Performance of Modified Fractional Frequency Reuse Algorithm in Random Ultra Dense Networks

TL;DR

This paper proposes a modified fractional frequency reuse algorithm that classifies users based on the power ratio between the serving and second nearest BSs, aiming to improve interference management in ultra dense 5G networks.

Contribution

It introduces a novel user classification method using power ratios, enhancing interference mitigation strategies in ultra dense network environments.

Findings

Increasing transmission power improves CEU performance.

Higher power degrades typical user performance.

Frequency reuse is effective in obstacle-rich environments.

Abstract

Mitigating intercell interference by employing fractional frequency reuse algorithms is one of the important approaches to improving user performance in 5G and Beyond 5G cellular network systems, which typically have a high density of Base Stations (BSs). While most frequency reuse algorithms are based on the downlink Signal-to-Interference-plus-Noise Ratio (SINR) or the distance between the user and its serving BS to classify Cell-Edge Users (CEUs) and Cell-Center Users (CCUs), this paper discusses a modified algorithm that uses the power ratio between the signal strengths from the serving BS and the second nearest BS for user classification. Specifically, if the power ratio is below a predefined threshold, the user is classified as a CEU and is served with higher transmission power. Simulation results show that increasing transmission power is necessary to enhance CEU performance, but it also degrades the performance of typical users. The use of frequency reuse algorithms is particularly feasible in environments with a high density of obstacles, where intercell interference can be effectively suppressed.