Fading Model Deviation in The NLOS Communication Channel in Limited Reflection

TL;DR

This paper introduces a K distribution-based model to improve the accuracy of NLOS communication channel fading predictions, especially when reflection and radiation angles vary, surpassing traditional Rayleigh models.

Contribution

The paper analytically applies the K distribution to NLOS fading modeling, demonstrating improved accuracy over Rayleigh and other models in practical scenarios.

Findings

K distribution provides better fit for NLOS fading data.

Model accuracy decreases with angle mismatch in traditional models.

Proposed model enhances prediction precision in varied reflection conditions.

Abstract

Statistical models are employed to characterize the clutter in the radar and the reflective signals of the telecommunication receivers. End to this, Rayliegh distribution is the simplest fading models in NLOS channels possessing low-accuracy in the high-resolution radars and distant telecommunication receivers. At present, high accuracy models such as the m-type Nakagami and hybrid GG distributions are utilized in order to model fading. However, despite the Non-Rayliegh models have better precision in the NLOS relative to the Rayliegh models, the accuracy of these models decreases when the radiation angle in the transmitter and the reflection angle in the receiver are different. In this paper, the K distribution function is analytically introduced and deployed to model the fading using practical data. Although this model was previously introduced to describe the clutter properties of the radar