Failure Detection for Pinching-Antenna Systems

TL;DR

This paper introduces a signal processing framework with tagged pilots for detecting failures in segmented pinching-antenna systems, achieving high accuracy with low pilot length and leveraging compressive sensing techniques.

Contribution

It develops a novel detection method using tagged pilots and compressive sensing, improving failure detection efficiency in segmented antenna systems.

Findings

Per-segment ML detector approaches joint ML performance.

Compressive sensing detector reliably detects failures with short pilots.

Method outperforms baseline detection methods with longer pilots.

Abstract

A signal processing-based framework is proposed for detecting random segment failures in segmented waveguide-enabled pinching-antenna systems. To decouple the passively combined uplink signal and to provide per-segment observability, tagged pilots are employed. A simple tag is attached to each segment and is used to apply a known low-rate modulation at the segment feed, which assigns a unique signature to each segment. Based on the tagged-pilot model, a low-complexity per-segment maximum-likelihood (ML) detector is developed for the case in which the pilot length is no smaller than the number of segments. For the case in which the pilot length is smaller than the number of segments, sparsity in the failure-indicator vector is exploited and a compressive sensing-based detector is adopted. Numerical results show that the per-segment detector approaches joint ML performance, while the compressive sensing-based detector achieves reliable detection with a short pilot and can outperform baselines that require much longer pilots.