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Inter-intra cellular pilot contamination mitigation for heterogeneous massive MIMO cellular systems

Author

Listed:
  • Abhinaba Dey

    (National Institute of Technology Silchar)

  • Prabina Pattanayak

    (National Institute of Technology Silchar)

Abstract

Massive multiple-input-multiple-output (MIMO) technology has been advocated as one of the most advanced and promising technologies for catering to the high data requirements of present and future cellular networks. It can be achieved by the installation of hundreds or thousands of antennas at the base station (BS), for serving tens of users. For making proper use of its high gain capabilities, it is required for the BS to have full knowledge of the channel between the users and itself which is obtained using channel state information (CSI). Pilot contamination has been identified as a major hindrance in the error-free computation of CSI. In this paper, a heterogeneous massive MIMO cellular system has been considered where the number of users present in different cells are assumed to be different. Moreover, the same pilots are reused by the users of each cell. This gives rise to the scenario of both inter-cellular and intra-cellular pilot contamination in the massive MIMO cellular system approach. To mitigate these aforesaid pilot contamination, two sub-optimal algorithms have been proposed in this correspondence which allocate the available same pilots to various users in a systematic manner based upon their perceived interference. In the first approach, the intra-cellular pilot contamination has been addressed before addressing the inter-cellular pilot contamination. The inter-cellular pilot contamination has been resolved ahead of the intra-cellular pilot contamination as per the second approach. Both these algorithms are designed with the aim of maximizing the system throughput. Hence, pilots with low interference are allocated to better channel conditioned users and vice-versa. On different performance parameters, the algorithms are evaluated and the simulation results show that the second pilot allocation strategy is more successful than the first scheme incurring the same computational complexity. Moreover, the effectiveness of the proposed algorithms have been presented by comparing with existing pilot contamination mitigation algorithms for various system metrics.

Suggested Citation

  • Abhinaba Dey & Prabina Pattanayak, 2022. "Inter-intra cellular pilot contamination mitigation for heterogeneous massive MIMO cellular systems," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 80(1), pages 91-103, May.
    • Handle: RePEc:spr:telsys:v:80:y:2022:i:1:d:10.1007_s11235-022-00889-z
    DOI: 10.1007/s11235-022-00889-z
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    References listed on IDEAS

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    1. Ehab Ali & Mahamod Ismail & Rosdiadee Nordin & Nor Fadzilah Abdulah, 2019. "Beamforming with 2D-AOA estimation for pilot contamination reduction in massive MIMO," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 71(4), pages 541-552, August.
    2. Hossein Akhlaghpasand & S. Mohammad Razavizadeh, 2017. "Adaptive pilot decontamination in multi-cell massive MIMO networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 66(3), pages 515-522, November.
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    Cited by:

    1. Pedro Ivo Cruz & Dimitri Leandro & Tito Spadini & Ricardo Suyama & Murilo Bellezoni Loiola, 2024. "Detecting malicious pilot contamination in multiuser massive MIMO using decision trees," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 86(4), pages 797-809, August.

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    1. Ehab Ali & Mahamod Ismail & Rosdiadee Nordin & Nor Fadzilah Abdulah, 2019. "Beamforming with 2D-AOA estimation for pilot contamination reduction in massive MIMO," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 71(4), pages 541-552, August.
    2. Pedro Ivo Cruz & Dimitri Leandro & Tito Spadini & Ricardo Suyama & Murilo Bellezoni Loiola, 2024. "Detecting malicious pilot contamination in multiuser massive MIMO using decision trees," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 86(4), pages 797-809, August.

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