FM Broadcasting Monitoring Method Based on Time Series Analysis

被引：0
|
作者：
Lu, Yong Qiu [1 ]
Lu, Qian Nan [1 ]
Chen, De Zhang [2 ]
Yang, Jing Jing [1 ]
Zhang, Liu [1 ]
Huang, Ming [1 ]
机构：
[1] Yunnan Univ, Sch Informat Sci & Engn, Wireless Innovat Lab, Kunming 650091, Yunnan, Peoples R China
[2] Radio Monitoring Ctr Yunnan Prov, Kunming 650228, Yunnan, Peoples R China
来源：
2020 XXXIIIRD GENERAL ASSEMBLY AND SCIENTIFIC SYMPOSIUM OF THE INTERNATIONAL UNION OF RADIO SCIENCE | 2020年
基金：
中国国家自然科学基金;
关键词：
SPECTRUM; CHALLENGES;
D O I：
10.23919/ursigass49373.2020.9232178
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
With the development of modern wireless applications and the popularization of Artificial Intelligence (AI), the intelligentization of radio monitoring system is a development direction. In this context, in order to achieve an intelligent FM broadcasting monitoring, this paper implemented an algorithm which consists three steps. Firstly, occupied channel is searched based on energy detection. Then, Autoregressive Integrated Moving Average (ARIMA) model is adopted to predict the abnormality in the spectrum of FM broadcast. Thirdly, a completely-fully connected neural network is applied to classify the spectrum, to find whether it is authorized spectrum or the frequency bands are occupied by unauthorized users. Results show that the recognition rate for authorized and unauthorized user is 100% and 79%, respectively.
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收藏
页数：4
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