Massive MIMO CSI Feedback Codebook Segmentation
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Solution Overview
Problem
The application of codebook-based CSI feedback in Massive MIMO systems faces challenges such as difficulty in code word selection and increased link overhead due to the need for a large number of code words, leading to complexity and high implementation costs.
Innovation Solution
A method and device for processing CSI that involves storing and determining precoding codebook models, allowing for the selection and use of these models to reduce codebook transmission overhead by determining the appropriate codebook model for CSI feedback based on channel detection results or eNodeB configuration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If codebook-based CSI feedback is applied in Massive MIMO systems, then channel information feedback capability is improved, but device complexity and link overhead increase due to the need for a large number of code words
Solution Approach 1:
The codebook is segmented into multiple codebook groups, each group containing a subset of code words. Instead of selecting from all code words directly, the system first selects a codebook group based on channel conditions, then selects a specific code word within that group. This segmentation reduces the search space and complexity of code word selection while maintaining feedback accuracy.
Solution Approach 2:
The patent extracts and transmits only the essential information needed for precoding - specifically the codebook group index and code word index within the group - rather than transmitting the complete channel matrix or all possible code word information. This extraction approach reduces link overhead while preserving the necessary channel state information for effective precoding.
2Reliability
If codebook-based CSI feedback is applied in Massive MIMO systems, then channel information feedback capability is improved, but link overhead increases due to the need for a large number of code words
Solution Approach 1:
By segmenting the codebook into groups and only transmitting the group index along with the intra-group code word index, the system significantly reduces the number of bits required for feedback. The segmentation allows the receiver to identify the appropriate codebook group first, then select a specific code word within that constrained set, rather than searching through the entire codebook.
Solution Approach 2:
The patent extracts only the critical identification parameters (codebook group index and code word index) from the complete channel state information. This extraction methodology transmits minimal necessary information to enable the transmitter to reconstruct the appropriate precoding matrix, thereby reducing link overhead while maintaining feedback effectiveness.
Data Source
AI summary
Provided are a method and device for processing Channel State Information (CSI), User Equipment (UE) and an Evolved Node B (eNodeB). The method includes: storing one or more sets of precoding codebook models the same as those of an eNodeB; determining a precoding codebook model for feeding back CSI; and sending the CSI to the eNodeB by adopting the determined precoding codebook model. By the solution, the problems of difficulty in code word selection and increase of link overhead during application of a codebook-based CSI feedback manner to massive Multi-input Multi-output (MIMO) in the related technology is solved, and the effect of reducing codebook transmission overhead is further achieved.