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

Chia-Pin Wang, Po Chiang Lin, Tsungnan Lin

Research output: Contribution to journalArticle

18 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)1661-1665
Number of pages5
JournalIEEE Transactions on Neural Networks
Volume17
Issue number6
DOIs
Publication statusPublished - 2006 Nov 1

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Quality of service
Learning
Medium access control
Neural networks

Keywords

  • Adaptive algorithm
  • IEEE 802.11e wireless local area networks (WLAN)
  • Neural networks (NNs)
  • Quality of service (QoS)

ASJC Scopus subject areas

  • Software
  • Medicine(all)
  • Computer Science Applications
  • Computer Networks and Communications
  • Artificial Intelligence

Cite this

A cross-layer adaptation scheme for improving IEEE 802.11e QoS by learning. / Wang, Chia-Pin; Lin, Po Chiang; Lin, Tsungnan.

In: IEEE Transactions on Neural Networks, Vol. 17, No. 6, 01.11.2006, p. 1661-1665.

Research output: Contribution to journalArticle

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