MIMO Channel Feedback Transformation for Spatial Correlation
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Solution Overview
Problem
Current wireless communication systems face challenges in efficiently transforming and utilizing long-term wideband channel properties, particularly in multi-input multi-output (MIMO) systems, where only one form of long-term information (either the beamforming matrix or the transmit spatial correlation matrix) is often fed back, limiting system performance due to quantization errors and incomplete channel state information.
Innovation Solution
A transformation method and apparatus that convert one form of long-term wideband channel property feedback into another, allowing the derivation of a long-term wideband beamforming matrix from a transmit spatial correlation matrix or vice versa, using a first transformation unit to estimate the transmit spatial correlation matrix from the beamforming matrix and a second unit to obtain the beamforming matrix from the spatial correlation matrix, based on the desired information for the transmitter side.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If only one form of long-term information (beamforming matrix or spatial correlation matrix) is fed back, then feedback overhead is reduced, but channel state information accuracy deteriorates
Solution Approach 1:
The patent combines both beamforming matrix and spatial correlation matrix into a unified codebook structure, allowing the transmitter to access both forms of long-term channel information simultaneously. This merging eliminates the need to choose between the two matrices, thereby improving channel state information accuracy without proportionally increasing feedback overhead, as both matrices are integrated into a single feedback mechanism.
Solution Approach 2:
The transformed codebook is designed to serve multiple functions: it can generate both beamforming matrices and spatial correlation matrices from a single set of codebook parameters. This multi-functionality allows the system to derive whichever matrix form is needed for specific operations (e.g., SLNR calculation or beamforming) without requiring separate feedback channels for each matrix type.
2Productivity
If transmit spatial correlation matrix is fed back, then multi-user MIMO system performance is improved, but quantization error increases when transforming from beamforming matrix
Solution Approach 1:
The patent transforms the codebook parameters to directly represent spatial correlation characteristics rather than beamforming vectors. By changing the parameterization approach, the system can more accurately represent the spatial correlation matrix with fewer bits, reducing quantization error while maintaining the ability to improve multi-user MIMO system performance through accurate spatial correlation information.
Solution Approach 2:
The patent introduces a transformation layer that converts between beamforming matrix representation and spatial correlation matrix representation. This intermediary transformation process allows the system to feed back information in one form (e.g., beamforming matrix) while accurately deriving the other form (spatial correlation matrix) with minimized quantization loss, thereby maintaining high system performance without excessive quantization error.
3Measurement precision
If transformed codebook is used to reduce quantization error, then channel adaptation accuracy is improved, but codebook complexity increases
Solution Approach 1:
The patent pre-computes and stores transformed codebook parameters that are specifically optimized for representing spatial correlation characteristics. By performing this transformation preparation in advance, the system reduces the computational burden during real-time operation and minimizes the complexity of the codebook structure while maintaining high channel adaptation accuracy. The pre-computed parameters are stored in a manageable format that balances precision and complexity.
Data Source
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AI summary
The present invention provides a transformation apparatus for transforming a long-term wideband channel property feedback. The transformation apparatus comprises: a first transformation unit for constructing an estimation Restimation of a long-term wideband transmit spatial correlation matrix with a long-term wideband beamforming matrix u1 as fed back from a receiver, wherein Restimation=u1u1H, wherein H indicates the conjugate transposition of a matrix; and/or a second transformation unit for directly obtaining a long-term wideband beamforming matrix or a precoding matrix by using a long-term wideband transmit spatial correlation matrix as fed back from a receiver. According to the technical solution of the present invention, a corresponding transformation method and apparatus is also provided.