A Joint SLNR-MMSE-based Adaptive Secure Transmission Technique for Broadband IoT Systems

Signal-to-leakage-and-noise ratio (SLNR)-based transmit precoding techniques are preferable options to perform secure transmission in a low to moderate signal-to-noise ratio (SNR) regime. The conventional SLNR-based techniques assume that a legitimate receiver can estimate and equalize its precoded virtual channels often exhibiting frequency selective property. However, in Internet-of-Things (IoT) systems, lowcost terminals do not always have such complex receivers. We hence propose a new secure transmission scheme for future broadband IoT systems, where the joint SLNR-minimum mean square error (MMSE)-based precoding is performed so that a legitimate terminal assuming a linear complexity receives secret information successfully. Moreover, the proposed scheme adaptively determines transmission rates according to ergodic capacities. Simulation results verify that the proposed method improves the transmission rates significantly while preventing active eavesdroppers from correct receiving.