Platform Driving The Ultimate Connectivity

平台驱动终极连接

• 批准号: EP/X04047X/2
• 负责人: Harald Haas
• 金额: --
• 依托单位: University of Cambridge
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FX04047X%2F2
• 关键词: Platform; Driving; Ultimate; Connectivity

The research of the TITAN platform is geared towards the ultimate network of networks and is structured in six strongly interconnected lighthouse projects which reflect all network elements - 1) the core, 2) optical fibre, 3) radio frequency (RF) including cellular and wireless networks, 4) emerging optical wireless networks for access and backhaul, 5) non-terrestrial networks involving satellites, aerial and underwater networks, and finally 6) quantum communication networks. The research on the core network focuses on a new architecture and artificial intelligence (AI) techniques that enable the integration of multi-access technologies for a seamless end-to-end service delivery by considering advanced requirements in terms of data rate, latency, security and energy efficiency. TITAN will conduct novel research that aims at orchestrating the different existing and emerging RF networks (3G, 4G, 5G, 6G, WiFi, Bluetooth, etc.) towards a single network by developing techniques that would optimally select the respective RF network, or networks, and develop the respective protocols to enable a seamless end-to-end connection. Because of the undisputed need for new spectrum in future networks, TITAN will crucially include new networks that are built around the terahertz and optical spectrum. Since these networks will benefit from new intelligent reflecting surfaces as part of a new network element, TITAN will include research on the networking aspects and the integration of reconfigurable intelligent surfaces (RIS) by building on the work on AI and machine learning (ML) developed for other parts of the network, such as edge and core. Optical fibre networks are an important element of a network of networks. Therefore, TITAN will address research questions on the optimum integration of advanced optical fibre technologies such as hollowcore fibres and new agile transceiver technologies to support key network requirements such as latency. Universal service availability and what is described as the 'digital divide' represent an increasing societal challenge. Therefore, TITAN will conduct critical research on the integration of non-terrestrial networks which include aerial, satellite and underwater networks all geared towards a seamless end-to-end service provision which is achieved by the holistic approach of TITAN. Lastly, TITAN will meaningfully integrate new quantum network technologies alongside conventional networks and will provide important guidance on the optimum use of both fundamental networks. An important consideration of TITAN is the extraction of sensing information from networks. All network elements have particular features and, in conjunction with ML techniques, important side information can be extracted. TITAN will investigate this capability for each network segment, but crucially brings the independent sensing information together to achieve an ultra-cognitive network which exhibits the highest level of self-x (configuration, healing, automation, optimisation).

TITAN 平台的研究面向最终的网络中的网络，由六个紧密互连的灯塔项目构成，反映了所有网络元素 - 1) 核心、2) 光纤、3) 射频 (RF)，包括蜂窝和无线网络，4) 用于接入和回程的新兴光无线网络，5) 涉及卫星、空中和水下网络的非地面网络，最后 6) 量子通信网络。核心网络的研究重点是新的架构和人工智能（AI）技术，通过考虑数据速率、延迟、安全性方面的高级要求，实现多接入技术的集成，以实现无缝的端到端服务交付和能源效率。 TITAN 将进行新颖的研究，旨在通过开发最佳选择相应 RF 网络的技术，将不同的现有和新兴 RF 网络（3G、4G、5G、6G、WiFi、蓝牙等）编排为单一网络，并开发相应的协议以实现无缝的端到端连接。由于未来网络对新频谱的需求无可争议，TITAN 将至关重要地包括围绕太赫兹和光谱构建的新网络。由于这些网络将受益于作为新网络元素一部分的新智能反射表面，TITAN 将在人工智能和机器学习 (ML) 工作的基础上，对网络方面和可重构智能表面 (RIS) 的集成进行研究对于网络的其他部分，例如边缘和核心。光纤网络是网络的重要组成部分。因此，TITAN 将解决空心光纤等先进光纤技术与新型敏捷收发器技术的最佳集成研究问题，以支持延迟等关键网络需求。普遍服务的可用性和所谓的“数字鸿沟”代表着日益严峻的社会挑战。因此，TITAN将对非地面网络的整合进行关键研究，包括空中、卫星和水下网络，所有这些都旨在通过TITAN的整体方法实现无缝的端到端服务提供。最后，TITAN 将有意义地将新的量子网络技术与传统网络集成，并将为这两种基础网络的最佳使用提供重要指导。 TITAN 的一个重要考虑因素是从网络中提取传感信息。所有网络元素都有特定的特征，结合机器学习技术，可以提取重要的辅助信息。 TITAN 将研究每个网络段的这种能力，但关键是将独立的感知信息整合在一起，以实现展示最高水平的 self-x（配置、修复、自动化、优化）的超认知网络。