Implementation method and device for QR decomposition of matrix

Abstract

The invention discloses an implementation method and device for QR decomposition of a matrix. The method includes the steps that a complex received signal vector yc and a complex communication channel matrix Hc are acquired; the complex received signal vector yc and the complex communication channel matrix Hc are combined and transformed to obtain a real matrix C; element elimination processing is conducted on each row of elements of the real matrix C through a coordinate rotation digital computation algorithm to obtain an upper triangular matrix R and a vector QTy at the same time. According to the method, the acquired complex received signal vector and the complex communication channel matrix are combined and transformed to obtain the specific real matrix, and then a Cordic algorithm is used for conducting element elimination processing on each row of elements of the real matrix to obtain the upper triangular matrix R and the vector QTy at the same time; hence, compared with a Gram-Schmidt method, hardware resources occupied when the QTy is additionally calculated are saved, namely the hardware resources occupied in the obtaining process of the upper triangular matrix R and the QTy are reduced.

Description

technical field [0001] The invention relates to the technical field of signal detection, in particular to a method and device for realizing QR decomposition of a matrix. Background technique [0002] In a MIMO (MIMO, Multiple Input Multiple Output, Multiple Input Multiple Output) system, the receiving end needs to detect the received multi-dimensional receiving signal to restore the multi-dimensional sending signal sent by the sending end. The above process is signal detection. [0003] When performing multi-dimensional signal detection, it is necessary to perform QR decomposition on the channel matrix in order to obtain the required upper triangular matrix R and vector Q T y, where Q T is the transpose matrix of normal orthogonal matrix Q, and y is according to the complex received signal vector y c The resulting real received signal vector. The more common QR decomposition method is the Gram-Schmidt method, that is, the Gram-Schmidt orthogonalization method. [0004] W...

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Problems solved by technology

[0004] When using the Gram-Schmidt method to perform QR decomposition on the channel matrix, the channel matrix is ​​decomposed in parallel to obtain the upper triangular matrix R, but it still needs to occupy more hardware resources to calculate Q T the y

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