Development of A Fully Data-Driven Artificial Intelligence and Deep Learning for URLLC Application in 6G Wireless Systems: A Survey
The full future of the sixth generation will develop a fully data-driven that provide terabit rate per second, and adopt an average of 1000+ massive number of connections per person in 10 years 2030 virtually instantaneously. Data-driven for ultra-reliable and low latency communication is a new service paradigm provided by a new application of future sixth-generation wireless communication 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. Artificial Intelligence provides a new technique to design wireless networks by apply learning, predicting, and make decisions to manage the stream of big data training individuals, which provides more the capacity to transform that expert learning to develop the performance of wireless networks. We study the developing technologies that will be the driving force are artificial intelligence, communication systems to guarantee low latency. This paper aims to discuss the efficiency of the developing network and alleviate the great challenge for application scenarios and study Holographic radio, enhanced wireless channel coding, enormous Internet of Things integration, and haptic communication for virtual and augmented reality provide new services on the 6G network. Furthermore, improving a multi-level architecture for ultra-reliable and low latency in deep Learning allows for data-driven AI and 6G networks for device intelligence, as well as allowing innovations based on effective learning capabilities. These difficulties must be solved in order to meet the needs of future smart networks. Furthermore, this research categorizes various unexplored research gaps between machine learning and the sixth generation.
Code (0)
등록된 구현이 없습니다.
Methods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Artificial intelligence inspired freeform optics design: a review
Integrating artificial intelligence (AI) techniques such as machine learning and deep learning into freeform optics design has significantly enhanced design efficiency, expanded the design space, and led to innovative so…
Proactive and Reactive Engagement of Artificial Intelligence Methods for Education: A Review
Quality education, one of the seventeen sustainable development goals (SDGs) identified by the United Nations General Assembly, stands to benefit enormously from the adoption of artificial intelligence (AI) driven tools …
ArticlesSchedulingInitial Development and Evaluation of the Creative Artificial Intelligence through Recurring Developments and Determinations (CAIRDD) System
Computer system creativity is a key step on the pathway to artificial general intelligence (AGI). It is elusive, however, due to the fact that human creativity is not fully understood and, thus, it is difficult to develo…
Machine Learning and Artificial Intelligence-Driven Multi-Scale Modeling for High Burnup Accident-Tolerant Fuels for Light Water-Based SMR Applications
The concept of small modular reactor has changed the outlook for tackling future energy crises. This new reactor technology is very promising considering its lower investment requirements, modularity, design simplicity, …
Patient-specific, mechanistic models of tumor growth incorporating artificial intelligence and big data
Despite the remarkable advances in cancer diagnosis, treatment, and management that have occurred over the past decade, malignant tumors remain a major public health problem. Further progress in combating cancer may be e…