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Environment Sensing Based Adaptive Acknowledgement and Backoff for the Next Generation WLAN

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Wireless Internet (WiCON 2019)

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Abstract

Wireless LAN (WLAN) developed quite fast over the last two decades, and the next generation WLAN standard: IEEE 802.11ax will be released in 2020. IEEE 802.11ax needs to improve the performance and user experience under the ultra-high-dense deployment of cells. Thus, the concept of spatial reuse (SR) is introduced in IEEE 802.11ax by enabling more communication links to simultaneously transmit. This paper proposes an environment sensing based link adaptation algorithm (ESBLA). ESBLA introduces intelligent environment sensing and identifies the environment into several types: nice environment, serious collision, and severe channel fading. After that, ESBLA adjust the media access control (MAC) layer transmission strategy according to the sensed environment type. The simulation results show that ESBLA can reduce the impact of intensive deployment interference as much as possible while guaranteeing high throughput.

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Acknowledgement

This work was supported in part by the National Natural Science Foundations of CHINA (Grant No. 61771390, No. 61871322, No. 61771392, No. 61271279, and No. 61501373), the National Science and Technology Major Project (Grant No. 2016ZX03001018-004), and Science and Technology on Avionics Integration Laboratory (20185553035).

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Correspondence to Mao Yang .

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© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Yan, Y., Li, B., Yang, M., Yan, Z. (2020). Environment Sensing Based Adaptive Acknowledgement and Backoff for the Next Generation WLAN. In: Deng, DJ., Pang, AC., Lin, CC. (eds) Wireless Internet. WiCON 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 317. Springer, Cham. https://doi.org/10.1007/978-3-030-52988-8_22

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  • DOI: https://doi.org/10.1007/978-3-030-52988-8_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-52987-1

  • Online ISBN: 978-3-030-52988-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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