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20242026
most citedOn the Robustness of Deep Learning-aided Symbol Detectors to Varying Conditions and Imperfect Channel Knowledge

4 citations · 6 across the 9 of their papers we have counts for

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eess.SP2024★ 1 cited

Modified Baum-Welch Algorithm for Joint Blind Channel Estimation and Turbo Equalization

Chin-Hung Chen, Boris Karanov, Ivana Nikoloska +3

Blind estimation of intersymbol interference channels based on the Baum-Welch (BW) algorithm, a specific implementation of the expectation-maximization (EM) algorithm for training…

cs.IT2024

Turbo Receiver Design for Differentially Encoded PSK in Bursty Impulsive Noise Channels

Chin-Hung Chen, Boris Karanov, Wim van Houtom +2

It has been recognized that the impulsive noise (IN) generated by power devices poses significant challenges to wireless receivers. In this paper, we comprehensively assess the ach…

eess.SP2024

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

Chin-Hung Chen, Wen-Hung Huang, Boris Karanov +3

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…

cs.IT2024★ 1 cited

Data-Driven Symbol Detection for Intersymbol Interference Channels with Bursty Impulsive Noise

Boris Karanov, Chin-Hung Chen, Yan Wu +2

We developed machine learning approaches for data-driven trellis-based soft symbol detection in coded transmission over intersymbol interference (ISI) channels in presence of burst…

cs.IT2024★ 4 cited

On the Robustness of Deep Learning-aided Symbol Detectors to Varying Conditions and Imperfect Channel Knowledge

Chin-Hung Chen, Boris Karanov, Wim van Houtum +3

Recently, a data-driven Bahl-Cocke-Jelinek-Raviv (BCJR) algorithm tailored to channels with intersymbol interference has been introduced. This so-called BCJRNet algorithm utilizes…