A Dictionary Learning-Based Channel Estimation Method for Ultra-Large MIMO Mixed Fields
By constructing a mixed field channel model based on a dictionary learning method, the problem of inaccurate mixed field channel estimation in the existing technology is solved, and accurate estimation and performance improvement of the mixed field channel are achieved.
Patent Information
- Application Number
- CN202411272040.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-11
- Publication Date
- 2025-10-14
- Estimated Expiration
- 2044-09-11
AI Technical Summary
Existing ultra-large-scale MIMO mixed-field channel estimation methods cannot accurately represent the characteristics of mixed-field channels. Existing methods usually use far-field or near-field dictionaries respectively, which cannot adapt to mixed-field communication scenarios.
A dictionary learning-based method is used to construct a mixed-field channel model. By establishing a mixed-field channel recovery problem and converting it into a dictionary learning problem, the orthogonal matching pursuit algorithm and gradient projection method are used to optimize the dictionary to achieve sparse representation and recovery of the mixed-field channel.
It can accurately capture the characteristics of mixed-field channels, achieve accuracy and robustness of channel estimation, and improve channel estimation performance.