| 基于高阶累积量和小波变换的调制识别算法 |
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| 引用本文： | 谭晓衡,褚国星,张雪静,杨扬. 基于高阶累积量和小波变换的调制识别算法[J]. 系统工程与电子技术, 2018, 40(1): 171-177. DOI: 10.3969/j.issn.1001-506X.2018.01.25 |
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| 作者姓名： | 谭晓衡 褚国星 张雪静 杨扬 |
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| 作者单位： | 1. 重庆大学生物感知与智能信息处理重庆市重点实验室, 重庆 400044; 2. 重庆大学通信工程学院, 重庆 400044; 3. 安徽四创电子股份有限公司, 安徽 合肥 230001 |
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| 摘 要： | 针对当前调制识别算法在低信噪比下识别率不高的问题,提出结合高阶累积量和小波变换的混合调制识别算法。该算法利用了小波变换提取的两个特征参数,以及基于四阶和六阶累积量构造出一个新的特征参数,并应用反向传播神经网络分类器对调制信号进行识别。仿真结果证明,该算法能够在信噪比低至2 dB时,识别率仍可达到98%以上,由此证明了该方法的有效性和稳健性。
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Modulation recognition algorithm based on high-order cumulants andwavelet transform |
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| TAN Xiaoheng,CHU Guoxing,ZHANG Xuejing,YANG Yang. Modulation recognition algorithm based on high-order cumulants andwavelet transform[J]. System Engineering and Electronics, 2018, 40(1): 171-177. DOI: 10.3969/j.issn.1001-506X.2018.01.25 |
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| Authors: | TAN Xiaoheng CHU Guoxing ZHANG Xuejing YANG Yang |
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| Affiliation: | 1. Chongqing Key Laboratory of Bio perception & Intelligent Information Processing, Chongqing University, Chongqing 400044, China; 2. College of Communication Engineering, Chongqing University, Chongqing 400044, China; 3. Anhui Sun Create Electronics Company Limited, Hefei 230001, China; |
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| Abstract: | A joint method is proposed based on combination of high order cumulants and wavelet transform for recognizing the major modulation schemes at low signal-to-noise ratios(SNRs) which are applied to concurrent communication systems. Two feature parameters using amplitude and phase of digital signals after wavelet transform and a new featureparameter are extracted from four-order and six-order cumulants and are used to identify the modulation schemes with back propagation neural network classifier. Simulationresults show that the average recognition rate is more than 98% with SNR higher than 2dB, which proves the validity and robustness of the method. |
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