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

## TL;DR

This paper introduces a new approach to reduce delays in wireless federated learning by optimizing antenna placement and client participation.

## Contribution

The paper introduces a novel framework combining PA placement and client sampling to minimize time-to-accuracy in FL.

## Key findings

- Optimizing PA placement and client participation reduces synchronization delays in FL.
- A two-class phase transition occurs where slow clients stop participating under high heterogeneity.
- Simulation results confirm the effectiveness of the proposed method in improving wall-clock accuracy.

## 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 a proxy for time-to-accuracy, coupling the exact expected maximum round latency via order statistics with a heterogeneity-aware statistical-efficiency proxy. 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 validate the structural findings and show that PASS enables more eligible participation, yielding higher wall-clock accuracy.