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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 11, 2019.
Abstract: The persisting challenges of the radio channel in vehicular networks entail the use of multi-antennas which is known as Multiple-Input Multiple-Output (MIMO). In order to obtain an efficient multi-user MIMO system, the power of the radio frequency (RF) components should be optimized. Necessarily practical solutions are essential to lower the vehicular nodes' complexity and support a robust Orthogonal Frequency Division Multiplexing (OFDM) discipline with a simplified equalization at the receiver. In this paper, the pre-coding Zadoff-Chu Sequence (ZCS) is employed along with the Discrete Cosine Transform (DCT) to control and optimize the high peak power. It intends the transmission over multi-user MIMO downlink vehicular channels. At last, the convex optimization is utilized to guarantee the peak-to-average power ratio (PAPR) minimization. Simulation results have shown that the proposed model can lessen the high PAPR compared to the least-square pre-coding. At the same time, it proved its effectiveness and accuracy as it enhances the transmission quality over multi-user MIMO-OFDM downlink vehicular channel.
Ahmed Ali and Esraa Eldesouky, “Controlling High PAPR in Vehicular OFDM-MIMO using Downlink Optimization Model under DCT Transform” International Journal of Advanced Computer Science and Applications(IJACSA), 10(11), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0101137
@article{Ali2019,
title = {Controlling High PAPR in Vehicular OFDM-MIMO using Downlink Optimization Model under DCT Transform},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0101137},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0101137},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {11},
author = {Ahmed Ali and Esraa Eldesouky}
}
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.