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http://dx.doi.org/10.3745/KIPSTC.2005.12C.1.063

Performance of an ML Modulation Classification of QAM Signals with Single-Sample Observation  

Kang Seog Geun (경상대학교 전기전자공학부)
Publication Information
The KIPS Transactions:PartC / v.12C, no.1, 2005 , pp. 63-68 More about this Journal
Abstract
In this paper, performance of a maximum-likelihood modulation classification for quadrature amplitude modulation (QAM) is studied. Unlike previous works, the relative classification performance with respect to the available modulations and performance limit with single-sample observation are presented. For those purposes, all constellations are set to have the same minimum Euclidean distance between symbols so that a smaller constellation is a subset of the larger ones. And only one sample of received waveform is used for multiple hypothesis test. As a result, classification performance is improved with increase in signal-to-noise ratio in all the experiments. Especially, when the true modulation format used in the transmitter is 4 QAM, almost perfect classification can be achieved without any additional information or observation samples. Though the possibility of false classification due to the symbols shared by subset constellations always exists, correct classification ratio of $80{\%}$ can be obtained with the single-sample observation when the true modulation formats are 16 and 64 QAM.
Keywords
Modulation Classification; Quadrature Amplitude Modulation; Constellation; Multiple Hypothesis Test; Likelihood Function;
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