Lai Hui-cheng, Chu Hui . An Automatic Modulation Recognizer Using Neural Networks Based on the Hybrid Mode[J]. Journal of Electronics & Information Technology, 2008, 30(5): 1203-1205. doi: 10.3724/SP.J.1146.2007.00515
Citation:
Lai Hui-cheng, Chu Hui . An Automatic Modulation Recognizer Using Neural Networks Based on the Hybrid Mode[J]. Journal of Electronics & Information Technology, 2008, 30(5): 1203-1205. doi: 10.3724/SP.J.1146.2007.00515
Lai Hui-cheng, Chu Hui . An Automatic Modulation Recognizer Using Neural Networks Based on the Hybrid Mode[J]. Journal of Electronics & Information Technology, 2008, 30(5): 1203-1205. doi: 10.3724/SP.J.1146.2007.00515
Citation:
Lai Hui-cheng, Chu Hui . An Automatic Modulation Recognizer Using Neural Networks Based on the Hybrid Mode[J]. Journal of Electronics & Information Technology, 2008, 30(5): 1203-1205. doi: 10.3724/SP.J.1146.2007.00515
On automatic modulation there are two approaches, decision-theoretic and statistical pattem. An automatic modulation recognition system to recognize four digital signal classes as MASK, MFSK, MPSK, MQAM is proposed in this paper, which using decision-theoretic based feature set addition to statistical pattem based feature set with momentum auto-adapted weight BP neural network. Performance is generally good when Signal to Noise Ratios (SNR) in 0-10dB, and the estimated carrier frequency differs from the actual carrier frequency of 0-100Hz, simulations show the results even larger than 97%, that confirm the robustness and practicability of this recognition method.
Nandi A K and Azzouz E E. Algorithms for automaticmodulation recognition of communication signals[J]. IEEETrans. on Communications, 1998, 46(4): 431-436.[2]Azzouz E E and Nandi A K. Procedure for automaticrecognition of analogue and digital modulations [J]. IEEProceedings, Communications, 1996, 143(5): 259-266.[3]Wong M L D and Nandi A K. Automatic digital modulationrecognition using spectral and statistical features withmulti-layer perceptrons[C]. ISSPA. KualaLumpur, Malaysia,2001-08, 2: 390-393.[4]李春辉. 调制体制识别算法综述[J]. 数字通信世界, 2005,20(11): 53-56.[5]Swami Anonthram and Sadler Brain M. Hierarchical digitalmodulation classification using cumulants[J].IEEE Trans. onCommunications.2000, 48(3):416-429[6]吕铁军, 肖先赐. 基于神经网络最佳分类器通信信号的调制识别[J]. 系统工程与电子技术, 2001, 23(5): 44-46.[7]陈玉芳, 雷霖. 提高BP 网络收敛速率的又一种算法[J]. 计算机仿真, 2004, 21(11): 74-76.
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