Interference mitigation in satellite–5G coexistence using CNN-based interference classification and power control

Parveen, Nagma and Abdullah, Khaizuran (2026) Interference mitigation in satellite–5G coexistence using CNN-based interference classification and power control. IFAC Journal of Systems and Control, 37 (NA). pp. 1-10. E-ISSN 2468-6018

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Abstract

The growing demand for wireless connectivity has increased pressure on shared spectrum, especially between satellite communication networks and emerging 5G systems. When these signals operate close to one another frequently, noticeable interference may occur and reduce signal quality. This study explores a deep learning-based interference mitigation approach that combines spectrogram-driven CNN classification with adaptive power control. The CNN model identifies three transmission cases satellite-only, terrestrial-only, and coexistence and achieved accuracy close to 98% during testing. Using the classification output, an adaptive power strategy was applied, resulting in an improvement in SINR from roughly 10 dB to over 27 dB under coexistence conditions. A feedforward neural network supported by a genetic algorithm was also used to fine-tune system parameters. The findings demonstrate that the proposed method strengthens terrestrial–satellite coexistence and offers a practical direction for interference control in future wireless systems.

Item Type:	Article (Journal)
Uncontrolled Keywords:	5G interference, satellite communication, deep learning, CNN, genetic algorithm, SINR optimization
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101 Telecommunication. Including telegraphy, radio, radar, television
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering Kulliyyah of Engineering > Department of Electrical and Computer Engineering
Depositing User:	Dr Khaizuran Abdullah
Date Deposited:	05 Aug 2026 15:24
Last Update:	05 Aug 2026 15:28
Queue Number:	2026-07-Q4470
URI:	http://irep.iium.edu.my/id/eprint/130458

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