Analytical Evaluation of Fractional Frequency Reuse for Heterogeneous Cellular Networks

TL;DR

This paper develops an analytical model to evaluate fractional frequency reuse techniques in heterogeneous cellular networks, providing insights into coverage, interference mitigation, and spectrum efficiency for different FFR strategies.

Contribution

It introduces a tractable analytical framework based on Poisson point processes for evaluating Strict FFR and SFR in heterogeneous networks, capturing deployment non-uniformity.

Findings

Strict FFR bands improve coverage and rate for cell-edge users.

SFR enables more efficient spectrum sharing while reducing interference.

Cross-tier interference impacts FFR performance in closed access tiers.

Abstract

Interference management techniques are critical to the performance of heterogeneous cellular networks, which will have dense and overlapping coverage areas, and experience high levels of interference. Fractional frequency reuse (FFR) is an attractive interference management technique due to its low complexity and overhead, and significant coverage improvement for low-percentile (cell-edge) users. Instead of relying on system simulations based on deterministic access point locations, this paper instead proposes an analytical model for evaluating Strict FFR and Soft Frequency Reuse (SFR) deployments based on the spatial Poisson point process. Our results both capture the non-uniformity of heterogeneous deployments and produce tractable expressions which can be used for system design with Strict FFR and SFR. We observe that the use of Strict FFR bands reserved for the users of each tier with the lowest average SINR provides the highest gains in terms of coverage and rate, while the use of SFR allows for more efficient use of shared spectrum between the tiers, while still mitigating much of the interference. Additionally, in the context of multi-tier networks with closed access in some tiers, the proposed framework shows the impact of cross-tier interference on closed access FFR, and informs the selection of key FFR parameters in open access.