Quantization of Combination Coefficients for CSI-RS Feedback
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Solution Overview
Problem
The existing New Radio (NR) Type II Channel State Indicator (CSI) feedback mechanisms face high overhead due to the need to report complex combination coefficients, with a significant portion of the total overhead occupied by sub-band amplitude and phase reporting, necessitating an efficient quantization approach to reduce feedback overhead while maintaining accuracy.
Innovation Solution
A method for quantizing combination coefficients based on wideband amplitudes corresponding to Discrete Fourier Transform (DFT) basis vector amplitudes, where the amplitude and phase of coefficients are quantized differently, with stronger coefficients using more bits and weaker coefficients using fewer bits, to minimize overhead while preserving coefficient accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex combination coefficients are reported with high precision, then coefficient accuracy is improved, but feedback overhead increases significantly
Solution Approach 1:
The patent applies different quantization precision to different coefficients based on their significance. Stronger coefficients (those with larger magnitudes) are quantized with higher precision using more bits, while weaker coefficients are quantized with lower precision using fewer bits. This local differentiation of quality resolves the contradiction by allocating feedback resources efficiently - maintaining high accuracy for important coefficients while reducing overhead for less important ones.
Solution Approach 2:
The patent changes the quantization parameter (number of bits) based on the amplitude strength of each coefficient. By dynamically adjusting the quantization precision parameter according to the coefficient's magnitude, the system achieves adaptive compression that maintains necessary accuracy while minimizing feedback overhead. This parameter change approach allows the system to optimize the trade-off between accuracy and overhead for each individual coefficient.
2Device complexity
If uniform quantization precision is applied to all coefficients, then implementation complexity is reduced, but overall coefficient accuracy deteriorates
Solution Approach 1:
The patent implements local quality by applying different quantization schemes to different subsets of coefficients. Stronger coefficients receive higher precision quantization while weaker coefficients receive lower precision quantization. This resolves the contradiction by showing that differentiated local treatment actually improves overall accuracy compared to uniform quantization, while the added complexity remains manageable through systematic classification.
Solution Approach 2:
The patent segments the set of all coefficients into different groups based on their amplitude strengths. By dividing coefficients into stronger and weaker groups and applying appropriate quantization to each segment, the system achieves better overall accuracy than uniform quantization would provide. The segmentation approach makes the complexity manageable by processing coefficients in organized groups rather than treating them all identically.
Data Source
AI summary
A wireless communication method for a terminal, a terminal, and a wireless communication system receive one or more Channel State Information Reference Signals (CSI-RSs). Further, quantization of combination coefficients of the one or more CSI-RSs corresponding to one or more spatial beams Discrete Fourier Transform (DFT) basis vector amplitudes is performed.