Abstract
This work investigates the secrecy issues for the secrecy reconfigurable intelligent surface-based integrated satellite unmanned aerial vehicle (UAV) relay networks with multiple vehicle eavesdroppers. Particularly, the maximal ratio combining (MRC) eavesdropping is utilized to overhear the legitimate signal information. The UAV is applied to forward the legitimate signal to the destination user. Reconfigurable intelligent surface is applied to ensure the transmission. Relied on the proposed secrecy system model and MRC eavesdropping scheme, this paper gets the detailed investigations for the secrecy outage probability (SOP) through the whole signal-to-noise ratios (SNRs) to valuate the effects of important parameters on the SOP. Moreover, to achieve the further impacts of main parameters on the SOP at high SNRs, the approximate analysis for the SOP is also gotten together with the secrecy diversity order (SDO) and secrecy coding gain (SCG). At last, several typical Monte Carlo (MC) results are obtained to present the rightness of obtained theoretical analysis.
Original language | English |
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Pages (from-to) | 1676 - 1685 |
Number of pages | 10 |
Journal | IEEE Transactions on Intelligent Vehicles |
Volume | 8 |
Issue number | 2 |
Early online date | 29 Nov 2022 |
DOIs | |
Publication status | Published - 1 Feb 2023 |
Bibliographical note
Funding Information:This work was supported in part by the National Science Foundation of China under Grants 62001517 and 61673108, in part by the National Postdoctoral Program for Innovative Talents under Grant BX20200101, in part by the Key Scientific Research Projects of Higher Education Institutions in Henan Province under Grant 23B510001, in part by Guangdong Basic and Applied Basic Research Foundation under Grant 2022A1515010999, in part by the Science and Technology Program of Guangzhou under Grant 202201011850, in part by the Scientific Research Project of EducationDepartment ofGuangdong under Grant 2021KCXTD061, in part by the Major Basic Research Project of the Natural Science Foundation of the Jiangsu Higher Education Institutions under Grant 19KJA110002, and in part by the Yancheng Institute of Technology High-level Talent Research Initiation Project under Grant XJR2022001.
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© 2016 IEEE.