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Scalable Statistical Channel Estimation and Its Applications in User-Centric Cell-Free Massive MIMO Systems.

Ling Xing¹, Dongle Wang¹, Xiaohui Zhang¹

¹School of Information Engineering, Henan University of Science and Technology, Luoyang 471023, China.

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|September 19, 2025

Summary

This study introduces a scalable method for estimating partial statistical channel state information (CSI) in cell-free massive MIMO systems. This approach improves performance for large-scale fading schemes while maintaining scalability.

Keywords:

cell-free channel state information massive MIMO power control scalability spectral efficiency

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Area of Science:

Wireless communication
Signal processing
Information theory

Background:

Cell-free massive MIMO (mMIMO) enhances system performance through collaborative signal processing.
Accurate channel state information (CSI) is crucial for mMIMO performance.
Existing statistical CSI acquisition methods for large-scale fading (LSF) are computationally intensive and not scalable for large networks.

Purpose of the Study:

To propose a scalable statistical CSI estimation method for user-centric cell-free mMIMO systems.
To enable blind estimation of partial statistical CSI for LSF schemes using uplink data signals.
To evaluate the applicability of the estimated CSI for downlink LSF precoding (LSFP) and power control.

Main Methods:

Blind estimation of partial statistical CSI using uplink data signals in a user-centric cell-free mMIMO architecture.
Application of estimated partial CSI for LSF precoding (LSFP) and power control in fully distributed precoding.

Main Results:

The proposed method achieves comparable spectral efficiency (SE) to traditional CSI acquisition schemes under LSFP, ensuring scalability.
When used for power control, the method significantly reduces fronthaul link CSI overhead.
Maintains nearly similar SE performance compared to existing solutions in power control applications.

Conclusions:

The developed scalable statistical CSI estimation method effectively addresses the limitations of traditional approaches in large-scale cell-free mMIMO networks.
The method offers a practical solution for improving LSF schemes and power control efficiency.
Demonstrates significant reductions in fronthaul overhead without compromising spectral efficiency.