP); direct-detection optical orthogonal frequency-division multiplexing (DDO-OFDM); low-complexity multicarrier equalizer by restoration of orthogonality (LMERO); standard single-mode fiber (SSMF); time-domain equalizer (TEQ); wavelength-division multiplexing (WDM)

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This article presents a low-complexity adaptive equalizer TEQ for optical OFDM systems, which reduces system adaptation complexity significantly through the design of the MERO algorithm and deployment of symmetrical TEQ properties. The study demonstrates that up to 50% reduction in system adaptation complexity can be achieved through optimizing system parameters. The low-complexity MERO simulation model shows superior performance with a shorter CP length compared to existing conventional algorithms, while maintaining lower complexity levels.
In this article, we report a low-complexity blind adaptive time-domain equalizer (TEQ) to reduce the cyclic prefix (CP) length for 100-Gb/s direct-detection optical orthogonal frequency-division multiplexing (OFDM) system combined with wavelength-division multiplexing system over 400-km standard single-mode fiber length. We show that a significant complexity reduction can be achieved by designing a modified cost function of multicarrier equalization based on orthogonality restoration (MERO) algorithm on one hand, and on deploying the symmetrical TEQ property on the other hand. Our article shows that the reduction of the system adaptation complexity can be realized up to 50% when designing and optimizing the stated system parameters. Our low-complexity MERO simulation model exhibits better performance, for a shorter CP length equal to $0.39$ % of the OFDM symbol duration, than the existing conventional algorithms in term of bit error rate versus optical signal-to-noise ratio with a much lower complexity.

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