Pinching Antennas Meet AI in Next-Generation Wireless Networks

TL;DR

This paper discusses how pinching antennas combined with artificial intelligence can enable adaptive, resilient, and self-optimizing next-generation wireless networks supporting demanding applications.

Contribution

It introduces the innovative integration of pinching antennas with AI for dynamic control and resource management in future wireless networks.

Findings

AI optimizes PA activation positions for better network performance

PAs support edge AI tasks like federated learning and over-the-air aggregation

The synergy enables adaptive and self-optimizing NG networks

Abstract

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.