A novel sub-optimum maximum-likelihood modulation classification algorithm for adaptive OFDM systems
Yucek, T.; Arslan, H.
Wireless Communications and Networking Conference, 2004. WCNC. 2004 IEEE
Volume 2, Issue , 21-25 March 2004 Page(s): 739 - 744 Vol.2
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Summary: Adaptive modulation is an effective method to increase the spectral efficiency of OFDM based high-speed wireless data transmission systems in time-dispersive (frequency-selective) channels. Blind modulation classification schemes play an important role in adaptive modulation systems to eliminate the need for transmitting the modulation information, thereby increasing spectral efficiency. In this paper, a maximum-likelihood (ML) modulation classifier which has the optimum performance in the presence of white noise is presented. A sub-optimum classifier, which greatly reduces the complexity, is derived from the optimum ML classifier. The performances of proposed classifiers are tested using Monte-Carlo simulations for ideal and non-ideal cases.

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