多无人机辅助通信的节能卸载策略

doi:10.13229/j.cnki.jdxbgxb.20240332

摘要/Abstract

摘要：

针对偏远地区或灾害场景中基础设施不完善、无法提供可靠通信的问题，提出了一种多无人机辅助用户的非正交多址接入中继系统。该系统综合考虑了信息因果、发射功率以及回传时延等约束，联合优化了卸载策略、发射功率、资源分配和轨迹以实现最小化系统能耗这一目标。针对优化问题的非凸性和复杂性，设计了一种两阶段在线资源分配方案进行求解。第一阶段，为消除复杂场景下对不确定信息的依赖，运用李雅普诺夫优化理论将优化问题分解为3个子问题。第二阶段，提出了一种交替迭代优化算法：首先，基于最大权匹配算法获得了用户卸载决策；其次，利用辅助变量法、连续凸逼近和拉格朗日对偶得到了传输功率和频率分配的闭式解；最后，将轨迹规划问题转化为凸问题，并使用凸优化工具进行求解。仿真结果表明：相较于基准算法，本文方案在满足系统长期稳定性约束的前提下，显著降低了系统能耗。

关键词: 计算机应用, 无人机, 航迹优化, 资源分配, 能耗最小化

Abstract:

To address the problem of inadequate infrastructure and inability to provide reliable communication in remote areas or disaster scenarios， a non orthogonal multiple access relay system with multiple drones assisting users is proposed. The system comprehensively considers constraints such as information causality， transmission power， and return delay， and jointly optimizes the offloading strategy， transmission power， resource allocation， and trajectory to achieve the goal of minimizing system energy consumption. Due to the non convexity and complexity of optimization problems， a two-stage online resource allocation scheme is designed for solving. In the first stage， to eliminate the dependence on uncertain information in complex scenarios， Lyapunov optimization theory is applied to decompose the optimization problem into three sub problems. In the second stage， an alternating iterative optimization algorithm was proposed： firstly， the user offloading decision was obtained based on the maximum weight matching algorithm； secondly， closed form solutions for transmission power and frequency allocation were obtained by utilizing auxiliary variable method， continuous convex approximation， and Lagrangian duality； finally， the trajectory planning problem is transformed into a convex problem and solved using the convex optimization tool. The simulation results show that compared to the benchmark algorithm， the proposed scheme significantly reduces system energy consumption while satisfying the long-term stability constraints of the system.

Key words: computer application, unmanned aerial vehicle, trajectory planning, resource allocation, energy minimization

中图分类号:

TP301

曾耀平,夏玉婷,陈世森,刘月强,江伟伟. 多无人机辅助通信的节能卸载策略[J]. 吉林大学学报(工学版), 2025, 55(12): 4083-4092.

Yao-ping ZENG,Yu-ting XIA,Shi-sen CHEN,Yue-qiang LIU,Wei-wei JIANG. Energy⁃efficient offloading strategy research for multi⁃UAV assisted communication[J]. Journal of Jilin University(Engineering and Technology Edition), 2025, 55(12): 4083-4092.

图/表 7

图1

表1

系统参数"

参数	含义	数值
$H$	无人机固定悬停高度	$300 ? m$
$V m a x$	无人机的最大飞行速度	$50 ? m / s$
$δ 2$	噪声功率	$10 - 12 W$
$f k, m a x$	无人机总计算能力	$16 ? G H z$
$f l, m m a x$	用户计算能力	$1 ? G H z$
$I m [n]$	用户的最大数据到达量	$1.5 × 105 ? b i t s / s$
$M g$	无人机质量	$9.65 ? k g$
$B$	信道带宽	$10 ? M H z$
$h 0$	功率信道增益	$- 50 ? d B$
$c m$	1 bit数据所需CPU周期数	$103 ? c y c l e / b i t$
$κ$	有效电容系数	$10 - 28$
$P D 2 U m a x$	用户和无人机通信最大传输功率	$1 ? W$
$P U 2 B m a x$	无人机和基站通信最大传输功率	$1 ? W$

表1

图2

图3

图4

图5

图6

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