최소 단어 이상 선택하여야 합니다.
최대 10 단어까지만 선택 가능합니다.
다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
NTIS 바로가기한국통신학회논문지 = The Journal of Korean Institute of Communications and Information Sciences, v.43 no.6, 2018년, pp.930 - 944
최익수 (Inha University Department of Information and Communication Engineering) , 장성진 (Inha University Department of Information and Communication Engineering) , 유상조 (Inha University Department of Information and Communication Engineering)
The AMC (automatic modulation scheme classification) plays an important role in identifying the modulation scheme of the primary user signal in the cognitive radio environment. In this paper, we propose a method of extracting the spectral correlation function and other statistical features from the ...
Y. Saleem and M. H. Rehmani, “Primary radio user activity models for cognitive radio networks: A survey,” J. Netw. Comput. Appl., vol. 43, pp. 1-16, Aug. 2014.
J. Mitola III, “Cognitive radio: an integrated agent architecture for software defined radio,” Ph.D. Dissertation, Royal Inst. Technol. Sweden, May 2000.
S. Haykin, “Cognitive radio: brain-empowered wireless communications,” IEEE J. Select. Areas Commun., vol. 3, no. 2, pp. 201-220, Feb. 2005.
O. 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. 137-156, 2007.
A. Ali and F. Yangyu, “Automatic modulation classification using deep learning based on sparse autoencoders with nonnegativity constraints,” IEEE Sign. Process. Lett., vol. 24, no. 11, pp. 1626-1630, Nov. 2017.
G. J. Mendis, J. Wei, and A. Madanayake, “Deep learning-based automated modulation classification for cognitive radio,” in Proc. IEEE Int. Conf. Commun. Syst. (ICCS), pp. 1-6, Shenzhen, China, Dec. 2016.
A. K. Nandi and E. E. Azzouz, “Algorithms for automatic modulation recognition of communication signals,” IEEE Trans. Commun., vol. 46, no. 4, pp. 431-436, Apr 1998.
F. Hameed, O. A. Dobre, and D. C. Popescu, “On the likelihood-based approach to modulation classification,” IEEE Trans. Wireless Commun., vol. 8, no. 12, pp. 5884-5892, Dec. 2009.
A. K. Nandi and E. E. Azzouz, “Algorithms for automatic modulation recognition of communication signals,” IEEE Trans. Commun., vol. 46, no. 4, pp. 431-436, Apr. 1998.
S. Z. Hsue and S. S. Soliman, “Automatic modulation classification using zero crossing,” IEE Proc. F. Radar Signal Process., vol. 137, no. 6, pp. 459-464, Dec. 1990.
A. Swami and B. M. Sadler, “Hierarchical digital modulation classification using cumulants,” IEEE Trans. Commun., vol. 48, no. 3, pp. 416-429, Mar. 2000.
J. Bagga and N. Tripathi, “Automatic modulation classification using spectral and statistical features and artificial neural networks,” The J. Applied Sci. Res., vol. 1, no. 4, pp. 250-260, Dec. 2014.
J. J. Popoola and R. van Olst, “Effect of training algorithms on performance of a developed automatic modulation classification using artificial neural network,” in Proc. Africon, pp. 1-6, Pointe-Aux-Piments,Mauritius, Sept. 2013.
H. Gang, L. Jiandong, and L. Donghua, "Study of modulation recognition based on HOCs and SVM," in Proc. IEEE Veh. Tech. Conf., vol. 2, pp. 898-902, Milan, Italy, May 2009.
M. W. Aslam, Z. Zhu, and A. K. Nandi, “Automatic modulation classification using combination of genetic programming and KNN,” IEEE Trans. Wireless Commun., vol. 11, no. 8, pp. 2742-2750, Aug. 2012.
Z. Zheng, T. Huang, H. Zhang, S. Sun, J. Wen, and P. Wang, “Towards a resource migration method in cloud computing based on node failure rule,” J. Intell. Fuzzy Syst., vol. 31, no. 5, pp. 2611-2618, 2016.
X. Shi, et al., “Graph processing on GPUs: A survey,” ACM Comput. Surv., vol. 50, no. 6, 2017.
T. Wang, C.-K. Wen, H. Wang, F. Gao, T. Jiang, and S. Jin, “Deep learning for wireless physical layer: Opportunities and challenges,” China Commun., vol. 14, no. 11, pp. 92-111, Nov. 2017
Z. Zhao and L. Tao, "A MPSK modulation classification method based on the maximum likelihood criterion," in Proc. Int. Conf. Sign. Process., vol. 2, pp. 1805-1808, Beijing, China, Aug. 2004.
V. G. Chavali and C. R. C. M. da Silva, “Classification of digital amplitude-phase modulated signals in time-correlated non-Gaussian channels,” IEEE Trans. Commun., vol. 61, no. 6, pp. 2408-2419, Jun. 2013.
W. Wei and J. M. Mendel, “Maximumlikelihood classification for digital amplitudephase modulations,” IEEE Trans. Commun., vol. 48, no. 2, pp. 189-193, Feb. 2000.
A. K. Nandi and E. E. Azzouz, “Automatic analogue modulation recognition,” Signal Process., vol. 46, no. 2, pp. 211-222, Oct. 1995.
R. A. El-Khoribi, M. A. I. Shoman, and A. G. Ahmed Mohammed, “Automatic digital modulation recognition using artificial neural network in cognitive radio,” in IJETTCS, vol. 3, no. 3, pp. 132-136, May-Jun. 2014.
C. Louis and P. Sehier, “Automatic modulation recognition with a hierarchical neural network,” in Proc. MILCOM, vol. 3, pp. 713-717, Fort Monmouth, NJ, USA, Oct. 1994.
A. K. Nandi and E. E. Azzouz, “Modulation recognition using artificial neural networks,” Signal Process., vol. 56, pp. 165-175, 1997.
Z. Yin, “Research of communication signal modulation scheme recognition based on one-class SVM bayesian algorithm,” in Proc. IEEE WiCom'2009, pp. 1-4, Beijing, China, Sept. 2009.
B. Kim, J. Kim, H. Chae, D. Yoon, and J. W. Choi, “Deep neural network-based automatic modulation classification technique,” in Proc. ICTC, pp. 579-582, Jeju, South Korea, Oct. 2016.
A. Engin, “Selecting of the optimal feature subset and kernel parameters in digital modulation classification by using hybrid genetic algorithm-support vector machines: HGASVM,” ELSEVIER, Expert Syst. with Appl., pp. 1391-1402, 2009.
J. Liu and Q. Luo, “A novel modulation classification algorithm based on daubechies5 wavelet and fractional fourier transform in cognitive radio,” in Proc. ICCT 2012, pp. 115-120, Chengdu, China, Nov. 2012.
K. Hassan, I. Dayoub, W. Hamouda, M. Berbineau, et al., “Automatic modulation recognition using wavelet transform and neural networks in wireless systems,” EURASIP J. Advances in Signal Process., vol. 2010, 2010.
H.-B. Guan, C.-Z. Ye, and X.-Y. Li, "Modulation classification based on spectrogram," in Proc. Int. Conf. Machine Learning and Cybernetics, pp. 3551-3556, Shanghai, China, Aug. 2004.
S. Theodoridis and K. Kourtroumbas, Pattern Recognition, New York: Academic Press, 1999.
C. M. Spooner, “Classification of co-channel communication signal using cyclic cumulants,” in Proc. Asilomar, pp. 531-536, Pacific Grove, CA, USA, Nov. 1995.
U. Satija, M. S. Manikandan, and B. Ramkumar, “Performance study of cyclostationary based digital modulation classification schemes,” in Proc. ICIIS2014, pp. 1-5, Gwalior, India, Dec. 2014.
B. Ramkumar, “Automatic modulation classification for cognitive radios using cyclic feature detection,” IEEE Circuits and Systems Mag., vol. 9, pp. 27-45, 2009.
I. S. Choi, S. J. Jang, S. J. Yoo, J. K. Choi, M. H. Seo, M. H. Park, and K. E. Lee, “History-based optimal sensing band selection algorithm in cognitive radio ad-hoc networks,” J. KICS, vol. 43, no. 2, pp. 227-280, 2017.
S. M. Yang, W. J. Song, I. S. Choi, and S. J. Yoo, “Implementation of deep learning-based motion classification system for IoT device control in ultrasonic sound environments,” J. KICS, vol. 42, no. 9, pp. 1796-1805, 2017.
Q. Yang and S. J. Yoo, “Optimal UAV path planning: Sensing data acquisition over IoT sensor networks using multi-objective bio-inspired algorithms,” IEEE Access, vol. 6, pp. 13671-13684, Mar. 2018.
*원문 PDF 파일 및 링크정보가 존재하지 않을 경우 KISTI DDS 시스템에서 제공하는 원문복사서비스를 사용할 수 있습니다.
Free Access. 출판사/학술단체 등이 허락한 무료 공개 사이트를 통해 자유로운 이용이 가능한 논문
※ AI-Helper는 부적절한 답변을 할 수 있습니다.