Sunji Oh
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Sunji Oh has a total of 3 co-authors. Here are the top co-authors by number of shared publications:
- Byungkwan Kim
Chungnam National University
1 shared publication Hyeongwoo Kim
Radio and Information Communications Engineering, Chungnam National University, Daejeon, Republic of Korea
1 shared publication- Jinha Kim
Radio and Information Communications Engineering, Chungnam National University, Daejeon, Republic of Korea
1 shared publication
Latest Publications
- Open Access
- 28 August 2025
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Access
- Vol. PP, 1
Spectrum Anomaly Detection Using Deep Neural Networks: A Wireless Signal Perspective
In modern society, LTE and 5G communications serve as essential infrastructures, making the stability of communication networks a critical challenge. However, advancements in wireless communication devices and technologies can lead to the transmission of illegal signals, device malfunctions, and radio interference, potentially causing degradation of communication performance. This study proposes a wideband spectrum monitoring method for LTE and 5G communication bands used in cellular networks by utilizing object detection techniques, thereby ensuring stable network performance and security. The proposed network accounts for the temporal and frequency characteristics present in signals on the spectrogram and is designed to exhibit high detection performance even for low-power signals. It achieved an mean Average Precision(mAP)50 performance of 80% at an Interference Signal Ratio(ISR) of –10dB corresponding to low power and an overall mAP50 performance of 93%.
- 28 August 2025
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Access
- Vol. PP, 1
Open AccessSpectrum Anomaly Detection Using Deep Neural Networks: A Wireless Signal Perspective
In modern society, LTE and 5G communications serve as essential infrastructures, making the stability of communication networks a critical challenge. However, advancements in wireless communication devices and technologies can lead to the transmission of illegal signals, device malfunctions, and radio interference, potentially causing degradation of communication performance. This study proposes a wideband spectrum monitoring method for LTE and 5G communication bands used in cellular networks by utilizing object detection techniques, thereby ensuring stable network performance and security. The proposed network accounts for the temporal and frequency characteristics present in signals on the spectrogram and is designed to exhibit high detection performance even for low-power signals. It achieved an mean Average Precision(mAP)50 performance of 80% at an Interference Signal Ratio(ISR) of –10dB corresponding to low power and an overall mAP50 performance of 93%.