Journal of Systems Engineering and Electronics ›› 2014, Vol. 25 ›› Issue (5): 742-747.doi: 10.1109/JSEE.2014.00085

• ELECTRONICS TECHNOLOGY • Previous Articles     Next Articles

Method of neural network modulation recognition based on clustering and Polak-Ribiere algorithm

Faquan Yang1,2, Zan Li1,*, Hongyan Li1, Haiyan Huang1, and Zhongxian Pan1   

  1. 1. State Key Laboratory of Integrated Service Networks, Xidian University, Xi’an 710071, China;
    2. School of Electrical and Information Engineering, Foshan University, Foshan 528000, China
  • Online:2014-10-23 Published:2010-01-03


To improve the recognition rate of signal modulation recognition methods based on the clustering algorithm under the low SNR, a modulation recognition method is proposed. The characteristic parameter of the signal is extracted by using a clustering algorithm, the neural network is trained by using the algorithm of variable gradient correction (Polak-Ribiere) so as to enhance the rate of convergence, improve the performance of recognition under the low SNR and realize modulation recognition of the signal 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 the methods that adopt clustering algorithm or neural network based on the back propagation 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 a broad application prospect in the modulating recognition.