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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Wong, M.L.D. Sie King Ting Nandi, A.K. |
| Copyright Year | 2008 |
| Description | Author affiliation: Signal Process. & Commun. Group, Univ. of Liverpool, Liverpool (Nandi, A.K.) || Sch. of Eng. & Sci., Swinburne Univ. of Technol. (Wong, M.L.D.; Sie King Ting) |
| 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. |
| Starting Page | 1 |
| Ending Page | 5 |
| File Size | 117363 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424442430 |
| DOI | 10.1109/ICSPCS.2008.4813755 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-12-15 |
| Publisher Place | Australia |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Maximum likelihood detection Channel capacity Modulatiuon Classification OFDM Bit error rate Broadband Wireless Proposals Machine intelligence Engines Couplings Naïve Bayes Network Transmitters Bit rate OFDM modulation |
| Content Type | Text |
| Resource Type | Article |
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