An Original Theoretical Model for Electromagnetic Wave Propagation in Sub-Saharan Dust-Laden Atmospheric Conditions at Millimeter Wave Frequencies

📖 ABSTRACT/OVERVIEW

Millimeter wave frequency bands above 24 GHz are central to 5G network capacity expansion through multi-gigabit short-range links, yet the propagation behavior of millimeter waves through the dust-laden atmospheric conditions prevalent across northern Nigeria and the Sahel during the harmattan season has not been theoretically characterized, creating a fundamental gap in 5G deployment planning for the North West and North East geopolitical zones. This doctoral study develops an original theoretical model for electromagnetic wave propagation through dust-laden atmospheric conditions at millimeter wave frequencies, providing the first physically grounded propagation model calibrated to sub-Saharan West African atmospheric aerosol conditions. The theoretical model extends Mie scattering theory to characterize interaction between millimeter wave radiation and non-spherical aerosol particles representative of Saharan dust observed in northern Nigeria, deriving original closed-form expressions for additional attenuation per unit length as a function of particle size distribution, number density, and dielectric properties. Particle size distribution parameters for the model were empirically determined from optical particle counter measurements conducted during harmattan events in Kano and Maiduguri over two measurement campaigns. Theoretical attenuation predictions are validated against direct millimeter wave link attenuation measurements at 28 GHz and 38 GHz conducted concurrently with aerosol sampling during three separate harmattan events. The original theoretical model achieves a root mean square prediction error of 0.34 dB/km against measured attenuation data, substantially outperforming ITU-R P.840 extrapolation. Keywords: millimeter wave, dust attenuation, propagation model, harmattan, 5G.

Need Complete Chapters of the Above Topic?

Get high-quality, Zero-AI research materials with current citations.

Request via WhatsApp 💬