A novel approach to channel profiling using the frequency selectiveness of WiFi CSI samples

Aryan Sharma, Deepak R. Mishra, Tanveer Zia, Aruna Prasad Seneviratne

Research output: Book chapter/Published conference paperConference paperpeer-review

5 Citations (Scopus)


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 Or-thogonal 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.
Original languageEnglish
Title of host publicationGLOBECOM 2020 - 2020 IEEE Global Communications Conference
Number of pages6
ISBN (Electronic)9781728182988
ISBN (Print)9781728182995
Publication statusPublished - 25 Jan 2021
Event2020 IEEE Global Communications Conference: GLOBECOM 2020 - Taipei International Convention Center (TICC) and via virtual platform, Taipei, Taiwan, Province of China
Duration: 07 Dec 202011 Dec 2020
https://ieeexplore.ieee.org/xpl/conhome/9322055/proceeding (proceedings)
https://globecom2020.ieee-globecom.org/ (conference website)

Publication series

NameIEEE Conference and Exhibition on Global Telecommunications (GLOBECOM)
ISSN (Print)1930-529X
ISSN (Electronic)2576-6813


Conference2020 IEEE Global Communications Conference
Abbreviated titleCommunications for Human and Machine Intelligence
Country/TerritoryTaiwan, Province of China
Internet address


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