Joint user association and power control for cell-free massive MIMO

Chongzheng Hao*, Thanh Tung Vu, Hien-Quoc Ngo, Minh N. Dao, Xiaoyu Dang, Chenghua Wang, Michalis Matthaiou

*Corresponding author for this work

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This work proposes novel approaches that jointly design user equipment (UE) association and power control (PC) in a downlink user-centric cell-free massive multiple-input multiple-output (CFmMIMO) network, where each UE is only served by a set of access points (APs) for reducing the fronthaul signalling and computational complexity. In order to maximize the sum spectral efficiency (SE) of the UEs, we formulate a mixed-integer nonconvex optimization problem under constraints on the per-AP transmit power, quality-of-service rate requirements, maximum fronthaul signalling load, and maximum number of UEs served by each AP. In order to efficiently solve the formulated problem, we propose two different schemes according to the different sizes of the CFmMIMO systems. For small-scale CFmMIMO systems, we present a successive convex approximation (SCA) method to obtain a stationary solution and also develop a learning-based method (JointCFNet) to reduce the computational complexity. For large-scale CFmMIMO systems, we propose a low-complexity suboptimal algorithm using accelerated projected gradient (APG) techniques. Numerical results show that our JointCFNet can yield similar performance and significantly decrease the run time compared with the SCA algorithm in small-scale systems. The presented APG approach is confirmed to run much faster than the SCA algorithm in large-scale systems while obtaining an SE performance close to that of the SCA approach. Moreover, the median sum SE of the APG method is up to about 2.8 fold higher than that of the heuristic baseline scheme.
Original languageEnglish
Journal IEEE Internet of Things Journal
Early online date09 Jan 2024
Publication statusEarly online date - 09 Jan 2024
Event2023 IEEE European Signal Processing Conference (EUSIPCO) - Helsinki, Finland
Duration: 04 Sept 202308 Sept 2023


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