3D Trajectory and Power Optimization Method Based on Full Spectrum Sharing

PEI Errong; CHEN Xinhu; CHEN Qimei; SUN Yuanxin; LI Wei

doi:10.11999/JEIT230261

Volume 46 Issue 3

Mar. 2024

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Article Navigation > Journal of Electronics & Information Technology > 2024 > 46(3): 835-847

PEI Errong, CHEN Xinhu, CHEN Qimei, SUN Yuanxin, LI Wei. 3D Trajectory and Power Optimization Method Based on Full Spectrum Sharing[J]. Journal of Electronics & Information Technology, 2024, 46(3): 835-847. doi: 10.11999/JEIT230261

Citation:

PEI Errong, CHEN Xinhu, CHEN Qimei, SUN Yuanxin, LI Wei. 3D Trajectory and Power Optimization Method Based on Full Spectrum Sharing[J]. Journal of Electronics & Information Technology, 2024, 46(3): 835-847. doi: 10.11999/JEIT230261

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3D Trajectory and Power Optimization Method Based on Full Spectrum Sharing

doi: 10.11999/JEIT230261 cstr: 32379.14.JEIT230261

1.
School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
2.
Electronic Information School, Wuhan University, Wuhan 430072, China
3.
Chongqing Jinmei Communication Co., Ltd, Chongqing 400035, China

Funds: The National Natural Science Foundation of China (62071077), Chongqing Chengyu Science and Technology Innovation Project (KJCXZD2020026)

Received Date: 2023-04-12
Rev Recd Date: 2023-07-27

Available Online: 2023-08-03

Publish Date: 2024-03-27

Abstract

Abstract

Due to the extreme shortage of licensed spectrum in cellular systems currently, unlicensed spectrum is thus recommended for cellular systems. The Unmanned Aerial Vehicle(UAV) flight trajectory and power control have a significant impact on spectrum utilization efficiency. However, Three-Dimensional(3D) flight trajectory and power optimization methods based on full spectrum sharing have rarely been unstudied. Therefore, a full spectrum sharing method is first proposed in this paper, where the UAV can use the unlicensed spectrum by controlling the transmission power of uplink cellular users and Device to Device (D2D) users without affecting the data transmission of WiFi devices; at the same time, the UAV can use the licensed spectrum without affecting other downlink cellular users. And then, based on the proposed full spectrum sharing method, a joint optimization problem of 3D flight trajectory and transmission power is constructed under the energy constraint of the UAV battery. In order to solve the proposed complex non-convex optimization problem with multi-variable coupling, the successive convex approximation technique and block coordinate descent method are used to transform the original problem into two convex optimization subproblems i.e. 3D trajectory optimization and power control and solve them iteratively. A large of simulation results show that the proposed spectrum sharing method based on 3D trajectory and power optimization significantly improves the spectrum utilization efficiency.
- Full spectrum sharing,
- Unmanned Aerial Vehicle (UAV) Communication,
- Device to Device (D2D),
- 3D trajectory,
- Power control

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References(28)

References

[1]	XU Yongjun, LIU Zijian, HUANG Chongwen, et al. Robust resource allocation algorithm for energy-harvesting-based D2D communication underlaying UAV-assisted networks[J]. IEEE Internet of Things Journal, 2021, 8(23): 17161–17171. doi: 10.1109/JIOT.2021.3078264.
[2]	PARVINI M, ZARIF A H, NOURUZI A, et al. Spectrum sharing schemes from 4G to 5G and beyond: Protocol flow, regulation, ecosystem, economic[J]. IEEE Open Journal of the Communications Society, 2023, 4: 464–517. doi: 10.1109/OJCOMS.2023.3238569.
[3]	NGUYEN H T, TUAN H D, DUONG T Q, et al. Joint D2D assignment, bandwidth and power allocation in cognitive UAV-enabled networks[J]. IEEE Transactions on Cognitive Communications and Networking, 2020, 6(3): 1084–1095. doi: 10.1109/TCCN.2020.2969623.
[4]	LI Xuanheng, CHENG Sike, DING Haichuan, et al. When UAVs meet cognitive radio: Offloading traffic under uncertain spectrum environment via deep reinforcement learning[J]. IEEE Transactions on Wireless Communications, 2023, 22(2): 824–838. doi: 10.1109/TWC.2022.3198665.
[5]	MENG Kaitao, WU Qingqing, MA Shaodan, et al. Throughput maximization for UAV-enabled integrated periodic sensing and communication[J]. IEEE Transactions on Wireless Communications, 2023, 22(1): 671–687. doi: 10.1109/TWC.2022.3197623.
[6]	JI Jiequ, ZHU Kun, NIYATO D, et al. Joint trajectory design and resource allocation for secure transmission in cache-enabled UAV-relaying networks with D2D communications[J]. IEEE Internet of Things Journal, 2021, 8(3): 1557–1571. doi: 10.1109/JIOT.2020.3013647.
[7]	CHEN Peixin, ZHOU Xuan, ZHAO Jian, et al. Energy-efficient resource allocation for secure D2D communications underlaying UAV-enabled networks[J]. IEEE Transactions on Vehicular Technology, 2022, 71(7): 7519–7531. doi: 10.1109/TVT.2022.3168277.
[8]	HUANG Yuwei, MEI Weidong, XU Jie, et al. Cognitive UAV communication via joint maneuver and power control[J]. IEEE Transactions on Communications, 2019, 67(11): 7872–7888. doi: 10.1109/TCOMM.2019.2931322.
[9]	HUA Meng, YANG Luxi, WU Qingqing, et al. 3D UAV trajectory and communication design for simultaneous uplink and downlink transmission[J]. IEEE Transactions on Communications, 2020, 68(9): 5908–5923. doi: 10.1109/TCOMM.2020.3003662.
[10]	TAO Zhenhui, ZHOU Fuhui, WANG Yuhao, et al. Resource allocation and trajectories design for UAV-assisted jamming cognitive UAV networks[J]. China Communications, 2022, 19(5): 206–217. doi: 10.23919/JCC.2021.00.007.
[11]	JIANG Yuhan and ZHU Jia. Three-dimensional trajectory optimization for secure UAV-enabled cognitive communications[J]. China Communications, 2021, 18(12): 285–296. doi: 10.23919/JCC.2021.12.018.
[12]	LI Hangqi and ZHAO Xiaohui. Throughput maximization with energy harvesting in UAV-assisted cognitive mobile relay networks[J]. IEEE Transactions on Cognitive Communications and Networking, 2021, 7(1): 197–209. doi: 10.1109/TCCN.2020.2988556.
[13]	WANG Haichao, WANG Jinlong, DING Guorui, 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. doi: 10.1109/JSAC.2018.2864375.
[14]	MATAR A S and SHEN Xuemin. Joint subchannel allocation and power control in licensed and unlicensed spectrum for multi-cell UAV-cellular network[J]. IEEE Journal on Selected Areas in Communications, 2021, 39(11): 3542–3554. doi: 10.1109/JSAC.2021.3088672.
[15]	ATHUKORALAGE D, GUVENC I, SAAD W, et al. Regret based learning for UAV assisted LTE-U/WiFi public safety networks[C]. 2016 IEEE Global Communications Conference, Washington, USA, 2016: 1–7.
[16]	CHEN Mingzhe, SAAD W, and YIN Changchuan. Echo state learning for wireless virtual reality resource allocation in UAV-enabled LTE-U networks[C]. 2018 IEEE International Conference on Communications, Kansas City, USA, 2018: 1–6.
[17]	CHEN Mingzhe, SAAD W, and YIN Changchuan. Liquid state machine learning for resource and cache management in LTE-U unmanned aerial vehicle (UAV) networks[J]. IEEE Transactions on Wireless Communications, 2019, 18(3): 1504–1517. doi: 10.1109/TWC.2019.2891629.
[18]	XU Chan, LI Deshi, CHEN Qimei, et al. Joint trajectory and transmission optimization for energy efficient UAV enabled eLAA network[J]. Ad Hoc Networks, 2021, 116: 102466. doi: 10.1016/j.adhoc.2021.102466.
[19]	XU Chan, CHEN Qimei, and LI Deshi. Joint trajectory design and resource allocation for energy-efficient UAV enabled eLAA network[C]. 2019 IEEE International Conference on Communications, Shanghai, China, 2019: 1–6.
[20]	XIONG Xinxuan, SUN Chao, NI Wei, et al. Three-dimensional trajectory design for unmanned aerial vehicle-based secure and energy-efficient data collection[J]. IEEE Transactions on Vehicular Technology, 2023, 72(1): 664–678. doi: 10.1109/TVT.2022.3203714.
[21]	NOBAR S K, AHMED M H, MORGAN Y, et al. Resource allocation in cognitive radio-enabled UAV communication[J]. IEEE Transactions on Cognitive Communications and Networking, 2022, 8(1): 296–310. doi: 10.1109/TCCN.2021.3103531.
[22]	HU Zhenzhen, ZENG Fanzi, XIAO Zhu, et al. Computation efficiency maximization and QoE-provisioning in UAV-enabled MEC communication systems[J]. IEEE Transactions on Network Science and Engineering, 2021, 8(2): 1630–1645. doi: 10.1109/TNSE.2021.3068123.
[23]	CAI Yuanxin, WEI Zhiqiang, HU Shaokang, et al. Resource allocation and 3D trajectory design for power-efficient IRS-assisted UAV-NOMA communications[J]. IEEE Transactions on Wireless Communications, 2022, 21(12): 10315–10334. doi: 10.1109/TWC.2022.3183300.
[24]	ZENG Yong, XU Jie, and ZHANG Rui. Energy minimization for wireless communication with rotary-wing UAV[J]. IEEE Transactions on Wireless Communications, 2019, 18(4): 2329–2345. doi: 10.1109/TWC.2019.2902559.
[25]	GAO Ning, ZENG Yong, WANG Jian, et al. Energy model for UAV communications: Experimental validation and model generalization[J]. China Communications, 2021, 18(7): 253–264. doi: 10.23919/JCC.2021.07.020.
[26]	SU Zhijie, FENG Wanmei, TANG Jie, et al. Energy-efficiency optimization for D2D communications underlaying UAV-assisted industrial IoT networks with SWIPT[J]. IEEE Internet of Things Journal, 2023, 10(3): 1990–2002. doi: 10.1109/JIOT.2022.3142026.
[27]	TRAN Q N, VO N S, BUI M P, et al. Spectrum sharing and power allocation optimised multihop multipath D2D video delivery in beyond 5G networks[J]. IEEE Transactions on Cognitive Communications and Networking, 2022, 8(2): 919–930. doi: 10.1109/TCCN.2021.3133838.
[28]	LAI Lifeng, FENG Daquan, ZHENG Fuchun, et al. CQI-based interference detection and resource allocation with QoS provision in LTE-U systems[J]. IEEE Transactions on Vehicular Technology, 2021, 70(2): 1421–1433. doi: 10.1109/TVT.2021.3052530.