TY - GEN
T1 - Enhancing Physical Layer Security in Large Intelligent Surface-aided Cooperative Networks
AU - Makin, Madi
AU - Arzykulov, Sultangali
AU - Celik, Abdulkadir
AU - Eltawil, Ahmed
AU - Nauryzbayev, Galymzhan
N1 - KAUST Repository Item: Exported on 2022-09-14
Acknowledgements: This work was supported by the Nazarbayev University (NU) Social Policy grant, the NU FDCRP Grant no. 240919FD3935, and the NU CRP Grant no. 11022021CRP1513.
PY - 2022/8/25
Y1 - 2022/8/25
N2 - Intelligent surfaces have recently been presented as a revolutionary technique and recognized as one of the candidates for beyond fifth-generation wireless networks. This paper investigates the physical layer security of a large intelligent surface (LIS) aided wireless system over Nakagami-m channels. We propose a phase-based adaptive modulation scheme, where LIS’s phase-shift optimization process is effectively utilized to enhance the system’s security. Moreover, the effect of the Nakagami-m fading parameter (m), correlation parameter (ρ), and a number of passive LIS elements (M) on the system performance are examined. The significant improvement in confidentiality is shown while evaluating the bit error rate performance of the proposed scheme.
AB - Intelligent surfaces have recently been presented as a revolutionary technique and recognized as one of the candidates for beyond fifth-generation wireless networks. This paper investigates the physical layer security of a large intelligent surface (LIS) aided wireless system over Nakagami-m channels. We propose a phase-based adaptive modulation scheme, where LIS’s phase-shift optimization process is effectively utilized to enhance the system’s security. Moreover, the effect of the Nakagami-m fading parameter (m), correlation parameter (ρ), and a number of passive LIS elements (M) on the system performance are examined. The significant improvement in confidentiality is shown while evaluating the bit error rate performance of the proposed scheme.
UR - http://hdl.handle.net/10754/680549
UR - https://ieeexplore.ieee.org/document/9860850/
U2 - 10.1109/vtc2022-spring54318.2022.9860850
DO - 10.1109/vtc2022-spring54318.2022.9860850
M3 - Conference contribution
BT - 2022 IEEE 95th Vehicular Technology Conference: (VTC2022-Spring)
PB - IEEE
ER -