In this paper we propose a novel path-loss model, the Weighted ABG (WABG), which suitably allows integrating or combine different available datasets, or previously proposed 5G propagation path-loss models from the state-of-the-art. Our proposal is therefore a new ABG-based approach which integrates other existing models, leading to the best possible approximation in least-square sense, considering different weighting policies. We evaluate the performance of the WABG in several 5G scenarios, and we carry out a complete comparison of the proposed method against several recently published ABG models, showing that the WABG obtains the best results in terms of model?s accuracy

Cátedra ISDEFE-UAH en TIC e Inteligencia Artificial