Abstract
The propagation of signal and its strength in an indoor area have become crucial in the era of fifth-generation (5G) and beyond-5G communication systems, which use high bandwidth. High millimeter wave (mmWave) frequencies present a high signal loss and low signal strength, particularly during signal propagation in indoor areas. It is considerably difficult to design indoor wireless communication systems through deterministic modeling owing to the complex nature of the construction materials and environmental changes caused by human interactions. This study presents a methodology of data-driven techniques that will be applied to predict path loss using artificial intelligence. The proposed methodology enables the prediction of signal loss in an indoor environment with an accuracy of 97.4%.
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