Joint position optimization, user association, and resource allocation for load balancing in UAV-assisted wireless networks
Unbalanced traffic distribution in cellular networks results in congestion and degrades spectrum efficiency. To tackle this problem, we propose an Unmanned Aerial Vehicle (UAV)-assisted wireless network in which the UAV acts as an aerial relay to divert some traffic from the overloaded cell to its a...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co., Ltd.
2024-02-01
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| Series: | Digital Communications and Networks |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352864822000323 |
| _version_ | 1797249167313076224 |
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| author | Daosen Zhai Huan Li Xiao Tang Ruonan Zhang Haotong Cao |
| author_facet | Daosen Zhai Huan Li Xiao Tang Ruonan Zhang Haotong Cao |
| author_sort | Daosen Zhai |
| collection | DOAJ |
| description | Unbalanced traffic distribution in cellular networks results in congestion and degrades spectrum efficiency. To tackle this problem, we propose an Unmanned Aerial Vehicle (UAV)-assisted wireless network in which the UAV acts as an aerial relay to divert some traffic from the overloaded cell to its adjacent underloaded cell. To fully exploit its potential, we jointly optimize the UAV position, user association, spectrum allocation, and power allocation to maximize the sum-log-rate of all users in two adjacent cells. To tackle the complicated joint optimization problem, we first design a genetic-based algorithm to optimize the UAV position. Then, we simplify the problem by theoretical analysis and devise a low-complexity algorithm according to the branch-and-bound method, so as to obtain the optimal user association and spectrum allocation schemes. We further propose an iterative power allocation algorithm based on the sequential convex approximation theory. The simulation results indicate that the proposed UAV-assisted wireless network is superior to the terrestrial network in both utility and throughput, and the proposed algorithms can substantially improve the network performance in comparison with the other schemes. |
| first_indexed | 2024-04-24T20:26:11Z |
| format | Article |
| id | doaj.art-b7175e89eefc4f5c8bf038d23638d9c1 |
| institution | Directory Open Access Journal |
| issn | 2352-8648 |
| language | English |
| last_indexed | 2024-04-24T20:26:11Z |
| publishDate | 2024-02-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Digital Communications and Networks |
| spelling | doaj.art-b7175e89eefc4f5c8bf038d23638d9c12024-03-22T05:39:57ZengKeAi Communications Co., Ltd.Digital Communications and Networks2352-86482024-02-011012537Joint position optimization, user association, and resource allocation for load balancing in UAV-assisted wireless networksDaosen Zhai0Huan Li1Xiao Tang2Ruonan Zhang3Haotong Cao4School of Electronics and Information, Northwestern Polytechnical University, Xi'an, 710072, China; State Key Laboratory of Integrated Services Networks, Xidian University, Xi'an, 710071, ChinaSchool of Electronics and Information, Northwestern Polytechnical University, Xi'an, 710072, ChinaSchool of Electronics and Information, Northwestern Polytechnical University, Xi'an, 710072, ChinaSchool of Electronics and Information, Northwestern Polytechnical University, Xi'an, 710072, ChinaDepartment of Computing, Hong Kong Polytechnic University, Hong Kong SAR, China; Corresponding author.Unbalanced traffic distribution in cellular networks results in congestion and degrades spectrum efficiency. To tackle this problem, we propose an Unmanned Aerial Vehicle (UAV)-assisted wireless network in which the UAV acts as an aerial relay to divert some traffic from the overloaded cell to its adjacent underloaded cell. To fully exploit its potential, we jointly optimize the UAV position, user association, spectrum allocation, and power allocation to maximize the sum-log-rate of all users in two adjacent cells. To tackle the complicated joint optimization problem, we first design a genetic-based algorithm to optimize the UAV position. Then, we simplify the problem by theoretical analysis and devise a low-complexity algorithm according to the branch-and-bound method, so as to obtain the optimal user association and spectrum allocation schemes. We further propose an iterative power allocation algorithm based on the sequential convex approximation theory. The simulation results indicate that the proposed UAV-assisted wireless network is superior to the terrestrial network in both utility and throughput, and the proposed algorithms can substantially improve the network performance in comparison with the other schemes.http://www.sciencedirect.com/science/article/pii/S2352864822000323Load balanceUnmanned aerial vehicleUser associationResource management |
| spellingShingle | Daosen Zhai Huan Li Xiao Tang Ruonan Zhang Haotong Cao Joint position optimization, user association, and resource allocation for load balancing in UAV-assisted wireless networks Digital Communications and Networks Load balance Unmanned aerial vehicle User association Resource management |
| title | Joint position optimization, user association, and resource allocation for load balancing in UAV-assisted wireless networks |
| title_full | Joint position optimization, user association, and resource allocation for load balancing in UAV-assisted wireless networks |
| title_fullStr | Joint position optimization, user association, and resource allocation for load balancing in UAV-assisted wireless networks |
| title_full_unstemmed | Joint position optimization, user association, and resource allocation for load balancing in UAV-assisted wireless networks |
| title_short | Joint position optimization, user association, and resource allocation for load balancing in UAV-assisted wireless networks |
| title_sort | joint position optimization user association and resource allocation for load balancing in uav assisted wireless networks |
| topic | Load balance Unmanned aerial vehicle User association Resource management |
| url | http://www.sciencedirect.com/science/article/pii/S2352864822000323 |
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