TY - GEN
T1 - Towards 3D deployment of UAV base stations in uneven terrain
AU - He, Xiaofei
AU - Yu, Wei
AU - Xu, Hansong
AU - Lin, Jie
AU - Yang, Xinyu
AU - Lu, Chao
AU - Fu, Xinwen
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/10/9
Y1 - 2018/10/9
N2 - Unmanned Aerial Vehicles (UAVs), also known as drones, have become a new paradigm to provide emergency wireless communication infrastructure when conventional base stations are damaged or unavailable. In this paper, we propose new schemes to enable the 3D deployment of drones, which can provide network coverage and connectivity services for users located in uneven terrain. We formalize two models, including optimal coverage model and optimal connectivity model, which belong to NP-hard. To be specific, we first consider both the quality of service (QoS) requirements of users and the capacity of drones. We then formalize the problem and design a heuristic scheme, called Particle Swarm Optimization (PSO) algorithm to achieve a cost-effective solution. We also address the optimal connectivity problem in a scenario, in which a number of isolated local networks have been established by users through ad hoc communication and/or device-to-device (D2D) communication. We further develop the cost-effective heuristic algorithm to effectively minimize the total number of required drones. Via extensive performance evaluation, our experimental results demonstrate that the proposed schemes can achieve the effective deployment of drones for users in uneven terrain with respect to the number of required drones.
AB - Unmanned Aerial Vehicles (UAVs), also known as drones, have become a new paradigm to provide emergency wireless communication infrastructure when conventional base stations are damaged or unavailable. In this paper, we propose new schemes to enable the 3D deployment of drones, which can provide network coverage and connectivity services for users located in uneven terrain. We formalize two models, including optimal coverage model and optimal connectivity model, which belong to NP-hard. To be specific, we first consider both the quality of service (QoS) requirements of users and the capacity of drones. We then formalize the problem and design a heuristic scheme, called Particle Swarm Optimization (PSO) algorithm to achieve a cost-effective solution. We also address the optimal connectivity problem in a scenario, in which a number of isolated local networks have been established by users through ad hoc communication and/or device-to-device (D2D) communication. We further develop the cost-effective heuristic algorithm to effectively minimize the total number of required drones. Via extensive performance evaluation, our experimental results demonstrate that the proposed schemes can achieve the effective deployment of drones for users in uneven terrain with respect to the number of required drones.
KW - Coverage and Connectivity
KW - Mobile Networks
KW - Network Performance Optimization
KW - Unmanned Aerial Vehicles
UR - https://www.scopus.com/pages/publications/85060436344
U2 - 10.1109/ICCCN.2018.8487319
DO - 10.1109/ICCCN.2018.8487319
M3 - 会议稿件
AN - SCOPUS:85060436344
T3 - Proceedings - International Conference on Computer Communications and Networks, ICCCN
BT - ICCCN 2018 - 27th International Conference on Computer Communications and Networks
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 27th International Conference on Computer Communications and Networks, ICCCN 2018
Y2 - 30 July 2018 through 2 August 2018
ER -