CSI Matrix Decomposition for Low-Overhead MIMO Feedback
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Solution Overview
Problem
Existing MIMO wireless communication systems face challenges in accurately and efficiently quantitating and feeding back channel state information (CSI) due to direct quantitation and feedback methods on CSI matrices, which do not effectively reduce feedback overhead.
Innovation Solution
The method involves decomposing the CSI matrix into orthogonal vector matrices, quantizing element information, and transmitting these matrices to enhance feedback accuracy while reducing overhead, using techniques such as differential quantization and broadband amplitude information processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If direct quantitation and feedback methods on CSI matrices are used, then the feedback process is simple, but the feedback overhead is high and accuracy is insufficient
Solution Approach 1:
The CSI matrix is segmented into multiple orthogonal vector matrices through decomposition. Each vector matrix represents a specific spatial direction or beam component, allowing selective feedback of only the most significant vectors based on their gain values, thereby reducing feedback overhead while maintaining accuracy
Solution Approach 2:
The method extracts and feeds back only the essential components of the CSI matrix - specifically the dominant orthogonal vectors and their corresponding gain values - rather than transmitting the entire matrix. This selective extraction reduces the quantity of feedback data while preserving the most critical channel information for precoding optimization
2Reliability
If more CSI feedback information is transmitted to improve precoding performance, then the accuracy of precoding increases, but the feedback overhead increases
Solution Approach 1:
The method applies local quality by providing different levels of feedback detail for different spatial components. Dominant vectors that contribute most to channel capacity receive more precise representation through explicit gain values, while less significant vectors are represented more compactly, optimizing the trade-off between precoding performance and feedback overhead
Data Source
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AI summary
Provided are a method and apparatus for transmitting and receiving channel state information, a communication node, and a storage medium. A CSI matrix H is decomposed to obtain a vector group, where the vector group comprises at least two vector matrices, element information of at least one vector matrix in the vector group is quantized, and the quantized element information is transmitted.