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Genetic algorithm combined with ray tracer for optimizing cell-free mMIMO topology in a confined environment

Ke Shen (UGent) , Toon De Pessemier (UGent) , Luc Martens (UGent) , Wout Joseph (UGent) and Yang Miao
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Abstract
This paper proposes a customized genetic algorithm (GA) to generate the optimal cell-free topology for multi-user massive MIMO (mMIMO) in a confined environment. As far as we know, it is beyond the literature and is the first attempt to apply GA in optimizing the base station (BS) antenna placement for cell-free mMIMO. The BS antennas' placement is encoded with an adjusted binary matrix representation, which is straightforward for the subsequent genetic operations. The explored candidates by GA can evolve beyond the parents, where the fitness of individuals is evaluated dynamically via a ray tracer channel simulator. Accelerated by a warm start strategy and elitist replacement, the proposed customized GA provides near-optimal results in experiments, applicable to generic environment with multiple mobile users and different signal-to-noise ratios.
Keywords
MASSIVE MIMO, SELECTION, PREDICTION, CROSSOVER, Massive MIMO, multi-user, topology, focusing performance, radio, propagation channel, ray tracer, genetic algorithm

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MLA
Shen, Ke, et al. “Genetic Algorithm Combined with Ray Tracer for Optimizing Cell-Free MMIMO Topology in a Confined Environment.” 2021 15TH EUROPEAN CONFERENCE ON ANTENNAS AND PROPAGATION (EUCAP), IEEE, 2021, doi:10.23919/EuCAP51087.2021.9410934.
APA
Shen, K., De Pessemier, T., Martens, L., Joseph, W., & Miao, Y. (2021). Genetic algorithm combined with ray tracer for optimizing cell-free mMIMO topology in a confined environment. 2021 15TH EUROPEAN CONFERENCE ON ANTENNAS AND PROPAGATION (EUCAP). Presented at the 15th European Conference on Antennas and Propagation (EuCAP), Online. https://doi.org/10.23919/EuCAP51087.2021.9410934
Chicago author-date
Shen, Ke, Toon De Pessemier, Luc Martens, Wout Joseph, and Yang Miao. 2021. “Genetic Algorithm Combined with Ray Tracer for Optimizing Cell-Free MMIMO Topology in a Confined Environment.” In 2021 15TH EUROPEAN CONFERENCE ON ANTENNAS AND PROPAGATION (EUCAP). IEEE. https://doi.org/10.23919/EuCAP51087.2021.9410934.
Chicago author-date (all authors)
Shen, Ke, Toon De Pessemier, Luc Martens, Wout Joseph, and Yang Miao. 2021. “Genetic Algorithm Combined with Ray Tracer for Optimizing Cell-Free MMIMO Topology in a Confined Environment.” In 2021 15TH EUROPEAN CONFERENCE ON ANTENNAS AND PROPAGATION (EUCAP). IEEE. doi:10.23919/EuCAP51087.2021.9410934.
Vancouver
1.
Shen K, De Pessemier T, Martens L, Joseph W, Miao Y. Genetic algorithm combined with ray tracer for optimizing cell-free mMIMO topology in a confined environment. In: 2021 15TH EUROPEAN CONFERENCE ON ANTENNAS AND PROPAGATION (EUCAP). IEEE; 2021.
IEEE
[1]
K. Shen, T. De Pessemier, L. Martens, W. Joseph, and Y. Miao, “Genetic algorithm combined with ray tracer for optimizing cell-free mMIMO topology in a confined environment,” in 2021 15TH EUROPEAN CONFERENCE ON ANTENNAS AND PROPAGATION (EUCAP), Online, 2021.
@inproceedings{8728356,
  abstract     = {{This paper proposes a customized genetic algorithm (GA) to generate the optimal cell-free topology for multi-user massive MIMO (mMIMO) in a confined environment. As far as we know, it is beyond the literature and is the first attempt to apply GA in optimizing the base station (BS) antenna placement for cell-free mMIMO. The BS antennas' placement is encoded with an adjusted binary matrix representation, which is straightforward for the subsequent genetic operations. The explored candidates by GA can evolve beyond the parents, where the fitness of individuals is evaluated dynamically via a ray tracer channel simulator. Accelerated by a warm start strategy and elitist replacement, the proposed customized GA provides near-optimal results in experiments, applicable to generic environment with multiple mobile users and different signal-to-noise ratios.}},
  author       = {{Shen, Ke and De Pessemier, Toon and Martens, Luc and Joseph, Wout and Miao, Yang}},
  booktitle    = {{2021 15TH EUROPEAN CONFERENCE ON ANTENNAS AND PROPAGATION (EUCAP)}},
  isbn         = {{9788831299022}},
  issn         = {{2164-3342}},
  keywords     = {{MASSIVE MIMO,SELECTION,PREDICTION,CROSSOVER,Massive MIMO,multi-user,topology,focusing performance,radio,propagation channel,ray tracer,genetic algorithm}},
  language     = {{eng}},
  location     = {{Online}},
  pages        = {{5}},
  publisher    = {{IEEE}},
  title        = {{Genetic algorithm combined with ray tracer for optimizing cell-free mMIMO topology in a confined environment}},
  url          = {{http://doi.org/10.23919/EuCAP51087.2021.9410934}},
  year         = {{2021}},
}

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