SLNR-Based Secure Energy Efficient Beamforming in Multibeam Satellite Systems

Motivated by the fact that both security and energy efficiency are the fundamental requirements and design targets of future satellite communications, this letter investigates secure energy efficient beamforming in multibeam satellite systems, where the satellite user in each beam is surrounded by a...

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Bibliographic Details
Published inIEEE transactions on aerospace and electronic systems Vol. 59; no. 2; pp. 2085 - 2088
Main Authors Lin, Zhi, An, Kang, Niu, Hehao, Hu, Yihua, Chatzinotas, Symeon, Zheng, Gan, Wang, Jiangzhou
Format Journal Article
LanguageEnglish
Published New York IEEE 01.04.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Alternating optimization
Array signal processing
Beamforming
Energy efficiency
Iterative algorithms
multibeam satellite (MS) systems
Optimization
Power consumption
Resource management
Satellite broadcasting
Satellite communications
Satellites
secrecy energy efficiency (SEE)
Security
signal-to-leakage-plus-noise ratio (SLNR)
Transmitting antennas
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Summary:Motivated by the fact that both security and energy efficiency are the fundamental requirements and design targets of future satellite communications, this letter investigates secure energy efficient beamforming in multibeam satellite systems, where the satellite user in each beam is surrounded by an eavesdropper attempting to intercept the confidential information. To simultaneously improve the transmission security and reduce power consumption, our design objective is to maximize the system secrecy energy efficiency (SEE) under the constraint of total transmit power budget. Different from the existing schemes with high complexity, we propose an alternating optimization scheme to address the SEE problem by decomposing the original nonconvex problem into subproblems. Specifically, we first utilize the signal-to-leakage-plus-noise ratio metric to obtain closed-form normalized beamforming weight vectors, while the successive convex approximation method is used to efficiently solve the power allocation subproblem. Then, an iterative algorithm is proposed to obtain the suboptimal solutions. Finally, simulations are provided to verify the superiority of the proposed scheme compared to the benchmark schemes.
ISSN:0018-9251
1557-9603
DOI:10.1109/TAES.2022.3190238