Reducing computation complexity by using elastic net regularization based pruned Volterra equalization in a 80 Gbps PAM-4 signal for inter-data center interconnects
| Autor: | Chun-Yen Chuang, Kai-Ming Feng, Jhih-Heng Yan, Young Kai Chen, Jyehong Chen, Govind Sharan Yadav |
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| Rok vydání: | 2020 |
| Předmět: |
Elastic net regularization
Signal processing business.industry Computer science Orthogonal frequency-division multiplexing Image quality Equalization (audio) Equalizer Image processing 02 engineering and technology 021001 nanoscience & nanotechnology 01 natural sciences Signal Atomic and Molecular Physics and Optics 010309 optics Optics Transmission (telecommunications) 0103 physical sciences 0210 nano-technology business Algorithm Phase modulation |
| Zdroj: | Optics express. 28(26) |
| ISSN: | 1094-4087 |
| Popis: | Volterra equalization (VE) presents substantial performance enhancement for high-speed optical signals but suffers from high computation complexity which limits its physical implementations. To address these limitations, we propose and experimentally demonstrate an elastic net regularization-based pruned Volterra equalization (ENPVE) to reduce the computation complexity while still maintain system performance. Our proposed scheme prunes redundant weight coefficients with a three-phase configuration. Firstly, we pre-train the VE with an adaptive EN-regularizer to identify significant weights. Next, we prune the insignificant weights away. Finally, we retrain the equalizer by fine-tuning the remaining weight coefficients. Our proposed ENPVE achieves superior performance with reduced computation complexity. Compared with conventional VE and L1 regularization-based Volterra equalizer (L1VE), our approach show a complexity reduction of 97.4% and 20.2%, respectively, for an O-band 80-Gbps PAM4 signal at a received optical power of −4 dBm after 40 km SMF transmission. |
| Databáze: | OpenAIRE |
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