Hybrid centralized-distributed precoding in fronthaul-constrained CF-mMIMO systems

2025-10-14

AI Summary

In cell-free massive MIMO (CF-mMIMO) systems with capacity-limited fronthaul links, balancing spectral efficiency (SE) and fronthaul overhead remains challenging, especially under heterogeneous user requirements. Method: This paper proposes a hybrid centralized–distributed precoding strategy that dynamically assigns users to either centralized or distributed precoding based on fronthaul capacity constraints. A joint optimization framework is formulated to determine user grouping and power allocation, subject to per-access-point (AP) power and fronthaul capacity limits. The non-convex problem is equivalently transformed and solved via an efficient algorithm. Contribution/Results: The proposed scheme achieves significant SE gains over pure centralized or pure distributed baselines across diverse system configurations, while maintaining strong adaptability to varying fronthaul capacities. It effectively bridges the trade-off between SE performance and fronthaul resource consumption, offering a practical solution for fronthaul-constrained CF-mMIMO deployments.

Technology Category

• Search and Optimization: Mixed Discrete/Continuous Search
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Machine Learning: Mixture of Experts (MoE)

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
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems

Abstract

We investigate a fronthaul-limited cell-free massive multiple-input multiple-output (CF-mMIMO) system and propose a hybrid centralized-distributed precoding strategy that dynamically adapts to varying fronthaul and spectral efficiency (SE) requirements. The proposed approach divides users into two groups: one served by centralized precoding and the other by distributed precoding. We formulate a novel optimization problem for user grouping and power control aimed at maximizing the sum SE, subject to fronthaul and per-access point (AP) power constraints. To tackle the problem, we transform it into a tractable form and propose efficient solution algorithms. Numerical results confirm the hybrid scheme's versatility and superior performance, consistently outperforming fully centralized and distributed approaches across diverse system configurations.

Problem

• Optimizing user grouping and power control in fronthaul-limited CF-mMIMO systems
• Maximizing sum spectral efficiency under fronthaul and AP power constraints
• Developing hybrid centralized-distributed precoding to adapt to varying requirements

Innovation

• Hybrid centralized-distributed precoding dynamically adapts
• User grouping and power control maximize efficiency
• Transforms optimization problem into tractable algorithms