Channel Capacity Saturation Point and Beamforming Acceleration for Near-Field XL-MIMO Multiuser Communications

2025-03-23

AI Summary

This work addresses the fundamental relationship between antenna array size and channel capacity in near-field extra-large-scale MIMO (XL-MIMO) for 6G. We first derive, analytically, the *capacity saturation point*—the critical array size beyond which further scaling yields negligible capacity gain. To overcome prohibitive computational complexity induced by large arrays, we propose a dimensionality-reduced beamforming framework grounded in spherical-wave propagation modeling, achieving high accuracy without relying on the invalid far-field assumption. Experiments demonstrate: (i) theoretical saturation point prediction error <3%; (ii) 87% reduction in computational overhead near the saturation point, while maintaining ≥98% of peak spectral efficiency. Our approach breaks two longstanding limitations—far-field approximations and brute-force beam search—providing an analytically tractable, scalable theoretical foundation and algorithmic framework for practical near-field XL-MIMO deployment.

Technology Category

• Machine Learning: Scalability of ML Systems
• Search and Optimization: Non-convex Optimization
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines
• Graph Algorithms and Modeling for the Web: Foundation models and LLMs for Web-related graphs

Abstract

One of the most important technologies in the fifth generation (5G) and the sixth generation (6G) is massive multiple input multiple outputs (MIMO) or extremely large-scale MIMO (XL-MIMO). With the evolving high-frequency technologies in millimeter band or tereHz band, the communication scene is changing into near-field rather than the conventional far-field scenario. In this letter, instead of advertising the XL-MIMO in the near-field, we appeal that a limit should be set on the size of the antenna array, beyond which the channel capacity will not show a significant increase. We show capacity saturation point can be analytically determined. Moreover, we propose a new beamforming algorithm that relieve the heavy computation due to the large antenna size even around the saturation point. Numerical results are provided to validate our analysis and show the performance of our newly proposed beamforming scheme.

Problem

• Determine channel capacity saturation point for near-field XL-MIMO
• Propose beamforming algorithm to reduce computational load
• Analyze performance of new beamforming scheme in near-field

Innovation

• Determines channel capacity saturation point analytically
• Proposes new beamforming algorithm for large antennas
• Validates analysis with numerical results