首页|Transfer-learning multi-input multi-output equalizer for mode-division multiplexing systems
Transfer-learning multi-input multi-output equalizer for mode-division multiplexing systems
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We propose a transfer-learning multi-input multi-output[TL-MIMO]scheme to significantly reduce the required training com-plexity for converging the equalizers in mode-division multiplexing[MDM]systems.Based on a built three-mode[LP01,LP11a,and LP11b]multiplexed experimental system,we thoughtfully investigate the TL-MIMO performances on the three-typed data,collecting from different sampling times,launching optical powers,and inputting optical signal-to-noise ratios[OSNRs].A dramatic reduction of approximately 40％-83.33％in the required training complexity is achieved in all three scenarios.Furthermore,the good stability of TL-MIMO in both the launched powers and OSNR test bands has also been proved.
Key Laboratory of Optical Fiber Sensing and Communication,Ministry of Education,University of Electronic Science and Technology of China,Chengdu 611731,China
Aston Institute of Photonics Technologies,Aston University,Birmingham B4 7ET,UK
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