面向6G终端的智能体用户设备协作多输入多输出（Agentic UE-CoMIMO）：从虚拟天线增强到AI原生虚拟化
Agentic UE-CoMIMO for 6G Terminals: From Virtual Antenna Augmentation to AI-Native Virtualization
- National Sun Yat-sen University（国立中山大学）
- National Yang Ming Chiao Tung University（国立阳明交通大学）
- MediaTek Inc.（联发科技股份有限公司）
- Imperial College London（伦敦帝国学院）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本文提出Agentic UE-CoMIMO技术，通过多类智能体协调实现设备协作，经直播与盲点感知场景验证，该技术可提升服务持续性，同时探讨了相关标准化等挑战。
AI中文摘要：
以终端用户为中心的协作多输入多输出（UE-CoMIMO）技术，允许周边设备组成虚拟多天线终端，以克服单个用户设备的天线限制。将这种协作扩展至通信、感知、计算及任务相关信息交换，需要一个控制层，该控制层需能解读用户意图、选择协作机制，并在条件变化时重新规划。本文提出Agentic UE-CoMIMO，其中设备微智能体、智能手机或CPE集线器智能体、边缘/网络智能体可协调设备参与、中继模式、流量拆分与复制、计算放置、语义令牌交换及拓扑重构。针对创作者中心直播和可穿戴设备协作盲点感知这两种系统级场景研究，将所提控制器与能力匹配的自适应基线进行对比。结果表明，通过提前预判变化并准备协作及回退动作，智能体控制能更长时间维持高质量直播，并在设备中断时保持盲点警告。我们还探讨了相关的标准化、互操作性、信任及验证挑战。
英文摘要：
End-user-centric collaborative MIMO (UE-CoMIMO) lets nearby devices form a virtual multi-antenna terminal to overcome the antenna limitations of individual user equipment. Extending such cooperation to communication, sensing, computing, and task-relevant information exchange requires a control layer that can interpret user intent, select cooperation mechanisms, and replan as conditions change. This article introduces Agentic UE-CoMIMO, in which device micro-agents, a smartphone or CPE hub agent, and edge/network agents coordinate device participation, relay modes, traffic splitting and duplication, compute placement, semantic-token exchange, and topology reconfiguration. Two system-level scenario studies on creator-centric live streaming and wearable-collaborative blind-spot sensing compare the proposed controller with capability-matched adaptive baselines. The results show that, by anticipating changes and preparing cooperation and fallback actions in advance, agentic control sustains high-quality streaming for longer and maintains blind-spot warnings through device outages. We also discuss the associated standardization, interoperability, trust, and validation challenges.
