Journal of Jilin University(Engineering and Technology Edition) ›› 2025, Vol. 55 ›› Issue (12): 4083-4092.doi: 10.13229/j.cnki.jdxbgxb.20240332

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Energyefficient offloading strategy research for multiUAV assisted communication

Yao-ping ZENG(),Yu-ting XIA,Shi-sen CHEN,Yue-qiang LIU,Wei-wei JIANG   

  1. School of Communication and Information Engineering,Xi'an University of Posts & Telecommunications,Xi'an 710121,China
  • Received:2024-03-30 Online:2025-12-01 Published:2026-02-03

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

CLC Number: 

  • TP301

Fig.1

System model"

Table 1

System parameter"

参数含义数值
H无人机固定悬停高度300?m
Vmax无人机的最大飞行速度50?m/s
δ2噪声功率10-12W
fk,max无人机总计算能力16?GHz
fl,mmax用户计算能力1?GHz
Im[n]用户的最大数据到达量1.5×105?bits/s
Mg无人机质量9.65?kg
B信道带宽10?MHz
h0功率信道增益-50?dB
cm1 bit数据所需CPU周期数103?cycle/bit
κ有效电容系数10-28
PD2Umax用户和无人机通信最大传输功率1?W
PU2Bmax无人机和基站通信最大传输功率1?W

Fig.2

Average system queue length for different V and weighting factors"

Fig.3

MEC energy consumption for different V and weighting factors"

Fig.4

Average system energy consumption for different task arrivals"

Fig.5

Combined impact of multiple factors on the overall power consumption of the system"

Fig.6

UAV trajectory"

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