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Computationally Efficient Channel Estimation in 5G Massive Multiple-Input Multiple-output Systems

1
Department of Electrical Engineering, University of Engineering & Technology, Peshawar P.O.B. 814, Pakistan
2
School of Electrical Engineering, University of Ulsan, Ulsan 44610, Korea
*
Author to whom correspondence should be addressed.
Electronics 2018, 7(12), 382; https://doi.org/10.3390/electronics7120382
Received: 9 November 2018 / Revised: 22 November 2018 / Accepted: 28 November 2018 / Published: 3 December 2018
(This article belongs to the Special Issue Massive MIMO Systems)
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Abstract

Traditional channel estimation algorithms such as minimum mean square error (MMSE) are widely used in massive multiple-input multiple-output (MIMO) systems, but require a matrix inversion operation and an enormous amount of computations, which result in high computational complexity and make them impractical to implement. To overcome the matrix inversion problem, we propose a computationally efficient hybrid steepest descent Gauss–Seidel (SDGS) joint detection, which directly estimates the user’s transmitted symbol vector, and can quickly converge to obtain an ideal estimation value with a few simple iterations. Moreover, signal detection performance was further improved by utilizing the bit log-likelihood ratio (LLR) for soft channel decoding. Simulation results showed that the proposed algorithm had better channel estimation performance, which improved the signal detection by 31.68% while the complexity was reduced by 45.72%, compared with the existing algorithms. View Full-Text
Keywords: 5G; massive MIMO; computational efficiency; precoding algorithms; channel estimation 5G; massive MIMO; computational efficiency; precoding algorithms; channel estimation
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Khan, I.; Zafar, M.H.; Ashraf, M.; Kim, S. Computationally Efficient Channel Estimation in 5G Massive Multiple-Input Multiple-output Systems. Electronics 2018, 7, 382.

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