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<p>Massive multiple-input multiple-output (M-MIMO) systems are considered a key technology to support the increasing data rate requirements of upcoming wireless communication systems. In frequency division duplex (FDD) systems, accurate downlink (DL) channel state information (CSI) is essential for achieving the full performance of M-MIMO, especially in scenarios with short coherence time blocks (CTBs), where the time available for pilot-based channel estimation is limited. This work addresses the problem of DL channel estimation in FDD-based M-MIMO systems under spatially correlated Rayleigh fading channels. We use the minimum mean square error (MMSE) estimator, which relies on second-order channel statistics. It performs estimation using pilot sequences designed based on the eigenstructure of the transmit correlation matrix that captures spatial channel characteristics. The estimation accuracy is measured using the mean square error (MSE). On the other hand, spatial correlation is modeled using the Weichselberger model, which provides a general and realistic representation of MIMO channels. To further benefit from spatial correlation, we propose using a uniform rectangular array (URA) instead of the traditional uniform linear array (ULA). Specifically, we construct the URA correlation matrix using the Kronecker product of ULA-based matrices and extend the Weichselberger model accordingly to describe spatial correlation in URA configurations. In a URA structure, each antenna element is typically surrounded by four adjacent elements, which increases inter-element spatial correlation and improves channel estimation performance. Numerical and theoretical results confirm the effectiveness of the proposed approach, showing consistent trends between simulation and analytical expressions.</p>

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Downlink channel estimation in FDD massive MIMO using eigenstructure-aware pilot design considering the Weichselberger spatial correlation model

  • 期刊论文

  • 发表日期：

    2026年1月20日

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  • Jamal Amadid,
  • Asma Khabba,
  • Zakaria El Ouadi,
  • Lahcen Sellak,
  • Abdelmouttalib Bousrout,
  • Abdelouhab Zeroual

摘要

Massive multiple-input multiple-output (M-MIMO) systems are considered a key technology to support the increasing data rate requirements of upcoming wireless communication systems. In frequency division duplex (FDD) systems, accurate downlink (DL) channel state information (CSI) is essential for achieving the full performance of M-MIMO, especially in scenarios with short coherence time blocks (CTBs), where the time available for pilot-based channel estimation is limited. This work addresses the problem of DL channel estimation in FDD-based M-MIMO systems under spatially correlated Rayleigh fading channels. We use the minimum mean square error (MMSE) estimator, which relies on second-order channel statistics. It performs estimation using pilot sequences designed based on the eigenstructure of the transmit correlation matrix that captures spatial channel characteristics. The estimation accuracy is measured using the mean square error (MSE). On the other hand, spatial correlation is modeled using the Weichselberger model, which provides a general and realistic representation of MIMO channels. To further benefit from spatial correlation, we propose using a uniform rectangular array (URA) instead of the traditional uniform linear array (ULA). Specifically, we construct the URA correlation matrix using the Kronecker product of ULA-based matrices and extend the Weichselberger model accordingly to describe spatial correlation in URA configurations. In a URA structure, each antenna element is typically surrounded by four adjacent elements, which increases inter-element spatial correlation and improves channel estimation performance. Numerical and theoretical results confirm the effectiveness of the proposed approach, showing consistent trends between simulation and analytical expressions.