@article{7e25bb09c6304394a5979ad25d5e87e8,
title = "A cross-layer adaptation scheme for improving IEEE 802.11e QoS by learning",
abstract = "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.",
keywords = "Adaptive algorithm, IEEE 802.11e wireless local area networks (WLAN), Neural networks (NNs), Quality of service (QoS)",
author = "Chiapin Wang and Lin, {Po Chiang} and Tsungnan Lin",
note = "Funding Information: Manuscript received May 29, 2006; revised July 1, 2006. This work was supported in part by Yulong Corporation under Grant 95-S-C01A and by Taiwan National Science Council under Grants 95-2219-E-002-018 and 95-2221-E-002-190.",
year = "2006",
month = nov,
doi = "10.1109/TNN.2006.883014",
language = "English",
volume = "17",
pages = "1661--1665",
journal = "IEEE Transactions on Neural Networks",
issn = "1045-9227",
publisher = "IEEE Computational Intelligence Society",
number = "6",
}