JOURNAL ARTICLE

Stochastic Geometry Based Dynamic Fractional Frequency Reuse for OFDMA Systems

Abstract

Fractional Frequency Reuse (FFR) has been acknowledged as an efficient Interference Management (IM) technique, which offers significant capacity enhancement and improves cell edge coverage with low complexity of implementation. The performance of cellular system greatly depends on the spatial configuration of base stations (BSs). In literature, FFR has been analyzed mostly with cellular networks described by Hexagon Grid Model (HGM). HGM is neither tractable nor scalable to the dense deployment of next generation wireless networks. Moreover, the perfect geometry based HGM tends to overestimate the system's performance and not able to reflect the reality. In this paper, we use the stochastic geometry approach; FFR is analyzed with cellular network modeled by homogeneous Poisson Point Process (PPP). PPP model provides complete randomness in terms of BS deployment, which captures the real network scenario. A dynamic FFR scheme is proposed in this article, which take into account the randomness of the cell coverage area described by Voronoi tessellation. It is shown that the proposed scheme outperforms the traditional fixed frequency allocation schemes in terms of capacity and capacity density.

Keywords:
Stochastic geometry Poisson point process Computer science Base station Cellular network Randomness Voronoi diagram Point process Mathematical optimization Wireless network Topology (electrical circuits) Algorithm Distributed computing Wireless Mathematics Geometry Computer network Telecommunications Statistics

Metrics

8
Cited By
0.74
FWCI (Field Weighted Citation Impact)
22
Refs
0.78
Citation Normalized Percentile
Is in top 1%
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Citation History

Topics

Advanced MIMO Systems Optimization
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Advanced Wireless Network Optimization
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Millimeter-Wave Propagation and Modeling
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
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