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Reducing the Computational Complexity of Massive MIMO using Pre-coding Techniques under Some Lower Orders

机译:在一些低阶下使用预编码技术降低大规模MIMO的计算复杂度

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Massive Multiple-input and Multiple-output (MIMO) is considered as a solution to the next generation cellular systems. It is visualized to provide extensive upgrade in capacity, along with the computational complexity as well as hardware. The main drawback of massive MIMO is the computational complexity in pre-coding, particularly when the "relative antenna-efficient Regularized Zero-Forcing (RZF)" is chosen to simplify Maximum Ratio Transmission (MRT). In this work, we propose to use the beam-forming methods, especially a hybrid pre-coding to reduce the system complexity in Massive MIMO. However, not only the system complexity, but also the computational complexity in pre-coding is the significant issue. In this regard, we propose another technique called Truncated Polynomial Expansion (TPE) pre-coding. It can emulate the same advantages of RZF, while offering the lower and extensible computational complexity that is achievable in an efficient pipelined fashion. By using random matrix theory, we can derive a closed-form expression of the SINR under TPE pre-coding. The proposed scheme is executed in an ideal Rayleigh fading channels, so that it produces highly desirable performance. Finally, we compare the results achieved from our proposed TPE pre-coding using three lower orders with RZF under various Channel State Information (CSI). It is obvious that our proposed method can provide the closest match to RZF, while the computational complexity is lower.
机译:大规模多输入多输出(MIMO)被视为下一代蜂窝系统的解决方案。它被可视化以提供容量的全面升级,以及计算复杂性和硬件。大规模MIMO的主要缺点是预编码中的计算复杂性,特别是在选择“相对天线效率的正则归零强制(RZF)”以简化最大比率传输(MRT)时。在这项工作中,我们建议使用波束形成方法,尤其是混合预编码,以降低Massive MIMO中的系统复杂性。然而,不仅系统复杂度,而且预编码中的计算复杂度也是重要的问题。在这方面,我们提出了另一种称为截断多项式扩展(TPE)预编码的技术。它可以模拟RZF的相同优点,同时提供以有效的流水线方式可实现的较低且可扩展的计算复杂性。通过使用随机矩阵理论,我们可以得出在TPE预编码下SINR的封闭形式。所提出的方案在理想的瑞利衰落信道中执行,因此产生了非常理想的性能。最后,我们比较了在各种信道状态信息(CSI)下使用RZF使用三个较低阶的建议TPE预编码所获得的结果。显然,我们提出的方法可以提供最接近RZF的匹配,而计算复杂度较低。

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