NDLI: Historical Spectrum Sensing Data Mining for Cognitive Radio Enabled Vehicular Ad-Hoc Networks

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Historical Spectrum Sensing Data Mining for Cognitive Radio Enabled Vehicular Ad-Hoc Networks

Content Provider	IEEE Xplore Digital Library
Author	Xin-Lin Huang Jun Wu Wenfeng Li Zhifeng Zhang Fusheng Zhu Minghao Wu
Copyright Year	2004
Abstract	In vehicular ad-hoc network (VANET), the reliability of communication is associated with driving safety. However, research shows that the safety-message transmission in VANET may be congested under some urgent communication cases. More spectrum resource is an effective way to solve transmission congestion. Hence, we introduce cognitive radio (CR) enabled VANET (CR-VANET), where CR device can detect possible idle spectrum for VANET communications and assist to timely broadcast safety-message. Given high-speed mobility of vehicles and dynamically-changing availability of channels, a novel prediction algorithm is proposed to pick out the channel with the greatest probability of availability, which can meet the quality of service (QoS) requirement of urgent communications and effectively avoid conflict with licensed users. Specifically, the spatiotemporal correlations among historical spectrum sensing data are exploited to form prior knowledge of channel availability probability, and Bayesian inference is used to derive posterior probability of channel availability. Comparing with other spectrum detection methods, the proposed algorithm has more than 8 percent detection performance improvement at false alarm probability 0.2, and thus can avoid access conflict with licensed users dramatically. Furthermore, the proposed algorithm always has larger packet reception probability (PRP) and lower transmission delay compared with conventional VANET broadcasting. Hence, the proposed algorithm can improve reliability of safety-message transmission and enhance driving safety significantly.
Sponsorship	IEEE Computer Society
Starting Page	59
Ending Page	70
Page Count	12
File Size	2241822
File Format	PDF
ISSN	15455971
Volume Number	13
Issue Number	1
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2016-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Sensors Vehicles Roads Hidden Markov models Vehicular ad hoc networks Data mining Data models Channel availability prediction Vehicular ad-hoc networks Cognitive radio data mining cognitive radio channel availability prediction spectrum sensing
Content Type	Text
Resource Type	Article
Subject	Computer Science Electrical and Electronic Engineering

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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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