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Jawarneh, Ahlam
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Computer Science & IT Electrical & Electronics Engineering

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Data detection method for uplink massive MIMO systems based on the long recurrence enlarged conjugate gradient Jawarneh, Ahlam; Albataineh, Zaid; Kadoch, Michel
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 4: August 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i4.pp3911-3921

Abstract

Although the mean square error (MMSE) approach is recognized to be near optimal for uplinking large-scale multiple-input-multiple-output (MIMO) systems, there are certain difficulties in the procedure related to matrix inversion. The long recurrence enlarged conjugate gradient (LRE-CG) approach is proposed in this study as a way to iteratively realize the MMMS algorithm while avoiding the complications of matrix inversion. In addition, a diagonal-approximate starting solution to the LRE-CG approach was used to speed up the conversion rate and reduce the complications required. It has been discovered that the LRE-CG-based approach has the ability to significantly reduce computational complexity. By comparing simulation results, it is clear that this new methodology surpasses well-established wayslike the Neumann series approximation-based method and the Gauss-Siedel iterative method. With a small number of iterations, the suggested approach achieves near-optimal performance of a standard MMSE algorithm.
Co-Authors Albataineh, Zaid Kadoch, Michel