Rician $K$-Factor-Based Analysis of XLOS Service Probability in 5G Outdoor Ultra-Dense Networks

TL;DR

This paper introduces a new performance metric called XLOS service probability for 5G ultra-dense networks, based on Rician K-factors, and provides a closed-form expression and analysis for it.

Contribution

It develops a Rician K-factor-based model for XLOS service probability, deriving a closed-form expression using Fox H-functions and analyzing its asymptotic behavior.

Findings

Closed-form expression for XLOS probability derived

Asymptotic behavior analyzed using residue theory

Numerical results validated by Monte-Carlo simulations

Abstract

In this report, we introduce the concept of Rician $K$-factor-based radio resource and mobility management for fifth generation (5G) ultra-dense networks (UDN), where the information on the gradual visibility between the new radio node B (gNB) and the user equipment (UE)---dubbed X-line-of-sight (XLOS)---would be required. We therefore start by presenting the XLOS service probability as a new performance indicator; taking into account both the UE serving and neighbor cells. By relying on a lognormal $K$-factor model, a closed-form expression of the XLOS service probability in a 5G outdoor UDN is derived in terms of the multivariate Fox H-function; wherefore we develop a GPU-enabled MATLAB routine and automate the definition of the underlying Mellin-Barnes contour via linear optimization. Residue theory is then applied to infer the relevant asymptotic behavior and show its practical implications. Finally, numerical results are provided for various network configurations, and underpinned by extensive Monte-Carlo simulations.