6G AI原生网络中的目标导向与语义通信：6G-GOALS方法
Goal-Oriented and Semantic Communication in 6G AI-Native Networks: The 6G-GOALS Approach
AI总结：
本文提出6G-GOALS方法，将目标导向与语义通信融入AI原生6G网络，通过AI增强的语义数据表示、基础AI推理和高效无线服务三大支柱，优化智能体间信息交换的带宽、延迟、能耗及电磁辐射。
摘要：
人工智能技术的最新进展显著扩展了设备智能，促进了分布式AI智能体之间的联合与协作。这些进步对未来6G移动网络架构提出了新的要求。为满足这些需求，必须超越经典边界，将通信、计算、控制和智能相集成。本文提出了面向AI原生6G网络的目标导向与语义通信的6G-GOALS方法。该方法将语义、语用和目标导向通信融入AI原生技术，旨在以更相关、更有效和更及时的方式促进智能体之间的信息交换，从而优化带宽、延迟、能量和电磁场（EMF）辐射。其重点是将数据提炼为最相关的形式和简洁的表示，与源意图或目标对象的目的和上下文对齐，或服务于特定目标。6G-GOALS建立在三个基本支柱之上：i）AI增强的语义数据表示、感知、压缩和通信，ii）基础AI推理和因果语义数据表示、上下文相关性以及面向目标有效性的价值，iii）由更高效的无线服务实现的可持续性。最后，我们展示了在近期用例中实现语义、目标导向和语用通信原则的两个概念验证。我们的研究涵盖了项目的愿景、方法和潜在影响。
英文摘要：
Recent advances in AI technologies have notably expanded device intelligence, fostering federation and cooperation among distributed AI agents. These advancements impose new requirements on future 6G mobile network architectures. To meet these demands, it is essential to transcend classical boundaries and integrate communication, computation, control, and intelligence. This paper presents the 6G-GOALS approach to goal-oriented and semantic communications for AI-Native 6G Networks. The proposed approach incorporates semantic, pragmatic, and goal-oriented communication into AI-native technologies, aiming to facilitate information exchange between intelligent agents in a more relevant, effective, and timely manner, thereby optimizing bandwidth, latency, energy, and electromagnetic field (EMF) radiation. The focus is on distilling data to its most relevant form and terse representation, aligning with the source's intent or the destination's objectives and context, or serving a specific goal. 6G-GOALS builds on three fundamental pillars: i) AI-enhanced semantic data representation, sensing, compression, and communication, ii) foundational AI reasoning and causal semantic data representation, contextual relevance, and value for goal-oriented effectiveness, and iii) sustainability enabled by more efficient wireless services. Finally, we illustrate two proof-of-concepts implementing semantic, goal-oriented, and pragmatic communication principles in near-future use cases. Our study covers the project's vision, methodologies, and potential impact.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
