Weighted ABG: A general framework for optimal combination of ABG Path-Loss Propagation Models

D. Casillas-Perez, C. Camacho-Gomez, S. Jimenez-Fernandez, A. Portilla-Figueras, S. Salcedo-Sanz
<span title="">2020</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q7qi7j4ckfac7ehf3mjbso4hne" style="color: black;">IEEE Access</a> </i> &nbsp;
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
more &raquo; ... 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. INDEX TERMS 5G, path-loss, mmWave, ABG propagation models, models combination.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2020.2999206">doi:10.1109/access.2020.2999206</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ob4gbm274bdrddn7bv44fkpwja">fatcat:ob4gbm274bdrddn7bv44fkpwja</a> </span>
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