Propagation Path Loss Models for 5G Urban Micro- and Macro-Cellular Scenarios

By Shu Sun, Theodore Ted S. Rappaport, Sundeep Rangan, Timothy A. Thomas, Amitava Ghosh, István Zsolt Kovács, Ignacio Rodriguez, Ozge Hizir Koymen, Andrzej Partyka, J. Jarvelainen. IEEE Vehicular Technology Conference, 2015

346 citations recorded by the source corpus.

This paper presents and compares two candidate large-scale propagation path loss models, the alpha-beta-gamma (ABG) model and the close-in (CI) free space reference distance model, for the design of fifth generation (5G) wireless communication systems in urban micro- and macro-cellular scenarios. Comparisons are made using the data obtained from 20 propagation measurement campaigns or ray- tracing studies from 2 GHz to 73.5 GHz over distances ranging from 5 m to 1429 m. The results show that the one-parameter CI model has a very similar goodness of fit (i.e., the shadow fading standard deviation) in both line-of-sight and non-line-of-sight environments, while offering substantial simplicity and more stable behavior across frequencies and distances, as compared to the three-parameter ABG model. Additionally, the CI model needs only one very subtle and simple modification to the existing 3GPP floating-intercept path loss model (replacing a constant with a close-in free space reference value) in order to provide greater simulation accuracy, more simplicity, better repeatability across experiments, and higher stability across a vast range of frequencies.

Subfields: Electrical and Electronic Engineering, Media Technology

View Paper: https://www.semanticscholar.org/paper/fd96dd217d106edb4ae812c874711d2a34bad2fa

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Citations in the corpus

Investigation of Prediction Accuracy, Sensitivity, and Parameter Stability of Large-Scale Propagation Path Loss Models for 5G Wireless Communications (2016, methodology): “, the floating-intercept or AB model) [25], where one merely needs to substitute the floating constant (which has been shown to vary substantially across different measurements, frequencies, and scenarios [2], [3]) with a freespace constant that is a function of frequency based on a 1-m standard fre”
Overview of Millimeter Wave Communications for Fifth-Generation (5G) Wireless Networks—With a Focus on Propagation Models (2017, methodology): “…it is commonly believed that path loss increases dramatically by moving up to mmWave frequencies, extensive work in various environments in [21], [28], [29], [83], and [84] shows that Friis’ equation [85] dictates this is true only when the antenna gain is assumed to be constant over frequency.”
3-D Millimeter-Wave Statistical Channel Model for 5G Wireless System Design (2016, neutral): “decibel [12], [27], [63].”
Indoor Office Wideband Millimeter-Wave Propagation Measurements and Channel Models at 28 and 73 GHz for Ultra-Dense 5G Wireless Networks (2015, methodology): “This model allows for simple calculations of large-scale path loss, as well as easy comparisons across frequency bands, environments, and measurements from other researchers [112], [122].”