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

TL;DR

This work addresses intercell interference in ultra-dense indoor networks by proposing a Modified Fractional Frequency Reuse (FFR) that classifies users based on the power ratio between the serving BS and the second-nearest BS, rather than relying on SINR or distance alone. The method leverages practical signals available for handover and cooperative communication, assigning CEUs higher transmit power (ratio $a$) to mitigate interference. Through PPP-based system modeling and Monte Carlo simulations, the study reveals a non-monotonic, threshold-dependent impact on coverage and highlights that higher obstacle-induced attenuation can significantly improve SIR by suppressing interference, while aggressive power scaling can degrade overall performance. The findings support the feasibility of implementing the modified FFR in dense 5G/6G scenarios, with practical implications for CEU/CCU management and interference mitigation 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.

Figures (4)

• Figure 1: Density of CEUs vs User Classification Threshold T
• Figure 2: Simulation steps
• Figure 3: User Coverage Probability vs Classification Threshold
• Figure 4: Simulation steps

Theorems & Definitions (5)

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