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Adaptive pilot decontamination in multi-cell massive MIMO networks

Author

Listed:
  • Hossein Akhlaghpasand

    (Iran University of Science and Technology (IUST))

  • S. Mohammad Razavizadeh

    (Iran University of Science and Technology (IUST))

Abstract

This paper considers the contaminated channel estimation in multicell very large multiuser multiple-input multiple-output networks. To provide desirable spectral efficiency of these systems, we propose two adaptive algorithms which their implementations do not require orthogonal pilot sequences. The first algorithm (i.e., normalized least mean square) has low complexity and also gives an acceptable spectral efficiency in channels with low attenuation. The second algorithm (i.e., recursive least square) is more robust against pilot contamination and provides the desirable spectral efficiency in very large number of antennas at the base stations. In simulations, the performance of the proposed algorithms is evaluated and also compared with the performance of the conventional minimum mean square error estimation.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:telsys:v:66:y:2017:i:3:d:10.1007_s11235-017-0302-7
    DOI: 10.1007/s11235-017-0302-7
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    Cited by:

    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. 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.

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