论文标题
迈向6G TK $μ$极端连接：建筑，关键技术和实验
Toward 6G TK$μ$ Extreme Connectivity: Architecture, Key Technologies and Experiments
论文作者
论文摘要
与当前的5G相比，第六代（6G）网络正在朝着系统性能指标的新功能和速度级增强。特别是，6G网络有望通过TBPS规模的数据速率，KBPS/Hz规模的光谱效率和$ $ $ $ $ $ s级延迟来实现极端的连通性能。为此，原始的三层6G网络体系结构旨在实现统一的全光谱无单元无线电访问，并为各种应用提供以任务为中心的敏捷敏捷支持。设计的体系结构由Super Edge节点（SEN）进行了特征，该节点（SEN）集成了连接性，计算，AI，数据等。在此基础上，在集中式单元中建立了Pervasive多级别（PML）AI的技术框架，以启用以任务为中心的接近实时时间分配和网络自动化。然后，我们引入了全光谱统一的无单元网络的无线电访问网络（RAN）架构，该网络是6G TK $μ$ Extreme Connectivity的最具吸引力的RAN候选者之一。进一步讨论了一些最有前途的关键技术，即无细胞的大型MIMO，光子辅助的Terahertz无线访问和时空二维通道编码。实施测试床并进行了广泛的试验以评估创新技术和方法。拟议的6G网络体系结构和技术框架展示了全方位服务和全幕应用应用程序的令人兴奋的潜力。
Sixth-generation (6G) networks are evolving towards new features and order-of-magnitude enhancement of systematic performance metrics compared to the current 5G. In particular, the 6G networks are expected to achieve extreme connectivity performance with Tbps-scale data rate, Kbps/Hz-scale spectral efficiency, and $μ$s-scale latency. To this end, an original three-layer 6G network architecture is designed to realise uniform full-spectrum cell-free radio access and provide task-centric agile proximate support for diverse applications. The designed architecture is featured by super edge node (SEN) which integrates connectivity, computing, AI, data, etc. On this basis, a technological framework of pervasive multi-level (PML) AI is established in the centralised unit to enable task-centric near-real-time resource allocation and network automation. We then introduce a radio access network (RAN) architecture of full spectrum uniform cell-free networks, which is among the most attractive RAN candidates for 6G TK$μ$ extreme connectivity. A few most promising key technologies, i.e., cell-free massive MIMO, photonics-assisted Terahertz wireless access and spatiotemporal two-dimensional channel coding are further discussed. A testbed is implemented and extensive trials are conducted to evaluate innovative technologies and methodologies. The proposed 6G network architecture and technological framework demonstrate exciting potentials for full-service and full-scenario applications.
