RAKE Receiver Autocorrelation Matrix Sharing for Uplink Interference
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Solution Overview
Problem
The high computational complexity in Interference Rejection Combining (IRC) processing on the building baseband unit (BBU) side of a RAKE receiver, which makes it impractical to calculate and invert the correlation matrix of interference and noise for each user, significantly reducing the demodulation performance of uplink data channels.
Innovation Solution
The method involves determining an autocorrelation inverse matrix of a cell common signal and sharing it among all RAKE users corresponding to the same Remote Radio Unit (RRU), allowing for multipath matching and using this shared matrix to calculate the autocorrelation inverse matrix of each user's signal, thereby reducing computational complexity and improving demodulation performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the correlation matrix of interference and noise is calculated and inverted for each user, then the anti-interference performance is improved, but the computational complexity becomes extremely high and cannot be realized
Solution Approach 1:
The patent segments the correlation matrix calculation by separating the common part (shared by all users) from the user-specific part. The common correlation matrix is calculated once for all users, while user-specific adjustments are made through rank-1 updates. This segmentation reduces computational complexity from O(U*N^3) to O(N^3 + U*N^2), where U is the number of users and N is the number of antennas.
Solution Approach 2:
The patent performs preliminary calculation of the common correlation matrix before individual user processing. By pre-calculating the shared correlation characteristics that are common to all users, the system avoids redundant computations for each user, significantly reducing the overall computational burden while maintaining accurate interference suppression.
2Device complexity
If traditional MRC technology is used, then the computational complexity is low, but the signal-to-noise ratio improvement is limited compared to IRC
Solution Approach 1:
The patent changes the parameter representation from full correlation matrices to compact forms using eigendecomposition and rank-1 updates. By representing the correlation matrix in terms of eigenvalues and eigenvectors, and using incremental updates for user-specific matrices, the system achieves IRC performance with computational complexity closer to MRC.
Data Source
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AI summary
The embodiments of the present invention provide an interference suppression method, device and computer storage medium. The method includes: an autocorrelation inverse matrix of a cell common signal is determined according to uplink sampling antenna data; multipath matching is performed according to the uplink sampling antenna data; an autocorrelation inverse matrix of a specified user signal is acquired from the autocorrelation inverse matrix of the cell common signal according to a result of the multipath matching for the specified user and multipath information; a combined weight for the specified user is calculated according to a channel estimation value of the specified user and the autocorrelation inverse matrix of the specified user signal; and a data channel of the specified user is modulated and demodulated based on the combined weight for the specified user.