K-means-based channel equalization method for polarization-division-multiplexed optical OFDM/OQAM systems
Proceedings of the International Conference on Artificial Intelligence, Information Processing and Cloud Computing(2019)
Abstract
In this work, we systemically analysis a k-means-clustering-based method to implement channel equalization for PDM fiber OFDM/OQAM system. We have experimentally demonstrated that the proposed k-means-based fiber nonlinearity mitigation technique is able to reduce computational complexity and improve the BER performance. Compared with the classical k-means clustering algorithm, the proposed method can quickly find appropriate initial centroids and correctly choose the centroids of the clusters to obtain the global optimal solutions.
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Key words
coherent communication, machine learning, optical communication, orthogonal frequency-division multiplexing/offset quadrature amplitude modulation (OFDM/OQAM)
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