Robust peak distortion equalization

TL;DR: A robust peak distortion (RPD) equalizer is proposed, in which it is shown that the RPD equalizer can be found efficiently using standard convex optimization packages, and outperforms traditional equalizers, and previously proposed robust equalizers.

Abstract: We consider the problem of designing a robust linear equalizer under channel uncertainties. Specifically, we propose a robust peak distortion (RPD) equalizer, in which we minimize the error probability of the worst-case sequence and the worst-case channel, in the uncertainty region. We show that the RPD equalizer can be found efficiently using standard convex optimization packages. We then demonstrate through simulations that under channel uncertainty the RPD equalizer outperforms traditional equalizers, and previously proposed robust equalizers.