Quality of Service in Wireless Cellular Networks Subject to Log-Normal Shadowing

TL;DR

This paper investigates how log-normal shadowing affects QoS in wireless cellular networks, revealing that increased shadowing variance can sometimes improve interference conditions and QoS metrics, especially with optimal handover policies.

Contribution

It uncovers a counterintuitive phenomenon where higher shadowing variance can reduce interference and improve QoS, supported by semi-analytic and probabilistic analysis.

Findings

Higher shadowing variance can reduce interference in certain scenarios.

Selecting the BS with the smallest path loss can improve QoS.

The phenomenon is related to the heavy-tailed nature of log-normal distribution.

Abstract

Shadowing is believed to degrade the quality of service (QoS) in wireless cellular networks. Assuming log-normal shadowing, and studying mobile's path-loss with respect to the serving base station (BS) and the corresponding interference factor (the ratio of the sum of the path-gains form interfering BS's to the path-gain from the serving BS), which are two key ingredients of the analysis and design of the cellular networks, we discovered a more subtle reality. We observe, as commonly expected, that a strong variance of the shadowing increases the mean path-loss with respect to the serving BS, which in consequence, may compromise QoS. However, in some cases, an increase of the variance of the shadowing can significantly reduce the mean interference factor and, in consequence, improve some QoS metrics in interference limited systems, provided the handover policy selects the BS with the smallest path loss as the serving one. We exemplify this phenomenon, similar to stochastic resonance and related to the "single big jump principle" of the heavy-tailed log-nornal distribution, studying the blocking probability in regular, hexagonal networks in a semi-analytic manner, using a spatial version of the Erlang's loss formula combined with Kaufman-Roberts algorithm. More detailed probabilistic analysis explains that increasing variance of the log-normal shadowing amplifies the ratio between the strongest signal and all other signals thus reducing the interference. The above observations might shed new light, in particular on the design of indoor communication scenarios.