About the Project
Automatic Modulation Classification (AMC) is an intermediate step between signal detection and demodulation. It is an essential process for a receiver that has no, or limited, knowledge of received signals. It is important for many areas such as spectrum management, interference identification. The project will review existing techniques and develop new and improved ones with either better accuracy or lower complexity or both.
This project will involve programming, signal processing, machine learning, mathematical analysis, and good writing ability for presentation of technical work. An ideal candidate will have a very good Master degree or a First Class Bachelor degree.
1. Z Zhu and A K Nandi, "Automatic Modulation Classification: Principles, Algorithms and Applications", Published by John Wiley & Sons, Chichester, West Sussex, UK, 2015 (ISBN 978-1-118-90649-1).
2. E E Azzouz and A K Nandi, "Automatic modulation recognition of communication signals", Published by Kluwer Academic Publishers, Amsterdam, Netherlands, 1996 (ISBN 0-7923-9796-7).
3. Z Zhu and A K Nandi, "Blind digital modulation classification using minimum distance centroid estimator and non-parametric likelihood function", IEEE Transactions on Wireless Communications, DOI: 10.1109/TWC.2014.2320724, vol. 13, no. 8, pp. 4483-4494, 2014.
4. Z Zhu, M W Aslam, and A K Nandi, "Genetic algorithm optimized distribution sampling test for M-QAM modulation classification", Signal Processing, vol. 94, no. 1, pp. 264-277, 2014.
5. M W Aslam, Z Zhu, and A K Nandi, "Automatic modulation classification using combination of genetic programming and KNN", IEEE Transactions on Wireless Communications, DOI: 10.1109/TWC.2012.060412.110460, vol. 11, no. 8, pp. 2742-2750, 2012.
6. A K Nandi and E E Azzouz, "Algorithms for automatic modulation recognition of
communication signals", IEEE Transactions on Communications, vol. 46, no. 4, 1998, pp. 431-436.
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