Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.3/54275

Title

Naive Bayes classification of adaptive broadband wireless modulation schemes with higher order cumulants

Author(s)

Wong, M. L. D.;  Sie King, Ting;  Nandi, A. K.

Abstract

Adaptive modulation schemes have been proposed to optimize Shannon's channel capacity in recent orthogonal frequency division multiplexing (OFDM) based broadband wireless standard proposals. By adapting the modulation type (effectively changing the number of bits per symbol) at the transmitter end one can improve the bit error rate (BER) during transmission at designated SNR. Blind detection of the transmitted modulation type is desirable to optimise the bandwidth available at the receivers. Hence, there is a need for an intelligent modulation classification engine at the receiver end. In this work, we evaluate some higher order statistical measures coupled with a classical Naive Bayes classifier for fast identification of adaptive modulation schemes. We also benchmark the experimental results with the optimal Maximum Likelihood Classifier, and Support Vector Machine based Classifier using the same feature set.

Publication type

Conference paper

Research centre

Swinburne University of Technology. Sarawak Campus. School of Engineering and Science

Source

Proceedings of the 2nd International Conference on Signal Processing and Communication Systems (ICSPCS 2008), Gold Coast, Australia, 15-17 December 2008

Publication year

2008

Keyword(s)

Broadband wireless;  Modulation classification;  Naive Bayes network;  OFDM

Publisher

IEEE

ISBN

9781424442430

Publisher URL

http://dx.doi.org/10.1109/ICSPCS.2008.4813755

Copyright

Copyright © 2008 IEEE.

Peer reviewed