Title :
Ultra-wideband signal modulation classification using RBF network
Author :
Ma, Bo ; Zuo, Lihua ; Chen, Xiaoguang
Author_Institution :
China Acad. of Space Technol., Beijing, China
Abstract :
In this paper, an Radial Basis Function (RBF) network based Ultra-Wide Band modulation scheme recognition algorithm is proposed. In the UWB receiver, the statistical characterization parameters of the UWB signal after A/D converter are extracted as the input neuron parameters of the input layer. Experiments show that the RBF network can achieve good recognition performance. The probability of the correct recognition of the RBF network with proper parameter spread is higher than 95% at 10dB SNR condition. Compared with the traditional pattern recognition and statistics judgment algorithms, the RBF recognizer can achieve higher correct recognition probability and can classify the modulation scheme automatically. The method may be widely used in the design of adaptive coding UWB systems.
Keywords :
adaptive codes; feature extraction; radial basis function networks; ultra wideband communication; RBF network; UWB receiver; adaptive coding UWB systems; radial basis function network; statistical characterization parameters; ultra wideband signal modulation classification; Artificial neural networks; Binary phase shift keying; Classification algorithms; Feature extraction; Pattern recognition; Probability; Mod Scheme recognition; RBF network; UWB; feature extraction;
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
DOI :
10.1109/ICCASM.2010.5623126
