Channel Estimation and Equalization for Spread-Response Precoding Systems in Fading Environments by J .

In the wireless communications setting, channel coding schemes must combat not only additive noise, but also distortions such as intersymbol interference and signal fading caused by multipath propagation. Spread-response precoding is a newly proposed method for communicating over such channels, which is attractive because it offers good performance while having efficient implementations and requiring no additional average power or bandwidth. Furthermore, these systems essentially transform the intersymbol interference into a more benign form of uncorrelated, additive noise at the receiver. In this thesis, we examine several theoretical and practical issues relating to fading channel estimation and equalization for use in these spread-response precoding systems. We first compare linear fading channel equalizers designed according to two seemingly different criteria of optimality, namely, the maximum signal-to-noise ratio (SNR) criterion and the minimum mean-square error (MMSE) criterion. Initially, we assume the fading channel impulse response is known at the receiver, and we show that, while the maximum SNR equalizer corresponds exactly to the MMSE equalizer for the case of a frequency nonselective channel, for the case of a slowly-varying, frequency selective channel this result holds only approximately. We examine the more general frequency selective case in some detail by comparing the frequency responses of the two equalizers and the bit-error probability of systems employing them. We then consider the case in which the fading channel coefficients are unknown at the receiver, but some form of direct channel measurement is obtained through the use of a pilot-tone. From these observations, we develop techniques based on the Kalman filter and the Expectation-Maximization algorithm for estimating and tracking the fading channel parameters. We examine how these estimates alter the form of the optimal equalizers, and assess their impact on the performance of spread-response precoding systems through analysis and simulation. Finally, we give some preliminary results from an implementation of these ideas within an indoor wireless testbed. We demonstrate the use of our channel estimation algorithms in characterizing the wireless channel found in the laboratory, and we compare transmissions over this channel with and without spread-response precoding. Thesis Supervisor: Gregory W. Wornell Title: Associate Professor of Electrical Engineering Acknowledgments I wish to express my sincere appreciation to my advisor, Prof. Gregory Wornell, for his guidance, encouragement, and support throughout my graduate studies in general and this thesis research in particular. For creating a productive environment in which to work, and nurturing me as a beginning researcher, I am truly grateful to him, and I look forward to continuing my studies under his supervision. I am also very indebted to two senior members of the Digital Signal Processing Group, Haralabos Papadopoulos and Dr. Steven Isabelle, for their assistance in developing some of the ideas in this thesis and their many thought provoking discussions about related research topics. Thanks go also to Alan Seefeldt, Richard Barron, and Matthew Secor of the Digital Signal Processing Group for sharing their random ideas, research-related or otherwise; to Walter Sun, Andrew Kim, and Dewey Tucker for our late-night study sessions and periodic lunch breaks; and finally to Jeffrey Karam, Brian Hearing, Santanu Das, and David Cuneo for joining me in stress-relieving athletic pursuits and other escapes from work. Lastly, I wish to offer a very special word of tribute to my family, Mom, Dad, Jenny, and Jill, for their continuous love and caring. Mom and Dad, you are my oldest teachers, always sharing your wisdom and supporting my endeavors unconditionally. Your sacrifices through the years have given me every opportunity to succeed, and as but a small token of my gratitude, I dedicate this work to you.