Analysis of Statistical QoS in Half Duplex and Full Duplex Dense Heterogeneous Cellular Networks

TL;DR

This paper develops a scalable mathematical framework to analyze statistical QoS in dense heterogeneous 5G networks, comparing half duplex and full duplex modes, and identifies the interference cancellation needed for full duplex to outperform half duplex.

Contribution

It introduces a lower bound for effective capacity analysis in dense networks and provides insights into the benefits and interference requirements of full duplex operation.

Findings

The proposed scheme is accurate and computationally efficient for large-scale systems.

Full duplex can outperform half duplex if self interference cancellation exceeds a certain threshold.

The framework offers insights into QoS improvements with mode migration in dense networks.

Abstract

Statistical QoS provisioning as an important performance metric in analyzing next generation mobile cellular network, aka 5G, is investigated. In this context, by quantifying the performance in terms of the effective capacity, we introduce a lower bound for the system performance that facilitates an efficient analysis. Based on the proposed lower bound, which is mainly built on a per resource block analysis, we build a basic mathematical framework to analyze effective capacity in an ultra dense heterogeneous cellular network. We use our proposed scalable approach to give insights about the possible enhancements of the statistical QoS experienced by the end users if heterogeneous cellular networks migrate from a conventional half duplex to an imperfect full duplex mode of operation. Numerical results and analysis are provided, where the network is modeled as a Matern point process. The results demonstrate the accuracy and computational efficiency of the proposed scheme, especially in large scale wireless systems. Moreover, the minimum level of self interference cancellation for the full duplex system to start outperforming its half duplex counterpart is investigated.