Beamforming with 2D-AOA estimation for pilot contamination reduction in massive MIMO

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1 Citation (Scopus)

Abstract

The upcoming fifth-generation wireless mobile systems are projected to be commercialized in the year 2020 and are set to play the main role in massive multiple input-multiple output (mMIMO) integrated with the technologies of beamforming antenna arrays. However, the performance of mMIMO is constrained by inter-cell interference from adjacent cells triggered by the reused pilot, an issue termed pilot contamination. To address this issue, this paper focuses on mitigating pilot contamination by implementing a suboptimal spatial source detection method based on the beamforming approach using a two-dimension-unitary estimation of the signal parameters through rotational invariance techniques algorithm. We jointly used 2D-AOA information (azimuth and elevation angles) and statistical channel estimations at the BSs to identify the channels correlation condition and evaluate the sum rate performance of users based on AOA. The detected signals from the uniform rectangular array are used to segregate the required signal from the interfering signal without any change to the pilot construction of the training signals. The performance of the minimum mean squared error beamforming (MMSE-beamforming) technique in the multi-cell mMIMO system of the aforementioned method is numerically evaluated and then compared with conventional methods that depend only on pilot identity information. The simulation reveals that the achievable sum rate gains of 2D-AOA and the pilot identity information techniques (best case) with respect to deterministic MMSE are 96.3% and 85.4%, respectively, thus showing the prospect of eliminating the majority of pilot contamination using the 2D-AOA estimation.

Original languageEnglish
JournalTelecommunication Systems
DOIs
Publication statusAccepted/In press - 1 Jan 2018

Fingerprint

Beamforming
MIMO systems
Contamination
Channel estimation
Invariance
Antenna arrays

Keywords

  • 2-D angle of arrival
  • 2D-UESPRIT
  • Massive MIMO
  • MMSE-beamforming
  • Pilot contamination
  • Uniform rectangular array

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

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title = "Beamforming with 2D-AOA estimation for pilot contamination reduction in massive MIMO",
abstract = "The upcoming fifth-generation wireless mobile systems are projected to be commercialized in the year 2020 and are set to play the main role in massive multiple input-multiple output (mMIMO) integrated with the technologies of beamforming antenna arrays. However, the performance of mMIMO is constrained by inter-cell interference from adjacent cells triggered by the reused pilot, an issue termed pilot contamination. To address this issue, this paper focuses on mitigating pilot contamination by implementing a suboptimal spatial source detection method based on the beamforming approach using a two-dimension-unitary estimation of the signal parameters through rotational invariance techniques algorithm. We jointly used 2D-AOA information (azimuth and elevation angles) and statistical channel estimations at the BSs to identify the channels correlation condition and evaluate the sum rate performance of users based on AOA. The detected signals from the uniform rectangular array are used to segregate the required signal from the interfering signal without any change to the pilot construction of the training signals. The performance of the minimum mean squared error beamforming (MMSE-beamforming) technique in the multi-cell mMIMO system of the aforementioned method is numerically evaluated and then compared with conventional methods that depend only on pilot identity information. The simulation reveals that the achievable sum rate gains of 2D-AOA and the pilot identity information techniques (best case) with respect to deterministic MMSE are 96.3{\%} and 85.4{\%}, respectively, thus showing the prospect of eliminating the majority of pilot contamination using the 2D-AOA estimation.",
keywords = "2-D angle of arrival, 2D-UESPRIT, Massive MIMO, MMSE-beamforming, Pilot contamination, Uniform rectangular array",
author = "Ehab Ali and Mahamod Ismail and Rosdiadee Nordin and Abdullah, {Nor Fadzilah}",
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N2 - The upcoming fifth-generation wireless mobile systems are projected to be commercialized in the year 2020 and are set to play the main role in massive multiple input-multiple output (mMIMO) integrated with the technologies of beamforming antenna arrays. However, the performance of mMIMO is constrained by inter-cell interference from adjacent cells triggered by the reused pilot, an issue termed pilot contamination. To address this issue, this paper focuses on mitigating pilot contamination by implementing a suboptimal spatial source detection method based on the beamforming approach using a two-dimension-unitary estimation of the signal parameters through rotational invariance techniques algorithm. We jointly used 2D-AOA information (azimuth and elevation angles) and statistical channel estimations at the BSs to identify the channels correlation condition and evaluate the sum rate performance of users based on AOA. The detected signals from the uniform rectangular array are used to segregate the required signal from the interfering signal without any change to the pilot construction of the training signals. The performance of the minimum mean squared error beamforming (MMSE-beamforming) technique in the multi-cell mMIMO system of the aforementioned method is numerically evaluated and then compared with conventional methods that depend only on pilot identity information. The simulation reveals that the achievable sum rate gains of 2D-AOA and the pilot identity information techniques (best case) with respect to deterministic MMSE are 96.3% and 85.4%, respectively, thus showing the prospect of eliminating the majority of pilot contamination using the 2D-AOA estimation.

AB - The upcoming fifth-generation wireless mobile systems are projected to be commercialized in the year 2020 and are set to play the main role in massive multiple input-multiple output (mMIMO) integrated with the technologies of beamforming antenna arrays. However, the performance of mMIMO is constrained by inter-cell interference from adjacent cells triggered by the reused pilot, an issue termed pilot contamination. To address this issue, this paper focuses on mitigating pilot contamination by implementing a suboptimal spatial source detection method based on the beamforming approach using a two-dimension-unitary estimation of the signal parameters through rotational invariance techniques algorithm. We jointly used 2D-AOA information (azimuth and elevation angles) and statistical channel estimations at the BSs to identify the channels correlation condition and evaluate the sum rate performance of users based on AOA. The detected signals from the uniform rectangular array are used to segregate the required signal from the interfering signal without any change to the pilot construction of the training signals. The performance of the minimum mean squared error beamforming (MMSE-beamforming) technique in the multi-cell mMIMO system of the aforementioned method is numerically evaluated and then compared with conventional methods that depend only on pilot identity information. The simulation reveals that the achievable sum rate gains of 2D-AOA and the pilot identity information techniques (best case) with respect to deterministic MMSE are 96.3% and 85.4%, respectively, thus showing the prospect of eliminating the majority of pilot contamination using the 2D-AOA estimation.

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