Performance analysis of fractional frequency reuse in random cellular networks

Lam, Sinh Cong

Performance analysis of fractional frequency reuse in random cellular networks

Lam, Sinh Cong

Permalink

Publication Type:: Thesis
Issue Date:: 2018

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

Adobe PDF

Download contents and abstractAdobe PDF (144.32 kB)

Adobe PDF

Download thesisAdobe PDF (1.36 MB)

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	Lam, Sinh Cong
dc.date.accessioned	2018-09-28T04:37:39Z
dc.date.available	2018-09-28T04:37:39Z
dc.date.issued	2018
dc.identifier.uri	http://hdl.handle.net/10453/127880
dc.description	University of Technology Sydney. Faculty of Engineering and Information Technology.	en_AU
dc.description.abstract	In a Long Term Evolution (LTE) cellular network, Fractional Frequency Reuse (FFR) is a promising technique that improves the performance of mobile users which experience low Signal-to-Interference-plus-Noise Ratios (SINRs). Recently, the random cellular network model, in which the Base Stations (BSs) are distributed according to a Poisson Point Process (PPP), is utilised widely to analyse the network performance. Therefore, this thesis aims to model and analyse performance of two well-known FFR schemes called Strict Frequency Reuse (FR) and Soft FR, in the random cellular network. Monte Carlo simulation is used throughout the thesis to verify the analytical results. The first part of this thesis follows 3rd Generation Partnership Project (3GPP) recommendations to model the Strict FR and Soft FR in downlink and uplink single-tier random cellular networks. The two-phase operation model is presented for both Cell-Center User (CCU) and Cell-Edge User (CEU). Furthermore, the thesis follows the resource allocation technique and properties of PPP to evaluate Intercell Interference (ICI) of the user. The closed-form expressions of the performance metrics in terms of classification probability and average coverage probability of the CCU and CEU are derived. Thereafter, the performance of FFR is analysed in multi-tier cellular networks which are comprised of different types of cells such as macrocells, picocells and femtocells. The focus of this part is to examine the effects of the number of users and number of Resource Blocks (RBs) on the network performance. A new network model, in which the SINR on data channels are used for user classification purpose, is proposed. The analytical results indicate that the proposed model can reduce the power consumption of the BS while improving the network data rate. This chapter introduces an approach to analyse the optimal value of SINR threshold and bias factor. The analytical results indicate that the proposed model can increase the network data rate by 16.08% and 18.63% in the case of Strict FR and Soft FR respectively while reducing power consumption of the BS on the data channel. Finally, the thesis develops an FFR random cellular network model with an FR factor of 1 using either Joint Scheduling or Joint Transmission with Selection Combining. The performance metrics in terms of average coverage probability are derived for Rayleigh fading environment. Generally, this thesis makes contributions to uplink and downlink of LTE networks in terms of performance analysis.	en_AU
dc.format	Thesis (PhD)
dc.language.iso	en_AU	en_AU
dc.relation	https://opus.lib.uts.edu.au/bitstream/10453/127880/2/02whole.pdf
dc.rights	au.edu.uts.lib/ppc
dc.rights	info:eu-repo/semantics/openAccess
dc.rights	The author owns the copyright in this thesis including all reproduction and reuse rights for the work. The work may not be altered without the permission of the copyright owner. Attribution is essential when quoting or paraphrasing from this thesis.
dc.subject	Fractional frequency reuse.	en_AU
dc.subject	Uplink cellular networks.	en_AU
dc.subject	Downlink random cellular networks.	en_AU
dc.subject	FFR random cellular network.	en_AU
dc.title	Performance analysis of fractional frequency reuse in random cellular networks	en_AU
dc.type	Thesis	en_AU
utslib.copyright.status	open_access

Abstract:

In a Long Term Evolution (LTE) cellular network, Fractional Frequency Reuse (FFR) is a promising technique that improves the performance of mobile users which experience low Signal-to-Interference-plus-Noise Ratios (SINRs). Recently, the random cellular network model, in which the Base Stations (BSs) are distributed according to a Poisson Point Process (PPP), is utilised widely to analyse the network performance. Therefore, this thesis aims to model and analyse performance of two well-known FFR schemes called Strict Frequency Reuse (FR) and Soft FR, in the random cellular network. Monte Carlo simulation is used throughout the thesis to verify the analytical results. The first part of this thesis follows 3rd Generation Partnership Project (3GPP) recommendations to model the Strict FR and Soft FR in downlink and uplink single-tier random cellular networks. The two-phase operation model is presented for both Cell-Center User (CCU) and Cell-Edge User (CEU). Furthermore, the thesis follows the resource allocation technique and properties of PPP to evaluate Intercell Interference (ICI) of the user. The closed-form expressions of the performance metrics in terms of classification probability and average coverage probability of the CCU and CEU are derived. Thereafter, the performance of FFR is analysed in multi-tier cellular networks which are comprised of different types of cells such as macrocells, picocells and femtocells. The focus of this part is to examine the effects of the number of users and number of Resource Blocks (RBs) on the network performance. A new network model, in which the SINR on data channels are used for user classification purpose, is proposed. The analytical results indicate that the proposed model can reduce the power consumption of the BS while improving the network data rate. This chapter introduces an approach to analyse the optimal value of SINR threshold and bias factor. The analytical results indicate that the proposed model can increase the network data rate by 16.08% and 18.63% in the case of Strict FR and Soft FR respectively while reducing power consumption of the BS on the data channel. Finally, the thesis develops an FFR random cellular network model with an FR factor of 1 using either Joint Scheduling or Joint Transmission with Selection Combining. The performance metrics in terms of average coverage probability are derived for Rayleigh fading environment. Generally, this thesis makes contributions to uplink and downlink of LTE networks in terms of performance analysis.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/127880