Analytical Evaluation of Fractional Frequency Reuse for OFDMA Cellular Networks

By Thomas David Novlan, Radha Krishna Ganti, Arunabha Ghosh, Jeffrey G. Andrews. IEEE Transactions on Wireless Communications, 2011

427 citations recorded by the source corpus.

Fractional frequency reuse (FFR) is an interference management technique well-suited to OFDMA-based cellular networks wherein the bandwidth of the cells is partitioned into regions with different frequency reuse factors. To date, FFR techniques have been typically been evaluated through system-level simulations using a hexagonal grid for the base station locations. This paper instead focuses on analytically evaluating the two main types of FFR deployments - Strict FFR and Soft Frequency Reuse (SFR) - using a Poisson point process to model the base station locations. The results are compared with the standard grid model and an actual urban deployment. Under reasonable special cases for modern cellular networks, our results reduce to simple closed-form expressions, which provide insight into system design guidelines and the relative merits of Strict FFR, SFR, universal reuse, and fixed frequency reuse. Finally, a SINR-proportional resource allocation strategy is proposed based on the analytical expressions and we observe that FFR provides an increase in the sum-rate as well as the well-known benefit of improved coverage for cell-edge users.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/36e6a7f5dbe5e969dc0e41aa1b703e3b5a3d48ab

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Citations in the corpus

On Stochastic Geometry Modeling of Cellular Uplink Transmission With Truncated Channel Inversion Power Control (2014, background): “Therefore, the coverage probability and the average spectral efficiency can only be improved through interference management techniques such as frequency reuse [25], interference cancellation [26], multiple-input-multiple-output (MIMO) antennas [27], interference avoidance via cognition [28], or mul”
Stochastic Geometry for Modeling, Analysis, and Design of Multi-Tier and Cognitive Cellular Wireless Networks: A Survey (2013, methodology): “[77], [78], [83], [85], [86] HCPP [9], [25]-[27], [32]-[35], [37], [39], [46] [54]-[60], [62]-[66] [68], [77], [78], [80], [81], [83], [85], [86] Technique #1”
Analytical Modeling of Uplink Cellular Networks (2012, result): “m spatial models for the network topology [8]. An advantage of this new approach is the ability to derive tractable expressions leading to more general performance characterizations and intuition [9]–[14]. In our recent work [11], we showed that a completely random (Poisson) placement of base statio”
Non-Orthogonal Multiple Access in Multi-Cell Networks: Theory, Performance, and Practical Challenges (2016, methodology): “ and cell-edge users. Detailed simulation parameters are provided in Table II. In our simulation, following schemes are considered: OMA, OMA-FFR, NOMA, NOMA-TDM, NOMA-JT, and NOMA-CB. In OMA-FFR, FFR [14] is used in controlling ICI on top of OMA transmission. Due to the effect of FFR, the cell-edge ”
Femtocells: Past, Present, and Future (2012, background): “How to best exploit these techniques is an active area of research [28], [80]–[83] and is the subject of two papers in this special issue [41], [84].”