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Modelling and Analysis of Performance Characteristics in a 60 Ghz 802.11ad Wireless Mesh Backhaul Network for an Urban 5G Deployment

Author

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  • Michael Mackay

    (School of Computer Science and Mathematics, Liverpool John Moores University, Byrom Street, Liverpool L3 3AF, UK)

  • Alessandro Raschella

    (School of Computer Science and Mathematics, Liverpool John Moores University, Byrom Street, Liverpool L3 3AF, UK)

  • Ogeen Toma

    (School of Computer Science and Mathematics, Liverpool John Moores University, Byrom Street, Liverpool L3 3AF, UK)

Abstract

With the widespread deployment of 5G gaining pace, there is increasing interest in deploying this technology beyond traditional Mobile Network Operators (MNO) into private and community scenarios. These deployments leverage the flexibility of 5G itself to support private networks that sit alongside or even on top of existing public 5G. By utilizing a range of virtualisation and slicing techniques in the 5G Core (5GC) and heterogeneous Radio Access Networks (RAN) at the edge, a wide variety of use cases can be supported by 5G. However, these non-typical deployments may experience different performance characteristics as they adapt to their specific scenario. In this paper we present the results of our work to model and predict the performance of millimeter wave (mmWave) backhaul links that were deployed as part of the Liverpool 5G network. Based on the properties of the 802.11ad protocol and the physical characteristics of the environment, we simulate how each link will perform with different signal-to-noise ratio (SNR) and Packet Error Rate (PER) values and verify them against real-world deployed links. Our results show good convergence between simulated and real results and provide a solid foundation for further network planning and optimization.

Suggested Citation

  • Michael Mackay & Alessandro Raschella & Ogeen Toma, 2022. "Modelling and Analysis of Performance Characteristics in a 60 Ghz 802.11ad Wireless Mesh Backhaul Network for an Urban 5G Deployment," Future Internet, MDPI, vol. 14(2), pages 1-16, January.
    • Handle: RePEc:gam:jftint:v:14:y:2022:i:2:p:34-:d:729826
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    References listed on IDEAS

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    1. Joongheon Kim & Jong-Kook Kim, 2016. "Achievable Rate Estimation of IEEE 802.11ad Visual Big-Data Uplink Access in Cloud-Enabled Surveillance Applications," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-16, December.
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    Cited by:

    1. Iffat Gheyas & Alessandro Raschella & Michael Mackay, 2023. "Optimal Meshing Degree Performance Analysis in a mmWave FWA 5G Network Deployment," Future Internet, MDPI, vol. 15(6), pages 1-19, June.

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