Wireless Transmission

Wireless transmission research focuses on improving the efficiency, reliability, and speed of data transfer across various applications, from vehicular communication and digital audio broadcasting to federated learning and point cloud processing. Current efforts concentrate on developing sophisticated models, including deep reinforcement learning for optimizing resource allocation in dynamic environments and Bayesian optimization for enhancing spatial reuse in dense networks, alongside advanced signal processing techniques to mitigate interference and improve data fidelity. These advancements are crucial for enabling the proliferation of data-intensive applications and improving the performance of existing wireless systems, impacting fields ranging from autonomous driving to the Internet of Things.