A Novel Approach to Channel Profiling Using the Frequency Selectiveness of WiFi CSI Samples

Abstract

Due to the increased proliferation of WiFi in public and private spaces, there is interest in exploiting WiFi for spatial monitoring. In this paper, we aim to characterize movement or objects in a channel using Channel State Information (CSI). Channel state information represents the degree to which a wireless signal has been attenuated and delayed, and hence we hope to characterize different objects and multipath channel characteristics from CSI. We place different static objects and moving humans in a channel and inspect the CSI for each channel condition. From the variations in CSI Amplitude we can accurately distinguish between a person walking, squatting, or standing still in the channel. To identify static objects, we present a novel approach by inspecting the CSI of different Orthogonal Frequency Division Multiplexing (OFDM) subcarriers. This paper makes a novel contribution, by observing frequency selective behavior of CSI for different channel stimuli. This can be used to improve channel detection accuracy.

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“…In this way, we are able to understand how signals of different frequencies are transformed by the same channel. In the same manner that different wavelengths of light are affected uniquely by physical medium, we expect that these varying frequency subcarriers will be uniquely attenuated and delayed by channel stimuli [31]. This will offer us insight into the channel composition.…”

“…Once pre-processing has been applied to CSI to accentuate human artefacts, ML is used to correlate features in CSI with corresponding changes in the channel. It has been shown that the CSI amplitude of different OFDM subcarrier frequencies can be exploited for profiling a static channel [29][30][31]. Applications that aim to profile static channels often use statistical features calculated on the CSI Amplitude profile across the domain of OFDM subcarriers [19,30].…”

“…Our data processing pipeline then uses a low-pass Finite Impulse Response (FIR) filter with an upper frequency of 5 Hz in order to attenuate the high frequency noise whilst preserving the CSI signal shape. Recent work, including our own [31], has shown correlation between the CSI amplitude profile across OFDM subcarriers and channel blockage [29]. We hence use statistical features that represent the distribution of CSI amplitudes across our OFDM subcarriers.…”