Structured Sparsity Learning-based pruned retraining Volterra Equalization for Data-Center Interconnects

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.