Low-complexity and phase noise tolerant carrier phase estimation for dual-polarization 16-QAM systems

Yuliang Gao; Pak Tao Lau; Shuangyi Yan; Chao Lu

doi:10.1364/OE.19.021717

Low-complexity and phase noise tolerant carrier phase estimation for dual-polarization 16-QAM systems

Yuliang Gao, Pak Tao Lau, Shuangyi Yan, Chao Lu

The Hong Kong Polytechnic University

Research output: Journal article publication › Journal article › Academic research › peer-review

87 Citations (Scopus)

Abstract

A low-complexity feed-forward carrier phase estimation (CPE) technique is presented for dual-polarization (DP)-16-QAM transmission systems. By combining QPSK partitioning, maximum likelihood (ML) detection and phase offset estimation between signals in different polarizations, simulation and experimental results for a 200Gb/s DP-16-QAM system demonstrate similar linewidth tolerance to the best feedforward CPE reported to date while the computational complexity is at least three times lower compared with other simplified feed-forward CPE techniques.

Original language	English
Pages (from-to)	21717-21729
Number of pages	13
Journal	Optics Express
Volume	19
Issue number	22
DOIs	https://doi.org/10.1364/OE.19.021717
Publication status	Published - 24 Oct 2011

ASJC Scopus subject areas

Atomic and Molecular Physics, and Optics

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10.1364/OE.19.021717

http://hdl.handle.net/10397/6536

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AB - A low-complexity feed-forward carrier phase estimation (CPE) technique is presented for dual-polarization (DP)-16-QAM transmission systems. By combining QPSK partitioning, maximum likelihood (ML) detection and phase offset estimation between signals in different polarizations, simulation and experimental results for a 200Gb/s DP-16-QAM system demonstrate similar linewidth tolerance to the best feedforward CPE reported to date while the computational complexity is at least three times lower compared with other simplified feed-forward CPE techniques.

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Low-complexity and phase noise tolerant carrier phase estimation for dual-polarization 16-QAM systems

Abstract

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