High-convergence-speed low-computation-complexity SVD algorithm for MIMO-OFDM systems

Cheng-Zhou Zhan, Kai-Yuan Jheng, Yen-Lian Chen, Ting-Jhun Jheng, A. Wu
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引用次数: 13

Abstract

Multiple-input multiple-output (MIMO) wireless communication systems with orthogonal frequency-division multiplexing (OFDM) achieve high spectral efficiency high channel capacity, and many MIMO-OFDM systems use the spatial multiplexing technique to improve the system performance. The MIMO-OFDM systems require the singular values and the corresponding singular vectors of the channel matrix by exploiting singular value decomposition (SVD). The information of the right singular-vector matrix can be fed back to the transmitter for linear precoding to improve the error performance when facing the channel matrix with rank deficiency problem. This work proposes a SVD algorithm with fast convergence speed, which is suitable for the MIMO channels with short coherent time. The proposed SVD algorithm has the following features: (1) low total computational complexity, (2) fast convergence speed, (3) the ability of reconfigurable to different numbers of transmitter and receiver antennas, and (4) insensitive to the dynamic range problem, which is suitable for hardware implementation.
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MIMO-OFDM系统的高收敛速度低计算复杂度SVD算法
多输入多输出(MIMO)无线通信系统采用正交频分复用技术(OFDM)实现了高频谱效率和高信道容量,许多MIMO-OFDM系统采用空间复用技术来提高系统性能。MIMO-OFDM系统利用奇异值分解(SVD)对信道矩阵的奇异值和对应的奇异向量进行要求。在面对秩不足信道矩阵时,可以将右奇异向量矩阵的信息反馈给发射机进行线性预编码,以提高误码性能。本文提出了一种收敛速度快的奇异值分解算法,适用于相干时间短的MIMO信道。本文提出的奇异值分解算法具有以下特点:(1)总计算复杂度低;(2)收敛速度快;(3)可对不同数量的收发天线进行重构;(4)对动态范围问题不敏感,适合硬件实现。
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