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Channel Estimation for mmWave Pinching-Antenna Systems
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The full potential of pinching-antenna systems (PAS) can be unblocked if pinching antennas can be accurately activated at positions tailored for the serving users', which means that acquiring accurate channel state information (CSI) at arbitrary positions along the waveguide is essential for the precise placement of antennas. In this work, we propose an innovative channel estimation scheme for millimeter-wave (mmWave) PAS. The proposed approach requires activating only a small number of pinching antennas, thereby limiting antenna switching and pilot overhead. Specifically, a base station (BS) equipped with a waveguide selectively activates subarrays located near and far from the feed point, each comprising a small number of pinching antennas. This configuration effectively emulates a large-aperture array, enabling high-accuracy estimation of multipath propagation parameters, including angles, delays, and path gains. Simulation results demonstrate that the proposed method achieves accurate CSI estimation and data rates while effectively reducing hardware switching and pilot overhead.
Forward citations
Cited by 3 Pith papers
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Pinching-Antenna Systems with In-Waveguide Attenuation: Performance Analysis and Algorithm Design
Pinching-antenna placement must trade free-space path loss against exponential in-waveguide attenuation; the paper gives a closed-form single-user solution and a rate-loss approximation, then extends to multi-user bea...
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Exploiting Pinching-Antenna Systems in Multicast Communications
Optimizing pinching-antenna positions along dielectric waveguides improves multicast rates, with closed-form results for a single antenna and iterative algorithms for multiple antennas or waveguides.
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A Gradient Meta-Learning Joint Optimization for Beamforming and Antenna Position in Pinching-Antenna Systems
A gradient meta-learning algorithm with two unrolled neural networks jointly optimizes beamforming and pinching-antenna positions, reporting 5.6 bits/s/Hz weighted sum rate and a 32.7% gain over alternating optimizati...
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