User association and power control in cell-free massive MIMO with the APG method

Chongzheng Hao, Tung T. Vu, Hien Quoc Ngo, Minh N. Dao, Xiaoyu Dang, Michail Matthaiou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)
50 Downloads (Pure)

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.

Original languageEnglish
Title of host publicationProceedings of the 31st European Signal Processing Conference, EUSIPCO 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1469-1473
Number of pages5
ISBN (Electronic)9789464593600
ISBN (Print)9798350328110
DOIs
Publication statusPublished - 01 Nov 2023
Event31st European Signal Processing Conference 2023 - Helsinki, Finland
Duration: 04 Sept 202308 Sept 2023

Publication series

NameEUSIPCO Proceedings
ISSN (Print)2219-5491
ISSN (Electronic)2076-1465

Conference

Conference31st European Signal Processing Conference 2023
Abbreviated titleEUSIPCO 2023
Country/TerritoryFinland
CityHelsinki
Period04/09/202308/09/2023

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