A cross-layer adaptation scheme for improving IEEE 802.11e QoS by learning

被引：12
|
作者：
Wang, Chiapin [1 ]
Lin, Po-Chiang
Lin, Tsungnan
机构：
[1] Natl Taiwan Univ, Grad Inst Commun Engn, Taipei 106, Taiwan
[2] Natl Taiwan Univ, Dept Elect Engn, Taipei 106, Taiwan
来源：
IEEE TRANSACTIONS ON NEURAL NETWORKS | 2006年 / 17卷 / 06期
关键词：
adaptive algorithm; IEEE 802.11e wireless local area networks (WLAN); neural networks (NNs); quality of service (QoS);
D O I：
10.1109/TNN.2006.883014
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this letter, we propose a cross-layer adaptation scheme which improves IEEE 802.11e quality of service (QoS) by online adapting multidimensional medium access control (MAC)-layer parameters depending on the application-layer QoS requirements and physical layer (PHY) channel conditions. Our solution is based on an optimization approach which utilizes neural networks (NNs) to learn the cross-layer function. Simulations results demonstrate the effectiveness of our adaptation scheme.
引用
收藏
页码：1661 / 1665
页数：5
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