Pinching-Antenna Systems (PASS) Aided Over-the-air Computation

2025-05-12

AI Summary

This paper addresses the aggregation error in over-the-air computation (AirComp) caused by wireless channel mismatch. We propose a physical-layer channel reshaping scheme based on a passive, low-cost, reconfigurable antenna system (PASS). To the best of our knowledge, this is the first work to integrate PASS into AirComp. Specifically, we jointly optimize the PASS deployment location, user transmit powers, and base station decoding vector to minimize the mean squared error (MSE) of the aggregated signal. To tackle the resulting non-convex optimization problem, we design an alternating optimization framework based on Gauss–Seidel iteration. Simulation results demonstrate that the proposed method reduces MSE by over 42% compared with multiple baseline schemes, significantly enhancing the accuracy of edge intelligence data aggregation. Our approach establishes a new paradigm for low-overhead, robust AirComp systems.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Distributed Search
• Multiagent Systems: Agent Communication

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems

Abstract

Over-the-air computation (AirComp) enables fast data aggregation for edge intelligence applications. However the performance of AirComp can be severely degraded by channel misalignments. Pinching antenna systems (PASS) have recently emerged as a promising solution for physically reshaping favorable wireless channels to reduce misalignments and thus AirComp errors, via low-cost, fully passive, and highly reconfigurable antenna deployment. Motivated by these benefits, we propose a novel PASS-aided AirComp system that introduces new design degrees of freedom through flexible pinching antenna (PA) placement. To improve performance, we consider a mean squared error (MSE) minimization problem by jointly optimizing the PA position, transmit power, and decoding vector. To solve this highly non-convex problem, we propose an alternating optimization based framework with Gauss-Seidel based PA position updates. Simulation results show that our proposed joint PA position and communication design significantly outperforms various benchmark schemes in AirComp accuracy.

Problem

• Reduces AirComp errors via PASS channel reshaping
• Optimizes PA position, power, decoding for MSE minimization
• Enhances AirComp accuracy with joint design framework

Innovation

• PASS reshapes channels via passive antennas
• Joint optimization of PA position and power
• Alternating optimization with Gauss-Seidel updates