Intelligent Reflecting Surface Enhanced Maritime Joint Sensing and Communication Systems: Performance Optimization

The maritime joint sensing and communication system (MSCS) has recently emerged as a promising solution to address the maritime spectrum scarcity issue for high-efficiency communication and environmental sensing. To mitigate the significant path loss experienced over the complex sea surface, the intelligent reflecting surface (IRS) is integrated into the MSCS to enhance the signal quality by dynamically adjusting the phases of its reflecting elements. Building upon this foundation, we aim to improve the sensing performance by maximizing the sensing signal-to-noise ratio while maintaining normal maritime communication, which involves optimizing active and passive beamforming vectors. Under the unpredictable environmental information and high-complexity and high-overhead channel information estimation in MSCS, we propose a heuristic algorithm based on genetic evolution to tackle this problem. To ensure the algorithm convergence and the feasibility of available solutions, we introduce an individual processing approach and an elitist reservation strategy in each genetic generation. Numerical results and simulations validate the convergence and efficacy of the proposed algorithm. Additionally, we analyze the effects of critical parameters and IRS structure on the algorithm performance.