Tutorial 11: A Unified Design Framework for Non-Linear MIMO Transceivers Using Majorization Theory

Location: Room 101D, TICC

Presented by

Michael Botros Shenouda, Daniel P. Palomar, Timothy N. Davidson

Abstract

Non-linear MIMO transceivers have the potential for considerable gains over linear transceivers, while maintaining a comparable complexity. These gains are achieved by implementing interference (pre) subtraction at either the transmitter, such as Tomlinson-Harashima Precoding (THP) systems and Dirty Paper Coding (DPC), or at the receiver, such as Decision Feedback Equalization (DFE) systems. For the class of linear MIMO transceivers, a large number of joint design strategies have been studied, and a unified framework that encompasses these designs was proposed based on Majorization theory. However, for many of the design criteria for which (jointly) optimal linear transceivers are known, the optimal non-linear transceiver has remained an open problem. Furthermore, the development of a unifying design framework for non-linear transceivers that encompasses these designs has appeared to be a challenging problem.

In this tutorial, we present unified design framework for the two dual non-linear MIMO systems: MIMO transceivers with Tomlinson-Harashima Precoding or Dirty Paper Coding, and those with Decision Feedback Equalization. It uses concepts from Majorization theory and convex optimization theory to develop optimal closed-form designs for a broad range of unsolved design objectives. It also characterizes the scenarios under which the designed non-linear transceivers are (strictly) superior to their linear counterparts. Furthermore, the framework extends to communication schemes that employ non-linear transceivers with limited feedback using concepts from Majorization theory and Grassmann packings.

Speaker Biography

Michael Botros Shenouda received the B.Sc. (Hons. 1) degree and the M.Sc. degree in Electrical Engineering from Cairo University in 2001 and 2003, respectively. He received the Ph.D. degree from McMaster University, Canada in 2008. His main areas of interest include wireless and MIMO communication, robust and convex optimization, and signal processing algorithms. He is also interested in majorization theory and its application in the unification of designs for non-linear MIMO transceivers.

Mr. Botros Shenouda was awarded an IEEE Best Student Paper Award at ICASSP 2006, and was also a finalist in the IEEE Best Student Paper competition at ICASSP 2007. He was the recipient of two provincial scholarships during his PhD degree. Mr. Botros Shenouda has also received the National Science and Engineering Council of Canada (NSERC) Postdoctoral Fellowship.

Daniel P. Palomar (S'99-M’03) received the Electrical Engineering and Ph.D. degrees (both with honors) from the Technical University of Catalonia (UPC), Barcelona, Spain, in 1998 and 2003, respectively. Since 2006, he has been an Assistant Professor in the Department of Electronic and Computer Engineering at the Hong Kong University of Science and Technology (HKUST), Hong Kong. He has held several research appointments, namely, at King's College London (KCL), London, UK; Technical University of Catalonia (UPC), Barcelona; Stanford University, Stanford, CA; Telecommunications Technological Center of Catalonia (CTTC), Barcelona; Royal Institute of Technology (KTH), Stockholm, Sweden; University of Rome “La Sapienza”, Rome, Italy; and Princeton University, Princeton, NJ.

Dr. Palomar is an Associate Editor of IEEE Transactions on Signal Processing, a Guest Editor of the IEEE Journal on Selected Areas in Communications 2008 special issue on “Game Theory in Communication Systems,” and the Lead Guest Editor of the IEEE Journal on Selected Areas in Communications 2007 special issue on “Optimization of MIMO Transceivers for Realistic Communication Networks.” He is a member of the IEEE SPCOM Technical Committee, a general chair of CAMSAP 2009, and a member of the organizing committee of SPAWC 2009.

He received a 2004/06 Fulbright Research Fellowship; the 2004 Young Author Best Paper Award by the IEEE Signal Processing Society; the 2002/03 best Ph.D. prize in Information Technologies and Communications by the Technical University of Catalonia (UPC); the 2002/03 Rosina Ribalta first prize for the Best Doctoral Thesis in Information Technologies and Communications by the Epson Foundation; and the 2004 prize for the best Doctoral Thesis in Advanced Mobile Communications by the Vodafone Foundation and COIT.

Tim Davidson received the B.Eng. (Hons. I) degree in Electronic Engineering from the University of Western Australia (UWA), Perth, in 1991 and the D.Phil. degree in Engineering Science from the University of Oxford, U.K., in 1995.

He is currently an Associate Professor in the Department of Electrical and Computer Engineering at McMaster University, Hamilton, Ontario, Canada, where he holds the (Tier II) Canada Research Chair in Communication Systems, and is currently serving as Acting Director of the School of Computational Engineering and Science. He is also a Registered Professional Engineer in the Province of Ontario. Dr. Davidson’s research interests lie in the general areas of communications, signal processing and control. He has held research positions at the Communications Research Laboratory at McMaster University, the Adaptive Signal Processing Laboratory at UWA, and the Australian Telecommunications Research Institute at Curtin University of Technology, Perth, Western Australia.

Dr. Davidson was awarded the 1991 J. A. Wood Memorial Prize (for “the most outstanding [UWA] graduand” in the pure and applied sciences) and the 1991 Rhodes scholarship for Western Australia. He is currently serving as an Associate Editor of the IEEE Transactions on Signal Processing and as an Editor of the IEEE Transactions on Wireless Communications. He has also served as an Associate Editor of the IEEE Transactions on Circuits and Systems II, and as a Guest Co-editor of issues of the IEEE Journal on Selected Areas in Communications and the IEEE Journal on Selected Topics in Signal Processing.


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