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Principal Component Analysis-Based Block Diagonalization Precoding Algorithm for MU-MIMO System

机译:基于主成分分析的MU-MIMO系统块对角斜度化预编码算法

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This paper designs a new paradigm for the performance improvement in block diagonalization (BD)-based precoding algorithms for multiple-user MIMO (MU-MIMO) systems. Even though various linear precoding algorithms have been found, they are complicated in terms of receiver architecture with decoder. In order to simplify the user equipment (UE), it is necessary to design a receiver without decoder. This is consummated using principal component analysis (PCA). The PCA along with QR decomposition and minimum mean squared error (MMSE) channel inversion helps in performance improvement and avoids the decoder at the receiver system. The principal component is calculated using QR decomposition instead of traditional singular value decomposition (SVD) decomposition to reduce the computational complexity. The simulation result shows that PCA-based precoding algorithm in comparison with the existing algorithm achieves comparatively better sum rate, lower bit error rate (BER) using a simplified receiver.
机译:本文设计了用于在块对角化(BD)的性能改善的新范例的基于预编码的多用户MIMO(MU-MIMO)系统的算法。尽管各种线性预编码算法已被发现,它们是复杂的与解码器接收机体系结构而言。为了简化所述用户设备(UE),有必要设计一种接收机,而不解码器。这是使用主成分分析(PCA)完善。用QR分解和最小均方误差(MMSE)信道反转沿PCA有助于性能改进,并且避免了在接收机系统的解码器。主成分使用QR分解,而不是传统的奇异值分解(SVD)分解,以减少计算的复杂计算。仿真结果表明,在与现有的算法比较基于PCA的预编码算法实现使用简化的接收机相对更好总和速率,更低的误码率(BER)。

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