Testbed to Study the Capture Effect: Can We Rely on this Effect in Modern Wi-Fi Networks

Khorov, Evgeny; Kureev, Aleksey; Levitsky, Ilya; Lyakhov, Andrey

doi:10.1109/blackseacom.2018.8433688

Cited by 15 publications

(9 citation statements)

References 6 publications

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“…This confirms a recent finding by Khorov et al[11], who identified the body capture effect in the similar, but not identical, AR9485.…”

supporting

confidence: 91%

“…Notably, among the four different Wi-Fi cards tested, capture of the preamble varies by as much as 7 s in terms of the delay offset. The experiments further show that some Wi-Fi cards exhibit body capture effects while others do not, thus crossvalidating findings from [11].…”

Section: Discussionsupporting

confidence: 66%

“…In [11], Khorov et al present a Wi-Fi testbed for investigating the capture effect. The testbed generates two data streams on the application layer, and processes them in parallel USRP transmission chains before sending them out over two antennas, generating a packet collision over-the-air.…”

Section: Benchmarking and Testbedsmentioning

confidence: 99%

“…Finally, all aforementioned papers except [11] focus on evaluating the behavior of a single type of Wi-Fi card (chipset). In contrast, we compare the behaviors of multiple cards and show that they vary significantly.…”

Section: Capture Effectmentioning

confidence: 99%

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Benchmarking the Physical Layer of Wireless Cards using Software-Defined Radios

Xin

Becker

Gvozdenovic

et al. 2019

Proceedings of the 22nd International ACM Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems

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Many performance characteristics of wireless devices are fundamentally influenced by their vendor-specific physical layer implementation. Yet, characterizing the physical layer behavior of wireless devices usually requires complex testbeds with expensive equipment, making such behavior inaccessible and opaque to the end user. In this work, we propose and implement a new testbed architecture for software-defined radio-based wireless device performance benchmarking. The testbed is capable of accessing and measuring physical layer protocol features of real wireless devices. The testbed further allows tight control of timing events, at a microsecond time granularity. Using the testbed, we measure the receiver sensitivity and signal capture behavior of Wi-Fi devices from different vendors. We identify marked differences in their performance, including a variation of as much as 20 dB in their receiver sensitivity. We further assess the response of the devices to truncated packets and show that this procedure can be employed to fingerprint the devices. CCS CONCEPTS• Networks → Network performance analysis; Mobile and wireless security; Wireless local area networks; • Hardware → Analog, mixed-signal and radio frequency test.

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“…This confirms a recent finding by Khorov et al[11], who identified the body capture effect in the similar, but not identical, AR9485.…”

supporting

confidence: 91%

Section: Discussionsupporting

confidence: 66%

Section: Benchmarking and Testbedsmentioning

confidence: 99%

Section: Capture Effectmentioning

confidence: 99%

See 2 more Smart Citations

Benchmarking the Physical Layer of Wireless Cards using Software-Defined Radios

Xin

Becker

Gvozdenovic

et al. 2019

Proceedings of the 22nd International ACM Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems

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show abstract

“…We also show the results for the Large Area and Two Groups cases, when the frame body capture effect is enabled. Capture effect is a phenomenon observed in some receivers [ 18 ], when an STA receiving two partially overlapping frames switches to a stronger one even if it is already receiving the weaker one. In our simulation, we considered that the switch happens if the power difference at the receiver is at least 10 dB.…”

Section: Resultsmentioning

confidence: 99%

What Is the Fastest Way to Connect Stations to a Wi-Fi HaLow Network?

Bankov

Khorov

Lyakhov

et al. 2018

Sensors

Self Cite

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Wi-Fi HaLow is an adaptation of the widespread Wi-Fi technology for the Internet of Things scenarios. Such scenarios often involve numerous wireless stations connected to a shared channel, and contention for the channel significantly affects the performance in such networks. Wi-Fi HaLow contains numerous solutions aimed at handling the contention between stations, two of which, namely, the Centralized Authentication Control (CAC) and the Distributed Authentication Control (DAC), address the contention reduction during the link set-up process. The link set-up process is special because the access point knows nothing of the connecting stations and its means of control of these stations are very limited. While DAC is self-adaptive, CAC does require an algorithm to dynamically control its parameters. Being just a framework, the Wi-Fi HaLow standard neither specifies such an algorithm nor recommends which protocol, CAC or DAC, is more suitable in a given situation. In this paper, we solve both issues by developing a novel robust close-to-optimal algorithm for CAC and compare CAC and DAC in a vast set of experiments.

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Coordinated Allocation of Radio Resources to Wi-Fi and Cellular Technologies in Shared Unlicensed Frequencies

et al. 2021

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Wireless connectivity is essential for industrial production processes and workflow management. Moreover, the connectivity requirements of industrial devices, which are usually long-term investments, are diverse and require different radio interfaces. In this regard, the 3GPP has studied how to support heterogeneous radio access technologies (RATs) such as Wi-Fi and unlicensed cellular technologies in 5G core networks. In some cases, these technologies coexist in the same spectrum. Dynamic spectrum sharing (DSS), which has already been proven to increase spectrum efficiency in licensed bands, can also be applied to this scenario. In this paper, we propose two solutions for mobile network operators (MNOs) or service providers to dynamically divide (multiplex) the radio resources of a shared channel between a Wi-Fi basic service set (BSS) and one or several carriers of scheduled wireless networks, such as cellular technologies, with a configurable level of sharing granularity. These solutions do not require modifications to the current commercial off-the-shelf (COTS) end devices. We adapt the existing IEEE 802.11 procedures to notify the Wi-Fi stations that they must share channels with different access networks. We demonstrate that our dynamic sharing proposals are also advantageous over direct coexistence and evaluate each of them quantitatively and qualitatively to determine when one or the other is preferable. The evaluation is particularized for IEEE 802.11ac and long-term evolution (LTE) license assisted access (LAA), but the solutions can be easily extended to 5G new radio-unlicensed (5G NR-U) or to any other wireless technology in which the network side schedules end device transmissions.

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Testbed to Study the Capture Effect: Can We Rely on this Effect in Modern Wi-Fi Networks

Cited by 15 publications

References 6 publications

Benchmarking the Physical Layer of Wireless Cards using Software-Defined Radios

Benchmarking the Physical Layer of Wireless Cards using Software-Defined Radios

What Is the Fastest Way to Connect Stations to a Wi-Fi HaLow Network?

Coordinated Allocation of Radio Resources to Wi-Fi and Cellular Technologies in Shared Unlicensed Frequencies

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