Hierarchical MIMO Codebook for Reduced Complexity
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Solution Overview
Problem
Existing MIMO systems face challenges in efficiently transmitting data due to high calculation complexity and quantization errors, particularly in spatially correlated channels, where current codebooks like Grassmannian and DFT-based codebooks are not optimized for single-user MIMO systems and increase complexity exponentially with codebook size.
Innovation Solution
A hierarchical codebook system is introduced, where a base codebook serves as the upper matrix and a child codebook generated based on chordal distance is used as the lower matrix, reducing system complexity while maintaining performance by selecting codewords with close chordal distances, and using the LBG algorithm for centroid calculations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the codebook size is increased to reduce quantization errors, then the transmission accuracy is improved, but the calculation complexity increases exponentially
Solution Approach 1:
The codebook is divided into multiple sub-codebooks, each handling a specific portion of the channel state space. Instead of searching through one large codebook, the system segments the search process across smaller sub-codebooks, reducing the computational burden while maintaining overall quantization accuracy.
Solution Approach 2:
The patent introduces a hierarchical structure with multiple levels (e.g., first level, second level, third level codebooks). This adds a dimensional aspect to the codebook organization, transforming the flat search problem into a multi-level search process that reduces complexity at each level while preserving accuracy.
2Reliability
If a large codebook is used to improve channel state information accuracy, then the system performance is improved, but the feedback overhead and processing time increase
Solution Approach 1:
The channel state information feedback process is segmented into multiple stages corresponding to different codebook levels. The feedback overhead is divided and managed at each level, reducing the time required to process and transmit the complete channel state information compared to a single large codebook search.
Solution Approach 2:
The patent performs preliminary codebook configuration and organization before the actual channel state estimation and feedback process. Sub-codebooks are pre-structured and indexed, allowing the receiving end to quickly search and select appropriate codewords without performing complex real-time calculations, thus reducing feedback processing time.
3Adaptability or versatility
If the Grassmannian codebook is used for i.i.d. channels, then the performance is optimized for independent channels, but the performance degrades in spatially correlated channels
Solution Approach 1:
The patent creates a universal codebook structure that can adapt to different channel conditions. By organizing multiple sub-codebooks that can be selectively applied or combined, the system achieves versatility for i.i.d. channels while also maintaining reliability for spatially correlated channels through appropriate sub-codebook selection and combination strategies.
Solution Approach 2:
The patent changes the structural parameters of the codebook by introducing hierarchical levels and multiple sub-codebooks with different characteristics. This allows the system to adjust the codebook parameters (such as codebook size, granularity, and organization) to match the specific channel conditions, whether i.i.d. or spatially correlated, thereby improving adaptability and reliability across different scenarios.
Data Source
AI summary
Disclosed is a multiple-input multiple-output (MIMO) system including a transmitting end and a receiving end, wherein the transmitting end includes: a hierarchical codebook in which at least one base codebook is designated as the upper matrix and a child codebook generated based on a chordal distance between respective codewords configuring the base codebook is designated as the lower matrix; a scheduler configured to receive channel state information from the receiving end and select precoding matrices from the hierarchical codebook based on the channel state information; and a precoder configured to apply the precoding matrices selected in the scheduler to data to be transmitted to the receiving end and transmit the selected precoding matrices through a plurality of antennas.