@misc{10481/107245,
year = {2025},
month = {7},
url = {https://hdl.handle.net/10481/107245},
abstract = {Accurate channel modeling plays a pivotal role in optimizing communication systems, and fitting field measurements to stochastic models is crucial for capturing the key propagation features and to map these to achievable system performances. In this work, we shed light on what’s the most appropriate alternative for channel fitting, when the ultimate goal is performance analysis. Results show that likelihood-based and average-error metrics should be used with caution, since they can largely fail to predict outage probability measures. We show that supremum-error fitting metrics with tail awareness are more robust to estimate both ergodic and outage performance measures, even when they yield a larger average-error fitting.},
organization = {MICIU/AEI/10.13039/501100011033 y FEDER/UE (PID2023-149975OB-I00)},
organization = {Consejería de Universidad, Investigación e Innovación (Junta de Andalucía) - (EMERGIA20-00297)},
organization = {FPU (FPU22/03392)},
organization = {Universidad San Francisco de Quito (Poli-Grants Program, Grant 33595)},
organization = {Universidad de Granada / CBUA (Open access)},
publisher = {IEEE},
keywords = {Channel fitting},
keywords = {Fading},
keywords = {Performance analysis},
title = {How Should One Fit Channel Measurements to Fading Distributions for Performance Analysis?},
doi = {10.1109/LCOMM.2025.3594554},
author = {Fernández, Santiago and Vega Sánchez, José David and Galeote Cazorla, Juan E. and López Martínez, Francisco Javier},
}