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.
翻译:第六代的全未来将开发完全由数据驱动的全未来,每秒提供高频率,并在2030年的10年中几乎瞬间采用平均1000+的人均连接量。数据驱动的超可靠和低潜伏通信是一种新的服务模式,由未来第六代无线通信和网络架构的新应用提供,涉及100+Gbps的数据率,含1毫秒的延迟度。关键制约因素是可用于传播大规模数据和设计完善的人工神经网络的计算能力的数量。人工智能提供了一种新的技术,通过应用学习、预测和做出决策来设计无线网络,以管理大型数据培训人员的流。数据驱动的超可靠和低潜伏通信能力为转变专家学习开发无线网络的能力提供了更多的能力。我们研究开发的驱动力是人工智能,通信系统能保证低潜伏。本文旨在讨论开发网络的效率,并减轻应用的智能广播、强化的智能频道差距、巨量的互联网、为虚拟和强化的虚拟和强化现实的通信网络提供新的能力,使甚低清晰的智能网络成为基于深度学习的智能网络。此外,必须改进基于甚高清晰的虚拟和高清晰的虚拟和高清晰的智能网络,使高清晰的学习网络提供新的服务。