RIS-Empowered Coexistence Between Self-Sustainable IoT and Radar Networks

This paper investigates the coexistence of a selfsustainable Internet of Things (IoT) network and a multiantenna radar system operating in a shared frequency band, empowered by a reconfigurable intelligent surface (RIS). A novel joint optimization framework is proposed to maximize the throughput of the IoT network while ensuring the reliability of radar detection. The formulation jointly considers RIS phaseshift design, radar signal covariance, and time scheduling. To begin with, we employ the Lagrangian duality framework along with the Karush-Kuhn-Tucker (KKT) optimality criteria to derive the closed-form solution for time resource allocation. Following this, an alternating optimization (AO) technique is formulated to jointly refine the radar covariance matrix and optimize the phase shifts applied by the RIS in a coordinated manner. A tailored iterative mechanism is introduced to handle a summation of fractional objectives, which are typically hard to solve directly. Moreover, to tackle the fundamental nonconvex challenges presented by the simultaneous optimization of sensing beamforming vectors and RIS phase shifts, an alternating optimization strategy combined with semidefinite programming (SDP) relaxation is employed. Lastly, comprehensive simulations validate that our proposed framework surpasses conventional strategies in terms of uplink throughput and radar detection accuracy. The results obtained from this study confirm that RIS holds significant promise as a crucial technology facilitating the advancement of next-generation integrated sensing and communication networks.