Secrecy Rate Optimization for MIMO Communication Radar System Employing Cuckoo Search Algorithm

The proposed Secrecy rate optimization in MIMO (Multiple Input Multiple Output) radar communication systems involve designing strategies to maximize the secrecy of the transmitted information. It balances the trade-off between communication performance (e.g., data rate) and the system’s security, ensuring that confidential information is protected from eavesdroppers. This research investigates the optimization of secrecy rates in MIMO radar communication systems by employing the Cuckoo Search (CS) algorithm enhanced with Levy flight. Traditional optimization methods for secrecy rates often encounter challenges due to the non-convex nature of the problem and the high-dimensional search space involved. To address these challenges, we implement the Cuckoo Search algorithm, which mimics the brood parasitism behavior of cuckoo birds, coupled with Levy flight-a random walk technique that enhances the exploration capability of the search algorithm. The proposed approach begins with the formulation of the secrecy rate optimization problem, considering the transmit covariance matrix, channel state information, and power constraints. The CS algorithm is then applied to iteratively refine the transmission covariance matrix and maximize the secrecy rate. Through comprehensive simulations, we demonstrate that the CS algorithm with Levy flight not only converges to high-quality solutions but also exhibits robust performance compared to conventional optimization methods. The performance of the CSA is evaluated against varying numbers of antennas at the eavesdropper, ranging from a minimum of five to a maximum of thirty. Comparative analysis demonstrates that the proposed CSA outperforms the traditional algorithms, achieving superior secrecy rates across all tested scenarios. These results underscore the efficacy of the CSA in bolstering secure communication in MIMO radar systems.