IEICE TRANSACTIONS on Communications
Access Point Selection Algorithm Based on Coevolution Particle Swarm in Cell-Free Massive MIMO Systems
Summary :
In this paper, we investigate the Access Point (AP) selection problem in Cell-Free Massive multiple-input multiple-output (MIMO) system. Firstly, we add a connecting coefficient to the uplink data transmission model. Then, the problem of AP selection is formulated as a discrete combinatorial optimization problem which can be dealt with by the particle swarm algorithm. However, when the number of optimization variables is large, the search efficiency of the traditional particle swarm algorithm will be significantly reduced. Then, we propose an ‘user-centric’ cooperative coevolution scheme which includes the proposed probability-based particle evolution strategy and random-sampling-based particle evaluation mechanism to deal with the search efficiency problem. Simulation results show that proposed algorithm has better performance than other existing algorithms.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E106-B No.7 pp.578-585
- Publication Date
- 2023/07/01
- Publicized
- 2023/01/13
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.2022EBP3125
- Type of Manuscript
- PAPER
- Category
- Antennas and Propagation
Authors
Hengzhong ZHI
Guangxi University,the Guangxi Key Laboratory of Multimedia Communications and Network Technology
Haibin WAN
Guangxi University,the Guangxi Key Laboratory of Multimedia Communications and Network Technology
Tuanfa QIN
Guangxi University,the Guangxi Key Laboratory of Multimedia Communications and Network Technology
Zhengqiang WANG
Chongqing University of Posts and Telecommunication
Keyword
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Hengzhong ZHI, Haibin WAN, Tuanfa QIN, Zhengqiang WANG, "Access Point Selection Algorithm Based on Coevolution Particle Swarm in Cell-Free Massive MIMO Systems" in IEICE TRANSACTIONS on Communications,
vol. E106-B, no. 7, pp. 578-585, July 2023, doi: 10.1587/transcom.2022EBP3125.
Abstract: In this paper, we investigate the Access Point (AP) selection problem in Cell-Free Massive multiple-input multiple-output (MIMO) system. Firstly, we add a connecting coefficient to the uplink data transmission model. Then, the problem of AP selection is formulated as a discrete combinatorial optimization problem which can be dealt with by the particle swarm algorithm. However, when the number of optimization variables is large, the search efficiency of the traditional particle swarm algorithm will be significantly reduced. Then, we propose an ‘user-centric’ cooperative coevolution scheme which includes the proposed probability-based particle evolution strategy and random-sampling-based particle evaluation mechanism to deal with the search efficiency problem. Simulation results show that proposed algorithm has better performance than other existing algorithms.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2022EBP3125/_p
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@ARTICLE{e106-b_7_578,
author={Hengzhong ZHI, Haibin WAN, Tuanfa QIN, Zhengqiang WANG, },
journal={IEICE TRANSACTIONS on Communications},
title={Access Point Selection Algorithm Based on Coevolution Particle Swarm in Cell-Free Massive MIMO Systems},
year={2023},
volume={E106-B},
number={7},
pages={578-585},
abstract={In this paper, we investigate the Access Point (AP) selection problem in Cell-Free Massive multiple-input multiple-output (MIMO) system. Firstly, we add a connecting coefficient to the uplink data transmission model. Then, the problem of AP selection is formulated as a discrete combinatorial optimization problem which can be dealt with by the particle swarm algorithm. However, when the number of optimization variables is large, the search efficiency of the traditional particle swarm algorithm will be significantly reduced. Then, we propose an ‘user-centric’ cooperative coevolution scheme which includes the proposed probability-based particle evolution strategy and random-sampling-based particle evaluation mechanism to deal with the search efficiency problem. Simulation results show that proposed algorithm has better performance than other existing algorithms.},
keywords={},
doi={10.1587/transcom.2022EBP3125},
ISSN={1745-1345},
month={July},}
Copy
TY - JOUR
TI - Access Point Selection Algorithm Based on Coevolution Particle Swarm in Cell-Free Massive MIMO Systems
T2 - IEICE TRANSACTIONS on Communications
SP - 578
EP - 585
AU - Hengzhong ZHI
AU - Haibin WAN
AU - Tuanfa QIN
AU - Zhengqiang WANG
PY - 2023
DO - 10.1587/transcom.2022EBP3125
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E106-B
IS - 7
JA - IEICE TRANSACTIONS on Communications
Y1 - July 2023
AB - In this paper, we investigate the Access Point (AP) selection problem in Cell-Free Massive multiple-input multiple-output (MIMO) system. Firstly, we add a connecting coefficient to the uplink data transmission model. Then, the problem of AP selection is formulated as a discrete combinatorial optimization problem which can be dealt with by the particle swarm algorithm. However, when the number of optimization variables is large, the search efficiency of the traditional particle swarm algorithm will be significantly reduced. Then, we propose an ‘user-centric’ cooperative coevolution scheme which includes the proposed probability-based particle evolution strategy and random-sampling-based particle evaluation mechanism to deal with the search efficiency problem. Simulation results show that proposed algorithm has better performance than other existing algorithms.
ER -
English
