面向无人机雷达通信一体化系统的轨迹与资源联合优化

doi:10.11959/j.issn.1000-436x.2021201

通信学报 ›› 2021, Vol. 42 ›› Issue (11): 182-192.doi: 10.11959/j.issn.1000-436x.2021201

面向无人机雷达通信一体化系统的轨迹与资源联合优化

范绍帅¹, 王煜菲¹, 田辉¹, Jie Zhang², 史金鑫³

¹ 北京邮电大学网络与交换技术国家重点实验室，北京 100876
² 英国谢菲尔德大学电子与电气工程系，谢菲尔德 S102TN
³ 中国人民解放军32683部队，辽宁沈阳 110000

修回日期:2021-09-25 出版日期:2021-11-25 发布日期:2021-11-01
作者简介:范绍帅（1987− ），男，山东烟台人，博士，北京邮电大学讲师，主要研究方向为5G及后5G组网及关键技术、智能信息处理及网络自组织技术、高精度定位技术
王煜菲（1997−），女，吉林松原人，北京邮电大学硕士生，主要研究方向为雷达通信一体化、无线网络资源分配等
田辉（1963− ），女，河南郑州人，博士，北京邮电大学教授、博士生导师，主要研究方向为先进移动通信系统及无线网络技术
Jie Zhang（1967− ），男，山东济南人，博士，英国谢菲尔德大学教授，主要研究方向为无线通信网络规划与优化、下一代无线通信网等
史金鑫（1983− ），男，辽宁康平人，中国人民解放军32683部队助理工程师，主要研究方向为网络信息化技术
基金资助:
国家自然科学基金资助项目(61790553);国家自然科学基金资助项目(61801044)

Joint optimization of trajectory and resource allocation for UAV integrated radar and communication system

Shaoshuai FAN¹, Yufei WANG¹, Hui TIAN¹, Jie Zhang², Jinxin SHI³

¹ State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China
² Department of Electronic and Electrical Engineering, University of Sheffield, Sheffield S102TN, UK
³ 32683 PLA (The Chinese People’s Liberation Army) Troops, Shenyang 110000, China

Revised:2021-09-25 Online:2021-11-25 Published:2021-11-01
Supported by:
The National Natural Science Foundation of China(61790553);The National Natural Science Foundation of China(61801044)

摘要/Abstract

摘要：

针对灵活高效的区域探测和数据回传任务，研究了时分复用模式下无人机雷达通信一体化系统（IRCS）的时间资源分配、功率资源分配和无人机轨迹的联合优化问题，以达到最大化系统雷达探测链路和通信传输链路的加权总容量的目的。为解决该非凸优化问题，采用了块坐标下降（BCD）算法及逐次凸逼近（SCP）技术，迭代优化时间资源分配、功率资源分配和无人机轨迹。仿真结果表明，所提方案可以得到收敛解，并且可以有效提升系统容量。

关键词: 雷达通信一体化系统, 无人机, 资源分配, 轨迹设计, 系统容量

Abstract:

For the flexible and efficient area detection and data transmission tasks, the joint optimization of time resource allocation, power resource allocation and the trajectory for UAV (unmanned aerial vehicle) trajectory for airborne IRCS (integrated radar and communication system) was studied in a TDM (time division multiplexing) manner, in order to maximize the total weighted capacity of the system’s radar detection link and communication transmission link.To solve the non-convex optimization problem, the BCD (block coordinate descent) and the SCP (successive convex programming) techniques were adopted to iteratively optimize the time resource allocation, power resource allocation and UAV trajectory.The simulation results demonstrate that the proposed method can obtain a convergent solution, and can effectively improve the capacity of the system.

Key words: integrated radar and communication system, UAV, resource allocation, trajectory design, system capacity

中图分类号:

TN914

范绍帅, 王煜菲, 田辉, Jie Zhang, 史金鑫. 面向无人机雷达通信一体化系统的轨迹与资源联合优化[J]. 通信学报, 2021, 42(11): 182-192.

Shaoshuai FAN, Yufei WANG, Hui TIAN, Jie Zhang, Jinxin SHI. Joint optimization of trajectory and resource allocation for UAV integrated radar and communication system[J]. Journal on Communications, 2021, 42(11): 182-192.

图/表 14

图1

图2

表1

仿真参数设置"

参数	数值
待探测区域数量（N）/个	4
时隙数量（M）/个	300
无人机总运行时间（T）/s	600
无人机飞行高度（H）/m	30
噪声功率谱密度（n₀）/(dBm.Hz^-1)	-174
系统带宽（B）/MHz	10
载波频率（f_c）/GHz	28
无人机最大功耗（E_max）/J	48
无人机最大飞行速度（v_max）/（m·s^-1）	5
参考信道增益（ρ₀）/dBm	-60
雷达发射天线增益（G_t）/dB	18
雷达接收天线增益（G_r）/dB	18
雷达有效截面（RCS）	1
达探测MI阈值（ $φ_{MI}^{\min}$ ）^[33]/ nat	2.5

表1

图3

图4

图5

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图7

图8

图9

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参考文献 33

[1]	GUPTA A , JHA R K . A survey of 5G network:architecture and emerging technologies[J]. IEEE Access, 2015,3: 1206-1232.
[2]	STURM C , WIESBECK W . Waveform design and signal processing aspects for fusion of wireless communications and radar sensing[J]. Proceedings of the IEEE, 2011,99(7): 1236-1259.
[3]	HAN L , WU K . Joint wireless communication and radar sensing systems-state of the art and future prospects[J]. IET Microwaves,Antennas ＆ Propagation, 2013,7(11): 876-885.
[4]	WANG F Z , LI H B . Joint power allocation for radar and communication co-existence[J]. IEEE Signal Processing Letters, 2019,26(11): 1608-1612.
[5]	AHMED A , ZHANG Y D , HIMED B . Distributed dual-function radar-communication MIMO system with optimized resource allocation[C]// Proceedings of 2019 IEEE Radar Conference (RadarConf). Piscataway:IEEE Press, 2019: 1-5.
[6]	ZHANG Z K , ZHU G Y , SABAHI M F . Poster Abstract:array resource allocation based on KKT optimization for radar and communication integration[C]// Proceedings of 2019 18th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN). Piscataway:IEEE Press, 2019: 307-308.
[7]	ALZENAD M , EL-KEYI A , YANIKOMEROGLU H . 3-D placement of an unmanned aerial vehicle base station for maximum coverage of users with different QoS requirements[J]. IEEE Wireless Communications Letters, 2018,7(1): 38-41.
[8]	LI P M , XU J . UAV-enabled cellular networks with multi-hop backhauls:placement optimization and wireless resource allocation[C]// Proceedings of 2018 IEEE International Conference on Communication Systems (ICCS). Piscataway:IEEE Press, 2018: 110-114.
[9]	CHEN M Z , SAAD W , YIN C C . 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.
[10]	MOGHADDASI J , WU K . Multifunctional transceiver for future radar sensing and radio communicating data-fusion platform[J]. IEEE Access, 2016,4: 818-838.
[11]	LIU Y F , WEI Z Q , YAN C ,et al. Effective capacity based power allocation for the coexistence of an integrated radar and communication system and a commercial communication system[J]. IEEE Access, 2020,8: 58629-58644.
[12]	CHEN X , WEI Z Q , FANG Z X ,et al. Performance of joint radar-communication enabled cooperative UAV network[C]// Proceedings of 2019 IEEE International Conference on Signal,Information and Data Processing (ICSIDP). Piscataway:IEEE Press, 2019: 1-4.
[13]	WANG X Y , FEI Z S , ZHANG J A ,et al. Constrained utility maximization in dual-functional radar-communication multi-UAV networks[J]. IEEE Transactions on Communications, 2021,69(4): 2660-2672.
[14]	张婷婷, 柴来 . 多无人机多目标路径规划[J]. 指挥信息系统与技术, 2020,11(6): 32-36,46.
	ZHANG T T , CHAI L . Path planning for UAVs and multiple targets[J]. Command Information System and Technology, 2020,11(6): 32-36,46.
[15]	LONG T , ZENG T , HU C ,et al. High resolution radar real-time signal and information processing[J]. China Communications, 2019,16(2): 105-133.
[16]	JI J Q , ZHU K , NIYATO D ,et al. Joint cache placement,flight trajectory,and transmission power optimization for multi-UAV assisted wireless networks[J]. IEEE Transactions on Wireless Communications, 2020,19(8): 5389-5403.
[17]	SKOLNIK M I . Radar handbook[M]. 3rd ed. New York: McGraw-Hill Companies, 2008.
[18]	CHIRIYATH A R , PAUL B , BLISS D W . Radar-communications convergence:coexistence,cooperation,and co-design[J]. IEEE Transactions on Cognitive Communications and Networking, 2017,3(1): 1-12.
[19]	YANG H , WEI Z Q , FENG Z Y ,et al. Queue-aware dynamic resource allocation for the joint communication-radar system[J]. IEEE Transactions on Vehicular Technology, 2021,70(1): 754-767.
[20]	YUAN X , FENG Z Y , ZHANG J A ,et al. Spatio-temporal power optimization for MIMO joint communication and radio sensing systems with training overhead[J]. IEEE Transactions on Vehicular Technology, 2021,70(1): 514-528.
[21]	CHIRIYATH A R , PAUL B , JACYNA G M ,et al. Inner bounds on performance of radar and communications co-existence[J]. IEEE Transactions on Signal Processing, 2016,64(2): 464-474.
[22]	PAUL B , BLISS D W . Estimation information bounds using the I-MMSE formula and Gaussian mixture models[C]// Proceedings of 2016 Annual Conference on Information Science and Systems (CISS). Piscataway:IEEE Press, 2016: 274-279.
[23]	LIU Y J , LIAO G S , XU J W ,et al. Adaptive OFDM integrated radar and communications waveform design based on information theory[J]. IEEE Communications Letters, 2017,21(10): 2174-2177.
[24]	WU Q Q , ZENG Y , ZHANG R . Joint trajectory and communication design for multi-UAV enabled wireless networks[J]. IEEE Transactions on Wireless Communications, 2018,17(3): 2109-2121.
[25]	唐良荣, 唐建湘, 范丰仙 ,等. 计算机导论：计算思维和应用技术[M]. 北京：清华大学出版社, 2015.
	TANG L R , TANG J X , FAN F X ,et al. Introduction to computer:computational thinking and applied techniques[M]. Beijing: Tsinghua University Press, 2015.
[26]	MATTINGLEY J , BOYD S . Real-time convex optimization in signal processing[J]. IEEE Signal Processing Magazine, 2010,27(3): 50-61.
[27]	BOYD S , VANDENBERGHE L . Convex optimization[M]. Cambridge: Cambridge University Press, 2004.
[28]	SáNCHEZ-GARCIA J , GARCIA-CAMPOS J M , TORAL S L ,et al. An intelligent strategy for tactical movements of UAVs in disaster scenarios[J]. International Journal of Distributed Sensor Networks, 2016,12(3): 8132812.
[29]	SIVARAM M , BATRI K , MOHAMMED A S ,et al. Exploiting the local optima in genetic algorithm using tabu search[J]. Indian Journal of Science and Technology, 2019,12(1): 1-13.
[30]	江舸, 杨陈, 周晓青 ,等. 雷达信号处理技术在太赫兹成像中的应用[J]. 强激光与粒子束, 2013,25(6): 1555-1560.
	JIANG G , YANG C , ZHOU X Q ,et al. Application of radar signal processing in terahertz imaging[J]. High Power Laser and Particle Beams, 2013,25(6): 1555-1560.
[31]	KALANTARI E , BOR-YALINIZ I , YONGACOGLU A ,et al. User association and bandwidth allocation for terrestrial and aerial base stations with backhaul considerations[C]// Proceedings of 2017 IEEE 28th Annual International Symposium on Personal,Indoor,and Mobile Radio Communications (PIMRC). Piscataway:IEEE Press, 2017: 1-6.
[32]	SHARMA N , MADHUKUMAR A S . Genetic algorithm aided proportional fair resource allocation in multicast OFDM systems[J]. IEEE Transactions on Broadcasting, 2015,61(1): 16-29.
[33]	SHI C G , WANG F , SELLATHURAI M ,et al. Power minimization-based robust OFDM radar waveform design for radar and communication systems in coexistence[J]. IEEE Transactions on Signal Processing, 2018,66(5): 1316-1330.

面向无人机雷达通信一体化系统的轨迹与资源联合优化

Joint optimization of trajectory and resource allocation for UAV integrated radar and communication system

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