Application of neural networks on rate adaptation in IEEE 802.11 WLAN with multiples nodes

Chiapin Wang*, Jungyi Hsu, Kucihsiang Liang, Ticntsung Tai

*此作品的通信作者

研究成果: 書貢獻/報告類型會議論文篇章

5 引文 斯高帕斯(Scopus)

摘要

The paper presents an adaptive Auto Rate Fallback (ARF) scheme to improve the performance of aggregate throughput in IEEE 802.11 Wireless Local Area Network (WLAN) with multiple nodes. When the number of contending nodes increases, using ARF will be likely to degrade transmission rates due to increasing packet collisions and can consequently cause a decline of the overall throughput. In this paper we propose a neural-network based adaptive ARF scheme which improves the throughput performance by dynamically adjusting the system parameters that determine the transmission rates according to the contention situations including the amount of contending nodes and traffic intensity. The performance of our scheme is evaluated and compared with that of other LA schemes by using the Qualnet simulator. Simulation results demonstrate the effectiveness of the propose algorithm to improve the performance of aggregate throughput in a variety of 802. 11 WLAN environments.

原文英語
主出版物標題Proceedings - 2010 3rd IEEE International Conference on Computer Science and Information Technology, ICCSIT 2010
頁面425-430
頁數6
DOIs
出版狀態已發佈 - 2010
事件2010 3rd IEEE International Conference on Computer Science and Information Technology, ICCSIT 2010 - Chengdu, 中国
持續時間: 2010 7月 92010 7月 11

出版系列

名字Proceedings - 2010 3rd IEEE International Conference on Computer Science and Information Technology, ICCSIT 2010
4

其他

其他2010 3rd IEEE International Conference on Computer Science and Information Technology, ICCSIT 2010
國家/地區中国
城市Chengdu
期間2010/07/092010/07/11

ASJC Scopus subject areas

  • 一般電腦科學
  • 電氣與電子工程

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