Main Instructors: Georgios B. Giannakis, University of Minnesota, and Shengli Zhou, University of Connecticut

Rate-optimal transmitter designs obeying the water-filling principle are well-documented, and widely applied when the propagation channel is deterministically known, and regularly updated at the transmitter. Albeit reasonable for wireline links, adaptive transmissions based on perfect CSI can be justified only when the fading is sufficiently slow. On the other hand, the proliferation of space time (ST) coding research we have witnessed lately, testifies to the efforts put towards the other extreme: non-adaptive (and thus conservative) designs requiring no CSI to be available at the transmitter. As no-CSI leads to robust but rather pessimistic designs, and perfect-CSI is probably a utopia for most wireless links, recent efforts geared towards quantification and exploitation of partial (or statistical) CSI promise to have great practical value, not only because they are capable of offering the ``jack of both trades,'' but also because they encompass the perfect-CSI and no-CSI paradigms.

This tutorial will highlight recent advances on multi-input multi-output (MIMO) communications based on partial CSI, from both information-theoretic and communications perspectives.

Outline:
1. Preliminaries, definitions, and context
2. Characterization of partial CSI
2a. Mean feedback
2b. Covariance feedback
3. Impact of partial CSI on MIMO capacity
3a. Capacity-optimizing transmissions
3b. Optimality of beamforming
4. Impact of imperfect CSI on system performance
5. Practical designs of adaptive transmitters based on partial CSI
5a. Combined space-time block coding and eigen-beamforming
5b. Adaptive multi-antenna modulation
5c. A transceiver optimization based on pilot-symbol-assisted-modulation (PSAM)
5d. Adaptive MIMO OFDM for frequency-selective fading channels
6. Summary, Challenges, Further research topics

Presenters’ short biographies:

Georgios B. Giannakis holds the ADC Wireless Telecommunications Chair at the Electrical and Computer Engineering Department at the University of Minnesota. Prior to that he spent 12 years at the University of Virginia. Professor Giannakis’ general academic interests include communications and signal processing, estimation and detection theory, time-series analysis, and system identification. His current research focuses on transmitter and receiver diversity techniques for single- and multi-user fading communication channels, precoding and space-time coding for block transmissions, multicarrier, and ultra-wideband wireless systems. He has published more than 160 journal papers, 300 conference papers, and he has edited two books on Signal Processing for Wireless and Mobile Communications. Dr. Giannakis has an electrical engineering educational background, with a BSEE (National Tech. University, Athens, Greece, 1981;), an MSEE, and Ph.D. EE (USC, 1983 and 1986, respectively) and he also has an MS in Mathematics (USC, 1986). Dr. Giannakis has been very active with the IEEE, winning four best paper awards, organizing workshops, and editing special issues.

Shengli Zhou received his B.S.EE in 1995 and his M.Sc.EE in 1998, from the University of Science and Technology of China (USTC), and the Ph.D.EE in 2002, from the University of Minnesota. He is now an Assistant Professor with the department of Electrical Engineering at the University of Connecticut. His research interests lie in the areas of communications and signal processing, including transceiver optimization, blind channel estimation and equalization algorithms, wireless, multi-carrier, space-time coded and spread-spectrum communication systems.