Reduced Codebook Precoder Search for MIMO CSI Feedback
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Solution Overview
Problem
In multi-antenna wireless communication systems, particularly in FDD systems, the complexity of providing channel state information (CSI) feedback to transmitters is high due to large codebooks, making it cumbersome to find rank information and precoding indices, which hinders system performance.
Innovation Solution
A method that reduces computational complexity by using a reduced codebook subset, where precoder elements are grouped into equivalence capacity ranks, allowing only one precoder element from each capacity group to be included in the subset, thereby determining channel state information with reduced computations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a large codebook is used in closed-loop MIMO systems, then system performance improves, but computational complexity increases exponentially
Solution Approach 1:
The patent segments the large codebook into multiple codebook subsets, each corresponding to different channel conditions or transmission scenarios. The receiver divides the full codebook search into smaller subset searches, reducing computational complexity while maintaining performance by selecting the appropriate subset based on channel characteristics.
Solution Approach 2:
The patent employs partial action by using only a subset of the full codebook rather than exhaustively searching all codebook entries. The receiver selects and searches only relevant codebook subsets based on channel conditions, achieving sufficient performance with reduced computational effort compared to exhaustive search.
2Measurement precision
If codebook size increases to improve CSI accuracy, then feedback precision improves, but feedback overhead and processing time increase
Solution Approach 1:
The patent segments the codebook into subsets that can be searched independently and in parallel. This segmentation allows the receiver to reduce feedback processing time by focusing search efforts on relevant subsets rather than exhaustively searching the entire codebook, while still maintaining CSI accuracy through appropriate subset selection.
Solution Approach 2:
The patent performs preliminary actions by pre-organizing the codebook into structured subsets based on channel characteristics or transmission parameters. This pre-organization enables the receiver to quickly identify and search only the relevant subsets, reducing feedback processing time while maintaining accuracy.
3Manufacturing precision
If exhaustive codebook search is performed to find optimal precoder, then precoding accuracy improves, but computational burden becomes prohibitive for large codebooks
Solution Approach 1:
The patent applies partial action by performing exhaustive search only within selected codebook subsets rather than the entire codebook. This approach maintains precoding accuracy within the context of relevant subsets while significantly reducing computational burden compared to exhaustive search of the full codebook.
Solution Approach 2:
The patent applies local quality by optimizing precoder selection locally within specific codebook subsets rather than uniformly across the entire codebook. Each subset is optimized for specific channel conditions or transmission scenarios, providing locally optimal precoding accuracy with reduced global computational complexity.
Data Source
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AI summary
Multiple antennas employed at the transmitter (110) and receiver (120) can significantly increase a MIMO system (100) capacity, especially when channel knowledge is available at the transmitter (110). Channel state information may be provided to the transmitter (110) by the receiver (120) in a codebook based precoding feedback. In a proposed approach is proposed in which the receiver (120) conducts a search of precoder elements of a codebook to provide the transmitter (110) 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.