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When Next-Gen Sensing Meets Legacy Wi-Fi: Performance Analyses of IEEE 802.11bf and IEEE 802.11ax Coexistence

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arxiv 2503.04637 v1 pith:A7PSZDVR submitted 2025-03-06 cs.NI cs.SYeess.SY

classification cs.NIcs.SYeess.SY
keywords sensingieeecoexistencewi-fidelaylegacynetworknetworks
verification ladder T0 review T1 audit T2 compute T3 formal
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Sensing is emerging as a vital future service in next-generation wireless networks, enabling applications such as object localization and activity recognition. The IEEE 802.11bf standard extends Wi-Fi capabilities to incorporate these sensing functionalities. However, coexistence with legacy Wi-Fi in densely populated networks poses challenges, as contention for channels can impair both sensing and communication quality. This paper develops an analytical framework and a system-level simulation in ns-3 to evaluate the coexistence of IEEE 802.11bf and legacy 802.11ax in terms of sensing delay and communication throughput. Forthis purpose, we have developed a dedicated ns-3 module forIEEE 802.11bf, which is made publicly available as open-source. We provide the first coexistence analysis between IEEE 802.11bfand IEEE 802.11ax, supported by link-level simulation in ns-3to assess the impact on sensing delay and network performance. Key parameters, including sensing intervals, access categories, network densities, and antenna configurations, are systematically analyzed to understand their influence on the sensing delay and aggregated network throughput. The evaluation is further extended to a realistic indoor office environment modeled after the 3GPP TR 38.901 standard. Our findings reveal key trade-offs between sensing intervals and throughput and the need for balanced sensing parameters to ensure effective coexistence in Wi-Fi networks.

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  1. A Tutorial-cum-Survey on Self-Supervised Learning for Wi-Fi Sensing: Trends, Challenges, and Outlook

    eess.SP 2025-05 conditional novelty 4.0 of 10

    A tutorial-cum-survey that evaluates SimCLR, SimSiam, VICReg, and Barlow Twins on three Wi-Fi CSI datasets, reporting near-supervised accuracy on two datasets but poor accuracy on a third.

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