Driven by the interplay among artificial intelligence, digital twin, and wireless networks, 6G is envisaged to go beyond data-centric services to provide intelligent and immersive experiences. To efficiently support intelligent tasks with customized service requirements, it becomes critical to develop novel information compression and transmission technologies, which typically involve coupled sensing, communication, and computation processes. To this end, task-oriented communication stands out as a disruptive technology for 6G system design by exploiting the task-specific information structures and folding the communication goals into the design of task-level transmission strategies. In this article, by developing task-oriented information extraction and network resource orchestration strategies, we demonstrate the effectiveness of task-oriented communication principles for typical intelligent tasks, including federated learning, edge inference, and semantic communication.

翻译：受人工智能、数字孪生与无线网络之间相互作用的驱动，6G被设想超越以数据为中心的服务，提供智能且沉浸式的体验。为高效支持具有定制化服务需求的智能任务，需发展新型信息压缩与传输技术，这些技术通常涉及耦合的感知、通信与计算过程。为此，任务导向通信通过利用任务特定的信息结构并将通信目标融入任务层级传输策略的设计，成为6G系统设计的一项颠覆性技术。本文通过开发任务导向的信息提取与网络资源编排策略，论证了任务导向通信原理在典型智能任务（包括联邦学习、边缘推理与语义通信）中的有效性。