Investigation of Prediction Accuracy, Sensitivity, and Parameter Stability of Large-Scale Propagation Path Loss Models for 5G Wireless Communications
Shu Sun, Theodore S. Rappaport, Timothy A. Thomas, Amitava Ghosh, Huan, C. Nguyen, Istvan Z. Kovacs, Ignacio Rodriguez, Ozge Koymen, Andrzej Partyka

TL;DR
This study compares large-scale propagation path loss models for 5G, finding that physically-based CI and CIF models outperform the ABG model in accuracy, stability, and simplicity across various environments and frequencies.
Contribution
It provides a comprehensive comparison of three path loss models, highlighting the advantages of CI and CIF models for 5G system design and standardization.
Findings
CI and CIF models have similar goodness of fit as ABG.
CI and CIF models are more stable across frequencies and distances.
CI and CIF models yield smaller prediction errors.
Abstract
This paper compares three candidate large-scale propagation path loss models for use over the entire microwave and millimeter-wave (mmWave) radio spectrum: the alpha-beta-gamma (ABG) model, the close-in (CI) free space reference distance model, and the CI model with a frequency-weighted path loss exponent (CIF). Each of these models have been recently studied for use in standards bodies such as 3GPP, and for use in the design of fifth generation (5G) wireless systems in urban macrocell, urban microcell, and indoor office and shopping mall scenarios. Here we compare the accuracy and sensitivity of these models using measured data from 30 propagation measurement datasets from 2 GHz to 73 GHz over distances ranging from 4 m to 1238 m. A series of sensitivity analyses of the three models show that the physically-based two-parameter CI model and three-parameter CIF model offer computational…
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Taxonomy
TopicsMillimeter-Wave Propagation and Modeling · Power Line Communications and Noise · Advanced MIMO Systems Optimization
