Title :
An EBPSK Demodulator based on ANN Detection
Author :
Feng, Man ; Wu, Lenan ; Gao, Peng
Author_Institution :
The Institute of Information Science and Engineering, Southeast University, Nanjing, China
Abstract :
High-speed and high-efficiency communication is a hot problem in the research field of communication. In this paper, one of higher efficiency ultra narrow-band (UNB) modulation schemes, named Extended Binary Phase Shift Keying (EBPSK), was presented. Then, aiming at the tiny waveform difference and detection problems, several novel detectors based on the Artificial Neural Network (ANN) are proposed and analyzed. The basic idea is to remove the most noise and interference using the impulse filter, and then extract the waveform differences of “0” and “1” by the good learning ability of ANN. Also the detection performances based on different networks are compared by computer simulation, which illustrates that the proposed novel detection method based ANN classifier has good performance and low computations.
Keywords :
Artificial neural networks; Demodulation; Detectors; Neurons; Noise; Training; Artificial Neural Network (ANN); Ultra narrow-band (UNB); extended binary phase shift keying (EBPSK); the impulse filter;
Conference_Titel :
Information Science and Engineering (ICISE), 2010 2nd International Conference on
Conference_Location :
Hangzhou, China
Print_ISBN :
978-1-4244-7616-9
DOI :
10.1109/ICISE.2010.5688897