Channel Estimation for 6G Near-Field Wireless Communications: A Comprehensive Survey

2025-07-31

AI Summary

The emergence of ultra-massive MIMO (UM-MIMO) extremely large aperture arrays (ELAAs) and terahertz (THz) bands in 6G systems renders conventional far-field channel models inadequate, necessitating rigorous near-field modeling and efficient estimation. Method: This paper systematically analyzes near-field propagation physics, rigorously defines the near-/far-field boundary based on electromagnetic theory, and proposes a spherical-wave channel model incorporating angle-range coupling. It establishes a unified high-dimensional near-field channel analysis framework tailored for ELAAs. Furthermore, it quantitatively compares direct estimation versus RIS-assisted cascaded estimation in terms of estimation accuracy, pilot overhead, and computational complexity. Contribution/Results: By integrating compressive sensing, sparse signal recovery, and electromagnetic modeling, the work provides both a theoretical foundation and a scalable technical pathway for near-field channel estimation in 6G systems, enabling accurate, low-overhead, and computationally tractable solutions for ELAA-THz scenarios.

Technology Category

• Machine Learning: Large Multimodal Models (LMMs)
• Cognitive Modeling & Cognitive Systems: Neural Spike Coding
• Intelligent Robots: State Estimation

Application Category

• Graph Algorithms and Modeling for the Web: Foundation models and LLMs for Web-related graphs
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation

Abstract

The sixth-generation (6G) wireless systems are expected to adopt extremely large aperture arrays (ELAAs), novel antenna architectures, and operate in extremely high-frequency bands to meet growing data demands. ELAAs significantly increase the number of antennas, enabling finer spatial resolution and improved beamforming. At high frequencies, ELAAs shift communication from the conventional far-field to near-field regime, where spherical wavefronts dominate and the channel response depends on both angle and distance, increasing channel dimensionality. Conventional far-field channel estimation methods, which rely on angular information, struggle in near-field scenarios due to increased pilot overhead and computational complexity. This paper presents a comprehensive survey of recent advances in near-field channel estimation. It first defines the near- and far-field boundary from an electromagnetic perspective and discusses key propagation differences, alongside a brief review of ELAA developments. Then, it introduces mainstream near-field channel models and compares them with far-field models. Major estimation techniques are reviewed under different configurations (single/multi-user, single/multi-carrier), including both direct estimation and RIS-assisted cascaded estimation. These techniques reveal trade-offs among estimation accuracy, complexity, and overhead. This survey aims to provide insights and foundations for efficient and scalable near-field channel estimation in 6G systems, while identifying key challenges and future research directions.

Problem

• Surveying near-field channel estimation for 6G ELAAs
• Comparing near- and far-field models and methods
• Analyzing trade-offs in accuracy, complexity, and overhead

Innovation

• ELAAs enable finer spatial resolution
• Near-field uses spherical wavefronts
• RIS-assisted cascaded estimation techniques