Optimal Bilinear Equalizer Beamforming Design for Cell-Free Massive MIMO Networks with Arbitrary Channel Estimators

2025-03-02

IEEE Transactions on Vehicular Technology

AI Summary

This paper addresses the joint uplink–downlink optimization of cell-free massive MIMO systems operating over spatially correlated Rician fading channels. Method: We propose a distributed Optimal Bilinear Equalizer (OBE) beamforming framework that unifies uplink and downlink modeling, accommodates arbitrary statistics-based channel estimators, and leverages random matrix theory for closed-form spectral efficiency analysis. Contribution/Results: We establish that, under Rayleigh fading, OBE combining performance is estimator-agnostic—a novel insight. Building on this, we develop an uplink–downlink OBE duality theory, yielding closed-form analytical solutions and a performance decoupling mechanism. We derive unified, closed-form expressions for achievable uplink/downlink spectral efficiency and OBE beamforming weights, applicable to any channel estimator. The proposed scheme significantly enhances system robustness and spectral efficiency while offering a scalable, low-complexity distributed optimization paradigm for unbounded massive MIMO deployments.

Technology Category

• Search and Optimization: Distributed Search
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• User Modeling, Personalization and Recommendation: Federated recommendation systems and personalization
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Security and Privacy: Large-scale security measurements

Abstract

This paper studies the distributed optimal bilinear equalizer (OBE) beamforming design for both the uplink and downlink cell-free massive multiple-input multiple-output networks. We consider arbitrary statistics-based channel estimators over spatially correlated Rician fading channels. In the uplink, we derive the achievable spectral efficiency (SE) performance and OBE combining schemes with arbitrary statistics-based channel estimators and compute their respective closed-form expressions. It is insightful to explore that the achievable SE performance is not dependent on the choice of channel estimator when OBE combining schemes are applied over Rayleigh channels. In the downlink, we derive the achievable SE performance expressions with BE precoding schemes and arbitrary statistics-based channel estimators utilized and compute them in closed form. Then, we obtain the OBE precoding scheme leveraging insights from uplink OBE combining schemes.

Problem

• Designs optimal bilinear equalizer beamforming for cell-free massive MIMO networks.
• Explores spectral efficiency with arbitrary channel estimators in uplink and downlink.
• Derives closed-form expressions for spectral efficiency and beamforming schemes.

Innovation

• Distributed optimal bilinear equalizer beamforming design
• Achievable spectral efficiency with arbitrary channel estimators
• Closed-form expressions for uplink and downlink performance