Fundamental Limits via CRB of Semi-Blind Channel Estimation in Massive MIMO Systems

This paper investigates the asymptotic behavior of the deterministic and stochastic Cramér-Rao Bounds (CRB) for semi-blind channel estimation in massive multiple-input multiple-output (MIMO) systems. We derive and analyze mathematically tractable expressions for both metrics under various asymptotic regimes, which govern the growth rates of the number of antennas, the number of users, the training sequence length, and the transmission block length. Unlike the existing work, our results show that the CRB can be made arbitrarily small as the transmission block length increases, but only when the training sequence length grows at the same rate and the number of users remains fixed. However, if the number of training sequences remains proportional to the number of users, the CRB converges to a non-vanishing constant. Numerical results are presented to support our findings and demonstrate the advantages of semi-blind channel estimation in reducing the required number of training sequences.

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Publication Details

Journal
IEEE Transactions on Signal Processing
Published
2025-01-01
DOI
https://doi.org/10.1109/tsp.2025.3598515
Primary Topic
Advanced MIMO Systems Optimization
Type
article
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article

Fundamental Limits via CRB of Semi-Blind Channel Estimation in Massive MIMO Systems

Abla Kammoun, Mohamed‐Slim Alouini, Xue Zhang
IEEE Transactions on Signal Processing
Advanced MIMO Systems Optimization
article

Fundamental Limits via CRB of Semi-Blind Channel Estimation in Massive MIMO Systems

Abla Kammoun, Mohamed‐Slim Alouini, Xue Zhang
article en

Abstract

This paper investigates the asymptotic behavior of the deterministic and stochastic Cramér-Rao Bounds (CRB) for semi-blind channel estimation in massive multiple-input multiple-output (MIMO) systems. We derive and analyze mathematically tractable expressions for both metrics under various asymptotic regimes, which govern the growth rates of the number of antennas, the number of users, the training sequence length, and the transmission block length. Unlike the existing work, our results show that the CRB can be made arbitrarily small as the transmission block length increases, but only when the training sequence length grows at the same rate and the number of users remains fixed. However, if the number of training sequences remains proportional to the number of users, the CRB converges to a non-vanishing constant. Numerical results are presented to support our findings and demonstrate the advantages of semi-blind channel estimation in reducing the required number of training sequences.

IEEE Transactions on Signal ProcessingVol. 73
King Abdullah University of Science and Technology (SA)
Openalex Percentile: Top 81%
Advanced MIMO Systems Optimization
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Fundamental Limits via CRB of Semi-Blind Channel Estimation in Massive MIMO Systems — Abla Kammoun, Mohamed‐Slim Alouini, et al. · IEEE Transactions on Signal Processing (2025) | TGRS Research Map | TGRS