Journal of Terahertz Science and Electronic Information Technology , Volume. 17, Issue 6, 959(2019)
Pattern recognition method of communication interference based on power spectrum density and neural network
Analysis and pattern recognition of the interference undergoing in the communication system can assist the self-adaptive adjustment of the communication system parameters, thereby the anti-jamming capability can be stronger and targeted. A wide-bandwidth communication system is researched. Previous research shows that multi-hidden-layer neural network can resolve any form of classification problems. In order to classify the five common interference patterns, a classification method which uses power spectrum density and two-hidden-layer neural networks is proposed. Simulation results show that, under different interference patterns and different Interference-Noise-Ratios(INR), the average recognition accuracy is above 99.6%. In all the other four interference patterns without comb-spectrum interference, the recognition accuracy is above 99.7%, while 98.4% in the comb-spectrum interference. The proposed method has relatively stable recognition ability, and can be applied to the detection of communication interference.
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ZHANG Zhibo, FAN Yaxuan, MENG Xiao. Pattern recognition method of communication interference based on power spectrum density and neural network[J]. Journal of Terahertz Science and Electronic Information Technology , 2019, 17(6): 959
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Received: Aug. 16, 2018
Accepted: --
Published Online: Feb. 24, 2020
The Author Email: Zhibo ZHANG (zhangzhibo94@qq.com)