Geometry-Based Channel Model for Drone-Assisted Millimetre Wave Hybrid Cellular Network

This study addresses the inadequacy of terrestrial channel models in capturing the three-dimensional propagation dynamics of drone-assisted hybrid cellular networks operating across sub-6 GHz and millimetre-wave (mmWave) bands. A geometry-based stochastic channel model is developed, integrating elevation-dependent line-of-sight (LoS) probabilities, frequency-specific path loss laws, log-normal shadowing, and user distribution via a homogeneous Poisson Point Process. Monte Carlo simulations in MATLAB evaluate performance across 2 GHz and 28 GHz carrier frequencies, UAV altitudes of 50–150 m, and link distances of 10–500 m. Results show LoS probability exceeds 97% at 60° elevation in suburban environments. At 100 m distance, expected path loss is 91.2 dB for sub-6 GHz versus 111.4 dB for mmWave, underscoring mmWave’s capacity–coverage trade-off. The study confirms that mmWave UAVs achieve high throughput under strong LoS conditions, while sub-6 GHz UAVs ensure reliable coverage in non-line-of-sight scenarios. Coverage probability and SNR are shown to be critically dependent on UAV altitude and density. These findings provide a scalable framework for optimizing aerial base station deployment in emergency or infrastructure-scarce settings, enabling resilient hybrid networks that exploit the complementary strengths of UHF and mmWave bands.