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

Variations in rainfall patterns across different regions reduce the accuracy of existing satellite channel models. As satellite services and 5G applications continue to advance, the development of accurate rain-impairment-aware channel models has become essential. This paper presents a prediction model for rain-induced impairments in High Throughput Satellite (HTS) and 5G satellite-to-land communication channels. The proposed model integrates three novel algorithms designed to characterize and analyze rain-induced attenuation and channel quality. Specifically, these algorithms calculate rain-specific attenuation, effective slant path lengths through rainfall, overall rain-induced attenuation, signal carrier-to-noise ratios, and symbol error rates across three conventional modulation schemes. Additionally, the study introduces a new database detailing rain-induced attenuation on HTS channels, considering various frequencies and rainfall intensities. Results indicate substantial fluctuations in HTS-to-land fade levels and signal quality during rainfall events, which could lead to communication link outages, particularly at higher-order modulation schemes. This study provides practical methods to analyze channel characteristics using actual rainfall measurements, thereby facilitating the effective design and deployment of future HTS and 5G system.