System Error Calibration in Large Datasets of Wireless Channel Sounding for Industrial Applications

Published

September 30, 2020

Author(s)

Qi Wang, Rick Candell, Zhibo Pang, Wei Liang

Abstract

The large comprehensive microwave wireless channel impulse response (CIR) reference dataset, measured by National Institute of Standards and Technology (NIST), has been a useful tool for industrial applications. While extensive and high-fidelity, two types of system errors have been discovered within the dataset, record clock glitch and carrier frequency offset. To calibrate the CIR, a channel sounder error calibration method (CSEC) is proposed. Two CSEC methods are proposed to compensate for system errors. One method is CSEC based on phase estimation and correction. Another CSEC method is on carrier frequency offset recovery. The L1-norm distance metric is deployed to measure the difference among CIRs and evaluate the performance of the CSEC. To demonstrate the consequence of these systemic errors, a case study involving physical layer user authentication is investigated showing a marked improvement in authentication accuracy after the systemic errors in the dataset are removed. Our results reveal that the accuracy of the CIR in the NIST reference dataset is noticeably improved by the CSEC. Moreover, the CSEC method may be used to correct other wireless channel sounder datasets with similar systemic errors.

Citation

IEEE JOURNAL OF EMERGING AND SELECTED TOPICS IN INDUSTRIAL ELECTRONICS

Pub Type

Journals

Download Paper

https://doi.org/10.1109/JESTIE.2021.3122839

Local Download

Keywords

industrial wireless communication, error calibration, NIST wireless sounding dataset, channel sounding, channel impulse response, synchronization

Citation

Wang, Q. , Candell, R. , Pang, Z. and Liang, W. (2020), System Error Calibration in Large Datasets of Wireless Channel Sounding for Industrial Applications, IEEE JOURNAL OF EMERGING AND SELECTED TOPICS IN INDUSTRIAL ELECTRONICS, [online], https://doi.org/10.1109/JESTIE.2021.3122839, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=930613 (Accessed October 9, 2025)