Monday 23 June 2014, 9:00-10:00am
Massive MIMO: Simplicity, Scalability, Speed, Uniform Service
Thomas L. Marzetta
Communications and Signal Processing Research Group
Bell Laboratories, Alcatel-Lucent
Murray Hill, NJ, USA
Abstract: Massive MIMO is similar in spirit to Computer Tomography, 3D Seismic Exploration, and Synthetic Aperture Radar, which arguably represent the greatest achievements of signal processing. What these have in common is the collection of massive amounts of data, and signal processing that is geared closely to underlying physics. Sparse data would, paradoxically, make the signal processing vastly more difficult and the final results vastly inferior.
Massive MIMO makes a clean break with current wireless practice: it upsets the traditional parity between service antennas and user antennas, it utilizes TDD reciprocal training, and it serves every active terminal in all of the time/frequency resources with aggressive spatial multiplexing and frequency independent power control. The most elementary multiplexing signal processing can yield order-of-magnitude spectral efficiency gains over LTE, power control ensures that users at the edges of the cell experience the same high throughput that users near the base station enjoy, any number of service antennas can be employed to advantage with no tightening of array tolerances, and radiated power is reduced in proportion to the number of antennas.
Thomas L. Marzetta was born in Washington, D.C. He received the PhD in electrical engineering from the Massachusetts Institute of Technology. His dissertation extended, to two dimensions, the three-way equivalence of autocorrelation sequences, minimum-phase prediction error filters, and reflection coefficient sequences. He worked for Schlumberger-Doll Research (1978 - 1987) to modernize geophysical signal processing for petroleum exploration. He headed a group at Nichols Research Corporation (1987 - 1995) which improved automatic target recognition, radar signal processing, and video motion detection. He joined Bell Laboratories in 1995 (formerly part of AT&T, then Lucent Technologies, now Alcatel-Lucent). Within the former Mathematical Sciences Research Center he was director of the Communications and Statistical Sciences Department. He is the originator of Massive MIMO which can provide huge improvements in wireless spectral-efficiency and energy-efficiency over 4G technologies.
Dr. Marzetta was the recipient of the 1981 ASSP Paper Award from the IEEE Signal Processing Society. He was elected a Fellow of the IEEE in 2003. He received the 2013 IEEE Guglielmo Marconi Best Paper Award, and he shared the Best Paper Award from the 2013 IEEE Online Green Communications Conference.
Monday 23 June 2014, 2:00-3:00pm
Signal Processing at the Millimeter Wave Frontier
Department of Electrical and Computer Engineering
University of California, Santa Barbara
Abstract: Millimeter (mm) wave communication represents the next wave of innovation in wireless, with essentially unlimited spectral availability as low-cost radio frequency integrated circuits (RFICs) become available at higher and higher carrier frequencies, starting with the 60 GHz unlicensed band. After a brief glimpse of the immense potential of these bands, we discuss some of the signal processing challenges associated with tapping this potential, focusing on the fundamentally different nature of MIMO geometry and signal processing at tiny wavelengths, which are an order of magnitude smaller than those in current cellular and WiFi systems. Much of this talk is devoted to the problem of adapting the electrically large yet physically compact antenna arrays possible at tiny wavelengths (a 1000 element array is palm-sized at 60 GHz, and the size of a postage stamp at 200 GHz). Standard least squares techniques do not apply, since we do not have access to individual elements. We discuss a compressive approach to such adaptation, and the new theory and algorithms that it stimulated on compressive estimation of continuous-valued parameters. If time permits, we will also briefly discuss the drastically different nature of spatial multiplexing at tiny wavelengths, and the challenge of “mostly digital” signal processing at very large bandwidths.
Upamanyu Madhow is Professor of Electrical and Computer Engineering at the University of California, Santa Barbara. His research interests broadly span communications, signal processing and networking, with current emphasis on millimeter wave communication, and on distributed and bio-inspired approaches to networking and inference. He received his bachelor's degree in electrical engineering from the Indian Institute of Technology, Kanpur, in 1985, and his Ph. D. in electrical engineering from the University of Illinois, Urbana-Champaign in 1990. He has worked as a research scientist at Bell Communications Research, Morristown, NJ, and as a faculty at the University of Illinois, Urbana-Champaign. Dr. Madhow is an IEEE Fellow, a recipient of the 1996 NSF CAREER award, and co-recipient of the 2012 IEEE Marconi prize paper award in wireless communications. He has served as Associate Editor for the IEEE Transactions on Communications, the IEEE Transactions on Information Theory, and the IEEE Transactions on Information Forensics and Security. He is the author of the textbook Fundamentals of Digital Communication, published by Cambridge University Press in 2008, and the forthcoming textbook, Introduction to Communication Systems, to be published by Cambridge University Press in 2014.
Tuesday 24 June 2014, 9:00-10:00am
Dense WiFi: The Next Frontier in WLAN Technology
Senior Principal Design Engineer
Sunnyvale, CA, USA
Abstract: WiFi is an immensely successful technology, with one billion WiFi-equipped devices sold annually and estimates that over half of smartphone traffic is carried on WiFi rather than cellular networks. However, as the popularity of WiFi has increased, so too has the occurrence of dense WiFi deployments, e.g., in large apartment buildings or in WiFi-covered stadiums. Providing good performance in such scenarios is challenging, particularly due to the decentralized and unplanned nature of WiFi. In this talk we will describe key technical obstacles faced in dense WiFi scenarios and will outline some potential solutions, such as methods for increased spatial reuse. We will also describe the recently formed IEEE 802.11ax task group, which is tasked with significantly improving dense WiFi performance.
Nihar Jindal received the B.S. degree in electrical engineering and computer science from the University of California at Berkeley in 1999 and the M.S. and Ph.D. degrees in electrical engineering from Stanford University, Stanford, CA, in 2001 and 2004, respectively. He is currently a Senior Principal Engineer at Broadcom Corporation, where he works on WLAN system design and 802.11 standardization. He was a recognized contributor to the 802.11ac and 802.11ah standards, and is currently an active participant in the 802.11ax task group. From 2004-2010 he served as an Associate (2010) and Assistant (2004-09) Professor in the Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis.
Dr. Jindal was the recipient of the IEEE Communications Society and Information Theory Society Joint Paper Award in 2005 and 2011, the University of Minnesota McKnight Land Grant Professorship Award in 2007, the NSF CAREER award in 2008, and the best paper award for the IEEE Journal on Selected Areas in Communications in 2009.
Wednesday 25 June 2014, 9:00-10:00am
Fiber-optic Communication in the Nonlinear Frequency Domain
Frank R. Kschischang
Department of Electrical and Computer Engineering
University of Toronto
Abstract: The generalized nonlinear Schrödinger (NLS) equation governs pulse propagation in optical fibers, describing the interplay between loss, noise, dispersion, and Kerr nonlinearity, and providing a challenging, yet commercially important, channel model for communication engineers and information theorists. In this work we explore the data communications applications of the nonlinear Fourier transform, a signal analysis technique that simplifies (for the NLS in lossless and noiseless fibers and certain other types of models) the complicated nonlinear spatio-temporal signal evolution to the action of a multiplicative "filter" in the nonlinear frequency domain. We propose a nonlinear analogue of linear frequency-division multiplexing that, unlike many other fiber-optic transmission strategies, deals with both dispersion and nonlinearity unconditionally and without the need for dispersion or nonlinearity compensation methods. (Joint work with Mansoor I. Yousefi and Siddarth Hari.)
Frank R. Kschischang is a Professor of Electrical and Computer Engineering at the University of Toronto, where he has been a faculty member since 1991. While on sabbatical leave, he visited MIT, Cambridge, MA in 1997-98 and ETH, Zürich, in 2005. While on research leave, supported by both a Killam Research Fellowship and a Hans Fischer Senior Fellowship of TUM/IAS, he visited the Technical University of Munich in 2011, and in 2012-13.
Prof. Kschischang's research interests are focused primarily on the area of channel coding techniques, applied to wireline, wireless and optical communication systems and networks. In 1999 he was a recipient of the Ontario Premier's Excellence Research Award and in 2001 (renewed in 2008) he was awarded the Tier I Canada Research Chair in Communication Algorithms at the University of Toronto. Jointly with Ralf Koetter he received the 2010 Communications Society and Information Theory Society Joint Paper Award. He received the 2012 Canadian Award in Telecommunications Research. He is a Fellow of IEEE, of the Engineering Institute of Canada, and of the Royal Society of Canada. He has received six departmental teaching awards, the 2006 Faculty Teaching Award, and the 2010 University of Toronto Faculty Award of Excellence.
During 1997-2000, Kschischang served as an Associate Editor for Coding Theory for the IEEE Transactions on Information Theory, and since January 2014, he serves as this journal's Editor-in-Chief. He also served as technical program co-chair for the 2004 IEEE International Symposium on Information Theory (ISIT), Chicago, and as general co-chair for ISIT 2008, Toronto. He served as the 2010 President of the IEEE Information Theory Society.