2008 IEEE Sarnoff Symposium

April 28 - 30, 2008, Nassau Inn in Princeton, NJ, USA

Sponsored by:

Co-sponsors:

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2007 Sarnoff Symposium

Tutorials

Advances in Automatic Modulation Classification Techniques.

Octavia Dobre

Assistant Professor
Faculty of Engineering & Applied Science Memorial University of Newfoundland St. John's, NL A1B 3X5, Canada
Email: dobre@engr.mun.ca

Duration:2.5 hours.

Summary

Automatic Modulation Classification (MC) is a major task of an intelligent radio receiver, with applications to both military and commercial communications. Finding solutions to the MC problem is a challenging task for communication engineers, especially in non-cooperative environments, in which no prior information on the incoming signal is available at the receive-side. This tutorial will provide the audience with an overview of possible solutions to MC, including likelihood- and feature-based methods. Cyclic statistics will be primarily examined as discriminating signal features. Main characteristics of diverse techniques will be presented, emphasizing their advantages and drawbacks.

Short Bio:
Octavia A. Dobre received the D. Eng. and Ph. D. degrees from the Polytechnic Institute of Bucharest, Romania, in 1991 and 2000, respectively. In 2000 she was the recipient of a British Royal Society fellowship. In 2001 she joined Stevens Institute of Technology in Hoboken, NJ, as a Fulbright fellow. Between 2002 and 2005, she was with the Department of Electrical and Computer Engineering at New Jersey Institute of Technology in Newark, NJ, as a Research Associate. Currently, she is an Assistant Professor with the Faculty of Engineering and Applied Science at Memorial University of Newfoundland, Canada. She has served as a chair and member of the technical program committees of various international conferences, and as a reviewer for numerous refereed journals. She has given a number of invited talks on the subject related to this tutorial, to both academia and industry. Her current research interests include blind modulation classification and parameter estimation, cognitive radio, cyclostationarity applications in communications and signal processing, and resource allocation in emerging wireless networks