Tail-Latency-Aware Federated Learning with Pinching Antenna: Latency, Participation, and Placement

TL;DR

This paper introduces PASS, a novel federated learning framework utilizing a pinching antenna to reshape uplink latencies, optimizing client participation and placement to reduce overall training time amid heterogeneity.

Contribution

It presents a joint optimization approach for PA placement and client participation in FL, coupling latency modeling with heterogeneity-aware convergence analysis.

Findings

PASS enables more client participation and higher accuracy.

Theoretical analysis reveals latency amplification effects and phase transition behavior.

Simulation confirms improved wall-clock training efficiency.

Abstract

Straggler synchronization is a dominant wall-clock bottleneck in synchronous wireless federated learning (FL). Under non-IID data, however, aggressively sampling only fast clients may significantly slow convergence due to statistical heterogeneity. This paper studies PASS-enabled FL, where a radiating pinching antenna (PA) can be activated at an arbitrary position along a dielectric waveguide to reshape uplink latencies. We consider a joint optimization of PA placement and client participation to minimize the expected time-to-accuracy, coupling the exact expected maximum round latency via order statistics with a heterogeneity-aware convergence factor. We derive first-order optimality conditions that reveal an explicit tail-latency premium in the KKT recursion, quantifying how latency gaps are amplified by maximum-order-statistic synchronization. Under a latency-class structure, we obtain a within-class square-root sampling law and establish a two-class phase transition where slow-class participation collapses under an explicit heterogeneity-threshold condition as the per-round sample size grows. For PA placement, we prove a piecewise envelope-derivative characterization and provide an exact breakpoint-and-root candidate-enumeration procedure. Simulation results verify the theoretical findings and show that PASS enables more eligible participation, yielding higher wall-clock accuracy.