Uplink Boost Eliminate User in Massive MIMO System Using Reinsch Algorithm

Soraya Mustika, E. Noerhayati, Anik Nurhandayani, S. Sendari, L. Gumilar
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Abstract

In the multiuser uplink system, Multiple Input Multiple Output (MIMO) linear detectors as Zero forcing or Minimum Mean Square Error (MMSE) is widely adopted. However, the computational complexity of the linear detector remains high due to the significant vast matrix, especially with the growing number of antennas and the user. Therefore, some strategies have been adopted to approach linear detectors to reduce complexity, but among previous research just focused on one linear detector. We utilize the singular value decomposition based on MMSE or ZF detector (SVD) and propose two algorithms to update and update the channel matrix SVD. The proposed update algorithm for the case when one user is attached to the base station. Golub Kahan and Reinsch, Gram Schmidt and Householder transform recursively to approach the diagonal matrix of singular values. This shows through simulation results that the proposed scheme exceeds the conventional scheme with reduced complexity and error 1-5%.
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基于Reinsch算法的大规模MIMO系统上行升压消除用户
在多用户上行系统中,多输入多输出(MIMO)线性检测器作为零强迫或最小均方误差(MMSE)被广泛采用。然而,线性探测器的计算复杂度仍然很高,因为矩阵非常庞大,特别是随着天线数量和用户数量的增加。因此,人们采用了一些策略来逼近线性检测器以降低复杂度,但以往的研究都集中在一种线性检测器上。利用基于MMSE或ZF检测器(SVD)的奇异值分解,提出了两种对信道矩阵SVD进行更新和更新的算法。提出了一个用户连接到基站的情况下的更新算法。Golub Kahan和Reinsch, Gram Schmidt和Householder用递归变换逼近奇异值的对角矩阵。仿真结果表明,该方案优于传统方案,复杂度降低1 ~ 5%,误差减小1 ~ 5%。
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