# AirPASS: Over-the-Air Federated Learning via Pinching Antenna Systems

arXiv: https://arxiv.org/abs/2607.06768 · HTML: https://mlsanity.com/paper/2607.06768/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 21 of its 29 references that are in the map.
- First posted on arXiv 7 Jul 2026.

## Builds on (most cited first, 21 of 21)

- [Communication-Efficient Learning of Deep Networks from Decentralized Data](https://mlsanity.com/paper/1602.05629/) (2016)
- [Federated Learning via Over-the-Air Computation](https://mlsanity.com/paper/1812.11750/) (2018)
- [Federated Learning over Wireless Fading Channels](https://mlsanity.com/paper/1907.09769/) (2019)
- [Federated Learning via Intelligent Reflecting Surface](https://mlsanity.com/paper/2011.05051/) (2020)
- [Scalable Hierarchical Over-the-Air Federated Learning](https://mlsanity.com/paper/2211.16162/) (2022)
- [Compute-Update Federated Learning: A Lattice Coding Approach Over-the-Air](https://mlsanity.com/paper/2409.06343/) (2024)
- [Over-the-Air Federated Learning via Weighted Aggregation](https://mlsanity.com/paper/2409.07822/) (2024)
- [Array Gain for Pinching-Antenna Systems (PASS)](https://mlsanity.com/paper/2501.05657/) (2025)
- [Pinching Antennas: Principles, Applications and Challenges](https://mlsanity.com/paper/2501.10753/) (2025)
- [Performance Analysis of Pinching-Antenna Systems](https://mlsanity.com/paper/2502.06701/) (2025)
- [MIMO-PASS: Uplink and Downlink Transmission via MIMO Pinching-Antenna Systems](https://mlsanity.com/paper/2503.03117/) (2025)
- [Pinching-Antenna Systems (PASS): A Tutorial](https://mlsanity.com/paper/2508.07572/) (2025)
- [Over-the-Air Federated Learning: Rethinking Edge AI Through Signal Processing](https://mlsanity.com/paper/2512.03719/) (2025)
- [Pinching-Antenna Systems (PASS) Aided Over-the-air Computation](https://mlsanity.com/paper/2505.07559/) (2025)
- [IRS Assisted Federated Learning A Broadband Over-the-Air Aggregation Approach](https://mlsanity.com/paper/2310.07405/) (2023)
- [Over-the-Air FEEL with Integrated Sensing: Joint Scheduling and Beamforming Design](https://mlsanity.com/paper/2501.06334/) (2025)
- [Pinching-Antenna Systems (PASS): Power Radiation Model and Optimal Beamforming Design](https://mlsanity.com/paper/2505.00218/) (2025)
- [Multi-Waveguide Pinching Antennas for ISAC](https://mlsanity.com/paper/2505.24307/) (2025)
- [Pinching-Antenna Systems-Enabled Multi-User Communications: Transmission Structures and Beamforming Optimization](https://mlsanity.com/paper/2508.14458/) (2025)
- [Pinching Antenna Systems for Integrated Sensing and Communications](https://mlsanity.com/paper/2508.19540/) (2025)
- [Energy-Efficient Over-the-Air Federated Learning via Pinching Antenna Systems](https://mlsanity.com/paper/2602.14250/) (2026)

## Abstract (arXiv)

This paper investigates over-the-air federated learning (AirFL) in wireless systems where the access point is equipped with a multi-waveguide pinching antenna system (PASS). We adopt the widely studied learning-oriented AirFL formulation, which seeks to maximize the number of selected devices while keeping the aggregation distortion below a prescribed threshold. The resulting joint optimization of device selection, receive beamforming, and pinching-antenna placement is highly nonconvex due to the intricate coupling among these system variables. To address this challenge, we develop AirPASS, an alternating optimization framework with two main components: a homotopy-Riemannian margin-consolidation method for device selection and receive beamforming under a fixed PASS configuration, and a homotopy-assisted geometry optimization method for updating the pinching-antenna positions under fixed selected devices and beamformer.