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Edge Station Throughput Enhancement Method Based on Energy Detection Threshold and Transmission Power Joint Dynamic Adjustment

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Smart Grid and Internet of Things (SGIoT 2022)

Abstract

With the surge in demand for wireless traffic and network quality of service, wireless local area network (WLAN) has developed into one of the most important wireless networks affecting human life. In high density scenarios, large numbers of Access Point (APs) and Stations(STAs) will be deployed in a limited area, means large amount of signals will be overlapped and coverage between Basic Service Sets (BSSs), interference and collisions will become more severe, and if the sensitivity of edge STA detection channel is not enough, such as the energy detection (ED) threshold and reception sensitivity mismatch of STAs, edge STA’s throughput may slow down seriously. So in this paper, we propose an edge STA throughput enhancement method based on ED threshold and TXPower joint dynamic adjustment to solve the problem of edge STA deceleration caused by ED threshold and reception sensitivity mismatch. By appropriately adjusting the ED threshold and TXPower of the BSSs with deceleration edge STAs, improving the sensitivity of edge STAs detection channel, and opportunity of edge STA’s transmission packet is not greatly affected. Through the method of establishing mathematical model and simulation verification, it has great practical significance.

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Acknowledgements

This work was supported in part by the National Natural Science Foundations of CHINA (Grant No. 61871322, No. 61771390, and No. 61771392), and Science and Technology on Avionics Integration Laboratory and the Aeronautical Science Foundation of China (Grant No. 20185553035, and No. 201955053002).

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Correspondence to Mao Yang .

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Lan, F., Li, B., Yang, M., Yan, Z. (2023). Edge Station Throughput Enhancement Method Based on Energy Detection Threshold and Transmission Power Joint Dynamic Adjustment. In: Deng, DJ., Chao, HC., Chen, JC. (eds) Smart Grid and Internet of Things. SGIoT 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 497. Springer, Cham. https://doi.org/10.1007/978-3-031-31275-5_22

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  • DOI: https://doi.org/10.1007/978-3-031-31275-5_22

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  • Online ISBN: 978-3-031-31275-5

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