6G Goal-Oriented AI-enabled Learning and Semantic Communication Networks (6G Goals)

6G目标导向的人工智能学习和语义通信网络（6G目标）

• 批准号: 10110118
• 金额: $ 49.05万
• 依托单位: IMPERIAL COLLEGE LONDON
• 依托单位国家: 英国
• 项目类别: EU-Funded
• 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=10110118
• 关键词: 6G; Goal; Oriented; AI; enabled

Wireless mobile communication has continually evolved towards higher data rates, with 5G expanding its scope to include massive and ultra-reliable low-latency links. The underlying quest in the wireless evolution has been to solve the technical problem of reliable data exchange between two end-points. 6G-GOALS will take the wireless system design to its next stage by considering the significance, relevance, and value of the transmitted data, transforming the potential of the emerging AI/ML-based architectures into a semantic and goal-oriented communication paradigm. Two trends corroborate the timeliness of 6G-GOALS: (1) the burden on wireless networks by data flows with low semantic content or relevance for the end goal; (2) the increased AI capability of network nodes and devices to extract ‘meaning’ and intention from unreliable data flows. These trends underpin the two main objectives of 6G-GOALS: (1) to reduce data traffic by conveying only the most relevant information; (2) to design data-efficient, robust, and resilient protocols that can adapt to network conditions and communication objectives using modern AI/ML techniques. The research breakthroughs and innovation of 6G-GOALS are three-fold: First, 6G-GOALS will develop AI/ML-empowered semantic data representation, sensing, and compression algorithms combining data-and-model-driven approaches, and work towards exploiting untapped gains from AI-based joint source channel coding. Second, 6G-GOALS will introduce semantic-oriented solutions for supporting distributed reasoning and time-sensitive communication, generalizing low- latency of 5G by tailoring communication to the actual goal. Finally, 6G-GOALS will introduce wireless technologies for sustainability in energy efficiency, EMF exposure, and spectrum management, by defining the concept of semantic cognitive radio

无线移动通信不断向更高的数据速率发展，5G 将其范围扩大到包括大规模和超可靠的低延迟链路，无线演进的根本任务是解决两端之间可靠数据交换的技术问题。 6G-GOALS 将考虑传输数据的重要性、相关性和价值，将无线系统设计带入下一阶段，将新兴的基于 AI/ML 的架构的潜力转化为语义和面向目标的通信范式。两个趋势证实了这一点。 6G-GOALS 的及时性：(1) 语义内容或与最终目标相关性较低的数据流给无线网络带来的负担；(2) 网络节点和设备从不可靠的内容中提取“含义”和意图的人工智能能力增强；这些趋势支撑了 6G-GOALS 的两个主要目标：(1) 通过仅传送最相关的信息来减少数据流量；(2) 设计能够适应网络条件的数据高效、稳健且有弹性的协议。和使用现代的沟通目标6G-GOALS的研究突破和创新有三个方面：首先，6G-GOALS将开发结合数据和模型驱动方法的AI/ML赋能的语义数据表示、感知和压缩算法。其次，6G-GOALS 将引入面向语义的解决方案来支持分布式推理和时间敏感通信，通过根据实际目标定制通信来推广 5G 的低延迟。最后，6G-GOALS 将通过定义语义认知无线电的概念，引入无线技术，以实现能源效率、EMF 暴露和频谱管理方面的可持续性