基于极端学习机线性化的 DSP 辅助中频光纤系统

IF 2.3 3区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Photonics Technology Letters Pub Date : 2024-12-04 DOI:10.1109/LPT.2024.3511135

Luis Carlos Vieira

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A DSP-Assisted IF-Over-Fiber System With Extreme Learning Machine-Based Linearization

This work proposes a densely allocated DSP-supported intermediate-frequency-over-fiber (IFoF) system with real-value single-hidden layer feedforward network (SLFN) post-equalization. The SLFN is trained using downsampled multichannel training signals (DMTSs) and the extreme learning machine (ELM) algorithm. The transmission of multichannel orthogonal frequency-division multiplexing (OFDM)-based IF signals over a 12.4-km direct-detection optical link is demonstrated, achieving adjacent channel leakage ratio (ACLR) improvements of up to 10 dB and significant reductions in error vector magnitude (EVM) due to the ELM-SLFN linearization scheme.

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来源期刊

IEEE Photonics Technology Letters 工程技术-工程：电子与电气

CiteScore

5.00

自引率

3.80%

发文量

404

审稿时长

2.0 months

期刊介绍： IEEE Photonics Technology Letters addresses all aspects of the IEEE Photonics Society Constitutional Field of Interest with emphasis on photonic/lightwave components and applications, laser physics and systems and laser/electro-optics technology. Examples of subject areas for the above areas of concentration are integrated optic and optoelectronic devices, high-power laser arrays (e.g. diode, CO2), free electron lasers, solid, state lasers, laser materials'' interactions and femtosecond laser techniques. The letters journal publishes engineering, applied physics and physics oriented papers. Emphasis is on rapid publication of timely manuscripts. A goal is to provide a focal point of quality engineering-oriented papers in the electro-optics field not found in other rapid-publication journals.