PAM-4 Eye-Opening Monitor Technique Using Gaussian Mixture Model for Adaptive Equalization

To meet the increasing demand for high-speed communication in VLSI (very large-scale integration) systems, next-generation data transmission standards (e.g., IEEE 802.3bs and PCIe 6.0) will adopt four-level pulse amplitude modulation (PAM-4) coding. Although PAM-4 is spectrally efficient to mitigate inter-symbol interference caused by bandwidth-limited wired channels, it more sensitive than conventional non-return-to-zero line evaluate received signal quality when using adaptive coefficient settings a equalizer during transmission, we propose an eye-opening monitor technique based on machine learning. The proposed uses Gaussian mixture model classify symbols. Simulation experimental results demonstrate feasibility of equalization