We discuss several di erent methods of improv- ing estimates of space-time channels, such as temporal parametrization, spatial parametrization, reduced rank channel estimation, bootstrap
Trang 1Signals and Systems
SPACE-TIME PROCESSING AND EQUALIZATION FOR WIRELESS
COMMUNICATIONS
Erik LindskogDissertation in Signal Processing to be publicly examined in room K23, Magistern, Dag Hammarskjolds vag 31, Uppsala, on June 7, 1999, at 10.15 a.m., for the degree of Doctor of Philosophy The discussion will be held in Swedish.
ABSTRACT Erik Lindskog, 1999 Space-time processing and equalization for wireless commu- nications Uppsala, 318pp ISBN 91-506-1350-2.
In this thesis several aspects of space-time processing and equalization for less communications are treated We discuss several di erent methods of improv- ing estimates of space-time channels, such as temporal parametrization, spatial parametrization, reduced rank channel estimation, bootstrap channel estimation, and joint estimation of an FIR channel and an AR noise model In wireless commu- nication the signal is often subject to intersymbol interference as well as interfer- ence from other users We here discuss space-time decision feedback equalizers and space-time maximum likelihood sequence estimators, which can alleviate the impact
wire-of these factors In case the wireless channel does not experience a large amount
of coupled delay and angle spread, sucient performance may be obtained by an equalizer with a less complex structure We therefore discuss various reduced com- plexity equalizers and symbol sequence estimators We also discuss re-estimating the channel and/or re-tuning the equalizer with a bootstrap method using esti- mated symbols With this method we can improve the performance of the channel estimation, the equalization, and the interferer suppression This method can also
be used to suppress asynchronous interferers When equalizers and symbol tion algorithms are designed based on estimated channels we need to consider how errors in the estimated channels, or errors due to time variations, a ect the perfor- mance of the equalizer or symbol detector We show that equalizers tuned based on ordinary least squares estimated channels exhibit a degree of self-robusti cation, which automatically compensates for potential errors in the channel estimates Key-words: Space-time processing, channel estimation, equalization, maximum likelihood sequence estimation, decision feedback equalization, interference sup- pression, robustness.
detec-Erik Lindskog, Signals and Systems, Uppsala University, PO Box 528, SE-751 20 Uppsala, Sweden.
Trang 2SPACE-TIME PROCESSING AND
Erik Lindskog
UPPSALA UNIVERSITY 1999
Trang 3in Signal Processing at Uppsala University, 1999
wire-of these factors In case the wireless channel does not experience a large amount
of coupled delay and angle spread, sucient performance may be obtained by an equalizer with a less complex structure We therefore discuss various reduced com- plexity equalizers and symbol sequence estimators We also discuss re-estimating the channel and/or re-tuning the equalizer with a bootstrap method using esti- mated symbols With this method we can improve the performance of the channel estimation, the equalization, and the interferer suppression This method can also
be used to suppress asynchronous interferers When equalizers and symbol tion algorithms are designed based on estimated channels we need to consider how errors in the estimated channels, or errors due to time variations, a ect the perfor- mance of the equalizer or symbol detector We show that equalizers tuned based on ordinary least squares estimated channels exhibit a degree of self-robusti cation, which automatically compensates for potential errors in the channel estimates Key-words: Space-time processing, channel estimation, equalization, maximum likelihood sequence estimation, decision feedback equalization, interference sup- pression, robustness.
detec-Erik Lindskog, Signals and Systems, Uppsala University, PO Box 528, SE-751 20 Uppsala, Sweden.
c Erik Lindskog 1999
ISBN 91-506-1350-2
Printed in Sweden by Elanders Graphic Systems AB, Angered 1999
Distributed by Signals and Systems, Uppsala University, Uppsala, Sweden
Trang 6This thesis consists of seven chapters The rst chapter is an overview ofspace-space time processing for wireless communications and serves as anintroduction to the subject The remaining chapters treat various aspects
of channel estimation, equalization and interferer suppression
Parts of the material in the respective chapters has been published in thefollowing papers:
Chapter 1:
Arogyaswami Paulraj and Erik Lindskog,
\A Taxonomy of space-time processing for wireless networks", IEE ings, Radar, Sonar and Navigation, vol 145, no 1, February 1998
Proceed-Chapter 2:
Erik Lindskog,
\Array Channel Identi cation Using Directional of Arrival tion" Proceedings of IEEE International Conference on Universal PersonalCommunications, Cambridge, Massachusetts, U.S.A., Sept 29 - Oct 2 1996,vol 2, pp 999-1003
Parametriza-Erik Lindskog,
\Channel Estimation Exploiting Pulse Shaping Information - A Channel terpolation Approach", UPTEC Report 97138R, Uppsala University, Signalsand Systems, 1997, PO Box 528, SE-751 20 Uppsala, Sweden
In-Erik Lindskog and Jonas Strandell,
\Multi-user Channel Estimation Exploiting Pulse Shaping Information".Proceedings of European Signal Processing Conference, Rhodos, Greece,Sept 8-11 1998
Trang 7Erik Lindskog and Claes Tidestav,
"Reduced rank channel estimation", IEEE Vehicular Technology ence, Houston, Texas, USA, May 16-20 1999
Confer-The methods in Section 2.3 and 2.5 has also been combined and publishedin:
Jonas Strandell and Erik Lindskog,
\Channel estimation by maximum likelihood projection onto a parametrizedsubspace" Proceedings of European Signal Processing Conference, Rhodos,Greece, Sept 8-11 1998,
Chapter 3:
Erik Lindskog, Anders Ahlen and Mikael Sternad,
\Combined Spatial and Temporal Equalization using an Adaptive AntennaArray and a Decision Feedback Equalization Scheme", Proceedings of Int.Conf on Acoustics, Speech and Signal Processing, Detroit, Michigan, U.S.A.,May 8-12 1995, vol 2, pp 1189-1192
Erik Lindskog, Anders Ahlen and Mikael Sternad,
\Spatio-Temporal Equalization for Multipath Environments in Mobile RadioApplications" Proceedings of 45h IEEE Vehicular Technology Conference,Rosemont, Illinois, USA, vol 1, July 26-29 1995, pp 399-403
Chapter 4:
Erik Lindskog,
\Multi-channel maximum likelihood sequence estimation" Proceedings ofthe 47th IEEE Vehicular Technology Conference, Phoenix, Arizona, USA,May 5-7 1997, vol 2, pp 715-719
Chapter 5:
Erik Lindskog,
\Making SMI-beamforming insensitive to the sampling timing for GSM nals", Proceedings of the Sixth International Symposium on Personal, In-door and Mobile Radio Communications, Toronto, Canada, September 27-29
sig-1995, vol 2, pp 664-668
Trang 8Erik Lindskog and Claes Tidestav,
\Reduced rank equalization", In Proceedings of IEEE International sium on Personal, Indoor and Mobile Radio Communication, Boston, Mas-sachusetts, USA, September 8-11 1998, Vol 3, pp 1081-1085
Sympo-Chapter 6:
Erik Lindskog,
\Combatting Co-Channel Interference in a TDMA System Using ence Estimates From Adjacent Frames" Proceedings of 29th Asilomar Con-ference on Signals, Systems & Computers, Paci c Grove, California, U.S.A.,Oct 30 - Nov 1 1995, vol 1, pp 367-371
Interfer-Claes Tidestav and Erik Lindskog,
\Bootstrap Equalization", Proceedings of IEEE International Conference onUniversal Personal Communications, Florence, Italy, October 5-9 1998
Chapter 7:
Mikael Sternad and Anders Ahlen and Erik Lindskog,
\Robust Decision Feedback Equalizers", Proceedings of Int Conf onAcoustics, Speech and Signal Processing, Minneapolis, Minnesota, U.S.A.,April 1993, vol 3, pp 555-558
Erik Lindskog, Mikael Sternad and Anders Ahlen,
\Designing Decision Feedback Equalizers to be Robust with respect to nel Time Variations", Proceedings of Nordic Radio Symposium seminar,Uppsala, Sweden, November 10-11 1993
Trang 10First, I wish to express my gratitude to my supervisors Professor AndersAhlen and Dr Mikael Sternad for their valuable guidance and supportduring my time as a graduate student It has been very stimulating andrewarding to work in their group Anders always has a positive outlook onthings, and Mikael will always nd interest in every problem you approachhim with I also want to give my thanks to them for their careful reading ofvarious manuscripts, including this thesis
I would also like to thank my other co-authors on various papers, ProfessorArogyaswami Paulraj, Claes Tidestav, Jonas Strandell, Mattias Wennstrom,
Dr Tommy Oberg Dr Anders Rydberg and Yulianto Naserudin for esting and rewarding co-operation Furthermore, I would like to thank MatsCedervall and Boon Ng for sharing some of their insights into the problem
inter-of temporal parametrization inter-of a channel
I am also grateful to Dr Soren Andersson, Dr Ulf Forssen, and Henrik Damm
at Ericsson Radio Systems for the experimental data that has been used insome of the evaluations in this thesis
My thanks also to the Swedish Research Council for Engineering Sciences(TFR), who has been the major nancial supporter of this work under con-tracts 281-95-800 and 281-98-654
During my time as a graduate student I have belonged to two di erentdepartments, System and Control in \House 8" and Signals and Systems
in \Magistern" It has been joyful and rewarding to meet and work withthe members of both departments and I would like express my warmestgratitude to all of them I would also like to thank our shared systemadministrator, Ove Ewerlid, for valuable help with computer problems andfor all the interesting discussions we have had at our favorite \hang-out"
A special mentioning also of my rst oce mate Kenth Ohrn for the goodcompany and to Fredrik Lingvall for introducing me to climbing in Uppsala
Trang 11I would also like to thank Professor John Proakis for the opportunity to visithim and his department at Northeastern University in Boston, USA I had
a great year at Northeastern University I especially appreciated the groupmeetings where many interesting presentations were held
I made many friends in Boston and I would like to thank them all for theirfriendship Among these I would especially like to thank: Bj rn Bjerke,
my Norwegian oce mate who I shared a lot of time with I now have amuch greater understanding of the Norwegian language Jose Fridman forhis humorous comments and his valuable advice Arda Aksu for his joy-ful and friendly attitude Erozan Kurtas for several interesting discussions
My room mates from Sigourney st, Timoor Sahkaruk, Zoran Mihajlovic andVladic Davidkovich for their companionship Zoran Coric, Sasha Djakovic,Alex Pantelic and Thomas and Tanya Thiemann, for the good times theyshowed me Hakan and Beth Thyr for showing me some of the \great out-doors" of America: Hakan introducing me to climbing and Beth for sailingwith me on the Charles River
I am also very grateful to Professor Arogyaswami Paulraj for the opportunity
to visit him and his excellent research group at Stanford University, USA
I had a very stimulating and rewarding visit I especially valued the openminded scienti c discussions at the weekly group meetings My thanks also
to all the members in the group
In California I had the privilege to become closer acquainted with my friend
to thank him for housing me when I arrived to California and for the greatcompanionship he o ered, then and later I also would like to thank myspecial friends, Maja Popovic and Kanna Rajan, for all the things we didtogether during my stay in California Further, my thanks to Roger Ger-mundsson for a great Christmas and New Years Eve celebration and forinteresting discussions about the construction, operation and repairs of aCorvette sports car
My greatest thanks to my parents, Inger and Jan, as well as the rest of myfamily including my aunt Anita, for all their help and support I also wouldlike to thank my brother Olof for the joy of sharing a boat together and forthe adventure of sailing the same boat across the sea to Gotland
Finally I would like to thank Maider for her patience and love
Trang 121 Space-Time Processing in Wireless Communication 1
1.1 Introduction 1
1.2 Outline of Space-Time Processing Schemes 3
1.3 Architecture Based Classi ... Optimal Space-Time DFE for ARMA Channels with ARMA Noise 111
3.2.2 Optimal Space-Time DFE for FIR Channels with AR Noise 115
3.2.3 Optimal Fixed Order Space-Time FIR-DFE for a... links is the diculty in determining thetransmit channel needed for transmit space-time processing
Space-time processing performance in receive and transmit can be very ferent due to the... Classi cation
Algorithms for space-time processing can be divided into those used forchannel estimation and those used for receive and transmit processing, seeFigure 1.6 We will discuss