5G Tutorial: Millimeter Wavelength Communication and Massive MIMO

Dr. Thomas Ketseoglou
California State Polytechnic University, Pomona
5G will require an assertive new technology deployment that aims at achieving orders of magnitude improvements in data throughput. This tutorial will address the fundamental ideas behind 5G MIMO, its physical layer, and the corresponding technical challenges. The tutorial will address how mm wavelength communication in conjunction with Massive MIMO offers the possibility of achieving the 5G high data rate requirements and what are the main technical challenges and impediments on the path of 5G deployment, including: propagation and channel models, beamforming techniques, and channel estimation. More explicitly the tutorial will cover the following issues:
  1. Introduction and historical perspective: 1G, 2G, 3G, 4G, 5G
  2. 5G Requirements
  3. 5G prevailing technologies: What is mm wavelength communication? What is Massive MIMO? What are the advantages of 5G techniques over current wireless techniques? Is there still space for Multi-Carrier techniques in 5G?
  4. Impediments to 5G: What is pilot contamination? How is channel estimation performed in 5G? What are some promising precoding techniques toward improved data communication?
  5. Conclusions
Speaker’s Biography
Thomas Ketseoglou (S.85-M.91-SM.96) received the B.S. degree from the University of Patras, Patras, Greece, in 1982, the M.S. degree from the University of Maryland, College Park, Maryland, USA, in 1986, and the Ph.D. degree from the University of Southern California, Los Angeles, California, USA, in 1990, all in electrical engineering. He worked in the wireless communications industry, including senior level positions with Siemens, Ericsson, Rockwell, and Omnipoint. From 1996 through 1998 he participated in TIA TR45.5 (now 3GPP2) 3G standardization, making significant contributions to the cdma2000 standard. He has been inventor and co-inventor in several essential patents in wireless communications. Since September 2003 he has been with the Electrical and Computer Engineering department of the California State Polytechnic University, Pomona, California, USA, where he is a professor. He spent his sabbatical leave in 2011 at the Digital Technology Center, University of Minnesota, Minneapolis, Minnesota, USA, where he taught digital communications and performed research on network data and machine learning techniques. He is a part-time lecturer at the University of California, Irvine. His teaching and research interests are in wireless communications, signal processing, and machine learning, with current emphasis on MIMO, optimization, localization, and link prediction.