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

Abstract

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.

Refrain

“…Specifically, Q-REFRAIN assumes that PPI is always detected, thus trying null frame handshake prior to every data transmission. 12 Results: We rebuild the experimental setup in Figures 1(a) and 7(a), and compare the performance of Q-REFRAIN with baseline 802.11. Figure 13 shows the results for the two-BSS scenario, where three stations are all active.…”

“…Real Wi-Fi devices have slightly different settings of RXSens and ED threshold[12] depending on their implementation. However, preamble-passing arises from the intrinsic disparity between the two CS thresholds, thus not being a device-specific phenomenon.…”

Situation-Awareness Interactive Self-Check-in Services by Smartphones and Smart Locks

“…As sensors are widely used, the advances in the sensor technologies are profound and the power of microcontrollers gets stronger (J. Wilmsdorff, J. Kolf, A. Kuijper, 2022, T. Kalsoom, N. Ramzan, S. Ahmed, and M. Ur-Rehman, 2020, G. Baluyot, S. Chen, J. Villaverde, D. Chung, 2019, P. Poudel, B. Ray, A. Milenkovic, 2021), various devices can become connected one to another wirelessly and they behave intelligently in response to the change of (surrounding) data states (J. Xiao, H. Li, M. Wu, H. Jin, M. Deen, J. Cao, 2023, L. Xin, J. Becker, S. Gvozdenovic, D. Starobinski, 2019, T. Renzler, M. Spork, C. Boano, K. Romer, 2018. One of such devices is a smart lock.…”