LPI-Based Resource Optimization Algorithm for Multi-carrier Dual-Function Radar-Communication System

The low probability of intercept (LPI) performance is pivotal for the self-safeguarding of dual-function radar-communication (DFRC) systems. This paper proposes an LPI-based resource optimization algorithm for the multi-carrier DFRC system. Different subcarriers are allocated reasonably to realize radar detection or communication transmission functions, which establishes the DFRC system model. The radar conditional mutual information and data transmission rate are derived to quantify the performance of radar and communication systems, respectively. These indicators are imposed on the constraints, aiming to ensure the performance of multi-target detection and multi-user communication. The optimization objective is to minimize the total transmit power to improve the LPI performance. To address the non-convexity of the optimization problem, a convex relaxation-based alternating algorithm is proposed. The variables are placed within an alternating framework, and the nonlinear inequality constraints are relaxed to apply Karush-Kuhn-Tucker (KKT) conditions for each iteration. Simulations validate that the proposed algorithm can provide lower transmit power for multi-target detection and multi-user communication, thereby facilitating the LPI performance of the DFRC system.