Task-Oriented Wave Processing with Stacked Intelligent Metasurfaces: Framework, Fusion, and Challenges

2026-07-20

AI Summary

This work addresses the performance conflicts and resource contention arising from conventional task-agnostic channels in 6G scenarios characterized by deep convergence of heterogeneous services. To overcome these challenges, the paper proposes a novel physical-layer computing paradigm based on stacked intelligent metasurfaces (SIMs). This paradigm reconfigures the wireless environment into a programmable signal processor, establishing a unified mapping framework that directly links service requirements to wave-domain synthesis. By leveraging the deep computational architecture of SIMs, the approach enables intrinsic co-design of sensing, communication, and computing. Notably, it pioneers the use of SIMs for task-oriented wave manipulation, thereby transitioning multi-service systems from mere coexistence to true symbiosis. Numerical results demonstrate that the proposed method effectively mitigates resource conflicts and significantly enhances overall system performance, offering a foundational enabler for service-native 6G architectures.

Abstract

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.

Problem

• 6G networks
• task-agnostic channels
• performance conflicts
• service integration
• wireless environment

Innovation

• Stacked Intelligent Metasurfaces
• Physical-layer Computing
• Wave-domain Synthesis
• Integrated Sensing and Communication
• Service Symbiosis