Multi-objective robust secure beamforming for cognitive satellite and UAV networks

doi:10.23919/JSEE.2021.000068

Journal of Systems Engineering and Electronics ›› 2021, Vol. 32 ›› Issue (4): 789-798.doi: 10.23919/JSEE.2021.000068

• SENSOR ARRAY SIGNAL PROCESSING AND ITS APPLICATIONS IN 5G/6G • Previous Articles Next Articles

Multi-objective robust secure beamforming for cognitive satellite and UAV networks

Zining WANG¹(), Min LIN^1,*(), Xiaogang TANG²(), Kefeng GUO²(), Shuo HUANG³(), Ming CHENG¹()

¹ School of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
² School of Space Information, Space Engineering University, Beijing 101407, China
³ Shanghai Aerospace Electronic Technology Institute, Shanghai 201109, China

Received:2021-02-01 Online:2021-08-18 Published:2021-09-30
Contact: Min LIN E-mail:wzn_email@163.com;linmin@njupt.edu.cn;titantxg@163.com;guokefeng.cool@163.com;hskidd@163.com;mingcheng@njupt.edu.cn
About author:|WANG Zining was born in 1997. He received his B.S. degree from Nanjing University of Posts and Telecommunications, Nanjing, China, in 2019. He is currently pursuing his Ph.D. degree in signal and information processing with Nanjing University of Posts and Telecommunications, Nanjing, China. His research interests include wireless communication and intelligent signal processing. E-mail: wzn_email@163.com||LIN Min was born in 1972. He received his B.S. degree from National University of Defense Technology, Changsha, China, in 1993, M.S. degree from Nanjing Institute of Communication Engineering, Nanjing, China, in 2000, and Ph.D. degree from Southeast University, Nanjing, in 2008, all in electrical engineering. From Apr. 2015 to Oct. 2015, he visited University of California, Irvine, as a senior research fellow. He is currently a professor and supervisor of Ph.D. and graduate students with Nanjing University of Posts and Telecommunications, Nanjing, China. His research interests include wireless communications and array signal processing. E-mail: linmin@njupt.edu.cn||TANG Xiaogang was born in 1977. He is currently an assistant professor of Xi’an Jiaotong University and Space Engineering University, Beijing, China. His research interests include mechatronics, pattern recognition, signal processing, and satellite communication. E-mail: titantxg@163.com||GUO Kefeng was born in 1990. He is currently an assistant professor with the School of Space Information, Space Engineering University. His current research interests are cooperative relay networks, MIMO communications, satellite communication, cognitive radio, NOMA technology and physical layer security. E-mail: guokefeng.cool@163.com||HUANG Shuo was born in 1985. He is now a senior engineer in Shanghai Aerospace Electronic Technology Institute. His current research interests include electronic engineering and satellite communications. E-mail: hskidd@163.com||CHENG Ming was born in 1991. He received his B.S. degree in information engineering from Nanjing University of Aeronautics and Astronautics in 2012, M.S. degree in communications engineering from Nanjing University of Aeronautics and Astronautics in 2015, and Ph.D. degree from Southeast University in 2020. His current research interests include applications of stochastic geometry, millimeter wave communications, massive MIMO, and intelligent reflecting surface. E-mail: mingcheng@njupt.edu.cn
Supported by:
This work was supported by the Key International Cooperation Research Project (61720106003), the National Natural Science Foundation of China (62001517), the Shanghai Aerospace Science and Technology Innovation Foundation (SAST2019-095), the NUPTSF (NY220111), and the Foundational Research Project of Complex Electronic System Simulation Laboratory (DXZT-JC-ZZ-2019-009; DXZT-JC-ZZ-2019-005)

Abstract

Abstract:

A multi-objective optimization based robust beamforming (BF) scheme is proposed to realize secure transmission in a cognitive satellite and unmanned aerial vehicle (UAV) network. Since the satellite network coexists with the UAV network, we first consider both achievable secrecy rate maximization and total transmit power minimization, and formulate a multi-objective optimization problem (MOOP) using the weighted Tchebycheff approach. Then, by supposing that only imperfect channel state information based on the angular information is available, we propose a method combining angular discretization with Taylor approximation to transform the non-convex objective function and constraints to the convex ones. Next, we adopt semi-definite programming together with randomization technology to solve the original MOOP and obtain the BF weight vector. Finally, simulation results illustrate that the Pareto optimal trade-off can be achieved, and the superiority of our proposed scheme is confirmed by comparing with the existing BF schemes.

Key words: cognitive satellite and unmanned aerial vehicle network (CSUN), multi-objective optimization, robust secure beamforming (BF), weighted Tchebycheff approach

Zining WANG, Min LIN, Xiaogang TANG, Kefeng GUO, Shuo HUANG, Ming CHENG. Multi-objective robust secure beamforming for cognitive satellite and UAV networks[J]. Journal of Systems Engineering and Electronics, 2021, 32(4): 789-798.

Figures/Tables 9

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References 36

1	LIN M, HUANG Q Q, COLA T D, et al Integrated 5G-satellite networks: a perspective on physical layer reliability and security. IEEE Wireless Communications, 2020, 27 (6): 152- 159. doi: 10.1109/MWC.001.2000143
2	HUANG Q Q, LIN M, ZHU W P, et al Performance analysis of integrated satellite-terrestrial multiantenna relay networks with multiuser scheduling. IEEE Trans. on Aerospace and Electronic Systems, 2020, 56 (4): 2718- 2731. doi: 10.1109/TAES.2019.2952698
3	SUN H Q, XIA W, HU X X, et al Earth observation satellite scheduling for emergency tasks. Journal of Systems Engineering and Electronics, 2019, 30 (5): 931- 945. doi: 10.21629/JSEE.2019.05.11
4	MENG S F, SHU J S, YANG Q, et al Analysis of detection capabilities of LEO reconnaissance satellite constellation based on coverage performance. Journal of Systems Engineering and Electronics, 2018, 29 (1): 98- 104. doi: 10.21629/JSEE.2018.01.10
5	MOZAFFARI M, SAAD W, BENNIS M, et al A tutorial on UAVs for wireless networks: applications, challenges, and open problem. IEEE Communications Surveys and Tutorials, 2019, 21 (3): 2334- 2360. doi: 10.1109/COMST.2019.2902862
6	KONG H C, LIN M, ZHU W P, et al Multiuser scheduling for asymmetric FSO/RF links in satellite-UAV-terrestrial networks. IEEE Wireless Communications Letters, 2020, 9 (8): 1235- 1239. doi: 10.1109/LWC.2020.2986750
7	LIN Z, LIN M, COLA T D, et al Supporting IoT with rate-splitting multiple access in satellite and aerial integrated networks. IEEE Internet of Things Journal, 2021, 8 (14): 11123- 11134. doi: 10.1109/JIOT.2021.3051603
8	XU Z, ZHANG E, CHEN Q W Rotary unmanned aerial vehicles path planning in rough terrain based on multi-objective particle swarm optimization. Journal of Systems Engineering and Electronics, 2020, 31 (1): 130- 141.
9	HUANG Q Q, LIN M, ZHU W P, et al Uplink massive access in mixed RF/FSO satellite-aerial-terrestrial networks. IEEE Trans. on Communications, 2021, 69 (4): 2413- 2426. doi: 10.1109/TCOMM.2021.3049364
10	LI B, FEI Z S, ZHANG Y UAV communications for 5G and beyond: recent advances and future trends. IEEE Internet of Things Journal, 2019, 6 (2): 2241- 2263. doi: 10.1109/JIOT.2018.2887086
11	LIU C X, FENG W, CHEN Y F, et al Cell-free satellite-UAV networks for 6G wide-area internet of things. IEEE Journal on Selected Areas in Communications, 2021, 39 (4): 1116- 1131. doi: 10.1109/JSAC.2020.3018837
12	HUANG Q Q, LIN M, WANG J B, et al Energy efficient beamforming schemes for satellite-aerial-terrestrial networks. IEEE Trans. on Communications, 2020, 68 (6): 3863- 3875. doi: 10.1109/TCOMM.2020.2978044
13	RUAN Y H, LI Y, ZHANG R, et al Cooperative resource management for cognitive satellite-aerial-terrestrial integrated networks towards IoT. IEEE Access, 2020, 8, 35759- 35769. doi: 10.1109/ACCESS.2020.2975012
14	KALANTARI A, ZHENG G, GAO Z, et al Secrecy analysis on network coding in bidirectional multibeam satellite communications. IEEE Trans. on Information Forensics and Security, 2015, 10 (9): 1862- 1874. doi: 10.1109/TIFS.2015.2432732
15	LIN Z, LIN M, OUYANG J, et al Beamforming for secure wireless information and power transfer in terrestrial networks coexisting with satellite networks. IEEE Signal Processing Letters, 2018, 25 (8): 1166- 1170. doi: 10.1109/LSP.2018.2842645
16	LIN Z, LIN M, CHAMPAGNE B, et al Secure and energy efficient transmission for RSMA-based cognitive satellite-terrestrial networks. IEEE Wireless Communication Letters, 2021, 10 (2): 251- 255. doi: 10.1109/LWC.2020.3026700
17	ARTI M K Channel estimation and detection in hybrid satellite-terrestrial communication systems. IEEE Trans. on Vehicular Technology, 2016, 65 (7): 5764- 5771. doi: 10.1109/TVT.2015.2456433
18	LI B, FEI Z S, CHU Z, et al Secure transmission for heterogeneous cellular networks with wireless information and power transfer. IEEE Systems Journal, 2018, 12 (10): 3755- 3766.
19	YAN Y, YANG W W, GUO D X, et al Robust secure beamforming and power splitting for millimeter-wave cognitive satellite–terrestrial networks with SWIPT. IEEE Systems Journal, 2020, 14 (3): 3233- 3244. doi: 10.1109/JSYST.2020.2991222
20	NG D W K, XIANG L, SCHOBER R. Multi-objective beamforming for secure communication in systems with wireless information and power transfer. Proc. of the 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications, 2013: 7−12.
21	LI Z, GONG S Q, XING C W, et al Multi-objective optimization for distributed MIMO networks. IEEE Trans. on Communications, 2017, 65 (10): 4247- 4259.
22	SUN Y, NG D W K, ZHU J, et al Multi-objective optimization for robust power efficient and secure full-duplex wireless communication systems. IEEE Trans. on Wireless Communications, 2016, 15 (8): 5511- 5526. doi: 10.1109/TWC.2016.2560815
23	YIN C Y, LIN Z, TAO X S, et al. Secure beamformer design for cognitive satellite terrestrial networks. Proc. of the IEEE 4th International Conference on Computer and Communications, 2018: 997−1002.
24	MIETTINEN L. Nonlinear multiobjective optimization. Boston: Kluwer Academic Publishers, 1999.
25	HOYHTYA M, KYROLAINEN J, HULKKONEN A, et al. Application of cognitive radio techniques to satellite communication. Proc. of the IEEE International Symposium on Dynamic Spectrum Access Networks, 2012: 540−551.
26	CUMANAN K, DING Z G, XU M, et al Secrecy rate optimization for secure multicast communications. IEEE Journal of Selected Topics in Signal Processing, 2016, 10 (8): 1417- 1432. doi: 10.1109/JSTSP.2016.2600518
27	CSISZAR I, KORNER J Broadcast channels with confidential messages. IEEE Trans. on Information Theory, 1978, 24 (3): 339- 348. doi: 10.1109/TIT.1978.1055892
28	LIN M, LIN Z, ZHU W P, et al Joint beamforming for secure communication in cognitive satellite terrestrial networks. IEEE Journal on Selected Areas in Communications, 2018, 36 (5): 1017- 1029. doi: 10.1109/JSAC.2018.2832819
29	LIN Z, LIN M, WANG J B Joint beamforming and power allocation for satellite-terrestrial integrated networks with non-orthogonal multiple access. IEEE Journal of Selected Topics in Signal Processing, 2019, 13 (3): 657- 670. doi: 10.1109/JSTSP.2019.2899731
30	International Telecommunication Union. Guidelines for evaluation of radio interface technologies for IMT-advanced. Document ITU-R M. 2135. Geneva: International Telecommunication Union, 2008.
31	ZHU H L, WANG J Z Chunk-based resource allocation in OFDMA systems—part I: chunk allocation. IEEE Trans. on Communications, 2009, 57 (9): 2734- 2744. doi: 10.1109/TCOMM.2009.09.080067
32	ZHU H L, WANG J Z Chunk-based resource allocation in OFDMA systems—part II: joint chunk, power and bit allocation. IEEE Trans. on Communications, 2012, 60 (2): 499- 509. doi: 10.1109/TCOMM.2011.112811.110036
33	FEI Z S, LI B, YANG S S, et al A survey of multi-objective optimization in wireless sensor networks: metrics, algorithms, and open problems. IEEE Communications Surveys & Tutorials, 2017, 19 (1): 550- 586.
34	MARLER R, ARORA J Survey of multi-objective optimization methods for engineering. Structural and Multidisciplinary Optimization, 2004, 26 (6): 369- 395. doi: 10.1007/s00158-003-0368-6
35	LUO Z Q, MA W K, SO M C, et al Semidefinite relaxation of quadratic optimization problems. IEEE Signal Processing Magazine, 2010, 27 (3): 20- 34. doi: 10.1109/MSP.2010.936019
36	LI B, FEI Z S, CHU Z, et al Robust chance-constrained secure transmission for cognitive satellite-terrestrial networks. IEEE Trans. on Vehicular Technology, 2018, 67 (5): 4208- 4219. doi: 10.1109/TVT.2018.2791859

Parameter	Value
UAV height/km	1
UPA	$8 \times 8$
Carrier frequency/GHz	2
3 dB angle/(°)	$\varphi _x^{3{\rm{dB}}}{\rm{ = 60,}}\;\varphi _y^{3{\rm{dB}}} = 10$
Antenna inter-element spacing	${d_1} = {d_2} = {\lambda / 2}$
Side-lobe level/dB	${S_m} = 20$
Bandwidth/KHz	$B{\rm{ = }}500$
Noise temperature/K	$T = 300$

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Multi-objective robust secure beamforming for cognitive satellite and UAV networks

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