Geometry-Aware GPR for Efficient Channel Estimation
Research Paper#Wireless Communication, Channel Estimation, Gaussian Process Regression🔬 Research|Analyzed: Jan 3, 2026 19:53•
Published: Dec 27, 2025 12:39
•1 min read
•ArXivAnalysis
This paper introduces a novel approach to channel estimation in wireless communication, leveraging Gaussian Process Regression (GPR) and a geometry-aware covariance function. The key innovation lies in using antenna geometry to inform the channel model, enabling accurate channel state information (CSI) estimation with significantly reduced pilot overhead and energy consumption. This is crucial for modern wireless systems aiming for efficiency and low latency.
Key Takeaways
- •Proposes a GPR-based channel estimation framework.
- •Employs a geometry-aware spectral mixture covariance function (GB-SMCF).
- •Reduces pilot overhead and training energy by up to 50%.
- •Addresses the problem of accurate CSI estimation from few noisy observations.
Reference / Citation
View Original"The proposed scheme reduces pilot overhead and training energy by up to 50% compared to conventional schemes."