Hybrid maximum likelihood modulation classification using multiple radios

IEEE Communications Letters

Volumn 17, Issue 10, 2013, Pages 1889-1892

  Ozdemir, Onur ^a   Li, Ruoyu ^b   Varshney, Pramod K ^c  

^a Boston Fusion Corp   (United States)

^b NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^c SYRACUSE UNIVERSITY   (United States)

Author keywords

data fusion; EM algorithm; ML estimation; Modulation classification

Indexed keywords

EM ALGORITHMS; EXPECTATION-MAXIMIZATION ALGORITHMS; MAXIMUM LIKELIHOOD APPROACHES; ML ESTIMATION; MODULATION CLASSIFICATION; MULTI-RADIO; MULTIPLE RADIOS; NUMERICAL RESULTS;

ALGORITHMS; DATA FUSION; PHASE MODULATION; SIGNAL TO NOISE RATIO;

AMPLITUDE MODULATION;

EID: 84888001386     PISSN: 10897798     EISSN: None     Source Type: Journal    
DOI: 10.1109/LCOMM.2013.081913.131351     Document Type: Article

References (4)

1. J. Hamkins, M. K. Simon, and J. H. Yuhen, Autonomous Software-Defined Radio Receivers for Deep Space Applications (JPL Deep-Space Communications and Navigation Series). Wiley-Interscience, 2006.
2. O. A. Dobre, A. Abdi, Y. Bar-Ness, and W. Su, "Survey of automatic modulation classification techniques: classical approaches and new trends, " IET Commun., vol. 1, no. 2, pp. 137-159, Apr. 2007.
3. A. Abdi, O. A. Dobre, R. Chauchy, Y. Bar-Ness, and W. Su, "Modulation classification in fading channels using antenna arrays, " in Proc. 2004 IEEE MILCOM, pp. 211-217.
4. W. Su and J. Kosinski, "Framework of network centric signal sensing for automatic modulation classification, " in Proc. 2010 IEEE ICNSC, pp. 534-539.