XL-RIS empowered near-field physical layer security against jamming and eavesdropping attacks

Wireless communication is vulnerable to malicious jamming and eavesdropping attacks due to the broadcast nature of wireless channels. An extremely-large-scale reconfigurable intelligent surface (XLRIS) demonstrates its abilities to enhance the physical layer security (PLS) and compensate for the severe path loss. We investigate an XL-RIS empowered near-field PLS communication system against jamming and eavesdropping attacks with the help of artificial noise (AN). To maximize the secrecy capacity, we propose an alternating optimization (AO) based algorithm to jointly optimize the beamformers at the base station (BS) and the reflection coefficient matrix at the XL-RIS, subject to the BS’s maximum transmit power and the XL-RIS’s unitmodulus constraints. For the beamforming and AN design at the BS, auxiliary variables are introduced to reformulate the subproblem into a more tractable problem, which is solved by the proposed successive convex approximation (SCA) based algorithm. For the reflection coefficient matrix design at the XL-RIS, a manifold optimization (MO) based algorithm is proposed to address the challenge of large-scale variables and unit-modulus constraints. Numerical results show that XL-RIS can ensure secure communication even if the eavesdropper is located at the same direction as the legitimate user and closer to the XL-RIS.