EMF-Compliant Power Control in Cell-Free Massive MIMO: Model-Based and Data-Driven Approaches

2025-11-28

AI Summary

This paper addresses user-centric cell-free massive MIMO systems, jointly optimizing uplink/downlink power allocation under electromagnetic field (EMF) exposure safety constraints to maximize the minimum user data rate. We propose a dual-path approach: a model-driven path employing continuous convex approximations (e.g., log-sum-exp) and iterative optimization to rigorously satisfy EMF constraints while ensuring performance; and a data-driven path that pioneers the integration of deep unfolding into this setting, yielding an end-to-end trainable architecture achieving near-optimal performance with ultra-low computational overhead. To the best of our knowledge, this is the first work unifying EMF compliance, proportional fairness, and low-complexity deployment—establishing a novel paradigm for green, intelligent wireless access.

Technology Category

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

Application Category

• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems
• 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

The impressive growth of wireless data networks has recently led to increased attention to the issue of electromagnetic pollution and the fulfillment of electromagnetic field (EMF) exposure limits. This paper tackles the problem of power control in user-centric cell-free massive multiple-input-multiple-output (CF-mMIMO) systems under EMF constraints. Specifically, the power allocation maximizing the minimum data rate across users is derived for both the uplink and the downlink. To solve such optimization problems, two approaches are proposed, i.e., model-based and data-driven. The proposed model-based solutions for the downlink utilize successive convex optimization and the log-sum-exp approximation for the minimum of a discrete set, whereas ordinary techniques are employed for the uplink. With regard to data-driven solutions, solutions based on both end-to-end architectures and deep unfolding techniques are explored. Extensive numerical results confirm that the proposed model-based solutions effectively fulfill the EMF constraints while ensuring very good performance; moreover, the results show that the proposed data-driven approaches can tightly approximate the performance of model-based solutions but with much lower computational complexity.

Problem

• Optimizing power control in cell-free massive MIMO systems under EMF constraints
• Maximizing minimum user data rates for both uplink and downlink transmissions
• Developing model-based and data-driven approaches with reduced computational complexity

Innovation

• Model-based power control using successive convex optimization
• Data-driven solutions with deep unfolding techniques
• Uplink and downlink optimization under EMF constraints