IEICE TRANSACTIONS on Communications
Fair Deployment of an Unmanned Aerial Vehicle Base Station for Maximal Coverage
Summary :
Unmanned aerial vehicle mounted base stations (UAV-BSs) can provide wireless cellular service to ground users in a variety of scenarios. The efficient deployment of such UAV-BSs while optimizing the coverage area is one of the key challenges. We investigate the deployment of UAV-BS to maximize the coverage of ground users, and further analyzes the impact of the deployment of UAV-BS on the fairness of ground users. In this paper, we first calculated the location of the UAV-BS according to the QoS requirements of the ground users, and then the fairness of ground users is taken into account by calculating three different fairness indexes. The performance of two genetic algorithms, namely Standard Genetic Algorithm (SGA) and Multi-Population Genetic Algorithm (MPGA) are compared to solve the optimization problem of UAV-BS deployment. The simulations are presented showing that the performance of the two algorithms, and the fairness performance of the ground users is also given.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E102-B No.10 pp.2014-2020
- Publication Date
- 2019/10/01
- Publicized
- 2019/04/26
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.2018DRP0008
- Type of Manuscript
- Special Section PAPER (Special Section on Exploring Drone for Mobile Sensing, Coverage and Communications: Theory and Applications)
- Category
Authors
Yancheng CHEN
PLA Army Engineering University
Ning LI
PLA Army Engineering University
Xijian ZHONG
PLA Army Engineering University
Yan GUO
PLA Army Engineering University
Keyword
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Yancheng CHEN, Ning LI, Xijian ZHONG, Yan GUO, "Fair Deployment of an Unmanned Aerial Vehicle Base Station for Maximal Coverage" in IEICE TRANSACTIONS on Communications,
vol. E102-B, no. 10, pp. 2014-2020, October 2019, doi: 10.1587/transcom.2018DRP0008.
Abstract: Unmanned aerial vehicle mounted base stations (UAV-BSs) can provide wireless cellular service to ground users in a variety of scenarios. The efficient deployment of such UAV-BSs while optimizing the coverage area is one of the key challenges. We investigate the deployment of UAV-BS to maximize the coverage of ground users, and further analyzes the impact of the deployment of UAV-BS on the fairness of ground users. In this paper, we first calculated the location of the UAV-BS according to the QoS requirements of the ground users, and then the fairness of ground users is taken into account by calculating three different fairness indexes. The performance of two genetic algorithms, namely Standard Genetic Algorithm (SGA) and Multi-Population Genetic Algorithm (MPGA) are compared to solve the optimization problem of UAV-BS deployment. The simulations are presented showing that the performance of the two algorithms, and the fairness performance of the ground users is also given.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2018DRP0008/_p
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@ARTICLE{e102-b_10_2014,
author={Yancheng CHEN, Ning LI, Xijian ZHONG, Yan GUO, },
journal={IEICE TRANSACTIONS on Communications},
title={Fair Deployment of an Unmanned Aerial Vehicle Base Station for Maximal Coverage},
year={2019},
volume={E102-B},
number={10},
pages={2014-2020},
abstract={Unmanned aerial vehicle mounted base stations (UAV-BSs) can provide wireless cellular service to ground users in a variety of scenarios. The efficient deployment of such UAV-BSs while optimizing the coverage area is one of the key challenges. We investigate the deployment of UAV-BS to maximize the coverage of ground users, and further analyzes the impact of the deployment of UAV-BS on the fairness of ground users. In this paper, we first calculated the location of the UAV-BS according to the QoS requirements of the ground users, and then the fairness of ground users is taken into account by calculating three different fairness indexes. The performance of two genetic algorithms, namely Standard Genetic Algorithm (SGA) and Multi-Population Genetic Algorithm (MPGA) are compared to solve the optimization problem of UAV-BS deployment. The simulations are presented showing that the performance of the two algorithms, and the fairness performance of the ground users is also given.},
keywords={},
doi={10.1587/transcom.2018DRP0008},
ISSN={1745-1345},
month={October},}
Copy
TY - JOUR
TI - Fair Deployment of an Unmanned Aerial Vehicle Base Station for Maximal Coverage
T2 - IEICE TRANSACTIONS on Communications
SP - 2014
EP - 2020
AU - Yancheng CHEN
AU - Ning LI
AU - Xijian ZHONG
AU - Yan GUO
PY - 2019
DO - 10.1587/transcom.2018DRP0008
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E102-B
IS - 10
JA - IEICE TRANSACTIONS on Communications
Y1 - October 2019
AB - Unmanned aerial vehicle mounted base stations (UAV-BSs) can provide wireless cellular service to ground users in a variety of scenarios. The efficient deployment of such UAV-BSs while optimizing the coverage area is one of the key challenges. We investigate the deployment of UAV-BS to maximize the coverage of ground users, and further analyzes the impact of the deployment of UAV-BS on the fairness of ground users. In this paper, we first calculated the location of the UAV-BS according to the QoS requirements of the ground users, and then the fairness of ground users is taken into account by calculating three different fairness indexes. The performance of two genetic algorithms, namely Standard Genetic Algorithm (SGA) and Multi-Population Genetic Algorithm (MPGA) are compared to solve the optimization problem of UAV-BS deployment. The simulations are presented showing that the performance of the two algorithms, and the fairness performance of the ground users is also given.
ER -
English
