Enhancing Wireless Communication Efficiency Using Dynamic Nonlinear Distortion Adaptive Optimization Analysis

Abstract Modern communication networks require improved signal quality and spectrum efficiency. Modern wireless communication relies heavily on the multiple input multiple output (MIMO) technology to improve spectrum efficiency and achieve faster data rates. However, the performance of MIMO systems is significantly hampered by non-linear distortions in power amplifiers (PA), especially under dynamic operating conditions. Traditional methods to reduce these distortions often lack the adaptability required for effective optimization. The proposed dynamic nonlinear distortion adaptive optimization analysis (DNDAOA) therefore introduces an adaptive approach that dynamically adjusts the pre-distortion signals using real-time feedback mechanisms. DNDAOA effectively reduces non-linear distortions and thus improves the performance of MIMO systems. Simulation results show that DNDAOA significantly increases spectrum efficiency, reduces error rates, and improves signal quality. This method is widely used in areas such as wireless telecommunications, internet of things (IoT), autonomous vehicles, and smart infrastructure, driving advances in connectivity, reliability, and data integrity.