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Energy-Efficient Over-the-Air Federated Learning via Pinching Antenna Systems

Saba Asaad, Ali Bereyhi

TL;DR

This work addresses energy-efficient over-the-air federated learning (OTA-FL) in wireless networks where large-scale fading degrades aggregation quality. It proposes a pass-assisted server architecture (PASS) and a low-complexity, computation-rate–driven optimization that jointly tunes PASS locations, device scheduling, and transmit scalars to minimize energy while meeting a target aggregation accuracy. The core contributions are: (i) a PASS-based OTA-FL formulation that links energy to the computation rate $\mathcal{R}_{comp}$, (ii) a two-tier alternating-optimization algorithm combining projection-based PASS tuning, Dinkelbach–DC power scaling, and step-wise scheduling, and (iii) numerical results showing substantial energy reduction compared with a fully digital MIMO server, and robustness to region size. The results demonstrate that PASS can provide substantial energy efficiency gains for distributed learning in next-generation wireless systems and motivate further exploration of MIMO-PASS extensions.

Abstract

Pinching antennas systems (PASSs) have recently been proposed as a novel flexible-antenna technology. These systems are implemented by attaching low-cost pinching elements to dielectric waveguides. As the direct link is bypassed through waveguides, PASSs can effectively compensate large-scale effects of the wireless channel. This work explores the potential gains of employing PASSs for over-the-air federated learning (OTA-FL). For a PASS-assisted server, we develop a low-complexity algorithmic approach, which jointly tunes the PASS parameters and schedules the mobile devices for minimal energy consumption in OTA-FL. We study the efficiency of the proposed design and compare it against the conventional OTA-FL setting with MIMO server. Numerical experiments demonstrate that using a single-waveguide PASS at the server within a moderately sized area, the required energy for model aggregation is drastically reduced as compared to the case with fully-digital MIMO server. This introduces PASS as a potential technology for energy-efficient distributed learning in next generations of wireless systems.

Energy-Efficient Over-the-Air Federated Learning via Pinching Antenna Systems

TL;DR

This work addresses energy-efficient over-the-air federated learning (OTA-FL) in wireless networks where large-scale fading degrades aggregation quality. It proposes a pass-assisted server architecture (PASS) and a low-complexity, computation-rate–driven optimization that jointly tunes PASS locations, device scheduling, and transmit scalars to minimize energy while meeting a target aggregation accuracy. The core contributions are: (i) a PASS-based OTA-FL formulation that links energy to the computation rate , (ii) a two-tier alternating-optimization algorithm combining projection-based PASS tuning, Dinkelbach–DC power scaling, and step-wise scheduling, and (iii) numerical results showing substantial energy reduction compared with a fully digital MIMO server, and robustness to region size. The results demonstrate that PASS can provide substantial energy efficiency gains for distributed learning in next-generation wireless systems and motivate further exploration of MIMO-PASS extensions.

Abstract

Pinching antennas systems (PASSs) have recently been proposed as a novel flexible-antenna technology. These systems are implemented by attaching low-cost pinching elements to dielectric waveguides. As the direct link is bypassed through waveguides, PASSs can effectively compensate large-scale effects of the wireless channel. This work explores the potential gains of employing PASSs for over-the-air federated learning (OTA-FL). For a PASS-assisted server, we develop a low-complexity algorithmic approach, which jointly tunes the PASS parameters and schedules the mobile devices for minimal energy consumption in OTA-FL. We study the efficiency of the proposed design and compare it against the conventional OTA-FL setting with MIMO server. Numerical experiments demonstrate that using a single-waveguide PASS at the server within a moderately sized area, the required energy for model aggregation is drastically reduced as compared to the case with fully-digital MIMO server. This introduces PASS as a potential technology for energy-efficient distributed learning in next generations of wireless systems.
Paper Structure (15 sections, 1 theorem, 32 equations, 3 figures, 3 algorithms)

This paper contains 15 sections, 1 theorem, 32 equations, 3 figures, 3 algorithms.

Table of Contents

  1. Introduction
  2. System Model
  3. Distributed Learning Setting
  4. PASS-assisted AirComp Aggregation
  5. PASS Channel Model
  6. Energy Model for OTA-FL
  7. Computation Rate
  8. Energy Model
  9. Energy Efficient OTA-FL Scheme
  10. PASS Transceiver Design
  11. Transmit Power Scaling
  12. Device Scheduling
  13. Two-Tier Algorithm and Its Complexity
  14. Numerical Experiments
  15. Conclusions

Key Result

Theorem 1

The solution to eq:M1-p is given by $\rho^\star = {\left\Vert \tilde{\boldsymbol{\varphi}} \right\Vert}/{Q}$ and $\mathbf{v}^\star = \left( {Q}/{\left\Vert \tilde{\boldsymbol{\varphi}} \right\Vert} \right)\tilde{\boldsymbol{\varphi}}$.

Figures (3)

  • Figure 1: Accuracy vs communication round at $D=50$ m and $\log P = 0$ dBm. The MIMO ps is unable to learn due to low receive SNR.
  • Figure 2: Accuracy vs area size. The results are reported after training a two-layer MLP for 20 rounds at $\log P = 0$ dBm.
  • Figure 3: Accuracy vs area size. The results are reported after training a two-layer MLP for 20 rounds at $D = 50$ m.

Theorems & Definitions (2)

  • Definition 1: Computation rate ni22FL
  • Theorem 1