Automatic Modulation Recognition in Wireless Multi-carrier Wireless Systems with Cepstral Features

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• 作者：Mohamed El-Hady M. Keshk (1)
  Mohammed Abd El-Naby (2)
  Rasha M. Al-Makhlasawy (3) (4)
  Heba A. El-Khobby (4)
  W. Hamouda (5)
  Mustafa M. Abd聽Elnaby (4)
  El-Sayed M. El-Rabaie (2)
  Moawad I. Dessouky (2)
  Saleh A. Alshebeili (6)
  Fathi E. Abd El-Samie (7) (8)
  
  1. Egyptian Space Program ; National Authority for Remote Sensing and Space Science ; Cairo ; Egypt
  2. Department of Electronics and Electrical Communications ; Faculty of Electronic Engineering ; Menoufia University ; Menouf ; 32952 ; Egypt
  3. Electronics Research Institute ; Dokky ; Egypt
  4. Faculty of Engineering ; Tanta University ; Tanta ; Egypt
  5. Concordia University ; Montreal ; Canada
  6. Electrical Engineering Department ; KACST-TIC in Radio Frequency and Photonics for the e-Society (RFTONICS) ; King Saud University ; Riyadh ; Kingdom of Saudi Arabia
  7. Department of Computer Science and Engineering ; Faculty of Electronic Engineering ; Menoufia University ; Menouf ; 32952 ; Egypt
  8. KACST-TIC in Radio Frequency and Photonics for the e-Society (RFTONICS) ; King Saud University ; Riyadh ; Kingdom of Saudi Arabia
  
• 关键词：ADMR ; OFDM ; MFCC ; DT ; SVM ; RPROANN ; AWGN ; SDR
• 刊名：Wireless Personal Communications
• 出版年：2015
• 出版时间：April 2015
• 年：2015
• 卷：81
• 期：3
• 页码：1243-1288
• 全文大小：11,297 KB
• 参考文献：1. Aslam, M. W., Zhu, Z., & Nandi, A. K. (2010). Automatic digital modulation classification using genetic programming with K-nearest neighbor. In / Military Communications Conference, 2010-MILCOM 2010 (pp. 1731鈥?736). San Jose, CA: IEEE.
  2. Hassan, K., Dayoub, I., Hamouda, W., & Berbineau, M. (2010). Automatic modulation recognition using wavelet transform and neural networks in wireless systems. / EURASIP Journal on Advances in Signal Processing. doi:10.1155/2010/532898 .
  3. Czylwik, A. (1996). Adaptive OFDM for wideband radio channels. In / Proceedings of Communications: The Key to Global Prosperity Global Telecommunications Conference GLOBECOM 鈥?6, vol. 1, pp. 713鈥?18, 18鈥?2 November 1996.
  4. Campello, J. (1998). Optimal discrete bit loading for multicarrier modulation systems. In / Proceedings of the IEEE International Symposium on Information Theory, p. 193.
  5. Park, C., Jang, W., & Nah, S. (2007). / Automatic modulation recognition using support vector machine in software radio applications. EW Lab., Agency for Defense Development, Korea.
  6. Li, J., Peng, J., Chu, H., & Zhu, W. (2005). Automatic digital modulation recognition using support vector machines and genetic algorithm. In / Second international symposium on neural networks. doi:10.1007/11427445_93 , ISNN 2005.
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  8. Sadler, M. B., & Swami, A. (2000). Hierarchical digital modulation classification using cumulants. / IEEE Transactions on Communications, / 48(3), 416鈥?29.
  9. Mobasseri, B. G. (November 1997). / Digital modulation classification using constellation shape. Department of Electrical and Computer Engineering, Villanova University, Villanova, PA 19085.
  10. Zhao, Y., Ren, G., & Zhong, Z. (May 2006). Modulation recognition of SDR receivers based on WNN. In / Proceedings of the 63rd IEEE vehicular technology conference (VTC 鈥?6), pp. 2140鈥?143.
  11. Attar, AR, Sheikhi, A, Abiri, H, Mallahzadeh, A (2006) A new method for communication system recognition. Iranian Journal of Science & Technology, Transaction B, Engineering 30: pp. 775-788
  12. Al-Makhlasawy, R. M., Elnaby, M. M. A., & El-Khobby, H. A. (2012). C24. Automatic modulation recognition in wireless systems using cepstral analysis and neural networks. In / Radio Science Conference (NRSC), pp. 353鈥?62, April 2012.
  13. Dobre, A. O., Abdi, A., Bar-Ness, Y., & Su, W. (2005). A survey of automatic modulation classification techniques: Classical approaches and new trends. In / Part of this work was published in a preliminary form and presented at the Sarnoff Symposium, Princeton, NJ, USA, under the title 鈥淏lind modulation classification: A concept whose time has come鈥? 18鈥?9 April 2005.
  14. Kinnunen, T. (2003). / Spectral features for automatic text independent speaker recognition. Licentiate鈥檚 Thesis, University of Joensuu, Department of Computer Science, Finland.
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  19. Zhao, Y., Ren, G., & Zhong, Z. (May 2006). Modulation recognition of SDR receivers based on WNN. In / Proceedings of the 63rd IEEE vehicular technology conference (VTC 鈥?6), pp. 2140鈥?143.
  20. Dreyfus, G (2005) Neural networks methodology and applications. Springer, Berlin, Heidelberg
  
• 刊物类别：Engineering
• 刊物主题：Electronic and Computer Engineering
  Signal,Image and Speech Processing
  Processor Architectures
  
• 出版者：Springer Netherlands
• ISSN：1572-834X

文摘

Automatic digital modulation recognition (ADMR) has become an interesting problem in wireless communication systems with various civil and military applications. In this paper, an ADMR algorithm is proposed for both orthogonal frequency division multiplexing and multi-carrier code division multiple access systems using discrete transforms and mel-frequency cepstral coefficients (MFCCs). The proposed algorithm uses one of the discrete cosine transform, discrete sine transform, and discrete wavelet transform with MFCCs to extract the modulated signal coefficients, and uses also either a support vector machine (SVM) or an artificial neural network (ANN) for modulation classification. Simulation results show that the proposed algorithm provides higher recognition rates than those obtained in previous studies, in addition to a superiority of SVM performance compared to ANN performance at low signal-to-noise ratios.