Low-complexity precoding method for downlink multi-user multiple-input multiple-output (MIMO) system

Abstract

The invention discloses a low-complexity precoding method for a downlink multi-user multiple-input multiple-output (MIMO) system. The method is characterized by comprising the following steps of: setting a global channel matrix, calculating a pseudo-inverse matrix of the global channel matrix, performing row decomposition on the global channel matrix, performing column decomposition on the pseudo-inverse matrix, performing orthogonal triangular decomposition on a block pseudo-inverse matrix of a user m, calculating an equivalent channel matrix of the user m, constructing a Hermitian matrix by using the equivalent channel matrix of the user m, performing LDL<H> decomposition on the Hermitian matrix, and calculating a precoding matrix and a receiving matrix of the user m according to L and D. The method has the advantages that by the null-space calculation of the pseudo-inverse matrix of the global channel matrix and the orthogonal triangular decomposition of a block, complex matrix singular value decomposition is avoided, and channel block diagonalization is quickly realized; and in addition, an equivalent channel of each single user is subjected to Hermitian matrix decomposition to finish the design of the precoding matrix, so that a calculation amount is effectively reduced under the condition of no loss of bit error rate performance.

Description

technical field [0001] The invention relates to a precoding technology in a multi-user MIMO communication system, in particular, a low-complexity precoding method in a downlink multi-user MIMO system. Background technique [0002] A multi-user MIMO (multiple-input multiple-output) system has multiple input antennas and multiple output antennas. In this system, since multiple users share channel resources, co-channel interference between users often results, thereby affecting communication performance. The precoding technology can effectively eliminate the interference among multiple users through the optimized processing of the transmitter, thus becoming an important research topic in the field of wireless communication. [0003] Precoding technology can be divided into linear precoding and nonlinear precoding, among which dirty paper coding (dirty paper coding, DPC) in nonlinear precoding can reach the upper bound of multi-user MIMO system capacity, but the complexity is to...

AI Technical Summary

Problems solved by technology

However, when the BD algorithm solves the null space by block diagonalization, it needs to perform multiple matrix singular value decomposition (SVD, singular value decomposition), and the computational complexity is still relatively high.

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