无人机辅助蜂窝网络的模式选择与资源优化

冯大权; 郑灿健; 孔祥琦

doi:10.11959/j.issn.2096-3750.2024.00380

您当前的位置：

首页 >

文章列表页 >

无人机辅助蜂窝网络的模式选择与资源优化

理论与技术 | 更新时间：2024-06-05

- 无人机辅助蜂窝网络的模式选择与资源优化
- Mode selection and resource optimization for UAV-assisted cellular networks
- 物联网学报 2024年8卷第1期页码：29-39
- 作者机构：
  
  1. 深圳大学电子与信息工程学院，广东深圳 518055
  2. 哈尔滨工业大学（深圳）电子与信息工程学院，广东深圳 518060
  3. 国家无线电监测中心检测中心，北京 100041
- 作者简介：
  
  [ "冯大权（1986- ），男，博士，深圳大学电子与信息工程学院副教授，主要研究方向为超可靠低时延通信、移动边缘计算和大规模物联网等" ]
  [ "郑灿健（1992- ），男，哈尔滨工业大学（深圳）电子与信息工程学院博士生，主要研究方向为超可靠低时延通信、短包通信、超密集网络等" ]
  [ "孔祥琦（1995- ），女，国家无线电监测中心检测中心工程师，主要研究方向为无线电设备检测、无线电频谱管理等" ]
- 基金信息：
  
  国家重点研发计划;The National Key Research and Development Program of China(2020YFB1807601);广东省重点研发计划;The Key Research and Development Program of Guangdong(2022B0101010001);深圳市科技计划;The Shenzhen Science and Technology Program(JCYJ20210324095209025)
- DOI：10.11959/j.issn.2096-3750.2024.00380
  中图分类号： TN92
- 纸质出版日期：2024-03-30，
  
  网络出版日期：2024-03，
- 稿件说明：
移动端阅览
冯大权, 郑灿健, 孔祥琦. 无人机辅助蜂窝网络的模式选择与资源优化[J]. 物联网学报, 2024,8(1):29-39.

DAQUAN FENG, CANJIAN ZHENG, XIANGQI KONG. Mode selection and resource optimization for UAV-assisted cellular networks. [J]. Chinese journal on internet of things, 2024, 8(1): 29-39.
冯大权, 郑灿健, 孔祥琦. 无人机辅助蜂窝网络的模式选择与资源优化[J]. 物联网学报, 2024,8(1):29-39. DOI： 10.11959/j.issn.2096-3750.2024.00380.

DAQUAN FENG, CANJIAN ZHENG, XIANGQI KONG. Mode selection and resource optimization for UAV-assisted cellular networks. [J]. Chinese journal on internet of things, 2024, 8(1): 29-39. DOI： 10.11959/j.issn.2096-3750.2024.00380.

摘要

研究了无人机（UAV

unmanned aerial vehicle）与蜂窝网络共存下的无线通信资源分配和优化方案。为了提高网络频谱利用率，无人机用户以全双工（FD

full duplex）或半双工（HD

half duplex）设备对设备（D2D

device-to-device）技术复用蜂窝频谱资源接入网络。此外，构造了一个联合接入控制、模式选择、功率控制和资源分配优化问题最大化网络的整体吞吐量，并保证无人机用户和地面蜂窝用户的服务质量要求。为解决这个问题，首先利用凸优化的第一阶段方法分别对全双工和半双工两种设备对设备模式进行接入控制和可行性判定。然后，对可接入无人机用户对使用凸凹过程（CCCP

convex and concave procedure）迭代算法求解功率控制问题。利用该局部最优值，原优化问题可以简化为加权最大化问题。最后，通过库恩-芒克斯（KM

Kuhn-Munrkes）算法对最优信道资源进行匹配，获得系统的全局最优吞吐量值。数值结果表明，所提方案能显著提高系统性能。

Abstract

The resource allocation and optimization scheme was studied in a coexistence scenario of unmanned aerial vehicle (UAV) and cellular communication network.To improve spectrum efficiency of the system

UAV users could reuse the cellular spectrum resources to access the network through full duplex or half duplex device-to-device technique.Additionally

a joint access control

mode selection

power control and resource allocation optimization problem was formulated to maximize the overall throughput of the network while ensuring quality of service requirements for both UAV users and ground cellular users.Specifically

the phase 1 method in the convex optimization was adopted for access control and feasibility check

and then the convex and concave procedure (CCCP) iterative algorithm was used to solve the power control problem for feasible UAV user pairs.By using this local optimum value

the original optimization problem can be simplified into a weighted maximization problem.Finally

the Kuhn-Munkres (KM) algorithm was used to match the optimal channel resources and obtain the global optimal throughput value of the system.Numerical results show that the proposed scheme can significantly improve the performance of system.

关键词

无人机通信全双工设备对设备技术模式选择功率控制资源分配与优化

Keywords

unmanned aerial vehicle communicationfull duplex device to device techniquemode selectionpower controlresources allocation and optimization

references

LI B, FEI Z S, ZHANG Y . UAV communications for 5G and beyond:recent advances and future trends[J]. IEEE Internet of Things Journal, 2019,6(2): 2241-2263.

ZENG Y, LYU J B, ZHANG R . Cellular-connected UAV:potential,challenges,and promising technologies[J]. IEEE Wireless Communications, 2019,26(1): 120-127.

ULLAH Z, AL-TURJMAN F, MOSTARDA L . Cognition in UAVaided 5G and beyond communications:a survey[J]. IEEE Transactions on Cognitive Communications and Networking, 2020,6(3): 872-891.

FENG D Q, LAI L F, LUO J J ,et al. Ultra-reliable and lowlatency communications:applications,opportunities and challenges[J]. Science China Information Sciences, 2021,64(2): 1-12.

WU H C, WEI Z Q, HOU Y Z ,et al. Cell-edge user offloading via flying UAV in non-uniform heterogeneous cellular networks[J]. IEEE Transactions on Wireless Communications, 2020,19(4): 2411-2426.

ZHOU H, WANG Z N, MIN G Y ,et al. UAV-aided computation offloading in mobile-edge computing networks:a stackelberg game approach[J]. IEEE Internet of Things Journal, 2023,10(8): 6622-6633.

曾耀平, 夏玉婷, 江伟伟 ,等. 加权能耗最小化的无人机辅助移动边缘计算策略研究[J]. 计算机工程, 2023: 1-11.

ZENG Y P, XIA Y T, JIANG W W ,et al. UAV-assisted mobile edge computing strategy for weighted energy minimization[J]. Computer Engineering, 2023: 1-11.

ZHANG Q Q, MOZAFFARI M, SAAD W ,et al. Machine learning for predictive on-demand deployment of uavs for wireless communications[C]// Proceedings of 2018 IEEE Global Communications Conference (GLOBECOM). Piscataway:IEEE Press, 2019: 1-6.

TANG H Y, WU Q Q, LI B Q . An efficient solution for joint power and trajectory optimization in UAV-enabled wireless network[J]. IEEE Access, 2019,7: 59640-59652.

BITHAS P S, NIKOLAIDIS V, KANATAS A G ,et al. UAV-toground communications:channel modeling and UAV selection[J]. IEEE Transactions on Communications, 2020,68(8): 5135-5144.

YE J, ZHANG C, LEI H J ,et al. Secure UAV-to-UAV systems with spatially random UAVs[J]. IEEE Wireless Communications Letters, 2019,8(2): 564-567.

吕鑫, 黎海涛, 黄嘉伟 . 软件定义UAV网络的自适应QoS机制研究[J]. 中国电子科学研究院学报, 2023,18(8): 717-723.

LYU X, LI H T, HUANG J W . Research on adaptive QoS mechanism for software defined UAV network[J]. Journal of China Academy of Electronics and Information Technology, 2023,18(8): 717-723.

LIN X H, SU G C, CHEN B ,et al. Striking a balance between system throughput and energy efficiency for UAV-IoT systems[J]. IEEE Internet of Things Journal, 2019,6(6): 10519-10533.

ABD-ELMAGID M A, DHILLON H S . Average peak age-ofinformation minimization in UAV-assisted IoT networks[J]. IEEE Transactions on Vehicular Technology, 2019,68(2): 2003-2008.

ZHENG C J, FENG D Q, ZHANG S L ,et al. Energy efficient V2X-enabled communications in cellular networks[J]. IEEE Transactions on Vehicular Technology, 2019,68(1): 554-564.

HU X Y, WONG K K, YANG K ,et al. UAV-assisted relaying and edge computing:scheduling and trajectory optimization[J]. IEEE Transactions on Wireless Communications, 2019,18(10): 4738-4752.

LI J, YI C Y, CHEN J Y ,et al. Joint trajectory planning,application placement,and energy renewal for UAV-assisted MEC:a triple-learner-based approach[J]. IEEE Internet of Things Journal, 2023,10(15): 13622-13636.

CHEN X Y, ZHAO N, CHANG Z ,et al. UAV-aided secure shortpacket data collection and transmission[J]. IEEE Transactions on Communications, 2023,71(4): 2475-2486.

HAMMAMI M, CHAIEB C, AJIB W ,et al. UAV-assisted wireless networks for stringent applications:resource allocation and positioning[C]// Proceedings of 2023 IEEE Wireless Communications and Networking Conference (WCNC). Piscataway:IEEE Press, 2023: 1-6.

唐菁敏, 黄嘉琪, 王炳文 ,等. 基于用户调度的多无人机辅助通信系统资源优化[J]. 北京航空航天大学学报, 2023: 1-15.

TANG J M, HUANG J Q, WANG B W ,et al. Joint optimization scheme of trajectories and resources allocation for UAV aided communication[J]. Journal of Beijing University of Aeronautics and Astronautics, 2023: 1-15.

ARAFAT M Y, MOH S . Routing protocols for unmanned aerial vehicle networks:a survey[J]. IEEE Access, 2019,7: 99694-99720.

MOZAFFARI M, SAAD W, BENNIS M ,et al. A tutorial on UAVs for wireless networks:applications,challenges,and open problems[J]. IEEE Communications Surveys ＆ Tutorials, 2019,21(3): 2334-2360.

DAI M H, HUANG N, WU Y ,et al. Unmanned-aerial-vehicleassisted wireless networks:advancements,challenges,and solutions[J]. IEEE Internet of Things Journal, 2023,10(5): 4117-4147.

HAYAT S, YANMAZ E, MUZAFFAR R . Survey on unmanned aerial vehicle networks for civil applications:a communications viewpoint[J]. IEEE Communications Surveys ＆ Tutorials, 2016,18(4): 2624-2661.

FENG D Q, LU L, YI Y W ,et al. Device-to-device communications underlaying cellular networks[J]. IEEE Transactions on Communications, 2013,61(8): 3541-3551.

FENG D Q, LU L, YI Y W ,et al. Device-to-device communications in cellular networks[J]. IEEE Communications Magazine, 2014,52(4): 49-55.

HUANG W H, YANG Z H, PAN C H ,et al. Joint power,altitude,location and bandwidth optimization for UAV with underlaid D2D communications[J]. IEEE Wireless Communications Letters, 2018,8(2): 524-527.

ZHANG T K, WANG Y, YI W Q ,et al. Joint optimization of caching placement and trajectory for UAV-D2D networks[J]. IEEE Transactions on Communications, 2022,70(8): 5514-5527.

MONEMI M, TABASSUM H . Performance of UAV-assisted D2D networks in the finite block-length regime[J]. IEEE Transactions on Communications, 2020,68(11): 7270-7285.

SHANG B D, LIU L J, RAO R M ,et al. 3D spectrum sharing for hybrid D2D and UAV networks[J]. IEEE Transactions on Communications, 2020,68(9): 5375-5389.

CHEN P X, ZHOU X, ZHAO J ,et al. Energy-efficient resource allocation for secure D2D communications underlaying UAVenabled networks[J]. IEEE Transactions on Vehicular Technology, 2022,71(7): 7519-7531.

YIN C, YANG H L, XIAO P ,et al. Resource allocation for UAVassisted wireless powered D2D networks with flying and ground eavesdropping[J]. IEEE Communications Letters, 2023,27(8): 2103-2107.

丁徐飞, 田文, 刘光杰 ,等. 基于D2D通信系统的无人机辅助物联网保密通信频谱共享方法[J]. 无线电工程, 2023: 1-9.

DING X F, TIAN W, LIU G J ,et al. Spectrum sharing planning of UAV-assisted secrecy communicationwith D2D communication systems in IoT[J]. Radio Engineering, 2023: 1-9.

LIU G, CHEN X H, DING Z G ,et al. Hybrid half-duplex/fullduplex cooperative non-orthogonal multiple access with transmit power adaptation[J]. IEEE Transactions on Wireless Communications, 2018,17(1): 506-519.

SHAHAB M B, SHIN S Y . Time shared half/full-duplex cooperative NOMA with clustered cell edge users[J]. IEEE Communications Letters, 2018,22(9): 1794-1797.

LI B, ZHAO S J, ZHANG R Q ,et al. Full-duplex UAV relaying for multiple user pairs[J]. IEEE Internet of Things Journal, 2021,8(6): 4657-4667.

DUO B, WU Q Q, YUAN X J ,et al. Energy efficiency maximization for full-duplex UAV secrecy communication[J]. IEEE Transactions on Vehicular Technology, 2020,69(4): 4590-4595.

SONG Q H, ZHENG F C, ZENG Y ,et al. Joint beamforming and power allocation for UAV-enabled full-duplex relay[J]. IEEE Transactions on Vehicular Technology, 2019,68(2): 1657-1671.

ZHU L P, ZHANG J, XIAO Z Y ,et al. Millimeter-wave fullduplex UAV relay:joint positioning,beamforming,and power control[J]. IEEE Journal on Selected Areas in Communications, 2020,38(9): 2057-2073.

MA Y H, NIU Y, HAN Z ,et al. Robust transmission scheduling for UAV-assisted millimeter-wave train-ground communication system[J]. IEEE Transactions on Vehicular Technology, 2022,71(11): 11741-11755.

WANG H C, WANG J L, DING G R ,et al. Spectrum sharing planning for full-duplex UAV relaying systems with underlaid D2D communications[J]. IEEE Journal on Selected Areas in Communications, 2018,36(9): 1986-1999.

周理辉, 肖霖, 吴法辉 ,等. 无人机全双工双向中继的资源及轨迹优化设计[J]. 北京邮电大学学报, 2023,46(1): 77-83.

ZHOU L H, XIAO L, WU F H ,et al. Resource and trajectory optimal design for unmanned aerial vehicles full duplex two-way relay[J]. Journal of Beijing University of Posts and Telecommunications, 2023,46(1): 77-83.

FENG D Q, JIANG W, QIAN G B ,et al. Mode selection and power allocation for UAV-assisted cellular networks[C]// Proceedings of 2021 13th International Conference on Wireless Communications and Signal Processing (WCSP). Piscataway:IEEE Press, 2021: 1-5.

BOYD S P, VANDENBERGHE L . Convex optimization[M]. Cambridge,UK: Cambridge, 2004.

Yuille A L, Rangarajan A . The concave-convex procedure (CCCP)[J]. Advances in Neural Information Processing Systems, 2001: 1033-1040.

WEST D B . Introduction to graph theory[M]. 2nd ed. Upper Saddle River,NJ: Prentice Hall, 2001.

AL-HOURANI A, KANDEEPAN S, LARDNER S . Optimal LAP altitude for maximum coverage[J]. IEEE Wireless Communications Letters, 2014,3(6): 569-572.

浏览量

111

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

面向信息年龄的车辆状态更新网络采样与功率控制

面向认知物联网的隐蔽通信智能功率控制