Development of a fully data-driven artificial intelligence and deep learning for URLLC application in 6G wireless systems: A survey

The future of the sixth generation (6G) involves the development of a fully data-driven method that provides terabit rate per second, and adopts over 1000 connections per person, in 10 years (2030 virtually instantaneously). Data-driven for ultra-reliable and low latency communication (URLLC) is a new service paradigm provided by a new application of future 6G wireless communications and network architecture, involving 100+ Gbps data rates with one-millisecond latency. The key constraint is the amount of computing power available to spread massive data and well-designed artificial neural networks (ANNs). Artificial Intelligence (AI) provides a new technique to design wireless networks by learning, predicting, and making decisions to manage the stream of Big Data training individuals which provides more capacity to transform expert learning in order to develop the performance of wireless networks. We study the developing artificial intelligence that will be the driving force for URLLC in 6G communication systems to guarantee low latency. This work discusses the efficiency of the developing networks and alleviating the great challenges for application scenarios such as holographic radios, enhanced wireless channel coding, enormous Internet of Things (IoT) integration, and haptic communication for virtual and augmented reality, which provide new services in the 6G network. Furthermore, improving a multi-level architecture (MLA) for URLLC in deep Learning (DL) allows for data-driven AI and 6G networks for device intelligence, as well as for innovations based on effective learning capabilities. These difficulties must be solved to meet the needs of future smart networks. Furthermore, this research categorizes various unexplored research gaps between machine learning (ML) and 6G.