Securing NOMA 6G Communications Leveraging Intelligent Omni-Surfaces Under Residual Hardware Impairments

In this manuscript, we introduce an efficient resource allocation strategy to enhance the security of an intelligent omni-surface (IOS) assisted secure Internet-of-things (IoT) enabled non-orthogonal multiple access (NOMA) network under residual hardware impairments (RHIs) resulting from imperfect hardware design. In particular, the goal is to maximize the sum secrecy rate of the considered multi-cluster based secure NOMA system assisted by an IOS node. This is achieved by optimizing both the active beamforming vectors of NOMA users within the transmission and reflection regions of the system, and the transmission and reflection coefficients of the IOS node, while adhering to quality-of-service, successive interference cancellation, power budget, and energy conservation constraints. Moreover, the presented alternating optimization framework tackles the significantly non-convex optimization problem through a two-stage process. Firstly, the active beamforming vectors are obtained using successive convex approximation (SCA) and second-order conic programming (SOCP) techniques. Secondly, based on the determined active beamforming vectors, the transmission and reflection coefficients of the IOS node are computed utilizing SCA and semi-definite relaxation (SDR) techniques, where rank-1 solution is achieved through Gaussian randomization method. Ultimately, the numerical simulations validate the efficacy of the suggested method over competing benchmarks, in terms of sum secrecy rate, showcasing its superiority in achieving fast convergence within a limited number of iterations.