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There is a tremendous need to maximize signal capacity without sacrificingenergy consumption and complexity in optical fiber communications due to therise of network traffic demand and critical latency-aware services such astelemedicine and the Internet-of-Things. In this work, the firstsystem-agnostic and training-data-free fiber nonlinearity compensator (NLC)using affinity propagation (AP) clustering is experimentally demonstrated. Itis shown that compared to linear equalization, AP can increase the signalquality-factor up to about 5 dB in 16-quadrature-amplitude-modulated coherentoptical systems by effectively tackling deterministic and stochasticnonlinearities. AP outperforms benchmark clustering algorithms and complexdeterministic schemes such as K-means, fuzzy-logic, digital-back propagationand Volterra-based NLC, offering a power margin extension of up to 4 dB.

Fiber-induced nonlinearity compensation in coherent optical systems by affinity propagation soft-clustering