Abstract
Next-generation Wi-Fi systems embrace large signal bandwidth to achieve significantly improved data rates, while requiring efficient methods for network monitoring and spectrum sharing applications. A radio receiver (RX) operating at low sampling rates can largely improve the energy- and cost-efficiency in such systems if it can extract useful network information such as the duration and structure of wireless packets. In this paper, we present the design of Swirls, a novel framework for sniffing Wi-Fi Physical layer information using RXs operating at sampling rates that are (much) smaller than the signal bandwidth. Swirls consists of three modules tailored for low sampling rate RXs: joint packet detection, optimized RX frequency selection, and packet property decoder. We implement Swirls using three software-defined radio platforms and extensively evaluate Swirls in real-world scenarios. The experiments show that for 20/40 MHz 802.11n packets, Swirls with 5 MHz sampling rate can achieve a mean absolute error (MAE) of transmission time and physical service data unit length decoding of 0.06 ms and 1.91 kB, respectively, at only 10 dB signal-to-noise ratio. With the same setting, Swirls simultaneously achieves a classification accuracy for the modulation and coding scheme, number of spatial streams, and bandwidth of 95.3%, 96.1%, and 95.6%, respectively. In an extreme case for 160 MHz 802.11ac/ax packets, Swirls with 2.5 MHz sampling rate (i.e., a downsampling ratio of 64) can still achieve an MAE of transmission time decoding of 0.47/0.67 ms.
- Methodology
- Image
Overview and key modules of the proposed system, Swirls, for monitoring Wi-Fi PHY layer information using radios operating at sampling rates that are (much) smaller than the signal bandwidth.
- Results
Evaluation of SWIRLS using an SDR setup and an AP-SDR setup in a lab
ImageSWIRLS in the wild: simultaneous monitoring of 3 sets Wi-Fi channels using a USRP X310, a PlutoSDR, and an RTL-SDR, all operating at 2.5 MHz.
ImageDifferent SDR platforms used for the experimental evaluation of SWIRLS: USRP X310, PlutoSDR, and RTL-SDR. - Citation
@inproceedings{gao2023swirls,
title={Swirls: Sniffing {Wi-Fi} using radios with low sampling rates},
author={Gao, Zhihui and Chen, Yiran and Chen, Tingjun},
booktitle={Proc. ACM MobiHoc'23},
year={2023} }