# Pinching Antennas Meet AI in Next-Generation Wireless Networks

arXiv: https://arxiv.org/abs/2511.07442 · HTML: https://mlsanity.com/paper/2511.07442/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 12 of its 15 references that are in the map.
- First posted on arXiv 3 Nov 2025.

## Builds on (most cited first, 12 of 12)

- [Deep Learning Enabled Semantic Communication Systems](https://mlsanity.com/paper/2006.10685/) (2020)
- [Federated Learning via Over-the-Air Computation](https://mlsanity.com/paper/1812.11750/) (2018)
- [Integrated Sensing and Communications: Towards Dual-functional Wireless Networks for 6G and Beyond](https://mlsanity.com/paper/2108.07165/) (2021)
- [Mobility-Aware Cluster Federated Learning in Hierarchical Wireless Networks](https://mlsanity.com/paper/2108.09103/) (2021)
- [Reconfigurable Intelligent Surface Enabled Federated Learning: A Unified Communication-Learning Design Approach](https://mlsanity.com/paper/2011.10282/) (2020)
- [Towards Efficient Communications in Federated Learning: A Contemporary Survey](https://mlsanity.com/paper/2208.01200/) (2022)
- [Flexible-Antenna Systems: A Pinching-Antenna Perspective](https://mlsanity.com/paper/2412.02376/) (2024)
- [Antenna Activation for NOMA Assisted Pinching-Antenna Systems](https://mlsanity.com/paper/2412.13969/) (2024)
- [Pinching-Antenna Systems (PASS): Architecture Designs, Opportunities, and Outlook](https://mlsanity.com/paper/2501.18409/) (2025)
- [Graph Neural Network Enabled Pinching Antennas](https://mlsanity.com/paper/2502.05447/) (2025)
- [Pinching-Antenna Systems (PASS) Aided Over-the-air Computation](https://mlsanity.com/paper/2505.07559/) (2025)
- [Straggler-Resilient Federated Learning over A Hybrid Conventional and Pinching Antenna Network](https://mlsanity.com/paper/2508.15821/) (2025)

## Abstract (arXiv)

Next-generation (NG) wireless networks must embrace innate intelligence in support of demanding emerging applications, such as extended reality and autonomous systems, under ultra-reliable and low-latency requirements. Pinching antennas (PAs), a new flexible low-cost technology, can create line-of-sight links by dynamically activating small dielectric pinches along a waveguide on demand. As a compelling complement, artificial intelligence (AI) offers the intelligence needed to manage the complex control of PA activation positions and resource allocation in these dynamic environments. This article explores the "win-win" cooperation between AI and PAs: AI facilitates the adaptive optimization of PA activation positions along the waveguide, while PAs support edge AI tasks such as federated learning and over-the-air aggregation. We also discuss promising research directions including large language model-driven PA control frameworks, and how PA-AI integration can advance semantic communications, and integrated sensing and communication. This synergy paves the way for adaptive, resilient, and self-optimizing NG networks.