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

Teerapat Sanguankotchakorn and Ganti V. Sowmya ,
Asian Institute of Technology, Pathumthani 12120, Thailand
Abstract—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. 

Index Terms—Massive MIMO, Zero-Forcing (ZF) pre-coding, RZF.

Cite: Teerapat Sanguankotchakorn and Ganti V. Sowmya, "Reducing the Computational Complexity of Massive MIMO using Pre-coding Techniques under Some Lower Orders," Journal of Communications, vol. 14, no. 6, pp. 498-503, 2019. Doi: 10.12720/jcm.14.6.498-503.
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