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Structured Sparsity Learning-Based Pruned Retraining Volterra Equalization for Data-Center Interconnects (W6A.23)

Presenter: govind sharan yadav, National Tsing Hua University Taiwan

We propose a structured sparsity learning-based pruned retraining Volterra equalization for inter-dadta-center interconnects. Compared with conventional VE, we achieve 95% and 90.5% complexity reduction without signal degradation for B2B and 40-km at 80-Gb/s PAM4, respectively.

Authors:govind sharan yadav, National Tsing Hua University Taiwan / Chun-Yen Chuang, National Chiao Tung University / Kai-Ming Feng, National Tsing Hua University Taiwan / Jyehong Chen, National Chiao Tung University / Young-Kai Chen, DARPA


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