Revisiting Near-Far Field Boundary in Dual-Polarized XL-MIMO Systems

2025-02-20

AI Summary

In 6G dual-polarized extra-large-scale MIMO (XL-MIMO) systems, the conventional near-field/far-field boundary model neglects the dynamic variation of cross-polarization discrimination (XPD), despite its significant impact under pronounced near-field effects. Method: We propose an XPD-aware redefinition of the near-field/far-field boundary. First, we introduce the novel concept of “non-uniform XPD distance,” jointly modeling co-polarized and cross-polarized channel components to overcome the limitations of single-polarization assumptions. Second, we integrate near-field electromagnetic propagation characteristics with dual-polarized array responses to design a low-complexity transmit covariance optimization algorithm. Contribution/Results: Numerical results demonstrate that the proposed scheme significantly enhances beamforming gain and spatial multiplexing performance in the near-field region, providing theoretical foundations for near-field intelligent reflecting surfaces and ultra-dense deployments in 6G.

Technology Category

• Search and Optimization: Non-convex Optimization
• Machine Learning: Hardware-aware ML
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web applications in cross-disciplinary domains and verticals such as mixed reality, smart cities, and digital health
• User Modeling, Personalization and Recommendation: Federated recommendation systems and personalization
• Graph Algorithms and Modeling for the Web: Graph neural networks and deep learning approaches for Web-related graphs

Abstract

Extremely large-scale multiple-input multiple-output (XL-MIMO) is expected to be an important technology in future sixth generation (6G) networks. Compared with conventional single-polarized XL-MIMO, where signals are transmitted and received in only one polarization direction, dual-polarized XL-MIMO systems achieve higher data rate by improving multiplexing performances, and thus are the focus of this paper. Due to enlarged aperture, near-field regions become non-negligible in XL-MIMO communications, necessitating accurate near-far field boundary characterizations. However, existing boundaries developed for single-polarized systems only consider phase or power differences across array elements while irrespective of cross-polarization discrimination (XPD) variances in dual-polarized XL-MIMO systems, deteriorating transmit covariance optimization performances. In this paper, we revisit near-far field boundaries for dual-polarized XL-MIMO systems by taking XPD differences into account, which faces the following challenge. Unlike existing near-far field boundaries, which only need to consider co-polarized channel components, deriving boundaries for dual-polarized XL-MIMO systems requires modeling joint effects of co-polarized and cross-polarized components. To address this issue, we model XPD variations across antennas and introduce a non-uniform XPD distance to complement existing near-far field boundaries. Based on the new distance criterion, we propose an efficient scheme to optimize transmit covariance. Numerical results validate our analysis and demonstrate the proposed algorithm's effectiveness.

Problem

• Revisits near-far field boundaries in dual-polarized XL-MIMO systems.
• Addresses cross-polarization discrimination in XL-MIMO boundary characterization.
• Proposes a scheme for optimizing transmit covariance in XL-MIMO.

Innovation

• Dual-polarized XL-MIMO systems
• Non-uniform XPD distance modeling
• Transmit covariance optimization scheme