Ultra Reliable Low Latency Communication

Ultra-reliable low-latency communication (URLLC) aims to deliver critical data with extremely high reliability and minimal delay, crucial for applications like autonomous driving and industrial automation. Current research focuses on optimizing resource allocation using techniques like reinforcement learning (including hierarchical and event-triggered approaches), and employing machine learning models such as Generative Adversarial Networks (GANs) and neural contextual bandits for accurate channel modeling and user admission control. These advancements are vital for enabling the next generation of time-sensitive applications by improving resource utilization and ensuring the stringent reliability and latency requirements of URLLC are met.