Wireless Infrastructure

Wireless infrastructure research focuses on improving the reliability, efficiency, and coverage of wireless networks, addressing challenges like insufficient connectivity in diverse environments and the increasing demand for location-based services. Current research emphasizes the development of adaptive and intelligent systems, employing techniques like convolutional neural networks (CNNs) for signal classification and Q-learning for dynamic spectrum access in applications such as autonomous driving and mobile infrastructure deployment using UAVs. These advancements aim to optimize network performance, reduce energy consumption (particularly in deep learning-based localization), and enhance the overall user experience across various applications.