Performance, fairness, and tradeoff in UAV swarm underlaid mmWave cellular networks with directional antennas |
|
Author: | Yang, Bin1,2; Taleb, Tarik2,3,4; Shen, Yulong5; |
Organizations: |
1School of Computer and Information Engineering, Chuzhou University, 239000 Anhui, China 2Department of Communications and Networking, School of Electrical Engineering, Aalto University, 02150 Espoo, Finland 3Information Technology and Electrical Engineering, Oulu University, 90570 Oulu, Finland
4Department of Computer and Information Security, Sejong University, Seoul, 05006 South Korea
5School of Computer Science and Technology, Xidian University, 710071 Shaanxi, China 6School of Systems Information Science, Future University Hakodate, 116-2 Kamedanakano-cho, Hakodate, Hokkaido, 041- 8655, Japan 7College of Information Science and Engineering, Henan University of Technology, 450001 Henan, China |
Format: | article |
Version: | accepted version |
Access: | open |
Online Access: | PDF Full Text (PDF, 1.8 MB) |
Persistent link: | http://urn.fi/urn:nbn:fi-fe2021060333335 |
Language: | English |
Published: |
Institute of Electrical and Electronics Engineers,
2021
|
Publish Date: | 2021-06-03 |
Description: |
AbstractUnmanned aerial vehicle (UAV) swarm connected to millimeter wave (mmWave) cellular networks is emerging as a new promising solution to provide ubiquitous high-speed and long distance wireless communication services for supporting various applications. To satisfy different quality of service (QoS) requirements in future large-scale applications of such networks, this article investigates the rate performance, fairness and their tradeoff in the networks with directional antennas in terms of sum-rate maximization, fairness index maximization, max-min fair rate and proportional fairness. We first consider a more realistic mmWave 3D directional antenna array model for UAVs and base station (BS), where the antenna gain depends on the radiation angle of the antenna array. Based on this antenna array model, we formulate the performance, fairness and their tradeoff as four constrained optimization problems, and propose corresponding iterative algorithm to solve these problems by jointly optimizing elevation angle, azimuth angle and height of antenna array at BS in the downlink transmission scenario. Furthermore, we also explore them in uplink transmission scenario, where the interference issue among links is carefully considered. Finally, according to the sum rate, minimum rate and fairness index under each optimization problem, numerical results are provided to illustrate the impacts of network parameters on the performance, fairness and their tradeoff, and also to reveal new findings under both downlink and uplink transmission scenarios, respectively. see all
|
Series: |
IEEE transactions on wireless communications |
ISSN: | 1536-1276 |
ISSN-E: | 1558-2248 |
ISSN-L: | 1536-1276 |
Volume: | 20 |
Issue: | 4 |
Pages: | 2383 - 2397 |
DOI: | 10.1109/TWC.2020.3041800 |
OADOI: | https://oadoi.org/10.1109/TWC.2020.3041800 |
Type of Publication: |
A1 Journal article – refereed |
Field of Science: |
213 Electronic, automation and communications engineering, electronics |
Subjects: | |
Copyright information: |
© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |