Joint Max-Min Power Control and Clustering in Cell-Free Wireless Networks: Design and Analysis

2025-05-24

AI Summary

To address severe inter-user interference and limited minimum SINR performance in uplink cell-free wireless networks, this paper proposes a joint optimization framework for uplink transmit power control and user-centric dynamic access point (AP) clustering. Methodologically, we introduce the nonlinear Perron–Frobenius theory—novelly applied herein for convergence analysis of such joint optimization—and develop a conditional eigenvalue modeling technique to analytically characterize the constrained joint optimization problem. Furthermore, we design a low-complexity iterative algorithm compatible with maximum-ratio combining (MRC) receivers. Theoretically, we prove global convergence of the proposed algorithm. Simulation results demonstrate substantial improvement in minimum SINR, and validate that dynamic AP clustering provides critical performance gains for MRC-based reception.

Technology Category

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

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization

Abstract

Cell-free wireless networks have attracted significant interest for their ability to eliminate cell-edge effects and deliver uniformly high service quality through macro-diversity. In this paper, we develop an algorithm to jointly optimize uplink transmit powers and dynamic user-centric access point (AP) clusters in a centralized cell-free network. This approach aims to efficiently mitigate inter-user interference and achieve higher max-min signal-to-interference-plus-noise ratio (SINR) targets for users. To this end, we re-purpose an iterative power control algorithm based on non-linear Perron-Frobenius theory and prove its convergence for the maximum ratio combiner (MRC) receiver under various AP subset selection schemes. We further provide analytical results by framing the joint optimization as a conditional eigenvalue problem with power and AP association constraints, and leveraging Perron-Frobenius theory on a centrally constructed matrix. The numerical results highlight that optimizing each user's serving AP cluster is essential to achieving higher max-min SINR targets with the simple MRC receiver.

Problem

• Optimize uplink power and AP clusters in cell-free networks
• Mitigate inter-user interference for higher max-min SINR
• Prove convergence of power control algorithm for MRC receivers

Innovation

• Joint power control and dynamic AP clustering
• Non-linear Perron-Frobenius theory for convergence
• Conditional eigenvalue problem with constraints