| Title |
Beamforming Algorithm for Improving Secrecy Rate in Multiple Flying RISs-supported Systems |
| Authors |
심윤아(Yuna Sim) ; 신승석(Seungseok Sin) ; 마진아(Jina Ma) ; 김지형(Jihyung Kim) ; 문상미(Sangmi Moon) ; 황인태(Intae Hwang) |
| DOI |
https://doi.org/10.5573/ieie.2023.60.11.3 |
| Keywords |
Deep neural network; Minorization-maximization; Reconfigurable intelligent surfaces; Secrecy rate; Successive convex approximation; Unmanned aerial vehicle |
| Abstract |
Wireless signals are vulnerable to eavesdropping due to the openness of wireless communication environments. Therefore, in order to increase the security performance of the physical layer, this paper considers multiple Flying RISs-supported system that combine unmanned aerial vehicle (UAV) with high altitude and mobility characteristics and reconfigurable intelligent surfaces (RIS) with high efficiency and low cost. First, we introduce the Deep Neural Network (DNN) algorithm to determine the appropriate location of multiple Flying RISs, and the penalty-based successive convex approximation (SCA) algorithm and minorization-maximization (MM) algorithm to optimize the transmission beamforming vector and the RIS beamforming vector. As a result of the simulation, it may be confirmed that the proposed technique has a higher secrecy rate than the existing technique. |