Reduced Codebook Precoder Search for MIMO CSI Feedback
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Solution Overview
Problem
In multi-antenna wireless communication systems, especially in FDD systems, finding channel state information (CSI) is complex due to the large size of codebooks, leading to high computational complexity and performance degradation in providing feedback for precoding, particularly in systems like 3GPP LTE and HSDPA.
Innovation Solution
A reduced codebook approach is implemented, where a subset of precoder elements is determined for each rank, with precoder elements grouped into equivalence capacity groups, reducing the search space and computational complexity while maintaining performance by selecting the precoder element with maximum capacity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a large codebook is used to improve precoding performance, then channel state information accuracy is improved, but computational complexity increases exponentially
Solution Approach 1:
The codebook is segmented into multiple subsets based on rank indicators (RI), where each subset contains precoder elements corresponding to a specific rank. This segmentation allows the receiver to search through smaller, manageable subsets rather than the entire large codebook, reducing computational complexity while maintaining precision for each rank category.
Solution Approach 2:
The invention extracts and removes redundant precoder elements from the full codebook to create reduced codebook subsets. By taking out only the necessary precoder elements for each rank, the system maintains the essential information needed for accurate CSI feedback while significantly reducing the search space and computational requirements.
2Device complexity
If the codebook size is reduced to lower complexity, then computational complexity decreases, but feedback performance degrades
Solution Approach 1:
The invention applies local quality by creating rank-specific precoder element subsets, where each subset is optimized for its particular rank indicator. This allows the system to maintain high feedback performance for each rank category while operating with smaller, less complex codebook portions, rather than uniformly reducing the entire codebook.
Solution Approach 2:
The system uses partial action by searching through only a subset of precoder elements corresponding to the indicated rank rather than exhaustively searching the entire codebook. This partial search approach reduces computational complexity while maintaining sufficient performance by focusing computation only on the relevant portion of the codebook.
3Measurement precision
If all precoder elements are searched to find optimal CSI, then measurement precision is improved, but time consumption increases
Solution Approach 1:
The codebook search process is segmented by rank indicator, where the receiver first determines the RI and then searches only through the corresponding precoder element subset. This segmentation dramatically reduces the search time compared to exhaustively searching all codebook entries, while maintaining precision within each rank category.
Solution Approach 2:
The system performs preliminary action by pre-dividing the codebook into rank-specific subsets and storing this structure in advance. This preliminary organization allows the receiver to quickly locate and search only the relevant precoder elements once the rank indicator is known, reducing feedback time without sacrificing measurement precision.
Data Source
AI summary
Multiple antennas employed at the transmitter and receiver can significantly increase a MIMO system capacity, especially when channel knowledge is available at the transmitter. Channel state information may be provided to the transmitter by the receiver in a codebook based precoding feedback. In a proposed approach is proposed in which the receiver conducts a search of precoder elements of a codebook to provide the transmitter with rank information and precoder control index that enhances capacity. Unlike the conventional exhaustive search, the proposed approach reduces complexity by reducing the search space of precoder elements for consideration. Performance loss is minimized by reducing the search space of higher rank precoder elements. For some ranks, the complexity is reduced without any performance sacrifice by grouping the precoder elements of the rank into groups of equivalent capacities and including at most one precoder element from each group into the search space.