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DOI: 10.14569/IJACSA.2018.090250
PDF

Behavior of the Minimum Euclidean Distance Optimization Precoders with Soft Maximum Likelihood Detector for High Data Rate MIMO Transmission

Author 1: MAHI Sarra
Author 2: BOUACHA Abdelhafid

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 9 Issue 2, 2018.

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Abstract: The linear closed loop Multiple-input Multiple-output (CL-MIMO) precoding techniques characterized by the channel state information knowledge (CSI), at both sides of the link, aims to improve information throughput and reduce the bit error rate in the communication system. The processing involves multiplying a signal by a precoding matrix, computing from the CSI with some optimized criteria. In this paper, we proposed a new concatenation of the precoders optimizing the minimal Euclidean distance with soft Maximum Likelihood (soft-ML) detection. We analyze the performance in terms of bit error rate (BER) for the proposed association with the three well-known quantized precoders: Maximum of minimum Euclidean distance (Max-dmin) precoder, Orthogonalized Spatial Multiplexing precoder (POSM), and Orthogonalized Spatial Multiplexing (OSM) based on the same criteria, in coded MIMO system over a Rayleigh fading channel, using Quadrature Amplitude Modulation (QAM). Simulations show the interest of the proposed association of the dmin-based precoder with a soft - Ml detector, and the best result is achieved for Max-dmin precoder.

Keywords: MIMO; max-dmin; POSM; singular values decomposition (SVD); soft-ML detector

MAHI Sarra and BOUACHA Abdelhafid, “Behavior of the Minimum Euclidean Distance Optimization Precoders with Soft Maximum Likelihood Detector for High Data Rate MIMO Transmission” International Journal of Advanced Computer Science and Applications(IJACSA), 9(2), 2018. http://dx.doi.org/10.14569/IJACSA.2018.090250

@article{Sarra2018,
title = {Behavior of the Minimum Euclidean Distance Optimization Precoders with Soft Maximum Likelihood Detector for High Data Rate MIMO Transmission},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2018.090250},
url = {http://dx.doi.org/10.14569/IJACSA.2018.090250},
year = {2018},
publisher = {The Science and Information Organization},
volume = {9},
number = {2},
author = {MAHI Sarra and BOUACHA Abdelhafid}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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