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Performance of Dense Wireless Networks in 5G and beyond Using Stochastic Geometry

Author

Listed:
  • Reza Aghazadeh Ayoubi

    (Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB), Politecnico di Milano, 20133 Milan, Italy)

  • Umberto Spagnolini

    (Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB), Politecnico di Milano, 20133 Milan, Italy
    Consorzio Nazionale Interuniversitario per le Telecomunicazioni (CNIT), 20133 Milan, Italy)

Abstract

Device density in cellular networks is expected to increase considerably in the near future. Accordingly, the access point (AP) will be equipped with massive multiple-input multiple-output (mMIMO) antennas, using collimated millimeter-wave (mmW) and sub-THz communications, and increasing the bandwidth to accommodate the growing data rate demands. In this scenario, interference plays a critical role and, if not characterized and mitigated properly, might limit the performances of the network. In this context, this paper derives the statistical properties of the aggregated interference power for a cellular network equipping a mMIMO cylindrical array. The proposed statistical model considers the link blockage and other network parameters such as antenna configuration and device density. The findings show that the characteristic function (CF) of the aggregated interference power can be regarded as a weighted mixture of two alpha-stable distributions. Furthermore, by analyzing the service probability, it is found that there is an optimal configuration of the array depending on the AP height and device density. The proposed statistical model can be part of the design of dense networks providing valuable insights for optimal network deployment and resource management and scheduling.

Suggested Citation

  • Reza Aghazadeh Ayoubi & Umberto Spagnolini, 2022. "Performance of Dense Wireless Networks in 5G and beyond Using Stochastic Geometry," Mathematics, MDPI, vol. 10(7), pages 1-30, April.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:7:p:1156-:d:786329
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    References listed on IDEAS

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    1. Shephard, N.G., 1991. "From Characteristic Function to Distribution Function: A Simple Framework for the Theory," Econometric Theory, Cambridge University Press, vol. 7(4), pages 519-529, December.
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    Cited by:

    1. Hao Li & Jiawei Cao & Guangkun Luo & Zhigang Wang & Houjun Wang, 2023. "A Novel Performance Bound for Massive MIMO Enabled HetNets," Mathematics, MDPI, vol. 11(13), pages 1-11, June.
    2. Young-Hwan You & Yong-An Jung & Sung-Hun Lee & Intae Hwang, 2022. "Complexity-Efficient Coherent Physical Cell Identity Detection Method for Cellular IoT Systems," Mathematics, MDPI, vol. 10(16), pages 1-18, August.

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