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  • 标题:DYNAMIC CHANNEL AWARE NEIGHBOUR SWITCHING PATH OPTIMIZATION TECHNIQUE FOR VANETs
  • 本地全文:下载
  • 作者:J. Uma Maheswari ; S.Karishma ; C.Nivetha
  • 期刊名称:International Journal on Computer Science and Engineering
  • 印刷版ISSN:2229-5631
  • 电子版ISSN:0975-3397
  • 出版年度:2017
  • 卷号:9
  • 期号:05
  • 页码:242-247
  • 出版社:Engg Journals Publications
  • 摘要:Cognitive radio for Vehicular Ad hoc Networks is an emerging technology that offer functionalities for the transmission of intra-vehicular commands and dynamic access to wireless services, while the vehicle is in transit. 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. The sensing process is initiated with the channel probe and channel aware sensing. Historical sensing lacks channel detection and overhearing of channel probe which results in higher channel access time and higher transfer rate. To overcome the drawbacks of the spatio-temporal sensing, we propose Dynamic Channel State Information (CSI) based channel allocation using dual consideration of Lateration technique. In dynamic CSI, the status of the last used channel is updated forehand to the requesting users and Lateration based neighbor detection implies for the number of available vehicles. The integrated approach minimizes channel access delay and improves the transmission rate of the CR-VANET improving the optimal performance of the network.
  • 关键词:Vehicular ad-hoc networks; Cognitive radio; Channel availability prediction; Spectrum sensing; Data mining.
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