Improvement of 5G performance through network densification in millimetre wave band

Al-Falahy, NFA ORCID: https://orcid.org/0000-0001-6133-5048 2018, Improvement of 5G performance through network densification in millimetre wave band , PhD thesis, University of Salford.

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Abstract

Recently, there has been a substantial growth in mobile data traffic due to the widespread of data hungry devices such as mobiles and laptops. The anticipated high traffic demands and low latency requirements stemmed from the Internet of Things (IoT) and Machine Type Communications (MTC) can only be met with radical changes to the network paradigm such as harnessing the millimetre wave (mmWave) band in Ultra-Dense Network (UDN). This thesis presents many challenges, problems and questions that arise in research and design stage of 5G network. The main challenges of 5G in mmWave can be characterised with the following attributes: i- huge traffic demands, with very high data rate requirements, ii- high interference in UDN, iii increased handover in UDN, higher dependency on Line of Sight (LOS) coverage and high shadow fading, and iv-massive MTC traffic due to billions of connected devices. In this work, software simulation tools have been used to evaluate the proposed solutions.

Therefore, we have introduced 5G network based on network densification. Network densification includes densification over frequency through mmWave, and densification over space through higher number of antennas, Higher Order Sectorisation (HOS), and denser deployment of small-cells. Our results show that the densification theme has significantly improved network capacity and user Quality of Experience (QoE). UDN network can efficiently raise the user experience to the level that 5G vision promised. However, one of the drawback of using UDN and HOS is the significant increase in Inter-Cell Interference (ICI). Therefore, ICI has been addressed in this work to increase the gain of densification.

ICI can degrade the performance of wireless network, particularly in UDN due to the increased interference from surrounding cells. We have used Fractional Frequency Reuse (FFR) as ICI Coordination (ICIC) for UDN network and HOS environment. The work shows that FFR has improved the network performance in terms of cell-edge data throughput and average cell throughput, and maintain the peak data throughput at a certain threshold. Additionally, HOS has shown even greater gain over default sectored sites when the interference is carefully coordinated.

To generalise the principle of densification, we have introduced Distributed Base Station (DBS) as the envisioned network architecture for 5G in mmWave. Remotely distributed antennas in DBS architecture have been harnessed in order to compensate for the high path loss that characterise mmWave propagation. The proposed architecture has significantly improved the user data throughput, decreased the unnecessary handovers as a result of dense network, increased the LOS coverage probability, and reduced the impact of shadow fading. Additionally, this research discusses the regulatory requirements at mmWave band for the Maximum Permissible Exposure (MPE).

Finally, scheduling massive MTC traffic in 5G has been considered. MTC is expected to contribute to the majority of IoT traffic. In this context, an algorithm has been developed to schedule this type of traffic. The results demonstrate the gain of using distributed antennas on MTC traffic in terms of spectral efficiency, data throughput, and fairness. The results show considerable improvement in the performance metrics.

The combination of these contributions has provided remarkable increase in data throughput to achieve the 5G vision of “massive” capacity and to support human and machine traffic.

Item Type: Thesis (PhD)
Contributors: Alani, OYK (Supervisor)
Schools: Schools > School of Computing, Science and Engineering > Salford Innovation Research Centre
Funders: Ministry of Higher Education and Scientific Research in Iraq, University of Anbar
Depositing User: NFA Al-Falahy
Date Deposited: 21 Sep 2018 10:22
Last Modified: 08 Jun 2020 02:30
URI: http://usir.salford.ac.uk/id/eprint/47192

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