Single carrier frequency domain compressed training adaptive equalization

Abstract

Compressed training approach offers to improve the spectral efficiency by significantly reducing the required training length. It is based on a convex optimization setting (SCFDE-CoTA) which combines two cost functions: 1) Least squares based training reconstruction performance, and 2) Infinity norm of equalizer outputs, which exploits magnitude boundedness assumption of digital communication symbols. In this article, we provide an extension of this framework to single carrier frequency domain equalizer based transceivers, where we show that the compressed training algorithms can be effectively implemented for training frequency domain equalizers. We provide examples to demonstrate the potential gain of the algorithm in terms of training length reduction and performance improvement.