AI 中文总结
针对6G网络服务融合挑战，引入基于堆叠智能超表面的物理层计算范式，建立统一框架映射服务需求到波域合成，研究服务融合及相关挑战，验证方法提升系统性能，为6G架构研究提供方向。
AI 中文摘要
第六代（6G）网络中多样服务的深度融合给传统与任务无关的信道带来重大挑战，常导致性能冲突。本文引入由堆叠智能超表面（SIM）实现的物理层计算范式，将无线环境从被动介质转变为可编程信号处理器。具体建立统一框架将高层服务需求直接映射到波域合成，研究多样服务融合，分析衍射信道建模和逆任务到相位映射等挑战。通过数值结果验证该方法使系统从简单共存提升到真正的服务共生，最后讨论关键研究方向为原生服务6G架构铺平道路。
英文摘要
The deep integration of diverse services in sixth-generation (6G) networks poses significant challenges to conventional task-agnostic channels, often resulting in performance conflicts. To resolve these bottlenecks, this article introduces a physical-layer computing paradigm enabled by stacked intelligent metasurfaces (SIMs), transforming the wireless environment from a passive medium into a programmable signal processor. Specifically, we establish a unified framework to map high-level service requirements directly to wave-domain synthesis. We then investigate the fusion of diverse services, demonstrating how the deep computational architecture of SIMs resolves resource conflicts in integrated sensing and communication (ISAC) and integrated communication and computation (ICC) scenarios. Furthermore, we critically analyze fundamental challenges, including diffractive channel modeling and inverse task-to-phase mapping, while validating through numerical results that this approach elevates the system from simple coexistence to true service symbiosis. Finally, we discuss key research directions to pave the way for service-native 6G architectures.
CommentsIEEE communications magazine
