Novel Machine Learning-Based Identification and Mitigation of 5G Interference for Radar Altimeters

Amaireh, Anas; Zhang, Yan

doi:10.1109/access.2024.3432833

IEEE Access

2024

DOI: 10.1109/access.2024.3432833

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Novel Machine Learning-Based Identification and Mitigation of 5G Interference for Radar Altimeters

Anas Amaireh,

Yan Zhang

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2024

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Cited by 2 publications

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Analysis of Electromagnetic Interference Effects of 5G Signals on Radio Altimeters

Duan,

Xu,

et al. 2024

Aerospace

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An analytical method is introduced to assess the susceptibility of radio altimeter (RA) receivers to adjacent-band fifth-generation (5G) signal interference and to quantify its impact on RA performance. The power-series method is employed to analyze the intermediate frequency (IF) signal gain compression effect of 5G signal interference on RA receivers. A behavioral-level simulation model of the RA receiver’s radio frequency (RF) front-end is constructed based on the advanced design system (ADS), and a 5G signal injection simulation is performed. The simulation results indicate that 5G signals can induce nonlinear effects in the RF front-end circuit of the RA, leading to IF signal gain compression, thereby affecting the subsequent signal processing of RA receivers. The interference effect on the RA receiver is influenced by factors such as the power and frequency of the 5G interference signal. To investigate this, an interference injection test was conducted on a specific RA receiver to validate the aforementioned interference mechanisms. The test results indicate that when the average power of the injected 5G signal at a frequency of 4000 MHz reaches −16 dBm, the IF signal power is significantly reduced. As the power of the 5G signal increases, this nonlinear effect becomes more pronounced. Furthermore, the height error ratio significantly increases, with consistent trends observed across different test frequencies. The interference threshold for the RA is lower when the signal frequency is closer to the RA operational signal frequency. Our research results demonstrate the efficacy of this method, providing a reference basis for studies on interference mechanisms and the evaluation of interference effects related to RA receivers within the electromagnetic environment of 5G signals.

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Analysis of Electromagnetic Interference Effects of 5G Signals on Radio Altimeters

Duan,

Xu,

et al. 2024

Aerospace

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Interference Mitigation in B5G Network Architecture for MIMO and CDMA: State of the Art, Issues, and Future Research Directions

Yang,

Qamar,

Kazmi

et al. 2024

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The emergence of Beyond 5G (B5G) networks introduces novel challenges related to interference management, particularly within the context of Multiple-Input, Multiple-Output (MIMO) and Code Division Multiple Access (CDMA) technologies. In this comprehensive review paper, we delve into the intricacies of interference mitigation techniques within the B5G framework, with a specific focus on MIMO and CDMA systems. Firstly, we provide a brief overview of MIMO and CDMA principles, emphasizing their significance in B5G networks. MIMO leverages spatial diversity by employing multiple antennas in both the transmitter and the receiver, thereby enhancing capacity and reliability. CDMA, on the other hand, enables multiple users to share the same frequency band by assigning unique codes to each user. Next, we categorize the various types of interference encountered in MIMO and CDMA systems. These include co-channel interference, adjacent-channel interference, and multiuser interference. Understanding these interference sources is crucial for designing effective mitigation strategies. Our exploration of interference mitigation techniques covers state-of-the-art approaches tailored for MIMO and CDMA scenarios. Lastly, we discuss future research directions in interference mitigation for B5G networks. This review paper provides valuable insights for researchers, practitioners, and network designers seeking to enhance the robustness and efficiency of B5G communication systems by effectively mitigating interference in MIMO and CDMA contexts.

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Novel Machine Learning-Based Identification and Mitigation of 5G Interference for Radar Altimeters

Cited by 2 publications

References 15 publications

Analysis of Electromagnetic Interference Effects of 5G Signals on Radio Altimeters

Analysis of Electromagnetic Interference Effects of 5G Signals on Radio Altimeters

Interference Mitigation in B5G Network Architecture for MIMO and CDMA: State of the Art, Issues, and Future Research Directions

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