Research Overview

This research explores Pinching‑Antenna Assisted Integrated Sensing and Communications (PASS–ISAC), focusing on the fundamental tradeoff between communication performance and sensing accuracy. Building on recent studies on PASS‑enabled rate regions, CRLB‑based sensing analysis, and joint antenna–power optimization, the work advances a closed‑loop, sensing‑aware system design that incorporates lightweight machine learning to interpret sensing quality and adapt system configurations dynamically. The approach enhances resource efficiency and practical relevance while maintaining strong analytical foundations for next‑generation ISAC systems.

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Key Findings

This work proposes a closed‑loop PASS–ISAC framework that uses CRLB‑based sensing quality and lightweight machine learning to adapt system configurations dynamically.

Sensing‑aware adaptation improves communication efficiency while maintaining sensing accuracy, without relying on complex optimization or deep learning.