6G Communication Systems Utilizing Intelligent Reflective Surfaces for Improved Data Rates Based on AI

Intelligent Reflecting Surfaces (IRSs) are essential for energy-efficient 6G networks; however, enhancing their performance to attain both elevated data rates and energy efficiency continues to be a formidable challenge. This paper uses artificial intelligence (AI) to solve this problem by creating a new AI-based optimization algorithm called Dynamic and Static Particle Swarm Optimization (DS-PSO). The suggested AI method intelligently learns the best phase-shift settings for IRS elements, balancing exploration and exploitation in real time to get the best signal-to-noise ratio at the receiver. The simulation results show that our method works, with the AI-optimized IRS model being up to 269% more energy-efficient than a standard IRS at 10 bits/s/Hz. This study highlights the considerable potential of AI algorithms in navigating the complex trade-offs of next-generation communication systems, establishing our model as a robust solution for sustainable 6G connectivity.