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Fast Modulation Classifier for Software Radio  

Park, Cheol-Sun (국방과학연구소 기술연구본부)
Jang, Won (국방과학연구소 기술연구본부)
Kim, Dae-Young (충남대학교 정보통신공학과)
Publication Information
The Journal of Korean Institute of Communications and Information Sciences / v.32, no.4C, 2007 , pp. 425-432 More about this Journal
Abstract
In this paper, we deals with automatic modulation classification capable of classifying incident signals without a priori information. The 7 key features which have good properties of sensitive with modulation types and insensitive with SNR variation are selected. The numerical simulations for classifying 9 modulation types using the these features are performed. The numerical simulations of the 4 types of modulation classifiers are performed the investigation of classification accuracy and execution time to implement the fast modulation classifier in software radio. The simulation result indicated that the execution time of DTC was best and SVC and MDC showed good classification performance. The prototype was implemented with DTC type. With the result of field trials, we confirmed the performance in the prototype was agreed with the numerical simulation result of DTC.
Keywords
Modulation Classification; Decision Tree Classifier; Minimum Distance Classifier; Neural Network Classifier; Support Vector Machine Classifier;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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1 A.K. Nandi and E.E. Azzouz, 'Algorithm for automatic modul ation recognition of communica tion signals,' IEEE Trans. Communications, vol. 46, no. 4, pp.431-436, April 1998   DOI   ScienceOn
2 Ilan Druckmann et al., 'Automatic modulation type recog nition,' IEEE Canadian Conf. on Electrical and Computer Engineering, pp.65-68, May 1998
3 Octavia A. Dobre et al., 'The classification of joint analog and digital modulations,' IEEE MILCOM '05, pp. 3010-3015, Oct. 2005
4 Roongroj Nopsuwanchai, and Al ain Biem, 'Prototype-based minimum error classifier for handwritten digits recognition,' IEEE ICASSP'04, pp.845-848, May 2004
5 L. Zhang, N. Fujiwara, K. Muramatsu, M. Daigo and S. Furumi, 'Land cover classification based on the universal pattern decomposition method,' Int'l Symp. on Remote Sensing of Environment, 2005
6 Hussam Mustafa and Milos Doroslovacki, 'Digital modula tion recognition using support vector machine classifier,' IEEE Conf. on Signals, Systems and Computers, pp.2238-2242, Nov. 2004
7 Zhilu Wu et al., 'Automatic digital modulation recognition based on supp ort vector machine,' IEEE Conf. on Neural Networks and Brain, pp. 1025-1028, Oct. 2005
8 Robert W. Jones, Spectrum Monitoring Handbook, ITU, 3rd ed, 1995, pp.222-237
9 Bin Le et al, 'Modulation identification using neural network for cognitive radios,' SDR forum technical conference, 2005
10 신용조, 진용옥, '신경망을 이용한 디지털 변조 방식의 자동식별,' 한국통신학회논문지, Vol.25, No.10B, pp1769-1776, 2000
11 Steve R. Gunn, Support Vector Machine for Classification and Regression, Technical Report, Univ. of Southampton, May 1998
12 Namjin Kim, Nasser Kehta rnavaz, Mark B. Yeary and Steve Thornton, 'DSP-based hirerarchical neural network modulation signal classification,' IEEE Trans. Neural Networks, vol.14, no.5, pp. 1065-1071, Sept. 2003   DOI   ScienceOn
13 B.Q.Hu, J. Yang, and J.L.He, 'A multiclassification model based on FSVMs,' NAFIPS '05, pp. 205-209, June 2005
14 M. Vastram Naik et al., 'Blind adaptive recognition of different QPSK modulated signals for software defined radio applica tion,' '06 COMSWARE, pp. 1-6, Jan. 2006
15 Andrew Webb, Statistical Pattern Recognition, 2nd ed., 2002, John Wiley & Sons, Ltd., pp.144-168
16 Octavia A. Dobre et al., 'A survey of automatic modulation classification Techniques: classi cal approaches and new trends,' IEE Proc. Communication, to be published in 2006
17 Stefan C. Kremer and Joanne Sheils, 'A testbed for automatic modulation recognition using artificial neural networks,' IEEE Canadian Conf. on Electrical and Computer Engi neering, pp.67-70, May 199
18 Wu Dan, Gu Xuemai, and Guo Qing, 'A new scheme of automatic modulation classifica tion using wavelet and WSVM,' 2nd Int'l Conf. on Mobile Technology, Applications and Systems, Nov. 2004
19 서승한, 윤여종, 진영환, 서영주, 임선민, 안재민, 은창수, 장원, 나선필, '아날로그 및 디지털 변조 신호의 자동인식,' 한국통신학회논문지, Vol.30, No.1C, pp.73-81, 2005   과학기술학회마을
20 E.E. Azzouz, and A.K.Nandi, 'Procedure for automatic recog nition of analogue and digital modulations,' IEE proceedings Communications, vol. 143, no.5, pp. 259-266, oct. 1996   DOI   ScienceOn
21 Anil K. Jain et al., 'Statistical pattern recognition: a review,' IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 22, no. 1, pp. 4-37, Jan. 2000   DOI   ScienceOn