The adoption of multiple-input multiple-output (MIMO) techniques in wireless communications systems is fueled by the promises of high spectral efficiency and robustness to multipath fading. A key component of a MIMO system is the MIMO detector at the receiver, whose job is to recover the symbols that are transmitted simultaneously from multiple transmitting antennas. In practical applications, the MIMO detector is often the bottleneck for both performance and complexity.
This tutorial presents the basic principles of MIMO detection. We describe the fundamental problem, and present an overview of MIMO techniques that are used in practice. These include linear detection techniques, such as the zero-forcing and mibomnimum-MSE detectors. We will provide several views of the decision-feedback detector, including the nulling-and-cancelling view, the matrix view, the Gram-Schmidt view, the whitened-matched filter view, and the linear-prediction view. We will compare the ZF and MMSE versions of these detectors. We will also describe multistage detectors and tree-based detectors like the sphere detector and its variations, as well as lattice-aided detectors. The impact of ordering on performance and complexity will be described.
This tutorial will provide an overview of MIMO detection as currently practiced, and it will identify emerging trends and current research in this area.
This tutorial will benefit practicing engineers and researchers who are interested in understanding and doing research in MIMO and related topics, particularly those who are engaged in the design of high-speed wireless data systems. MIMO is currently a very hot topic in both the academic and industrial communities and it is anticipated that this tutorial will be very well attended.
Scope and Motivation
The scope of this tutorial is MIMO detection. By way of contrast, our tutorial is not about: capacity analysis, propagation models, space-time codes, transmitter beamforming, feedback schemes, OFDM, etc. Instead, we focus on the signal processing a receiver must do to recover symbols that are transmitted simultaneously from multiple antennas. The motivation for this scope is simple: In real-world applications, detection is the bottleneck for both complexity and performance.
Dr. John R. Barry received the M.S. and Ph.D. degrees from the University of California at Berkeley in 1987 and 1992, respectively, both in electrical engineering. Since 1985 he has held engineering positions in the fields of communications and radar systems at Bell Communications Research, IBM T.J. Watson Research Center, Hughes Aircraft Company, and General Dynamics. He is a frequent author and instructor in the field of MIMO communications. He is a coauthor of Digital Communication, Third Edition, Kluwer, 2004, and the author of Wireless Infrared Communications, Kluwer, 1994. He received the 1992 David J. Griep Memorial Prize and the 1993 Eliahu Jury Award from U.C. Berkeley, a 1993 Research Initiation Award from NSF, and a 1993 IBM Faculty Development Award. He joined the Georgia Tech faculty in 1992, where he is a professor with the School of Electrical and Computer Engineering.