A New Specific Combination Method of Wireless Communication Modulation Recognition Based on Clustering and Neural Network

YANG Faquan; LI Zan; LUO Zhongliang

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A New Specific Combination Method of Wireless Communication Modulation Recognition Based on Clustering and Neural Network

更新时间：2023-12-11

- A New Specific Combination Method of Wireless Communication Modulation Recognition Based on Clustering and Neural Network
- Acta Scientiarum Naturalium Universitatis SunYatseni Vol. 54, Issue 2, Pages: 24-29(2015)
- 作者机构：
  
  1. 佛山科学技术学院电子与信息工程学院,广东,佛山,528000
  2. 
  3. 西安电子科技大学综合业务网理论及关键技术国家重点实验室,陕西,西安,710071
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2015，
  
  Published Online：25 March 2015，
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YANG Faquan, LI Zan, LUO Zhongliang. A New Specific Combination Method of Wireless Communication Modulation Recognition Based on Clustering and Neural Network. [J]. Acta Scientiarum Naturalium Universitatis SunYatseni 54(2):24-29(2015)
DOI：

YANG Faquan, LI Zan, LUO Zhongliang. A New Specific Combination Method of Wireless Communication Modulation Recognition Based on Clustering and Neural Network. [J]. Acta Scientiarum Naturalium Universitatis SunYatseni 54(2):24-29(2015) DOI：

摘要

针对现有基于聚类算法的信号调制识别在低信噪比时识别率低的缺点，文中采用聚类算法提取信号特征参数，通过变梯度 PolakRibiere BP修正算法对神经网络进行训练，以提高收敛速度，改善在低信噪比条件下网络识别性能，实现对基于星座图调制方式信号的调制识别，仿真结果表明，在低信噪比条件下，调制识别率和单独采用聚类算法或基于BP算法的神经网络识别时比较提高30%以上，在信噪比为4dB 条件下识别率可达到90% ，且系统易于实现，在信号调制识别中具有广泛的应用前景。

Abstract

To improve the recognition rate of the signal

a modulation recognition method is proposed based on the clustering algorithm under the low SNR. The characteristic parameter of the signal is extracted by using a clustering algorithm

neural network is trained by using the algorithm of variable gradient correction BP so as to enhance the rate of convergence.The performance of recognition under the low SNR is improved

and the modulation recognition of the signal is realized based on the modulation system of the constellation diagram. Simulation results show that the recognition rate based on this algorithm is enhanced over 30% compared with methods of adopting clustering algorithm or neural network based on BP algorithm alone under the low SNR. The recognition rate can reach 90% when the SNR is 4 dB

and the method is easy to be achieved so that it has broad application prospect in the modulating recognition.

关键词

变梯度修正BP算法聚类算法特征值的提取神经网络调制识别

Keywords

algorithm of variable gradient correction BPclustering algorithmfeature extractionneural networkmodulation recognition

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Related Institution

School of Aeronautics and Astronautics， Sun Yat-sen University

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School of Intelligent Systems Engineering， Sun Yat-sen University / Guangdong Provincial Key Laboratory of Intelligent Transportation System / Key Laboratory of Video and Image Intelligent Analysis and Application Technology，Ministry of Public Security

Department of Earth Sciences, Sun Yatsen University，Guangzhou 510275, China

School of Geographical Sciences,Guangzhou University

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