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Electrical Engineering and Systems Science > Signal Processing

arXiv:2405.10828 (eess)
[Submitted on 17 May 2024]

Title:Analysis of Impulsive Interference in Digital Audio Broadcasting Systems in Electric Vehicles

Authors:Chin-Hung Chen, Wen-Hung Huang, Boris Karanov, Alex Young, Yan Wu, Wim van Houtum
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Abstract:Recently, new types of interference in electric vehicles (EVs), such as converters switching and/or battery chargers, have been found to degrade the performance of wireless digital transmission systems. Measurements show that such an interference is characterized by impulsive behavior and is widely varying in time. This paper uses recorded data from our EV testbed to analyze the impulsive interference in the digital audio broadcasting band. Moreover, we use our analysis to obtain a corresponding interference model. In particular, we studied the temporal characteristics of the interference and confirmed that its amplitude indeed exhibits an impulsive behavior. Our results show that impulsive events span successive received signal samples and thus indicate a bursty nature. To this end, we performed a data-driven modification of a well-established model for bursty impulsive interference, the Markov-Middleton model, to produce synthetic noise realization. We investigate the optimal symbol detector design based on the proposed model and show significant performance gains compared to the conventional detector based on the additive white Gaussian noise assumption.
Comments: 44th Symposium on Information Theory and Signal Processing in the Benelux (SITB 2024), Delft, the Netherlands
Subjects: Signal Processing (eess.SP); Machine Learning (cs.LG)
Cite as: arXiv:2405.10828 [eess.SP]
  (or arXiv:2405.10828v1 [eess.SP] for this version)
  https://doi.org/10.48550/arXiv.2405.10828

Submission history

From: Chinhung Chen [view email]
[v1] Fri, 17 May 2024 14:48:37 UTC (405 KB)
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