Secured and Intelligent Massive Machine-to-Machine Communication for 6G

为了满足预期过多的需求服务，6G被设想为一个革命性的范例，将5G无线网络中增强的宽带、海量接入以及超可靠和低延迟服务的能力提升到更强大和智能的水平。这一举措将在整个无线通信协议栈中带来重大的多学科研究挑战，包括移动网络的建模和部署方式。6G网络的结构将是高度异构、密集部署和动态的。再加上紧凑的服务质量，这种复杂的架构将导致传统网络运营例程难以为继。作为回应，人工智能(AI)，特别是机器学习(ML)、语义通信和数字孪生(DT)作为实现全智能网络编排和管理的解决方案应运而生。通过从不确定和动态环境中学习，支持AI的信道估计和频谱管理将为充分发挥超宽带技术的优异性能开辟机会。此外，超大规模接入带来的能源和安全挑战可以通过应用基于人工智能的方法来缓解。SEON项目的总体研究目标是开发和设计6G安全智能大规模机器对机器通信的无缝无线接入网络系统。除了技术开发，为了满足即将到来的6G时代对未来劳动力的迫切需求，这个合作项目将为博士生创建一个培训网络，他们将为未来6G网络的设计和实施做出贡献。

To satisfy the expected plethora of demanding services, 6G is envisioned as a revolutionary paradigm to carry forward the capacities of enhanced broadband, massive access, and Ultra-reliable and low latency services in 5G wireless networks to a more robust and intelligent level. This move will introduce significant new multidisciplinary research challenges emerging throughout the wireless communication protocol stacks, including the way the mobile network is modelled and deployed. The structure of 6G networks will be highly heterogeneous, densely deployed, and dynamic. Combined with the tight quality of services, such complex architecture will result in the untenability of legacy network operation routines. In response, artificial intelligence (AI), especially machine learning (ML), Semantic Communication and Digital Twin (DT) are emerging as solutions to realize the fully intelligent network orchestration and management. By learning from uncertain and dynamic environments, AI-enabled channel estimation and spectrum management will open up opportunities for bringing the excellent performance of Ultra-broadband techniques into full play. Additionally, challenges brought by Ultra-massive access concerning energy and security can be mitigated by applying AI-based approaches. The overall research objective of the SCION project is to develop and design the network systems for seamless wireless access for Secure and Intelligent Massive Machine-to-Machine Communications for 6G. In addition to technology development, to meet the urgent needs for the future working force of the coming 6G era, this collaborative project will create a training network for Doctoral Candidates who will contribute to the design and implementation of future 6G networks.