Channel quality predictions assisted by new algorithms for high throughput satellite and 5G systems

Area of Science:

• Satellite communications engineering
• Radio wave propagation
• Signal processing

Background:

• Existing satellite channel models lack accuracy due to rainfall variations.
• Advancements in High Throughput Satellite (HTS) and 5G services necessitate rain-aware channel modeling.

Purpose of the Study:

• To develop a prediction model for rain-induced impairments in HTS and 5G satellite-to-land communication channels.
• To characterize rain-induced attenuation and its impact on signal quality.

Main Methods:

• Integration of three novel algorithms to calculate rain-specific attenuation, slant path lengths, and overall attenuation.
• Analysis of signal carrier-to-noise ratios and symbol error rates for different modulation schemes.
• Development of a new database for rain-induced attenuation on HTS channels across various frequencies and rainfall intensities.

Main Results:

• Substantial fluctuations in HTS-to-land fade levels and signal quality observed during rainfall.
• Potential for communication link outages, especially with higher-order modulation schemes.
• Validation of the model using actual rainfall measurements.

Conclusions:

• The proposed model provides practical methods for analyzing rain-induced channel impairments.
• Accurate modeling is essential for the effective design and deployment of future HTS and 5G satellite systems.
• Understanding rain fade is critical for ensuring reliable satellite communication links.