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Joint Energy Detection and Transmission Power Adjustment for FIM Problem in High Density WLANs

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Smart Grid and Internet of Things (SGIoT 2022)

Abstract

With the rapid development of mobile internet services, the intensive deployment of wireless local area network (WLAN) is inevitable. Traditional WLAN uses carrier sense/collision avoidance (CSMA/CA) mechanism to avoid interference between links as much as possible. In the multi access points (APs) scenario, the traditional CSMA/CA may lead to the flow in the middle (FIM) problem, resulting in a sharp reduction in the throughput of the intermediate nodes and affecting the fairness of the whole network. Existing researches have shown that the FIM problem is more serious in the high density WLAN network. The existing researches on the FIM problem mainly focus on the dynamic optimization of a single parameter, the fairness and performance of the network cannot be well guaranteed. Therefore, this paper proposes a FIM oriented down link (DL) multi-parameter joint dynamic control scheme. AP as a centralized controller, regularly obtains the transmission status of the whole network, reduces the transmission opportunities of the strong AP through adaptive dynamic power and energy detection threshold control (A-DPEC) algorithm, and improves the transmission opportunities of the starvation AP, so as to achieve the performance and fair balance of the whole network. The simulation results show that the proposed scheme outperforms the comparing schemes.

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Acknowledgement

This work was supported in part by the National Natural Science Foundations of CHINA (Grant No. 61871322, No. 61771392, and No. 61771390), 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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Wang, Y., Yang, Q., Yang, M., Yan, Z., Li, B. (2023). Joint Energy Detection and Transmission Power Adjustment for FIM Problem in High Density WLANs. 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_20

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  • DOI: https://doi.org/10.1007/978-3-031-31275-5_20

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-031-31275-5

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