无人机辅助D2D通信网络安全通信资源分配算法

doi:10.11959/j.issn.1000-436x.2024014

Abstract

Abstract:

To solve the problems of energy limitation, spectrum shortage, and serious co-frequency interference in the unmanned aerial vehicle (UAV)-assisted D2D (device-to-device) communication network under passive eavesdropping, the concept of the network secrecy energy efficiency was introduced by taking into account the secrecy rate and transmit power constraints of each user.Based on the physical layer secure transmission theory, the joint optimization problem of spectrum multiplexing and power control strategies was investigated to maximize the network secrecy energy efficiency.The problem was a nonlinear nonconvex problem, a resource allocation algorithm combining Dinkelbach’s algorithm and the convex approximation algorithm was proposed to transform the nonconvex optimization problem into a geometric planning problem through the convex approximation algorithm and ensure that the original problem converges to the global optimal solution by Dinkelbach’s algorithm.Simulation results show that the proposed algorithm can effectively mitigate the co-channel interference, improve the network secrecy energy efficiency, and balance the relationship between the secure communication performance and power consumption of the network.

Key words: UAV, D2D communication, energy efficiency, resource allocation, physical layer security

CLC Number:

TN92

Xiaowan ZENG, Haijun WANG, Lei HUANG, Dongtang MA. Resource allocation algorithm for secure communication in UAV-assisted D2D communication network[J]. Journal on Communications, 2024, 45(2): 115-126.

Figures/Tables 6

参数	值
蜂窝用户数量M	1～8
D2D对数量N	1～8
无人机高度h/m	100～1 000
D2D对最大传输距离d_n,n/m	25
地面用户和UAV之间的路径损耗参数(α, β, η_LoS, η_NLoS)	(12.08, 0.11, 1.6, 23)
载波频率f_c/GHz	2.4
D2D对之间的路径损耗参数 $(G^{'}, ξ^{'})$	(1.58×10^-15, 4)
蜂窝用户、Eve与D2D对接收端之间的路径损耗参数(G, ξ)	(1.55×10^-13, 3.76)
阴影衰落对应的信道增益 $ζ_{m, n} 、 ζ_{n^{'}, n} 、 ζ_{m, e} 、 ζ_{n, e} 、 ζ_{n, n}$	$ζ_{m, n} 、 ζ_{n^{'}, n} 、 ζ_{m, e} 、 ζ_{n, e} 、 ζ_{n, n} \sim N (0, 5)$
蜂窝用户的最低保密速率 $R_{m}^{CS}$ /(bit·(s·Hz)^-1)	1
D2D对的最低保密速率 $R_{m}^{DS}$ /(bit·(s·Hz)^-1)	1
蜂窝用户和D2D对的发射功率上限P_max/W	1
高斯白噪声σ²/ dBm	-121.45
功率放大器效率因子η	0.35
设备的电路功耗P_cir/W	0.1
收敛阈值ε₁、ε₂	10^-1
Dinkelbach算法迭代次数 $T_{1}^{\max}$	30
凸近似算法的迭代次数 $T_{1}^{\max}$	15

References 25

[1]	MOZAFFARI M , SAAD W , BENNIS M ,et al. A tutorial on UAVs for wireless networks:applications,challenges,and open problems[J]. IEEE Communications Surveys ＆ Tutorials, 2019,21(3): 2334-2360.
[2]	LIU X N , LI Z , ZHAO N ,et al. Transceiver design and multihop D2D for UAV IoT coverage in disasters[J]. IEEE Internet of Things Journal, 2019,6(2): 1803-1815.
[3]	XU Y J , GUI G , GACANIN H ,et al. A survey on resource allocation for 5G heterogeneous networks:current research,future trends,and challenges[J]. IEEE Communications Surveys ＆ Tutorials, 2021,23(2): 668-695.
[4]	FOTOUHI A , QIANG H R , DING M ,et al. Survey on UAV cellular communications:practical aspects,standardization advancements,regulation,and security challenges[J]. IEEE Communications Surveys ＆Tutorials, 2019,21(4): 3417-3442.
[5]	WYNER A D . The wire-tap channel[J]. The Bell System Technical Journal, 1975,54(8): 1355-1387.
[6]	CSISZAR I , KORNER J . Broadcast channels with confidential messages[J]. IEEE Transactions on Information Theory, 1978,24(3): 339-348.
[7]	GUO D K , CAO K , XIONG J ,et al. A lightweight key generation scheme for the Internet of things[J]. IEEE Internet of Things Journal, 2021,8(15): 12137-12149.
[8]	袁敏鑫 . 基于 D2D 场景下无人机辅助的蜂窝网络通信系统能效研究[D]. 哈尔滨:哈尔滨工业大学, 2022.
	YUAN M X . Research on energy efficiency of UAV-assisted cellular network communication system based on D2D scene[D]. Harbin:Harbin Institute of Technology, 2022.
[9]	高远, 谭蓉俊, 邓志祥 . 无人机辅助物理层安全下的保密性能优化[J]. 电子与信息学报, 2022,44(8): 2730-2738.
	GAO Y , TAN R J , DENG Z X . Secrecy performance optimization of unmanned aerial vehicle-aided physical layer security[J]. Journal of Electronics ＆ Information Technology, 2022,44(8): 2730-2738.
[10]	YANG B , TALEB T , FAN Y Y ,et al. Mode selection and cooperative jamming for covert communication in D2D underlaid UAV networks[J]. IEEE Network, 2021,35(2): 104-111.
[11]	SU Z J , FENG W M , TANG J ,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.
[12]	QI X H , YUAN M X , ZHANG Q Y ,et al. Joint power-trajectory- scheduling optimization in a mobile UAV-enabled network via alternating iteration[J]. China Communications, 2022,19(1): 136-152.
[13]	ZHANG J X , CHUAI G , GAO W D . Energy-efficient optimization for energy-harvesting-enabled mmWave-UAV heterogeneous networks[J]. Entropy, 2022,24(2): 300.
[14]	ALSHAROA A , YUKSEL M . Energy efficient D2D communications using multiple UAV relays[J]. IEEE Transactions on Communications, 2021,69(8): 5337-5351.
[15]	SELIM M M , RIHAN M , YANG Y T ,et al. Optimal task partitioning,Bit allocation and trajectory for D2D-assisted UAV-MEC systems[J]. Peer-to-Peer Networking and Applications, 2021,14(1): 215-224.
[16]	文阳 . 抖动无人机空-地通信窃听与窃听对抗研究[D]. 北京:北京邮电大学, 2021.
	WEN Y . Research on eavesdropping and anti-eavesdropping in air-to-ground communications with jittery UAV[D]. Beijing:Beijing University of Posts and Telecommunications, 2021.
[17]	CHEN P X , ZHOU X , ZHAO J ,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.
[18]	YU H Y , GUO S T , YANG Y Y ,et al. Secrecy energy efficiency optimization for downlink two-user OFDMA networks with SWIPT[J]. IEEE Systems Journal, 2019,13(1): 324-335.
[19]	余雪勇, 邱礼翔, 宋家宁 ,等. 无人机辅助边缘计算中安全通信与能效优化策略[J]. 通信学报, 2023,44(3): 45-54.
	YU X Y , QIU L X , SONG J N ,et al. Security communication and energy efficiency optimization strategy in UAV-aided edge computing[J]. Journal on Communications, 2023,44(3): 45-54.
[20]	AL-HOURANI A , KANDEEPAN S , LARDNER S . Optimal LAP altitude for maximum coverage[J]. IEEE Wireless Communications Letters, 2014,3(6): 569-572.
[21]	LIANG L , LI G Y , XU W . Resource allocation for D2D-enabled vehicular communications[J]. IEEE Transactions on Communications, 2017,65(7): 3186-3197.
[22]	DINKELBACH W . On nonlinear fractional programming[J]. Management Science, 1967,13(7): 492-498.
[23]	祁忠勇, 李威锖, 林家祥 . 信号处理与通信中的凸优化从基础到应用[M]. 北京: 电子工业出版社, 2021.
	QI Z Y , LI W J , LIN J X . Convex optimization in signal processing and communication:from basic to application[M]. Beijing: Electronic Industry Press, 2021.
[24]	BOYD S, VANDENBERGHE L . 凸优化[M]. 王书宁,许鋆,黄晓霖,译. 北京: 清华大学出版社, 2013.
	BOYD S , VANDENBERGHE L . Convex optimization[M]. WANG S N,XU J,HUANG X L (translate). Beijing: Tsinghua University Press, 2013.
[25]	MONTES D O M A , STUTZLE T , BIRATTARI M ,et al. Frankenstein’s PSO:a composite particle swarm optimization algorithm[J]. IEEE Transactions on Evolutionary Computation, 2009,13(5): 1120-1132.

Metrics

Recommended 0

No Suggested Reading articles found!

Resource allocation algorithm for secure communication in UAV-assisted D2D communication network

RichHTML

PDF

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 6

References 25

Related Articles 15

Metrics

Recommended 0

[1]	Wei JI, Xuxin YANG, Fei LI, Ting LI, Yan LIANG, Yunchao SONG. Energy consumption optimization scheme in UAV-assisted MEC system based on optimal SIC order [J]. Journal on Communications, 2024, 45(2): 18-30.
[2]	Zhuo LU, Qihui WU, Fuhui ZHOU. Algorithm for intelligent collaborative target search and trajectory planning of MAV/UAV [J]. Journal on Communications, 2024, 45(1): 31-40.
[3]	Bin LI, Sicong PENG, Zesong FEI. Beamforming and resource optimization in UAV integrated sensing and communication network with edge computing [J]. Journal on Communications, 2023, 44(9): 228-237.
[4]	Fatang CHEN, Ruofan ZHANG. Research on IoV resource allocation algorithm assisted by reconfigurable intelligent surface [J]. Journal on Communications, 2023, 44(9): 70-78.
[5]	Fan YANG, Cheng YANG, Jie HUANG, Shilong ZHANG, Tao YU, Xun ZUO, Chuan YANG. Resource allocation strategy based on deep reinforcement learning in 6G dense network [J]. Journal on Communications, 2023, 44(8): 215-227.
[6]	Fatang CHEN, Miao HUANG, Yufeng JIN. Resource allocation strategy of low earth orbit satellite oriented to user transmission difference [J]. Journal on Communications, 2023, 44(8): 125-133.
[7]	Feng ZENG, Zheng ZHANG, Zhigang CHEN. Computation offloading and resource allocation strategy based on deep reinforcement learning [J]. Journal on Communications, 2023, 44(7): 124-135.
[8]	Yun LI, Qian GAO, Zhixiu YAO, Shichao XIA, Jishen LIANG. Joint optimization method of intelligent service arrangement and computing-networking resource allocation for MEC [J]. Journal on Communications, 2023, 44(7): 51-63.
[9]	Lu BAI, Mingran SUN, Ziwei HUANG, Tao FENG, Xiang CHENG. Multi-UAV cooperative channel model for emergency communication [J]. Journal on Communications, 2023, 44(7): 38-50.
[10]	Yuming ZHANG, Lianming XU, Siyuan YIN, Linrun JIANG, Li WANG, Aiguo FEI. AoI-oriented low-energy-consumption information collection and transmission scheduling mechanism for emergency UAV networks [J]. Journal on Communications, 2023, 44(7): 1-13.
[11]	Li WANG, Aiguo FEI, Ping ZHANG, Lianming XU. Research on new frameworks and key technologies for intelligent emergency command communication networks [J]. Journal on Communications, 2023, 44(6): 1-11.
[12]	Zaijian WANG, Huimin GU. Network slicing resource allocation strategy based on joint optimization [J]. Journal on Communications, 2023, 44(5): 234-245.
[13]	Xueyong YU, Lixiang QIU, Jianing SONG, Hongbo ZHU. Security communication and energy efficiency optimization strategy in UAV-aided edge computing [J]. Journal on Communications, 2023, 44(3): 45-54.
[14]	Jingming XIA, Yufeng LIU, Ling TAN. Research on multi-UAV energy consumption optimization algorithm for cellular-connected network [J]. Journal on Communications, 2023, 44(2): 185-197.
[15]	Guojun LI, Xu HOU, Changrong YE, Yiping LUO. Wide area cooperative resource allocation algorithm for shortwave communication access network [J]. Journal on Communications, 2023, 44(2): 112-121.