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

Summary

This research develops improved methods to predict how rainfall affects satellite and 5G communications in the United Arab Emirates. Scientists created three new computer algorithms that use actual rainfall measurements from six weather stations across the UAE to predict signal degradation more accurately than existing international standards. The study shows that during heavy rain, satellite systems must switch to simpler transmission methods to maintain reliable communication, and provides practical guidance for designing more robust satellite systems.

Background

High Throughput Satellite (HTS) systems operating at frequencies above 17 GHz are challenged by precipitation-induced attenuation, which degrades signal quality particularly at Ku-band and Ka-band frequencies. Existing international rain attenuation prediction models rely on generalized rainfall data rather than region-specific measurements, introducing significant inaccuracies in predictions.

Objective

This study presents a novel prediction model for rain-induced impairments in HTS and 5G satellite-to-land communication channels using actual measured rainfall data from the UAE. The model integrates three new algorithms to characterize rain-induced attenuation and assess channel quality across different modulation schemes and frequencies.

Results

Results demonstrate substantial fluctuations in HTS fade levels during rainfall events, with attenuation at 30 GHz significantly higher than at 20 GHz. The proposed model achieved 18-35% improvement in accuracy compared to ITU-based predictions. At 20 GHz under extreme rainfall, QPSK maintains acceptable symbol error rates while higher-order modulation schemes become unsuitable.

Conclusion

The study provides practical methods for analyzing HTS channel characteristics using actual rainfall measurements, enabling more accurate design and deployment of satellite and 5G systems. The region-specific model can be adapted to other semi-arid regions by recalibrating with local meteorological data and rainfall statistics.
  • Published in:Scientific Reports,
  • Study Type:Technical Research Study,
  • Source: PMID: 41047392, DOI: 10.1038/s41598-025-20199-z
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