DNA-GA: A New Approach of Network Performance Analysis

TL;DR

DNA-GA is a novel microscopic and macroscopic network performance analysis method that incorporates shadow fading, non-uniform user distributions, and arbitrary cell shapes, enhancing 5G system evaluations.

Contribution

The paper introduces DNA-GA, extending previous Gaussian approximation methods to include SIR analysis and macroscopic analysis approaches for detailed network performance evaluation.

Findings

DNA-GA naturally considers shadow fading.

It handles non-uniform user distributions and various fading types.

It accommodates arbitrary cell shapes for hotspot scenarios.

Abstract

In this paper, we propose a new approach of network performance analysis, which is based on our previous works on the deterministic network analysis using the Gaussian approximation (DNA-GA). First, we extend our previous works to a signal-to-interference ratio (SIR) analysis, which makes our DNA-GA analysis a formal microscopic analysis tool. Second, we show two approaches for upgrading the DNA-GA analysis to a macroscopic analysis tool. Finally, we perform a comparison between the proposed DNA-GA analysis and the existing macroscopic analysis based on stochastic geometry. Our results show that the DNA-GA analysis possesses a few special features: (i) shadow fading is naturally considered in the DNAGA analysis; (ii) the DNA-GA analysis can handle non-uniform user distributions and any type of multi-path fading; (iii) the shape and/or the size of cell coverage areas in the DNA-GA analysis can be made arbitrary for the treatment of hotspot network scenarios. Thus, DNA-GA analysis is very useful for the network performance analysis of the 5th generation (5G) systems with general cell deployment and user distribution, both on a microscopic level and on a macroscopic level.