Channel Prediction Based Scheduling for Data Dissemination in VANETs

Fanhui Zeng, Rongqing Zhang, Xiang Cheng, Liuqing Yang

Research output: Contribution to journalArticlepeer-review

90 Scopus citations


In vehicular ad hoc networks (VANETs), cooperative data dissemination is a promising approach addressing the problem of limited connection time between vehicles and road side units. However, existing data dissemination strategies rely too much on real-time channel state information, resulting in high communication overhead and transmission delay. To reduce the communication overhead and thus enhance the system throughput, we propose a channel prediction based scheduling strategy for data dissemination in VANETs. The channel prediction is built upon the recursive least squares algorithm. With low computational complexity, our proposed strategy achieves high scheduling efficiency verified by simulations of transmission delay and system throughput under both urban and highway scenarios.

Original languageEnglish (US)
Article number7867848
Pages (from-to)1409-1412
Number of pages4
JournalIEEE Communications Letters
Issue number6
StatePublished - Jun 2017
Externally publishedYes

Bibliographical note

Funding Information:
This work was jointly supported by the National Natural Science Foundation of China (Grant No. 61622101 and 61571020), the Ministry National Key Research and Development Project under Grant 2016YFE0123100, the National 973 project (Grant No. 2013CB336700), the open research fund of the State Key Laboratory of Integrated Services Networks, Xidian University (Grant No. ISN18-14), and the National Science Foundation under grant number CNS-1343189.

Publisher Copyright:
© 2017 IEEE.


  • Channel prediction
  • data dissemination
  • vehicular ad hoc networks


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