Codebook Information Processing for 5G PMI Selection
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Solution Overview
Problem
The complexity of Precoding Matrix Index (PMI) selection in 5G systems with large-scale antenna arrays is high due to the large number of codebooks, leading to increased computational complexity for User Equipment (UE) in acquiring and feeding back channel state information.
Innovation Solution
A method that reduces the number of calculations by performing a coarse search to determine an approximate range of PMI values, followed by a fine search to determine exact values, using a three-level separated search manner for PMI1, PMI2, and second PMI, thereby reducing the overall search complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a traverse search algorithm is used for PMI selection in 5G systems with large-scale antenna arrays, then the accuracy of channel state information feedback is improved, but the calculation complexity increases significantly
Solution Approach 1:
The patent segments the PMI selection process into three independent levels: first PMI1 selection, first PMI2 selection, and second PMI selection. Each level searches a reduced subset of codebooks rather than traversing all codebooks simultaneously. This segmentation reduces the search space from O(N1×N2×N3) to O(N1+N2+N3), significantly lowering calculation complexity while maintaining feedback accuracy.
Solution Approach 2:
The patent transforms the traditional two-dimensional codebook structure (horizontal and vertical beam directions) into a three-dimensional search space by introducing the second PMI for subband-level adjustments. This dimensional expansion allows the system to achieve more precise channel state information feedback by searching across multiple dimensions independently, rather than traversing the entire combined space.
2Adaptability or versatility
If the number of CSI-RS ports and precoding codebook resolution are increased to support future 5G systems, then the system performance is improved, but the number of codebooks increases leading to higher computational complexity
Solution Approach 1:
The patent divides the large codebook into three manageable segments corresponding to first PMI1, first PMI2, and second PMI. Each segment represents a specific aspect of precoding (wideband horizontal, wideband vertical, and subband adjustments respectively). This segmentation allows the system to support a large number of codebooks for high-resolution precoding while reducing the computational burden by searching each segment independently rather than traversing all codebooks at once.
Solution Approach 2:
The patent introduces dynamic adaptation by allowing different search strategies and parameters for each PMI level. The first PMI1 and PMI2 operate at wideband level providing stable baseline precoding, while the second PMI operates at subband level providing dynamic adjustments. This dynamic multi-level approach enables the system to adapt to varying channel conditions without requiring exhaustive search across all codebooks.
Data Source
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AI summary
A codebook information processing method, a terminal, and a computer-readable storage medium are provided. The method includes: acquiring first value information corresponding to a wideband precoding matrix index (first PMI) when a coarse search is performed; and determining codebook information to be used according to the first value information and a preset precoding matrix index (PMI) selection rule.