Feature Extraction and Classification for Communication Channels in Wireless Mechatronic Systems

Published

August 24, 2021

Author(s)

Jing Geng, Mohamed Hany, Rick Candell, Yongkang Liu, Karl Montgomery, Shuvra Bhattacharyya

Abstract

For accurate characterization and evaluation of wireless mechatronic systems, effective modeling of wireless communication channels is of paramount importance, especially to simulation-oriented methods. Conventional simulation methods employ mathematical models to abstract details of prototype channels. Although such mathematical models often have rigorous theoretical underpinnings, they can be weak in capturing complex environmental characteristics and complex forms of diversity that are exhibited in industrial communication environments. To address this problem, we develop, in this paper, a new approach to deriving effective simulation models for industrial communication channels. Our approach involves field measurements from actual wireless mechatronic environments together with feature extraction from the measurements, and data-driven classification based on the extracted features. Our approach leads to a general framework for simulating wireless mechatronic systems in a way that realistically incorporates the complex channel characteristics of these systems.

Conference Dates

June 9-11, 2021

Conference Location

Linz, AT

Conference Title

17th IEEE International Conference on Factory Communication Systems (WFCS)

Pub Type

Conferences

Download Paper

https://doi.org/10.1109/WFCS46889.2021.9483590

Local Download

Keywords

Industrial wireless, feature extraction, communication channels

Citation

Geng, J. , Hany, M. , Candell, R. , Liu, Y. , Montgomery, K. and Bhattacharyya, S. (2021), Feature Extraction and Classification for Communication Channels in Wireless Mechatronic Systems, 17th IEEE International Conference on Factory Communication Systems (WFCS), Linz, AT, [online], https://doi.org/10.1109/WFCS46889.2021.9483590, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=932629 (Accessed October 9, 2025)