Multi Flow Transmission

Multi-flow transmission aims to optimize the efficient and reliable transfer of multiple data streams across networks, addressing challenges like interference and limited communication resources. Current research focuses on developing advanced algorithms, such as distributed policy gradient methods and graph neural network-based reinforcement learning, to manage these challenges, often incorporating techniques like intelligent reflecting surfaces to enhance signal transmission. These advancements are crucial for improving the performance of next-generation communication systems, including 6G networks and smart grids, by enabling higher data rates and more robust network operation. The development of efficient and scalable solutions is key to supporting the increasing demands of data-intensive applications.