Research on Dynamic Topology Model-based Routing Algorithms in 6G Large-scale UAV Networks

LIU Hanze; YANG Zhutian; WU Zhilu; YANG Wei; ZHU Weiqiang

doi:10.11999/JEIT211140

Volume 44 Issue 3

Mar. 2022

Turn off MathJax

Article Contents

Article Navigation > Journal of Electronics & Information Technology > 2022 > 44(3): 815-824

LIU Hanze, YANG Zhutian, WU Zhilu, YANG Wei, ZHU Weiqiang. Research on Dynamic Topology Model-based Routing Algorithms in 6G Large-scale UAV Networks[J]. Journal of Electronics & Information Technology, 2022, 44(3): 815-824. doi: 10.11999/JEIT211140

Citation:

LIU Hanze, YANG Zhutian, WU Zhilu, YANG Wei, ZHU Weiqiang. Research on Dynamic Topology Model-based Routing Algorithms in 6G Large-scale UAV Networks[J]. Journal of Electronics & Information Technology, 2022, 44(3): 815-824. doi: 10.11999/JEIT211140

Citation:

PDF( 8618 KB)

Research on Dynamic Topology Model-based Routing Algorithms in 6G Large-scale UAV Networks

doi: 10.11999/JEIT211140

1.
School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150000, China
2.
Nanjing Electronic Equipment Institute, Nanjing 210000, China

Received Date: 2021-10-18
Accepted Date: 2022-02-16
Rev Recd Date: 2022-02-15

Available Online: 2022-02-23

Publish Date: 2022-03-28

Abstract

Abstract

With the development of wireless communication and Unmanned Aerial Vehicle (UAV) technology, the establishment of a large-scale UAV cloud covering and connecting various wireless terminals in a wide area using the advantages of mobility, stability and wide coverage has become an important development direction for future 6G wireless communication networks. How to quickly and accurately plan the optimal path in the complex network topology of the UAV cloud has become an urgent problem to be solved. Therefore, by using the gradient principle in the gravitational field, a new dynamic network topology model designed to be applicable to multiple routing schemes is designed, and the calculation and selection of routing paths under complex topological networks is realized based on this model. This model uses the characteristics of gradient itself in order to achieve path optimization for the communication needs of high-density and high-coverage UAV clouds that may appear in future 6G applications. Simulation results show that the topology model and routing methods proposed in this paper outperform many routing schemes currently applied and studied in terms of link communication quality and average energy consumption.
- 6G UAV communication,
- Routing,
- Topology model,
- Routing metrics

FullText(HTML)

References(18)

References

[1]	贾向东, 路艺, 纪澎善, 等. 大规模无人机协助的多层异构网络设计及性能研究[J]. 电子与信息学报, 2021, 43(9): 2632–2639. doi: 10.11999/JEIT200443 JIA Xiangdong, LU Yi, JI Pengshan, et al. Design of large-scale UAV-assisted multi-tier heterogeneous networks and performance research[J]. Journal of Electronics &Information Technology, 2021, 43(9): 2632–2639. doi: 10.11999/JEIT200443
[2]	ZHAO Nan, LU Weidang, SHENG Min, et al. UAV-assisted emergency networks in disasters[J]. IEEE Wireless Communications, 2019, 26(1): 45–51. doi: 10.1109/MWC.2018.1800160
[3]	KO J, TERZIS A, DAWSON-HAGGERTY S, et al. Connecting low-power and lossy networks to the internet[J]. IEEE Communications Magazine, 2011, 49(4): 96–101. doi: 10.1109/MCOM.2011.5741163
[4]	WINTER T, THUBERT P, BRANDT A, et al. RFC 6550 RPL: IPv6 routing protocol for low-power and lossy networks[S]. 2012.
[5]	YANG Y and WANG J. Design guidelines for routing metrics in multihop wireless networks[C]. The 27th Conference on Computer Communications, Phoenix, USA, 2008: 1615–1623.
[6]	LAI Xiaohan, JI Xiaoyu, ZHOU Xinyan, et al. Energy efficient link-delay aware routing in wireless sensor networks[J]. IEEE Sensors Journal, 2018, 18(2): 837–848. doi: 10.1109/JSEN.2017.2772321
[7]	QIU Ying, LI Shining, LI Zhigang, et al. Multi-gradient routing protocol for wireless sensor networks[J]. China Communications, 2017, 14(3): 118–129. doi: 10.1109/CC.2017.7897328
[8]	TANG Fengxiao, MAO Bomin, FADLULLAH Z M, et al. On removing routing protocol from future wireless networks: A real-time deep learning approach for intelligent traffic control[J]. IEEE Wireless Communications, 2018, 25(1): 154–160. doi: 10.1109/MWC.2017.1700244
[9]	ZHANG Jiajie, WENG Jian, LUO Weiqi, et al. REMT: A real-time end-to-end media data transmission mechanism in UAV-aided networks[J]. IEEE Network, 2018, 32(5): 118–123. doi: 10.1109/MNET.2018.1700382
[10]	LIU Miao, SONG Tiecheng, HU Jing, et al. Deep learning-inspired message passing algorithm for efficient resource allocation in cognitive radio networks[J]. IEEE Transactions on Vehicular Technology, 2019, 68(1): 641–653. doi: 10.1109/TVT.2018.2883669
[11]	DING Ruijin, XU Yadong, GAO Feifei, et al. Deep reinforcement learning for router selection in network with heavy traffic[J]. IEEE Access, 2019, 7: 37109–37120. doi: 10.1109/ACCESS.2019.2904539
[12]	WANG Xiaolin, CHEN Cailian, HE Jianping, et al. Learning-based online transmission path selection for secure estimation in edge computing systems[J]. IEEE Transactions on Industrial Informatics, 2021, 17(5): 3577–3587. doi: 10.1109/TII.2020.3012090
[13]	HEINZELMAN W B, CHANDRAKASAN A P, and BALAKRISHNAN H. An application-specific protocol architecture for wireless microsensor networks[J]. IEEE Transactions on Wireless Communications, 2002, 1(4): 660–670. doi: 10.1109/TWC.2002.804190
[14]	DE COUTO D S J, AGUAYO D, BICKET J, et al. A high-throughput path metric for multi-hop wireless routing[J]. Wireless Networks, 2005, 11(4): 419–434. doi: 10.1007/s11276-005-1766-z
[15]	ANCILLOTTI E, BRUNO R, and CONTI M. Reliable data delivery with the IETF routing protocol for low-power and lossy networks[J]. IEEE Transactions on Industrial Informatics, 2014, 10(3): 1864–1877. doi: 10.1109/TII.2014.2332117
[16]	ZHANG Taimin, JI Xiaoyu, and XU Wenyuan. Jamming-resilient backup nodes selection for RPL-based routing in smart grid AMI networks[J/OL]. Mobile Networks and Applications, 2020.
[17]	MAUVE M, WIDMER J, and HARTENSTEIN H. A survey on position-based routing in mobile ad hoc networks[J]. IEEE Network, 2001, 15(6): 30–39. doi: 10.1109/65.967595
[18]	HUANG Haojun, YIN Hao, MIN Geyong, et al. Energy-aware dual-path geographic routing to bypass routing holes in wireless sensor networks[J]. IEEE Transactions on Mobile Computing, 2018, 17(6): 1339–1352. doi: 10.1109/TMC.2017.2771424