IRC Matrix Segmentation for MIMO Receiver Complexity
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Solution Overview
Problem
The complexity of interference rejection combining (IRC) processing in LTE-A systems, particularly with multiple input multiple output (MIMO) transmission, leads to complicated receiver processing due to the need for inversion of large matrices, which hampers performance and efficiency, especially in complex interference environments.
Innovation Solution
The method involves generating an N * N interference and noise covariance matrix from signals received via N antennas, performing Cholesky decomposition and upper triangular matrix inversion to obtain a block matrix, expanding it to a 2N * 2N noise whitening matrix, and using this matrix to whiten received signals and channel estimation values for minimum mean square error (MMSE)-IRC processing, thereby reducing complexity and improving processing speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional MMSE-IRC processing is used to support MIMO transmission with 4 receiving antennas, then interference rejection capability is improved, but receiver processing complexity increases due to inversion of 8x8 matrix
Solution Approach 1:
The patent segments the large 8x8 matrix inversion problem into smaller 4x4 matrix operations by exploiting the block diagonal structure of the covariance matrix. Instead of inverting one large matrix, the method divides the processing into multiple smaller independent matrix inversions, significantly reducing computational complexity while maintaining the same interference rejection performance.
2Reliability
If matrix inversion is performed for IRC processing in MIMO systems, then interference mitigation is achieved, but computational burden increases
Solution Approach 1:
The patent applies segmentation by breaking down the large matrix inversion into smaller block matrix operations. The covariance matrix is structured in blocks that can be processed independently, reducing the overall computational burden from O(n^3) for an 8x8 matrix to multiple O((n/2)^3) operations for 4x4 blocks.
Solution Approach 2:
The patent changes the processing approach by utilizing the specific block diagonal structure of the covariance matrix. Instead of general matrix inversion, it applies specialized algorithms that exploit this structure, effectively changing the computational parameters from general-purpose to structure-optimized operations.
Data Source
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AI summary
Disclosed in an embodiment of the disclosure is an interference rejection combining (IRC) method supporting transmit diversity, in which an N*N interference and noise covariance matrix corresponding to one subcarrier is generated from signals, in a transmit diversity mode, received at cell reference signal (CRS) resource positions via N receiving antennas, where N is greater than or equal to 3; Cholescy decomposition and upper triangular matrix inversion is performed on the N*N interference and noise covariance matrix to obtain an N*N block matrix; the N*N block matrix is expanded to a 2N*2N noise whitening matrix; and the received signals and channel estimation values are whitened according to the noise whitening matrix, and the whitened received signals and channel estimation values used to obtain a minimum mean square error-IRC (MMSE-IRC) processing result. Also disclosed are an IRC device supporting the transmit diversity, and a computer storage medium.