ITLGSPFeb 15

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

arXiv:2602.14250v1
Originality Incremental advance
AI Analysis

This addresses energy efficiency for distributed learning in next-generation wireless systems, representing an incremental improvement over existing methods.

The paper tackles the problem of high energy consumption in over-the-air federated learning by proposing pinching antenna systems (PASSs) at the server, which drastically reduce the required energy for model aggregation compared to conventional MIMO servers.

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.

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