TY - GEN
T1 - User association and power control in cell-free massive MIMO with the APG method
AU - Hao, Chongzheng
AU - Vu, Tung T.
AU - Ngo, Hien Quoc
AU - Dao, Minh N.
AU - Dang, Xiaoyu
AU - Matthaiou, Michail
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/85178379973
UR - http://purl.org/au-research/grants/arc/DP230101749
U2 - 10.23919/EUSIPCO58844.2023.10289821
DO - 10.23919/EUSIPCO58844.2023.10289821
M3 - Conference proceeding contribution
AN - SCOPUS:85178379973
SN - 9798350328110
SP - 1469
EP - 1473
BT - 31st European Signal Processing Conference (EUSIPCO 2023)
PB - European Association for Signal Processing (EURASIP)
CY - Piscataway, NJ
T2 - 31st European Signal Processing Conference, EUSIPCO 2023
Y2 - 4 September 2023 through 8 September 2023
ER -