An Enhanced Polar-Domain Dictionary Design for Elevated BSs in Near-Field U-MIMO

2026-02-04

AI Summary

This work addresses the mismatch between channel modeling and practical deployment in near-field ultra-massive MIMO (U-MIMO) systems, which arises from neglecting base station height in conventional dictionary design. To resolve this, the study introduces a polar-domain sampling grid optimization framework that explicitly incorporates arbitrary base station heights into near-field U-MIMO dictionary construction. By minimizing the optimal normalized mean square error, the proposed method generates a high-fidelity representation grid and integrates it with the P-SOMP algorithm for efficient channel estimation. Departing from traditional correlation-based design paradigms, the approach significantly enhances both channel estimation accuracy and spectral efficiency in sub-terahertz hybrid U-MIMO systems, demonstrating its effectiveness particularly in elevated base station scenarios.

Technology Category

• Search and Optimization: Sampling/Simulation-based Search
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Machine Learning: Matrix & Tensor Methods

Application Category

• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Search and Retrieval-Augmented AI: Vertical and domain-specific search

Abstract

Near-field U-MIMO communications require carefully optimized sampling grids in both angular and distance domains. However, most existing grid design methods neglect the influence of base station height, assuming instead that the base station is positioned at ground level - a simplification that rarely reflects real-world deployments. To overcome this limitation, we propose a generalized grid design framework that accommodates arbitrary base station locations. Unlike conventional correlation-based approaches, our method optimizes the grid based on the minimization of the optimal normalized mean squared error, leading to more accurate channel representation. We evaluate the performance of a hybrid U-MIMO system operating at sub-THz frequencies, considering the P-SOMP algorithm for channel estimation. Analytical and numerical results show that the proposed design enhances both channel estimation accuracy and spectral efficiency compared to existing alternatives.

Problem

• Near-field U-MIMO
• base station height
• sampling grid design
• channel estimation
• sub-THz communications

Innovation

• near-field U-MIMO
• grid design
• base station height
• normalized mean squared error
• sub-THz