Antenna Tilt

Antenna tilt optimization aims to improve wireless network performance by adjusting antenna angles to enhance coverage and capacity. Current research focuses on developing efficient algorithms, including reinforcement learning (RL) approaches like multi-agent RL with graph neural networks and contextual linear bandits, to learn optimal tilt control policies, often incorporating information from neighboring cells or using model-based methods to improve sample efficiency. These advancements are significant because they enable more efficient and adaptive network management, potentially leading to improved user experience and reduced operational costs in cellular and other wireless systems.