Bayesian Decision Algorithm for Symbol Diversity in a Three-Channel Redundant System Under Harsh Electromagnetic Disturbances

• Published in: IEEE transactions on electromagnetic compatibility Vol. 66; no. 5; pp. 1329 - 1338
• Main Authors: Gonzalez-Atienza, Miriam, Vanoost, Dries, Verbeke, Mathias, Pissoort, Davy
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.10.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive algorithms; Adaptive systems; Availability; Bayes methods; Bayesian analysis; Bayesian learning; Communications systems; Decision making; Disturbances; Electromagnetic interference; electromagnetic interference (EMI); Electronic systems; Modular systems; Printed circuits; Safety critical; symbol diversity; Symbols; triple modular redundant (TMR) system; Voltage measurement
• ISSN: 0018-9375; 1558-187X; 1558-187X
• DOI: 10.1109/TEMC.2024.3422619

As electronic systems increasingly take on safety-critical tasks, establishing strong and dependable communication becomes crucial for their correct operation. Any malfunction, potentially caused by disruptions such as electromagnetic (EM) interference, could compromise the integrity of the transmitted data and lead to severe consequences. This article presents an adaptive Bayesian decision algorithm designed to increase the certainty and reliability of the received data in challenging EM environments. The algorithm is designed to maintain a balance between the required level of certainty in the output and the system's availability. The method is validated on a symbol-diverse constellation transmitted through a triple modular redundant communication channel. A comparison with two different scenarios evaluates the algorithm's performance in terms of accuracy and availability. Compared to the baseline setup, the algorithm notably increases the accuracy by up to 40.25%. Furthermore, the comparative analysis highlights the algorithm's adaptability across various frequency combinations for EM disturbances.