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IEEE 802.11 rate adaptation: a practical approach

Published: 04 October 2004 Publication History

Abstract

Today, three different physical (PHY) layers for the IEEE 802.11 WLAN are available (802.11a/b/g); they all provide multi-rate capabilities. To achieve a high performance under varying conditions, these devices need to adapt their transmission rate dynamically. While this rate adaptation algorithm is a critical component of their performance, only very few algorithms such as Auto Rate Fallback (ARF) or Receiver Based Auto Rate (RBAR) have been published and the implementation challenges associated with these mechanisms have never been publicly discussed. In this paper, we first present the important characteristics of the 802.11 systems that must be taken into account when such algorithms are designed. Specifically, we emphasize the contrast between low latency and high latency systems, and we give examples of actual chipsets that fall in either of the different categories. We propose an Adaptive ARF (AARF) algorithm for low latency systems that improves upon ARF to provide both short-term and long-term adaptation. The new algorithm has very low complexity while obtaining a performance similar to RBAR, which requires incompatible changes to the 802.11 MAC and PHY protocol. Finally, we present a new rate adaptation algorithm designed for high latency systems that has been implemented and evaluated on an AR5212-based device. Experimentation results show a clear performance improvement over the algorithm previously implemented in the AR5212 driver we used.

References

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Agere systems. WaveLAN 802.11b chipset for Standard Form Factors; Preliminary Product Brief. December 2002.
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Atheros Commuincations. Atheros Wireless LAN 2.4/5-GHz 802.11a/b/g 108 Mbps Turbo Radio-on-a-Chip WLAN Networking Products and Technology Overview. < http://www.atheros.com/pt/index.html >, July 2004.
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G. Holland, N. Vaidya, and P. Bahl. A Rate-Adaptive MAC Protocol for Multi-Hop Wireless Networks. In Proceeding ACM MOBICOM, July 2001.
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M. Lacage, M. H. Manshaei, and T. Turletti. IEEE 802.11 Rate Adaptation: A Practical Approach. INRIA Research Report number 5208 < http://www.inria.fr/rrrt/rr -- 5208.html >, May 2004.
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Madwifi. Project Information. < http://sourceforge.net/projects/madwifi/>, July 2004.
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M. Manshaei and T. Turletti. Simulation-Based Performance Analysis of 802.11a Wireless LAN. In Proceeding of International Symposium on Telecommunications. IRAN-Isfahan, August 2003.
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      cover image ACM Conferences
      MSWiM '04: Proceedings of the 7th ACM international symposium on Modeling, analysis and simulation of wireless and mobile systems
      October 2004
      334 pages
      ISBN:1581139535
      DOI:10.1145/1023663
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      Published: 04 October 2004

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      Author Tags

      1. ARF
      2. IEEE 802.11
      3. MADWIFI
      4. PHY rate selection
      5. RBAR

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      • (2024)TravellingFL: Communication Efficient Peer-to-Peer Federated LearningIEEE Transactions on Vehicular Technology10.1109/TVT.2023.333289873:4(5005-5019)Online publication date: Apr-2024
      • (2024)Fast Packet Loss Inferring via Personalized Simulation-Reality DistillationIEEE Transactions on Mobile Computing10.1109/TMC.2023.3281725(1-10)Online publication date: 2024
      • (2024)Energy-adaptive Network Switching via Intra-device ScalingICC 2024 - IEEE International Conference on Communications10.1109/ICC51166.2024.10622926(2853-2858)Online publication date: 9-Jun-2024
      • (2023)Joint User Association and Wireless Scheduling with Smaller Time-Scale Rate Adaptation2023 21st International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)10.23919/WiOpt58741.2023.10349840(223-230)Online publication date: 24-Aug-2023
      • (2023)Machine Learning for Link Adaptation Problem Formulation in VANETs2023 17th International Conference on Telecommunication Systems, Services, and Applications (TSSA)10.1109/TSSA59948.2023.10366997(1-5)Online publication date: 12-Oct-2023
      • (2023)A Channel Selection Model Based on Trust Metrics for Wireless CommunicationsIEEE Transactions on Network and Service Management10.1109/TNSM.2023.327757820:4(4517-4527)Online publication date: Dec-2023
      • (2023)Application of Machine Learning for Link Adaptation in VANETs2023 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)10.1109/SOLI60636.2023.10425136(1-5)Online publication date: 11-Dec-2023
      • (2023)Research on adaptive rate algorithm in bee colony ad hoc network2023 3rd International Conference on Neural Networks, Information and Communication Engineering (NNICE)10.1109/NNICE58320.2023.10105796(690-693)Online publication date: 24-Feb-2023
      • (2023)Deployment-Friendly Link Adaptation in Wireless Local-Area Network Based on On-Line Reinforcement LearningIEEE Communications Letters10.1109/LCOMM.2023.332796427:12(3424-3428)Online publication date: Dec-2023
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