Resource optimization for energy‐efficient NOMA‐based multi‐UAV‐enabled relaying networks
Abstract Owing to the advantages of low cost, flexibility, and the transmission characteristics of air–ground (AG) channels, using the unmanned aerial vehicle (UAV) as mobile relay to assist wireless communication has received significant interest recently. A green non‐orthogonal multiple access (NO...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-07-01
|
| Series: | IET Communications |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/cmu2.12623 |
| _version_ | 1797788905623257088 |
|---|---|
| author | Hang Hu Qi An Yangchao Huang Ranran Gu Senhao Zhao Shihao Liu |
| author_facet | Hang Hu Qi An Yangchao Huang Ranran Gu Senhao Zhao Shihao Liu |
| author_sort | Hang Hu |
| collection | DOAJ |
| description | Abstract Owing to the advantages of low cost, flexibility, and the transmission characteristics of air–ground (AG) channels, using the unmanned aerial vehicle (UAV) as mobile relay to assist wireless communication has received significant interest recently. A green non‐orthogonal multiple access (NOMA)‐based multi‐UAV‐enabled relaying system with different rate requirements is proposed here. To improve energy efficiency (EE) of the UAV relays, an optimization problem for user grouping, UAV trajectory design and resource allocation under the constraints of information causality constraint, UAVs' maximum service capacity, maximum transmit power constraint, and different communication rate requirements of the mobile users (MUs) is formulated. According to the grouping results, the UAVs' trajectory and power allocation by Dinkelbach method, successive convex approximation, and condensation algorithm are alternately optimized. To solve this highly coupled non‐linear mixed integer programming problem, a graph‐based grouping algorithm is proposed to reduce the relative distance between the UAV relay and the MU. Simulation results show that the proposed optimization algorithm can effectively improve the EE performance of this NOMA‐based multi‐UAV‐enabled relaying system. |
| first_indexed | 2024-03-13T01:43:12Z |
| format | Article |
| id | doaj.art-e721621b4e3d4b2382df66ec0acab8b5 |
| institution | Directory Open Access Journal |
| issn | 1751-8628 1751-8636 |
| language | English |
| last_indexed | 2024-03-13T01:43:12Z |
| publishDate | 2023-07-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Communications |
| spelling | doaj.art-e721621b4e3d4b2382df66ec0acab8b52023-07-03T11:41:05ZengWileyIET Communications1751-86281751-86362023-07-0117111288129910.1049/cmu2.12623Resource optimization for energy‐efficient NOMA‐based multi‐UAV‐enabled relaying networksHang Hu0Qi An1Yangchao Huang2Ranran Gu3Senhao Zhao4Shihao Liu5College of Information and Navigation Air Force Engineering University Xi'an ChinaCollege of Graduate School Air Force Engineering University Xi'an ChinaCollege of Information and Navigation Air Force Engineering University Xi'an ChinaAir Force Command College Beijing ChinaCollege of Graduate School Air Force Engineering University Xi'an ChinaCollege of Graduate School Air Force Engineering University Xi'an ChinaAbstract Owing to the advantages of low cost, flexibility, and the transmission characteristics of air–ground (AG) channels, using the unmanned aerial vehicle (UAV) as mobile relay to assist wireless communication has received significant interest recently. A green non‐orthogonal multiple access (NOMA)‐based multi‐UAV‐enabled relaying system with different rate requirements is proposed here. To improve energy efficiency (EE) of the UAV relays, an optimization problem for user grouping, UAV trajectory design and resource allocation under the constraints of information causality constraint, UAVs' maximum service capacity, maximum transmit power constraint, and different communication rate requirements of the mobile users (MUs) is formulated. According to the grouping results, the UAVs' trajectory and power allocation by Dinkelbach method, successive convex approximation, and condensation algorithm are alternately optimized. To solve this highly coupled non‐linear mixed integer programming problem, a graph‐based grouping algorithm is proposed to reduce the relative distance between the UAV relay and the MU. Simulation results show that the proposed optimization algorithm can effectively improve the EE performance of this NOMA‐based multi‐UAV‐enabled relaying system.https://doi.org/10.1049/cmu2.12623radiocommunicationtelecommunication networks |
| spellingShingle | Hang Hu Qi An Yangchao Huang Ranran Gu Senhao Zhao Shihao Liu Resource optimization for energy‐efficient NOMA‐based multi‐UAV‐enabled relaying networks IET Communications radiocommunication telecommunication networks |
| title | Resource optimization for energy‐efficient NOMA‐based multi‐UAV‐enabled relaying networks |
| title_full | Resource optimization for energy‐efficient NOMA‐based multi‐UAV‐enabled relaying networks |
| title_fullStr | Resource optimization for energy‐efficient NOMA‐based multi‐UAV‐enabled relaying networks |
| title_full_unstemmed | Resource optimization for energy‐efficient NOMA‐based multi‐UAV‐enabled relaying networks |
| title_short | Resource optimization for energy‐efficient NOMA‐based multi‐UAV‐enabled relaying networks |
| title_sort | resource optimization for energy efficient noma based multi uav enabled relaying networks |
| topic | radiocommunication telecommunication networks |
| url | https://doi.org/10.1049/cmu2.12623 |
| work_keys_str_mv | AT hanghu resourceoptimizationforenergyefficientnomabasedmultiuavenabledrelayingnetworks AT qian resourceoptimizationforenergyefficientnomabasedmultiuavenabledrelayingnetworks AT yangchaohuang resourceoptimizationforenergyefficientnomabasedmultiuavenabledrelayingnetworks AT ranrangu resourceoptimizationforenergyefficientnomabasedmultiuavenabledrelayingnetworks AT senhaozhao resourceoptimizationforenergyefficientnomabasedmultiuavenabledrelayingnetworks AT shihaoliu resourceoptimizationforenergyefficientnomabasedmultiuavenabledrelayingnetworks |