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An Optimal Channel Bonding Strategy for IEEE 802.11be

  • Northwestern Polytechnical University Xian

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Although there are a large number of available channels that can be bonded together for data transmission in the next generation WLAN, i.e., IEEE 802.11be protocol, it may cause long data transmission time to transmit large files due to the inefficient channel bonding strategies. This paper proposes an optimal channel bonding strategy based on the optimal stopping theory. Firstly, under the constraint of the number of available channels, the problem of minimizing the transmission time of large files is formulated as an optimal stopping problem, where the time duration of large file transmission is defined as the sum of channel accessing time and data transmission time after successful access into the channel, Secondly, the threshold of successful bonded channel number is derived based on the optimal stopping theory. When the channel access is successful, data transmission is performed if the number of bondable channels is larger than the threshold. Otherwise this data transmission opportunity is dropped and channel competition is resumed. The simulation results show that, compared with the traditional EDCA if access-success then-transmit strategy and the fixed bonding channel number threshold strategy, the data transmission completion time of large file is shortened by more than 40%.

源语言英语
主期刊名Smart Grid and Internet of Things - 4th EAI International Conference, SGIoT 2020, Proceedings
编辑Yi-Bing Lin, Der-Jiunn Deng
出版商Springer Science and Business Media Deutschland GmbH
453-467
页数15
ISBN(印刷版)9783030695132
DOI
出版状态已出版 - 2021
活动4th EAI International Conference on Smart Grid and Internet of Things, SGIoT 2020 - TaiChung, 中国台湾
期限: 5 12月 20206 12月 2020

出版系列

姓名Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
354
ISSN(印刷版)1867-8211
ISSN(电子版)1867-822X

会议

会议4th EAI International Conference on Smart Grid and Internet of Things, SGIoT 2020
国家/地区中国台湾
TaiChung
时期5/12/206/12/20

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