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

无线移动通信持续发展为更高的数据速率，5G扩大了其范围，包括大规模和超可靠的低延迟链接。无线进化中的基本任务是解决两个终点之间可靠数据交换的技术问题。 6G目标将通过考虑传输数据的重要性，相关性和价值将无线系统设计提升到下一阶段，从而将基于AI/ML的架构的潜力转变为语义和面向目标的通信范式。两种趋势证实了6G目标的及时性：（1）通过低语义内容或最终目标相关的数据流对无线网络的燃烧； （2）从不可靠的数据流中提取“含义”和意图的网络节点和设备的AI能力提高。这些趋势在6G目标的两个主要目标下：（1）仅传达最相关的信息来减少数据流量； （2）设计具有现代AI/ML技术的网络条件和通信目标的数据效率，健壮和依赖的协议。 6G目标的研究突破和创新是三倍：首先，6G目标将开发AI/ML授权的语义数据表示，感应和压缩算法，结合了数据和模型驱动的方法，并致力于从基于AI的联合源源源源源编码中利用未限制的差异。其次，6G目标将引入以语义为导向的解决方案，以支持分布式推理和时间敏感的通信，从而通过将沟通定制为实际目标，从而概括了5G的低潜伏期。最后，6G目标将通过定义语义认知无线电的概念来引入无线技术，以实现能源效率，EMF暴露和频谱管理的可持续性技术