@inproceedings{dc398544b67849788709d8575b302e78,
title = "MPPSK Demodulation Based on Neural Network under Impulsive Noise",
abstract = "Artificial neural network (ANN) has been widely used in many different fields including wireless communications, and shows superior properties. A novel demodulation scheme based on ANN for M-ary position phase shift keying (MPPSK) is proposed in this paper, which can be used to demodulate strictly band limited MPPSK signal with impulsive noise. Although high-order MPPSK signal can increase spectral efficiency in long-waveform channel, the main lobe of the signal is limited by the antenna, which causes inter-symbol-interference (ISI) and energy loss. Therefore, the symbol error rate (SER) cannot meet the requirement of the system. This paper proposes a novel scheme based on ANN to solve interference caused by the antenna and impulsive noise. The simulations demonstrate that this scheme can improve demodulation performance significantly for low frequency MPPSK signal, compared with a common demodulation scheme.",
keywords = "Demodulation, Impulsive noise, MPPSK, Neural network",
author = "Tan Qiuyue and Zhao Ling",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2nd IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2019 ; Conference date: 20-01-2019 Through 22-01-2019",
year = "2019",
month = jan,
doi = "10.1109/ICEICT.2019.8846265",
language = "英语",
series = "Proceedings of 2019 IEEE 2nd International Conference on Electronic Information and Communication Technology, ICEICT 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "15--19",
booktitle = "Proceedings of 2019 IEEE 2nd International Conference on Electronic Information and Communication Technology, ICEICT 2019",
address = "美国",
}