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Goodput analysis and link adaptation for IEEE 802.11a wireless LANs
Abstract
Link adaptation to dynamically select the data transmission rate at a given time has been recognized as an effective way to improve the goodput performance of the IEEE 802.11 wireless local-area networks (WLANs). Recently, with the introduction of the new high-speed 802.11a physical layer (PHY), it is even more important to have a well-designed link adaptation scheme work with the 802.11a PHY such that its multiple transmission rates can be exploited. In this paper, we first present a generic method to analyze the goodput performance of an 802.11a system under the distributed coordination function (DCF) and express the expected effective goodput as a closed-form function of the data payload length, the frame retry count, the wireless channel condition, and the selected data transmission rate. Then, based on the theoretical analysis, we propose a novel MPDU (MAC protocol data unit)-based link adaptation scheme for the 802.11a systems. It is a simple table-driven approach and the basic idea is to preestablish a best PHY mode table by applying the dynamic programming technique. The best PHY mode table is indexed by the system status triplet that consists of the data payload length, the wireless channel condition, and the frame retry count. At runtime, a wireless station determines the most appropriate PHY mode for the next transmission attempt by a simple table lookup, using the most up-to-date system status as the index. Our in-depth simulation shows that the proposed MPDU-based link adaptation scheme outperforms the single-mode schemes and the autorate fallback (ARF) scheme-which is used in Lucent Technologies' WaveLAN-II networking devices-significantly in terms of the average goodput, the frame drop rate, and the average number of transmission attempts per data frame delivery.
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Cited by
CoopMAC: A Cooperative MAC for Wireless LANs
Liu, P., Tao, Z., Narayanan, S., Korakis, T., & Panwar, S. (2007) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2007.070210 · Cited by 658
Learning and Adaptation in Cognitive Radios Using Neural Networks
Baldo, N., & Zorzi, M. (2008) · 2008 5th IEEE Consumer Communications and Networking Conference · doi:10.1109/ccnc08.2007.229 · Cited by 102
Metadata
- Authors
- Qiao, D., Choi, S., & Shin, K. G.
- Venue
- IEEE Transactions on Mobile Computing
- Published
- 2002-10
- Volume
- 1
- Issue
- 4
- Pages
- 278-292
- ISSN
- 1536-1233 (ISSN-L)
- 1558-0660
- 2161-9875
- OpenAlex
- W2141273556
- Cited by
- 560
- References
- 0
- FWCI
- 30.74
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Goodput analysis and link adaptation for IEEE 802.11a wireless LANs. https://app.cochat.ai/papers/10.1109/tmc.2002.1175541
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- Qiao, D., Choi, S., & Shin, K. G. (2002). Goodput analysis and link adaptation for IEEE 802.11a wireless LANs. IEEE Transactions on Mobile Computing. https://doi.org/10.1109/tmc.2002.1175541
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