Dr. Matolak

David Matolak

Professor, Electrical Engineering
College of Engineering and Computing
Electrical Engineering

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David W. Matolak received the B.S. degree from The Pennsylvania State University, M.S. degree from The University of Massachusetts, and Ph.D. degree from The University of Virginia, all in electrical engineering.

He has over 25 years’ experience in communication system research, development, and deployment, with industry, government institutions, and academia, including AT&T Bell Labs, L3 Communication Systems, MITRE, and Lockheed Martin. He has over 250 publications and eight patents. He was a professor at Ohio University (1999-2012), and since 2012 has been a professor at the University of South Carolina. He has been Associate Editor for the IEEE Transactions on Vehicular Technology and the IEEE Transactions on Wireless Communications, visting scientist/professor at NASA, NIST, the German Aerospace Center, and L3Harris Technologies. Professor Matolak is a Distinguished Lecture of the IEEE Vehicular Technology Society, and he has delivered several dozen invited presentations at a variety of international venues. His research interests are radio channel modeling and communication techniques for non-stationary fading channels. Prof. Matolak is a Fellow of the IEEE, a member of standards groups in RTCA and ITU, and a member of Eta Kappa Nu, Sigma Xi, Tau Beta Pi, URSI, ASEE, and AIAA

Email: matolak@cec.sc.edu


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Recent Work

Wireless Communications, particularly at the physical and data link layers

Research slide

Modulation and detection

Modulation and detection, including low-probability of detection (LPD), robust signaling for reliable and covert communications, anti-jam, multi-carrier and spread spectrum, and game-theoretic networking

Wireless channel characterization

Wireless channel characterization: measurement, analysis, and modeling for channels from HF through millimeter wave bands, including statistically non-stationary, multi-band, and extreme settings, as well as vehicle-vehicle, air-ground, and time-frequency representations

Statistical signal

Statistical signal processing for adaptive estimation, detection, performance monitoring, and reconfigurable transceivers

It doesn't matter how beautiful your theory is, it doesn't matter how smart you are. If it doesn't agree with experiment, it's wrong.

Richard P. Feynman

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