2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information
Login Paper Search My Schedule Paper Index Help

My ICASSP 2021 Schedule

Note: Your custom schedule will not be saved unless you create a new account or login to an existing account.
  1. Create a login based on your email (takes less than one minute)
  2. Perform 'Paper Search'
  3. Select papers that you desire to save in your personalized schedule
  4. Click on 'My Schedule' to see the current list of selected papers
  5. Click on 'Printable Version' to create a separate window suitable for printing (the header and menu will appear, but will not actually print)

Paper Detail

Paper IDSPCOM-4.4
Paper Title KALMAN FILTER BASED MIMO CSI PHASE RECOVERY FOR COTS WIFI DEVICES
Authors Chu Li, Ruhr University Bochum, Germany; Jeremy Brauer, PHYSEC GmbH, Germany; Aydin Sezgin, Ruhr University Bochum, Germany; Christian Zenger, PHYSEC GmbH, Germany
SessionSPCOM-4: Channel Estimation for MIMO and Multiuser Systems
LocationGather.Town
Session Time:Thursday, 10 June, 15:30 - 16:15
Presentation Time:Thursday, 10 June, 15:30 - 16:15
Presentation Poster
Topic Signal Processing for Communications and Networking: [SPC-CHAN] Channel modelling and estimation
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract Recently channel state information (CSI) measurements from the commercial multi-input multi-output (MIMO) WiFi systems have been ubiquitously used for different wireless sensing applications. However, the phase of the CSI realizations is usually distorted severely by phase errors due to the hardware impairments, which significantly reduce the sensing performance. In this paper, we directly utilize the modeling of the phase distortions caused by the hardware impairments and propose an adaptive CSI estimation approach based on Kalman filter (KF) with maximum-a-posteriori (MAP) estimation that considers the CSI from the previous time. The performance of the proposed algorithm is compared against the Cramer–Rao lower bound (CRLB). Simulation and experimental results demonstrate that our approach can track the channel variations while eliminating the phase errors accurately.