On the Design and Performance of QRD-Based Beamforming Feedback for Wi-Fi Sensing

Recently, channel state information (CSI) extracted from Wi-Fi signals has enabled a variety of Wi-Fi sensing applications beyond communications. However, the extraction of CSI relies on specific Wi-Fi devices, which severely limits the CSI-based sensing applications. In this paper, we exploit the beamforming matrix, a compressed version of CSI that is fed back from the beamformee to the beamformer without encryption, for Wi-Fi sensing. In order to recover more channel information from the beamforming matrix for sensing, a QR decomposition (QRD)-based beamforming feedback scheme is proposed in this paper. We analyze the effectiveness of the proposed QRD-based scheme in terms of sensing and communication performance. Simulation results show that the Doppler frequency shift, time of flight, angle of departure, as well as the amplitude information can be recovered using the proposed scheme and at the same time, the spectral efficiency of the proposed QRD-based scheme is comparable to that of the existing SVD-based scheme. We implement the proposed scheme on IEEE 802.11ac/ax based Wi-Fi devices. The experimental results on human respiration and finger tracking demonstrate that the proposed scheme works well for practical Wi-Fi sensing.