Codebook Search Dimension Reduction MIMO Precoding
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Solution Overview
Problem
In closed-loop MIMO transmission or storage systems, the complexity and resource intensity of searching for an optimal codeword in a large codebook for precoding can lead to performance degradation due to changing channel conditions, making it difficult to efficiently find a better-suited codeword.
Innovation Solution
The implementation of dimension reduction techniques to compute distance values between the optimal codeword and other codewords in the codebook, either by reducing the dimensions of the null-spaces of codewords or using dimension-reduced versions of codewords, to simplify the search process and enhance efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a large codebook is used for precoding to improve spectrum efficiency and receiving quality, then the system performance is improved, but the complexity and resource intensity of codebook search increases
Solution Approach 1:
The codebook search process is segmented into two stages: first identifying a small set of candidate codewords using simplified distance calculations, then selecting the final codeword from these candidates. This segmentation reduces the overall search complexity while maintaining accuracy.
Solution Approach 2:
Instead of computing exact distance values for all codewords in the large codebook, the patent computes distance values for only a subset of candidate codewords. This partial action approach reduces computational resources while still finding the optimal precoding matrix.
2Measurement precision
If the codebook size is increased to improve precoding accuracy, then the receiving quality improves, but the time and resources required for search increase
Solution Approach 1:
The system performs preliminary identification of candidate codewords using simplified distance metrics before conducting the final selection. This preliminary action filters out unlikely candidates early, reducing the time required for the complete search process.
Solution Approach 2:
The patent computes distance values for only a partial set of candidate codewords rather than the entire codebook, reducing search time while maintaining sufficient precision for finding the optimal precoding matrix.
3Reliability
If exhaustive codebook search is performed to find the optimal codeword, then the precoding performance is optimized, but the system performance deteriorates due to high computational load
Solution Approach 1:
The exhaustive search is segmented into candidate identification and final selection phases, allowing the system to achieve optimal precoding performance without the full computational burden of evaluating every codeword.
Solution Approach 2:
The system performs partial distance calculations on a subset of candidate codewords rather than exhaustive calculations on the entire codebook, maintaining precoding performance while improving system throughput.
Data Source
AI summary
Systems are provided for searching for a codeword from a plurality of codewords in a codebook for use in precoding, for example, as used in a multiple-input multiple-output (MIMO) transmission system. Dimension reduction techniques may be utilized to reduce the complexity and enhance the efficiency of the codebooks search. Null-spaces of an optimal codeword and codewords in a codebook may be computed. Distance values may be computed based on the null=spaces of the codewords. A codeword may be selected from the codebook based on a minimum distance value from the optimal codeword.