# A Learnable SIM Paradigm: Fundamentals, Training Techniques, and Applications

arXiv: https://arxiv.org/abs/2603.24599 · HTML: https://mlsanity.com/paper/2603.24599/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 10 of its 20 references that are in the map.
- First posted on arXiv 13 Mar 2026.

## Builds on (most cited first, 10 of 10)

- [Reconfigurable Intelligent Surfaces for 6G: Emerging Hardware Architectures, Applications, and Open Challenges](https://mlsanity.com/paper/2312.16874/) (2023)
- [Multi-User MISO with Stacked Intelligent Metasurfaces: A DRL-Based Sum-Rate Optimization Approach](https://mlsanity.com/paper/2408.04837/) (2024)
- [Emerging Technologies in Intelligent Metasurfaces: Shaping the Future of Wireless Communications](https://mlsanity.com/paper/2411.19754/) (2024)
- [Doubly-Dispersive MIMO Channels with Stacked Intelligent Metasurfaces: Modeling, Parametrization, and Receiver Design](https://mlsanity.com/paper/2501.07724/) (2025)
- [Stacked Intelligent Metasurfaces for Multiuser Beamforming in the Wave Domain](https://mlsanity.com/paper/2302.03188/) (2023)
- [Stacked Intelligent Metasurface-Aided MIMO Transceiver Design](https://mlsanity.com/paper/2311.09814/) (2023)
- [Reconfigurable Intelligent Surface (RIS)-aided Vehicular Networks: Their Protocols, Resource Allocation, and Performance](https://mlsanity.com/paper/2203.02691/) (2022)
- [Intelligent Reflecting Surfaces and Next Generation Wireless Systems](https://mlsanity.com/paper/2402.16453/) (2024)
- [Navigating the Dual-Use Nature and Security Implications of Reconfigurable Intelligent Surfaces in Next-Generation Wireless Systems](https://mlsanity.com/paper/2510.11113/) (2025)
- [Stacked Intelligent Metasurfaces-Based Electromagnetic Wave Domain Interference-Free Precoding](https://mlsanity.com/paper/2601.19313/) (2026)

## Abstract (arXiv)

Stacked intelligent metasurfaces (SIMs) represent a breakthrough in wireless hardware by comprising multilayer, programmable metasurfaces capable of analog computing in the electromagnetic (EM) wave domain. By examining their architectural analogies, this article reveals a deeper connection between SIMs and artificial neural networks (ANNs). Leveraging this profound structural similarity, this work introduces a learnable SIM architecture and proposes a learnable SIM-based machine learning (ML) paradigm for sixth-generation (6G)-andbeyond systems. Then, we develop two SIM-empowered wireless signal processing schemes to effectively achieve multi-user signal separation and distinguish communication signals from jamming signals. The use cases highlight that the proposed SIM-enabled signal processing system can significantly enhance spectrum utilization efficiency and anti-jamming capability in a lightweight manner and pave the way for ultra-efficient and intelligent wireless infrastructures.