# Radio Frequency Interference, Its Mitigation and Its Implications for the Civil Aviation Industry
## 3 Literature Review
The study highlights the advantages of frequency domain analysis, which accurately measures signal strength across frequencies. Using a spectrum analyzer, maintenance personnel can evaluate the spectral distribution of signals, identifying frequency, power, harmonic components, and noise. This method enhances ILS debugging and calibration, particularly for single-antenna performance and transmitter output adjustments. It also stresses the importance of training to avoid electromagnetic interference and adhering to regulations to reduce external disruptions. Figure 11: Path loss in long-range A/G communication system in study by [PERSON], [PERSON], and [PERSON] [29]. Figure 10: Utilization of specific frequency band by UAV in study by [PERSON] et al. [28]. [PERSON] [31] highlights the distribution of near-field (NF) signals in localizer antenna systems within a radius of 150 m. It contrasts the NF behavior with far-field (FF) characteristics, underscoring the complexity and intricacy of NF measurements. The study constructs a three-dimensional model, refined through phase analysis and on-site data, to evaluate signal distributions against theoretical predictions. The results indicate that the NF distributions vary significantly with elevation angles and reflection coefficients, with unequal amplitude signals producing higher relative amplitudes at lower angles. In addition, the research examines the effects of Fresnel loss and directional weakening on signal transmission. According to [PERSON] et al. [32] the primary concern with 5G technology is its potential to interfere with radar altimeters due to overlapping frequency ranges (3.7-3.98 GHz for 5G and 4.2-4.4 GHz for radar altimeters). This overlap could pose safety risks during critical flight phases, such as landing and take-off. The study evaluated compatibility by simulating realistic interference scenarios, taking into account various factors, such as the positioning of 5G base stations and the characteristics of radar altimeters. The findings indicated a higher likelihood of interference at lower altitudes, where precise altitude measurements are crucial. To mitigate these risks, the article recommends reducing the transmission power of 5G base stations in specific areas, especially near airports. It also suggests additional strategies such as antenna down-tilting and creating exclusion zones. [PERSON] [33] explores the conflict between US regulatory bodies regarding the deployment of 5G technology and its potential effects on Aircraft safety, specifically focusing on radio altimeters. It begins by outlining the planned expansion into C-band frequencies, which has sparked concerns about possible interference with aviation instruments. The methodology includes an analysis of data from various stakeholders, such as the FAA and FCC, to evaluate the risks posed by 5G transmissions. The discussion highlights the importance of cooperation between regulators and industry players to address safety issues while progressing with 5G implementation. It also points out that other countries have managed to roll out 5G with necessary precautions, in contrast to the regulatory hurdles faced in the US. Ultimately, the article advocates for a more data-driven strategy to resolve future disputes over spectrum allocation. [PERSON] et al. [34] developed a deep learning method for detecting GNSS interference using Aircraft data from GPS and AHRS. The model operates in near real-time, analyzing sensor data to identify RFI. It combines temporal sequence modeling with anomaly detection to detect subtle interference patterns missed by rule-based systems. Achieving 83.5% accuracy, it outperforms traditional techniques. [PERSON] et al. [35] conducted similar work. However, it heavily depended on large labeled training data, which is often unavailable, limiting scalability and deployment. Studies such as [PERSON] et al. [36], [PERSON] et al. [37], and [PERSON] et al.