Partial Adaptive MIMO Transmission via Dominant Eigen Dimensions
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Solution Overview
Problem
In Multiple-Input Multiple-Output (MIMO) systems, the high overhead of feedback information for channel state information hampers performance due to increased quantization noise, especially in time-varying channels, necessitating a method to reduce feedback while maximizing system capacity.
Innovation Solution
The method employs partial adaptive transmission using dominant eigen dimensions of the correlation matrix, generating long-term and short-term precoding matrices, and power allocation information, with reduced feedback overhead by focusing on virtual antennas with high power gain, thereby reducing the dimensionality of the channel matrix and feedback information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If full adaptive transmission method is used to maximize system capacity, then system capacity is improved, but feedback information overhead increases and quantization noise increases
Solution Approach 1:
The patent segments the channel dimensions into dominant eigen dimensions and non-dominant eigen dimensions based on the correlation matrix analysis. By identifying and transmitting data only through the dominant eigen dimensions (those with eigenvalues above a threshold), the system reduces the effective dimensionality of the MIMO channel, thereby reducing feedback overhead while maintaining most of the system capacity.
Solution Approach 2:
The patent extracts only the essential information needed for adaptive transmission by performing SVD on the correlation matrix and selecting only the dominant eigen dimensions. This extraction process removes redundant dimensions that contribute minimally to system capacity, reducing the feedback information overhead while preserving the critical channel characteristics needed for high-rate transmission.
2Loss of information
If quantization method is used to reduce feedback information overhead, then feedback overhead is reduced, but quantization noise increases and performance decreases
Solution Approach 1:
The patent segments the channel dimensions to identify dominant eigen dimensions that carry the most significant channel information. By focusing quantization and feedback only on these dominant dimensions rather than all channel dimensions, the system reduces quantization noise impact while maintaining transmission performance.
Solution Approach 2:
The patent changes the parameter space by transforming the channel representation from the original MIMO channel matrix to the eigen dimension space via SVD. This parameter transformation allows the system to work with a reduced set of dominant eigenvalues and eigenvectors, reducing quantization requirements while preserving essential channel characteristics for reliable transmission.
3Productivity
If MIMO channel information is fed back periodically from receiving end to transmitting end, then system capacity is improved, but feedback overhead increases
Solution Approach 1:
The patent segments the channel state information feedback into dominant and non-dominant components. By performing SVD on the correlation matrix and identifying only the dominant eigen dimensions (those with eigenvalues above a threshold), the system reduces the amount of feedback information needed while maintaining the essential channel characteristics required for high system capacity.
Solution Approach 2:
The patent extracts only the critical channel information contained in the dominant eigen dimensions of the correlation matrix. This extraction eliminates redundant feedback data from non-dominant dimensions, reducing feedback overhead while preserving the key channel state information needed for adaptive transmission and high system capacity.
Data Source
AI summary
An apparatus and method for partial adaptive transmission in a Multiple-Input Multiple-Output (MIMO) system are provided. The method includes estimating a correlation matrix between Transmit (Tx) antennas and an average Signal to Noise Ratio (SNR) and generating a long-term precoding matrix composed of a predetermined number of dominant eigen dimensions of the correlation matrix by using the estimated correlation matrix and average SNR. The apparatus and method provide a new adaptive MIMO transmission method capable of reducing the feedback information overhead and maximizing performance.