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Big Data Analysis and Prediction of Electromagnetic Spectrum Resources: A Graph Approach

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成果类型:
期刊论文
作者:
Zhang, Han;Peng, Siqi;Zhang, Jingyu;Lin, Yun
通讯作者:
Yun Lin
作者机构:
[Peng, Siqi; Lin, Yun; Zhang, Han] Harbin Engn Univ, Coll Informat & Commun Engn, Harbin 150001, Peoples R China.
[Zhang, Jingyu] Changsha Univ Sci & Technol, Sch Comp & Commun Engn, Changsha 410004, Peoples R China.
通讯机构:
[Yun Lin] C
College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China<&wdkj&>Author to whom correspondence should be addressed.
语种:
英文
关键词:
spectrum resources;big data analysis and prediction;graph;spatial correlation;deep learning
期刊:
Sustainability
ISSN:
2071-1050
年:
2023
卷:
15
期:
1
页码:
508-
基金类别:
This work is supported by the National Natural Science Foundation of China (61771154) and the Fundamental Research Funds for the Central Universities (3072021CF0815). This work is also supported by the Key Laboratory of Advanced Marine Communication and Information Technology, Ministry of Industry and Information Technology, Harbin Engineering University, Harbin, China.
机构署名:
本校为其他机构
院系归属:
计算机与通信工程学院
摘要:
In the field of wireless communication, the increasing number of devices makes limited spectrum resources more scarce and accelerates the complexity of the electromagnetic environment, posing a serious threat to the sustainability of the industry's development. Therefore, new effective technical methods are needed to mine and analyze the activity rules of spectrum resources to reduce the risk of frequency conflict. This paper introduces the idea of graphs and proposes a spectrum resource analysis and prediction architecture based on big data. In this architecture, a spatial correlation model o...

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