|
|||||
|
|
| 基于聚类与神经网络的无线通信联合调制识别新方法 | |
| 引用本文： | 杨发权,李赞,罗中良.基于聚类与神经网络的无线通信联合调制识别新方法[J].中山大学学报(自然科学版),2015,54(2):24-29. |
| 作者姓名： | 杨发权 李赞 罗中良 |
| 作者单位： | 1. 佛山科学技术学院电子与信息工程学院， 广东 佛山 528000； 2. 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； 3. 惠州学院电子科学系， 广东 惠州 516007 |
| 基金项目： | 国家自然科学基金资助项目(61072070,61301179);科技型中小企业创新资金项目(14C26214402603);广东省科技计划资助项目(2011B010200030,2012B010100038) |
| 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4d B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。 |
| 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 |
A New Specific Combination Method of Wireless Communication Modulation Recognition Based on Clustering and Neural Network |
|
| 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,2015,54(2):24-29. | |
| Authors: | YANG Faquan LI Zan LUO Zhongliang |
| Affiliation: | 1. School of Electronics and Information Engineering , Foshan University , Foshan 528000, China; 2. State Key Laboratory of Integrated Service Networks , Xidian University , Xian 710071 , China; 3.Department of Electronic Science ,Huizhou University, Huizhou 516007, China |
| 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. |
| Keywords: | algorithm of variable gradient correction BP clustering algorithm feature extraction neural network modulation recognition |
| 本文献已被 CNKI 等数据库收录！ | |
| 点击此处可从《中山大学学报(自然科学版)》浏览原始摘要信息 | |
| 点击此处可从《中山大学学报(自然科学版)》下载全文 | |
