Reliable Communications over Rapidly Time-Varying Channels

Geert Leus,Ananthram Swami,Jean-Paul Linnartz,Xiaoli Ma,Cihan Tepedelenlioğlu,Georgios Giannakis

doi:10.1155/asp/2006/39672

Abstract

1 Faculty of Electrical Engineering, Mathematics, and Computer Science, Delft University of Technology, Mekelweg 4, 2628CD Delft, The Netherlands 2Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN 55455, USA 3Philips Research, 5656 AA Eindhoven, The Netherlands 4 School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA 5Army Research Lab., 2800 Powder Mill Road, Adelphi, MD 20783-1197, USA 6Department of Electrical Engineering, Arizona State University, Tempe, AZ 85287, USA

Highlights

Different models have recently been proposed to track time-varying channels, such as the basis expansion model (BEM) and the Gauss-Markov model (GMM)
Market studies predict a rapid growth of high data rate mobile applications such as TV broadcast and video streaming and multiperson wireless gaming
In the first two papers, the authors rely on the complex exponential BEM to develop training-based and semiblind channel estimators

Summary

Introduction

Different models have recently been proposed to track time-varying channels, such as the basis expansion model (BEM) and the Gauss-Markov model (GMM). In the first two papers, the authors rely on the complex exponential BEM to develop training-based and semiblind channel estimators. Both papers present training-based channel estimation algorithms exploiting frequency/time-multiplexed pilots.

Results

Conclusion