MIMO Precoding Matrix Generation Accounting for Channel Estimation Errors
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Solution Overview
Problem
Conventional MIMO systems rely on assumptions that the actual channel matrix is equal to the estimated channel matrix, which is far from reality, leading to suboptimal precoding and reduced throughput.
Innovation Solution
The method involves generating channel matrices based on estimated channel matrices and channel estimation error matrices, iteratively computing diagonal matrices, and using these to determine an efficient precoding matrix for signal transmission, thereby accounting for estimation errors and improving throughput.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional linear precoding methods are used that assume the actual channel matrix equals the estimated channel matrix, then the system complexity is kept low, but the throughput performance deteriorates due to inaccurate channel assumptions
Solution Approach 1:
The patent performs preliminary actions by pre-computing channel matrices based on estimated channel matrices and channel estimation error matrices before actual signal transmission. The base station generates multiple channel matrices (H1, H2, ..., HL) in advance using equation Hl = Ĥ + H̃l, where Ĥ is the estimated channel matrix and H̃l are error matrices. This preliminary computation allows the system to account for channel estimation errors before precoding, improving throughput without significantly increasing real-time complexity.
Solution Approach 2:
The patent creates copies of the channel matrix by generating multiple channel matrices (H1, H2, ..., HL) from the estimated channel matrix Ĥ. Each copy incorporates different channel estimation error matrices to represent various possible actual channel conditions. These copied channel matrices are then used in the precoding computation, allowing the system to handle channel uncertainty without requiring complex real-time channel measurement.
2Measurement precision
If the base station uses the estimated channel matrix directly as the actual channel matrix, then the precoding computation is simple, but the precision of channel representation deteriorates
Solution Approach 1:
The patent changes the parameters of the channel matrix by incorporating channel estimation error matrices into the estimated channel matrix. Instead of using Ĥ directly, the system generates multiple channel matrices Hl = Ĥ + H̃l, where H̃l represents error matrices with specific statistical properties. This parameter change allows the system to account for channel estimation inaccuracies, improving the effective accuracy of channel representation while maintaining manageable complexity through the structured error model.
3Reliability
If conventional precoding methods are used without accounting for channel estimation errors, then the system operation is simple, but the reliability of signal transmission deteriorates
Solution Approach 1:
The patent performs preliminary action by pre-computing channel matrices that incorporate channel estimation errors before signal transmission. The base station generates channel matrices Hl = Ĥ + H̃l in advance, where the error matrices H̃l are generated based on known statistical properties of channel estimation errors. This preliminary computation enhances transmission reliability by accounting for channel uncertainties before precoding, without significantly increasing the complexity of the actual transmission operation.
Data Source
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AI summary
Methods discussed herein provide more efficient precoding matrices for precoding signals prior to transmission. The methods discussed herein improve throughput in wireless MIMO systems. Methods discussed herein are applicable to frequency division duplexing (FDD) systems, time division duplexing (TDD) systems as well as other wireless communication systems.