@inproceedings{507e16e590c44364b3f061fe11864f66,
title = "User association and power control in cell-free massive MIMO with the APG method",
abstract = "This work proposes a novel approach that jointly designs user equipment (UE) association and power control in a downlink user-centric cell-free massive multiple-input multiple-output (CFmMIMO) network, where each access point (AP) only serves only a set of its associated UEs for reducing the backhaul signaling and computational complexity. Aiming at maximizing the sum spectral efficiency (SE) of the UEs, we formulate a mixed-integer nonconvex optimization problem with quality-of-service and power constraints. Then, we propose a novel accelerated projected gradient (APG) algorithm to obtain a suboptimal solution to the formulated problem. The proposed algorithm is suitable for large-scale CFmMIMO systems with low complexity. Numerical results show that the 50%-likely SE of the proposed method is up to about 2.8 fold higher than that of the heuristic baseline scheme. The APG approach is confirmed to run much faster than the successive convex approximation (SCA) algorithm while obtaining a SE performance close to the SCA approach.",
author = "Chongzheng Hao and Vu, {Tung T.} and Ngo, {Hien Quoc} and Dao, {Minh N.} and Xiaoyu Dang and Michail Matthaiou",
year = "2023",
month = nov,
day = "1",
doi = "10.23919/EUSIPCO58844.2023.10289821",
language = "English",
isbn = "9798350328110",
series = "EUSIPCO Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1469--1473",
booktitle = "Proceedings of the 31st European Signal Processing Conference, EUSIPCO 2023",
address = "United States",
note = "31st European Signal Processing Conference 2023, EUSIPCO 2023 ; Conference date: 04-09-2023 Through 08-09-2023",
}