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CSI Data Collection

CSI data collection is the first step toward the implementation of a practical wireless sensing system. This section introduces one of the most famous Wi-Fi sensing datasets, the Widar3 dataset, so that beginners can quickly get start with wireless sensing with minimal effort. This section also introduces three of the most famous CSI collection tools that researchers can use to try out collecting CSI data with COTS NICs

Widar3 Dataset​

Open datasets are essential to provide comprehensive knowledge for model training and a unified benchmark for model comparison. Open datasets are even more necessary in the wireless sensing field because RF signals are more sensitive to devices and deployment environments. However, the absence of high-quality and large-scale datasets has become the bottleneck that hindered the progress of wireless sensing technology. Existing wireless sensing datasets suffer from small scales and limited scenarios in 2019 when we started to build the Widar3 dataset. Widar37 is a wireless sensing dataset for human activity recognition. It is collected from commodity Wi-Fi NICs in the form of RSSI and CSI. It consists of 258,000 instances of hand gestures with a duration of 8,620 minutes and from 75 domains. Widar3 is so far the largest and most comprehensive dataset in this field and receives widespread attention from researchers all over the world. Widar3 dataset is publicly available at IEEE DataPort (official data repository) and continues evolving to contain more types of activities.

PicoScenes Platform​

PicoScenes 1 is a versatile and powerful middleware for CSI-based Wi-Fi sensing research. It is one of the very few tools that support the latest 802.11ac/ax protocols. It supports many prevalent commercial NICs, including Qualcomm Atheros AR9300 (QCA9300), Intel Wireless Link 5300 (IWL5300), Intel AX200 and Intel AX210. PicoScenes supports up to 27 NICs to work concurrently for packet injection and CSI measurement.

PicoScenes is architecturally versatile and flexible. It encapsulates all the low-level features into unified and hardware-independent APIs and exposes them to the upper-level plugin layer. As a result, users can quickly prototype their own measurement plugins.

The data reported by PicoScenes can be parsed in MATLAB as a struct, containing the CSI data of different packets, subcarriers, and antennas. The struct also includes other helpful information such as timestamps, RSSI, and the signal-to-noise ratio (SNR).

The homepage2 of this tool can be accessed for more detailed information.

Intel 5300 NIC CSI Tool​

This CSI Tool 3 is built upon the Intel WiFi Wireless Link 5300 802.11n MIMO radios, using a modified firmware and the open-source Linux wireless driver. It includes all the software and scripts required to collect, read, and parse CSI.

The IWL5300 provides 802.11n CSI of 30 subcarrier groups. Each group contains 2 adjacent subcarriers given 20 MHz bandwidth or 4 given 40 MHz bandwidth. Each CSI sample is a complex number, with a signed 8-bit resolution for both real and imaginary parts. One CSI record is a A×30A \times 30 matrix, where MM is the number of pairs of transmitting and receiving antennas.

The homepage4 of this tool can be accessed for detailed information.

Atheros CSI Tool​

Atheros CSI Tool 5 is an open-source 802.11n measurement and experimentation tool. It enables the extraction of detailed PHY wireless communication information from the Atheros WiFi NICs, including the Channel State Information (CSI), the received packet payload, and other information (the time stamp, the RSSI of each antenna, the data rate, \etc). Atheros-CSI-Tool is built on top of ath9k, an open-source Linux kernel driver supporting Atheros 802.11n PCI/PCI-E chips. Thus, this tool theoretically supports all types of Atheros 802.11n WiFi chipsets. We have tested it on Atheros AR9580, AR9590, AR9344, and QCA9558. Furthermore, Atheros CSI Tool is open source, and all functionalities are implemented in software without any modification to the firmware. Therefore, one can extend the functionalities of Atheros CSI Tool with their own codes under the GPL license.

Atheros-CSI-Tool works on various Linux distributions, \eg, Ubuntu, OpenWRT, Linino, \etc. Different Linux distribution works with different hardware. Ubuntu works for personal computers like laptops or desktops. OpenWRT works for embedded devices such as WiFi routers. Linino works for IoT devices, such as Arduino YUN. The official website provides the source code for the Ubuntu version and OpenWRT version of the Atheros CSI tool.

The homepage6 of this tool can be accessed for detailed information.

  1. Widar3 Dataset↩
  2. Zhiping Jiang, Tom H Luan, Xincheng Ren, Dongtao Lv, Han Hao, Jing Wang, Kun Zhao, Wei Xi, Yueshen Xu, and Rui Li. 2021. Eliminating the Barriers: Demystifying Wi-Fi Baseband Design and Introducing the PicoScenes Wi-Fi Sensing Platform. IEEE Internet of Things Journal (2021).↩
  3. PicoScenes Platform↩
  4. Daniel Halperin, Wenjun Hu, Anmol Sheth, and David Wetherall. 2011. Tool release: Gathering 802.11 n traces with channel state information. ACM SIGCOMM computer communication review (2011).↩
  5. CSI Tool↩
  6. Yaxiong Xie, Zhenjiang Li, and Mo Li. 2018. Precise power delay profiling with commodity Wi-Fi. IEEE Transactions on Mobile Computing (2018).↩
  7. Atheros CSI Tool↩