Abstract
This paper presents broadband simulations and measurements of Millimeter-Waves (mm-wave) propagation in a rugged underground mine environment. Mathematical formulation was carried out in the framework of Uniform Theory of Diffraction (UTD) to develop a deterministic Ray-Tracing (RT) model under Line-Of-Sight (LOS) condition. The developed theoretical model was then validated experimentally in Frequency Domain (FD) and Time Domain (TD). A significant agreement between simulations and measurements is achieved in both domains. The rough surfaces of the mine are modeled deterministically as groups of diffracting wedges having random dimensions (heights, angles) being transversely oriented throughout the gallery. Acute (inferior to 30°) and obtuse (superior to 120°) wedges angles are found to have significant effects on the overall propagation performance. In the mm-wave band, the UTD diffraction phenomenon is evident and must be considered in the design of underground mine channels. In fact, the presented model is found to be capable of predicting the complex multipath of underground mine channels, due to the ray-optical behavior at mm-wave bands.
Highlights
Thanks to the recent development of the 5G and IoT technologies, the underground mining industry is expected to evolve into a new era of ‘‘smart mining mobility’’ where infrastructures, mining machinery, and miners will be interconnected to achieve optimal automation, mobility, ultra-high safety, and productivity
Relevant literature review about wall surface roughness effect on propagation channel in tunnels is scares. This effect is a source of an important path loss, and should be taken into consideration for a rigorous prediction of the signal power
A further addition of single-diffracted rays associated with side surfaces A and B yields the Channel Transfer Function (CTF) of Fig. 6(b), while the relative amplitude of the received signal varies within 20 dB with large-scale fading trend that follows CTF of Fig. 6(a) and a small-scale fading that repeats every 57.2 MHz
Summary
Thanks to the recent development of the 5G and IoT technologies, the underground mining industry is expected to evolve into a new era of ‘‘smart mining mobility’’ where infrastructures, mining machinery, and miners will be interconnected to achieve optimal automation, mobility, ultra-high safety, and productivity. Relevant literature review about wall surface roughness effect on propagation channel in tunnels is scares. Latest studies based on experimental mm-wave channel measurements were performed in an underground mine and subway tunnels [10], [11]. Authors in [15], examine the channel propagation at the mm-wave frequency band in a short tunnel using a time-domain channel measurement Channel parameters, such as K-factor, rootmean-square delay spread, and shadowing are investigated. In [16] the study considers the channel performance of mm-wave MIMO system in a subway tunnel, using raytracing-based simulations and experimental measurements. A high-gain directional horn antenna is recommended in [6] for MIMO channel measurements conducted in underground mine tunnels in order to overcome high propagation losses at 60-GHz frequency band. The measured Channel Transfer Function (CTF) is expressed as: CTF meas
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