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Register a new userBeacons in Dense Wi-Fi Networks: How to Befriend with Neighbors in the 5G World?
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Added by
Dmitry Bankov
Publication date
2019
fields
Informatics Engineering
and research's language is
English
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To address 5G challenges, IEEE 802.11 is currently developing new amendments to the Wi-Fi standard, the most promising of which is 802.11ax. A key scenario considered by the developers of this amendment is dense and overlapped networks typically present in residential buildings, offices, airports, stadiums, and other places of a modern city. Being crucial for Wi-Fi hotspots, the hidden station problem becomes even more challenging for dense and overlapped networks, where even access points (APs) can be hidden. In this case, user stations can experience continuous collisions of beacons sent by different APs, which can cause disassociation and break Internet access. In this paper, we show that beacon collisions are rather typical for residential networks and may lead to unexpected and irreproducible malfunction. We investigate how often beacon collisions occur, and describe a number of mechanisms which can be used to avoid beacon collisions in dense deployment. Specifically, we pay much attention to those mechanisms which are currently under consideration of the IEEE 802.11ax group.
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Ultra Reliable Low Latency Communications (URLLC) is an important challenge for the next generation wireless networks, which poses very strict requirements to the delay and packet loss ratio. Satisfaction is hardly possible without introducing additional functionality to the existing communication technologies. In the paper, we propose and study an approach to enable URLLC in Wi-Fi networks by exploiting an additional radio similar to that of IEEE 802.11ba. With extensive simulation, we show that our approach allows decreasing the delay by orders of magnitude, while the throughput of non-URLLC devices is reduced insignificantly.
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We show experimentally that workload-based AP-STA associations can improve system throughput significantly. We present a predictive model that guides optimal resource allocations in dense Wi-Fi networks and achieves 72-77% of the optimal throughput with varying training data set sizes using a 3-day trace of real cable modem traffic.
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We unveil the existence of a vulnerability in Wi-Fi, which allows an adversary to remotely launch a Denial-of-Service (DoS) attack that propagates both in time and space. This vulnerability stems from a coupling effect induced by hidden nodes. Cascading DoS attacks can congest an entire network and do not require the adversary to violate any protocol. We demonstrate the feasibility of such attacks through experiments with real Wi-Fi cards, extensive ns-3 simulations, and theoretical analysis. The simulations show that the attack is effective both in networks operating under fixed and varying bit rates, as well as ad hoc and infrastructure modes. To gain insight into the root-causes of the attack, we model the network as a dynamical system and analyze its limiting behavior. The model predicts that a phase transition (and hence a cascading attack) is possible when the retry limit parameter of Wi-Fi is greater or equal to 7, and explicitly characterizes the phase transition region in terms of the system parameters.
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