Joint CoMP Transmission for UAV-Aided Cognitive Satellite Terrestrial Networks

This paper investigates a novel architecture of coordinated multi-point (CoMP) transmission in the cognitive satellite-terrestrial network associated with an unmanned aerial vehicle (UAV). We consider the downlink communication where the UAV and base station (BS) cooperatively serve the terrestrial...

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Main Authors: Meng Hua, Yi Wang, Min Lin, Chunguo Li, Yongming Huang, Luxi Yang
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8611345/
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spelling doaj-97fb415e80744fc1ab71d35cf98c04f72021-03-29T22:35:55ZengIEEEIEEE Access2169-35362019-01-017149591496810.1109/ACCESS.2019.28929968611345Joint CoMP Transmission for UAV-Aided Cognitive Satellite Terrestrial NetworksMeng Hua0https://orcid.org/0000-0002-3121-6344Yi Wang1https://orcid.org/0000-0003-3833-4287Min Lin2Chunguo Li3Yongming Huang4https://orcid.org/0000-0003-3616-4616Luxi Yang5School of Information Science and Engineering, Southeast University, Nanjing, ChinaSchool of Electronics and Communication Engineering, Zhengzhou University of Aeronautics, Zhengzhou, ChinaKey Laboratory of Broadband Wireless Communication and Sensor Network Technology, Ministry of Education, Nanjing University of Posts and Telecommunications, Nanjing, ChinaSchool of Information Science and Engineering, Southeast University, Nanjing, ChinaSchool of Information Science and Engineering, Southeast University, Nanjing, ChinaSchool of Information Science and Engineering, Southeast University, Nanjing, ChinaThis paper investigates a novel architecture of coordinated multi-point (CoMP) transmission in the cognitive satellite-terrestrial network associated with an unmanned aerial vehicle (UAV). We consider the downlink communication where the UAV and base station (BS) cooperatively serve the terrestrial user by sharing the licensed satellite network spectrum. The goal of this paper is to maximize the achievable rate of the terrestrial user by jointly optimizing BS/UAV transmit power allocation and UAV trajectory, subjecting to the interference temperature threshold imposed on satellite network as well as UAV mobility constraint. The formulated problem is shown in a complicated non-convex form, which is hard to tackle. To this end, we decompose the original problem into two sub-problems, and the block coordinate descent method is employed to solve the two sub-problems alternately. Specifically, for the first sub-problem, the optimal BS/UAV transmit power is obtained with a given UAV trajectory by using the Lagrangian dual method. For the second sub-problem, the UAV trajectory is attained with a given BS/UAV power allocation by using the successive convex approximation technique. Simulation results show that our proposed joint CoMP transmission scheme significantly improves the terrestrial network throughput compared with other benchmark schemes.https://ieeexplore.ieee.org/document/8611345/Unmanned aerial vehiclesatellite-terrestrial networksUAV trajectorycoordinated multi-point
collection DOAJ
language English
format Article
sources DOAJ
author Meng Hua
Yi Wang
Min Lin
Chunguo Li
Yongming Huang
Luxi Yang
spellingShingle Meng Hua
Yi Wang
Min Lin
Chunguo Li
Yongming Huang
Luxi Yang
Joint CoMP Transmission for UAV-Aided Cognitive Satellite Terrestrial Networks
IEEE Access
Unmanned aerial vehicle
satellite-terrestrial networks
UAV trajectory
coordinated multi-point
author_facet Meng Hua
Yi Wang
Min Lin
Chunguo Li
Yongming Huang
Luxi Yang
author_sort Meng Hua
title Joint CoMP Transmission for UAV-Aided Cognitive Satellite Terrestrial Networks
title_short Joint CoMP Transmission for UAV-Aided Cognitive Satellite Terrestrial Networks
title_full Joint CoMP Transmission for UAV-Aided Cognitive Satellite Terrestrial Networks
title_fullStr Joint CoMP Transmission for UAV-Aided Cognitive Satellite Terrestrial Networks
title_full_unstemmed Joint CoMP Transmission for UAV-Aided Cognitive Satellite Terrestrial Networks
title_sort joint comp transmission for uav-aided cognitive satellite terrestrial networks
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2019-01-01
description This paper investigates a novel architecture of coordinated multi-point (CoMP) transmission in the cognitive satellite-terrestrial network associated with an unmanned aerial vehicle (UAV). We consider the downlink communication where the UAV and base station (BS) cooperatively serve the terrestrial user by sharing the licensed satellite network spectrum. The goal of this paper is to maximize the achievable rate of the terrestrial user by jointly optimizing BS/UAV transmit power allocation and UAV trajectory, subjecting to the interference temperature threshold imposed on satellite network as well as UAV mobility constraint. The formulated problem is shown in a complicated non-convex form, which is hard to tackle. To this end, we decompose the original problem into two sub-problems, and the block coordinate descent method is employed to solve the two sub-problems alternately. Specifically, for the first sub-problem, the optimal BS/UAV transmit power is obtained with a given UAV trajectory by using the Lagrangian dual method. For the second sub-problem, the UAV trajectory is attained with a given BS/UAV power allocation by using the successive convex approximation technique. Simulation results show that our proposed joint CoMP transmission scheme significantly improves the terrestrial network throughput compared with other benchmark schemes.
topic Unmanned aerial vehicle
satellite-terrestrial networks
UAV trajectory
coordinated multi-point
url https://ieeexplore.ieee.org/document/8611345/
work_keys_str_mv AT menghua jointcomptransmissionforuavaidedcognitivesatelliteterrestrialnetworks
AT yiwang jointcomptransmissionforuavaidedcognitivesatelliteterrestrialnetworks
AT minlin jointcomptransmissionforuavaidedcognitivesatelliteterrestrialnetworks
AT chunguoli jointcomptransmissionforuavaidedcognitivesatelliteterrestrialnetworks
AT yongminghuang jointcomptransmissionforuavaidedcognitivesatelliteterrestrialnetworks
AT luxiyang jointcomptransmissionforuavaidedcognitivesatelliteterrestrialnetworks
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