能效最优准则下无人机空中高度的优化算法

陈卡

doi:10.15892/j.cnki.djzdxb.2023.03.009

弹箭与制导学报 >

2023 , Vol. 43 >Issue 3: 62 - 67

DOI: https://doi.org/10.15892/j.cnki.djzdxb.2023.03.009

能效最优准则下无人机空中高度的优化算法

陈卡

展开

驻马店职业技术学院公共教学部,河南驻马店 463000

陈卡(1981—),男,讲师,研究方向:计算机应用,无人机能效优化。

收稿日期: 2022-07-09

网络出版日期: 2025-02-07

基金资助

吉林省科技发展计划资助项目(20190902010TC),吉林省教育厅职业教育与成人教育教学改革研究课题(2018ZCY244)

收起

Optimal Energy Efficient Based Aerial Altitude Optimization of Unmanned Aerial Vehicle

CHEN Ka

Expand

Zhumadian Vocational and Technical College, Zhumadian 463000, Henan, China

Received date: 2022-07-09

Online published: 2025-02-07

Fold

摘要

利用无人机(unmanned aerial vehicle, UAV)组建空中移动基站,可为地面终端用户提供更灵活、高效的接入服务。受UAV覆盖范围和有限能量的约束,研究如何建立能效最优的UAV部署算法至关重要。为此,提出能效最优准则下无人机空中高度的优化算法(optimal energy efficient based aerial altitude optimization, EEAO)。先在满足用户最小速率要求和UAV高度的约束条件下,构建能效最优的高度优化的目标函数。同时,定义能效时不仅考虑UAV的通信能耗,还考虑UAV在垂直爬升和悬停阶段的能耗。再分别利用和序列凸规划法(sequential convex programming, SCP)和单调分式规划法(monotonic fractional programming, MFP)求解目标函数,获取能效最优的UAV高度值。性能分析表明,基于SCP法求解的最优高度值与基于MFP法求解的最优高度值相近。同时,相比于不考虑悬停阶段UAV的能耗,考虑悬停阶段UAV的能耗可提升网络能效。

关键词： 空中通信系统; 能效; 和序列凸规划法; 单调分式规划法; 空中高度

本文引用格式

陈卡 . 能效最优准则下无人机空中高度的优化算法[J]. 弹箭与制导学报, 2023 , 43(3) : 62 -67 . DOI: 10.15892/j.cnki.djzdxb.2023.03.009

Abstract

Utilizing a unmanned aerial vehicle (UAV) to build aerial mobile small cell can provide more flexible and efficient services for ground terminal users. Constrained by the coverage and limited energy of the UAV, it is necessary to study how to build an optimal energy efficient based deployment of UAV. Therefore, objective function is constructed that maximizing the global energy efficiency, subject to altitude and minimum individual date rate constraints. When maximizing the energy efficient, both energy required for communication and energy consume by aerial vehicle, including the energy consumed by the rotor of UAV during climbing and hovering. Sequential convex programming (SCP) and monotonic fractional programming (MFP) are used to solve the objective function. Numerical results show that solution obtained from SCP is the same as the optimal solution form MFP. In addition, there is a gain in energy efficient when the UAV is hovering at an optimal altitude determined by considering the non-zero roto energy consumption of UAV.

Key words： aerial communication system; energy efficient; sequential convex programming; monotonic fractional programming; aerial altitude

[an error occurred while processing this directive]

参考文献

原文顺序 | 文献年度倒序 | 文中引用次数倒序

[1]	吴立志, 崔彦琛, 朱红伟, 等. 基于离散粒子群算法多旋翼无人机任务分配研究[J]. 消防科学与技术, 2020, 39(5): 662-665. WU L Z, CUI Y C, ZHU H W, et al. Research on the multi-rotor UAV multi-task assignment based on discrete particle swarm optimization algorithm[J]. Fire Science and Technology, 2020, 39(5): 662-665.

[2]	张杰勇, 钟赟, 孙鹏, 等. 有人/无人机协同作战指挥控制系统技术[J]. 指挥与控制学报, 2021, 7(2): 203-214. ZHANG J Y, ZHONG Y, SUN P, et al. Command and control system and technology for manned/unmanned aerial vehicle cooperative operation[J]. Journal of Command and Control, 2021, 7(2): 203-214.

[3]	BABU N, NTOUGIAS K, PAPADIAS C B, et al. Energy efficient altitude optimization of an aerial access point[C]// IEEE. Proceedings of the 2020 IEEE 31st Annual International Symposium on Person, Indoor and Mobile Radio. New York: IEEE, 2020: 2883-2888.

[4]	邵太华, 陈洪辉, 舒振, 等. 面向无人作战指挥控制的任务智能解析技术[J]. 指挥与控制学报, 2021, 7(2): 146-162. SHAO T H, CHEN H H, SHU Z, et al. Mission intelligent parsing for unmanned combat command and control[J]. Journal of Command and Control, 2021, 7(2): 146-162.

[5]	付有斌, 康巧燕, 王建峰, 等. 无人机飞行自组网通信协议[J]. 指挥与控制学报, 2021, 7(1): 89-96. FU Y B, KANG Q Y, WANG J F, et al. Communication protocols for UAV flying Ad-Hoc network[J]. Journal of Command and Control, 2021, 7(1): 89-96.

[6]	SUBIN E, HOON L, PARK J, et al. UAV-Aided wireless communication designs with propulsion energy limitations[J]. IEEE Transactions on Vehicular Technology, 2019, 69(1): 651-662.

[7]	ZENG Y, XU J, ZHANG R. Energy minimization for wireless communication with rotary-wing UAV[J]. IEEE Transactions on Wireless Communications, 2019, 18(4): 2329-2345.

[8]	ZENG Y, ZHANG R. Energy-efficient UAV communication with trajectory optimization[J]. IEEE Transaction on Wireless Communications, 2017, 16(6): 3747-3760.

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

[10]	台文鑫, 王钇翔, 李森, 等. 基于动态选择机制的低信噪比单声道语音增强算法[J]. 计算机应用研究, 2021, 38(9): 2604-2608. TAI W X, WANG Y X, LI S, et al. Monaural speech enhancement algorithm based on dynamic selection mechanism under low SNR[J]. Application Research of Computers, 2021, 38(9): 2604-2608.

[11]	BABU N, PAPADIAS C B, POPOVSKI P. Energy-efficient 3D deployment of aerial access points in a UAV communication system[J]. IEEE Communications Letters, 2020, 24(12): 2883-2888.

[12]	翟璐璐. 基于能量效率和覆盖率优化的UAV部署算法[J]. 国外电子测量技术, 2021(12): 24-29. ZHAI L L. Energy-efficient and coverage optimization-based deployment of unmanned aerial vehicle[J]. Foreign Electronic Measurement Technology, 2021(12): 24-29.

[13]	ABEYWICKRAMA H V, JAYAWICKRAMA B A, YING H, et al. Comprehensive energy consumption model for unmanned aerial vehicles, based on empirical studies of battery performance[J]. IEEE Access, 2018, 6(9): 58383-58394.

[14]	JORSWIECK E, ZAPPONE A. Energy efficiency in wireless networks via fractional programming theory[J]. Foundations & Trends in Communications & Information Theory, 2014, 4(11): 185-399.

[15]	周祥, 张洪波, 何睿智, 等. 基于凸优化的再入轨迹三维剖面规划方法[J]. 航空学报, 2020, 41(11): 61-77. ZHOU X, ZHANG H B, HE R Z, et al. Entry trajectory planning method based on 3D profile via convex optimization[J]. Acta Aeronautica et Astronautica Sinica, 2020, 41(11): 61-77.

[16]	袁富宇, 肖碧琴, 刘凯, 等. 关于TMA的Taylor级数法的分析[J]. 指挥控制与仿真, 2022, 44(1): 38-43. DOI YUAN F Y, XIAO B Q, LIU K, et al. Analysis of Taylor seriers method for TMA[J]. Command Control & Simulation, 2022, 44(1): 38-43.

[17]	张欢, 周云生, 姜义成. 一种基于凸优化的四站时差定位算法[J]. 应用科技, 2021, 1(8): 76-80. ZHANG H, ZHOU Y S, JIANG Y C. Four-station time difference positioning algorithm based on convex optimization[J]. Applied Science and Technology, 2021, 1(8): 76-80.

[18]	韩文艳, 余国林. 一类广义凸多目标分式规划近似弱有效解的最优性[J]. 南昌大学学报(理科版), 2020, 44(2): 107-112. HAN W Y, YU G L. Optimality of a class of generalized convex multi-objective fractional programming approximate weak efficient solutions[J]. Journal of Nanchang University(Natural Science), 2020, 44(2): 107-112.

Options

文章导航