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  • 标题:Controlling High PAPR in Vehicular OFDM-MIMO using Downlink Optimization Model under DCT Transform
  • 本地全文:下载
  • 作者:Ahmed Ali ; Esraa Eldesouky
  • 期刊名称:International Journal of Advanced Computer Science and Applications(IJACSA)
  • 印刷版ISSN:2158-107X
  • 电子版ISSN:2156-5570
  • 出版年度:2019
  • 卷号:10
  • 期号:11
  • DOI:10.14569/IJACSA.2019.0101137
  • 出版社:Science and Information Society (SAI)
  • 摘要: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.
  • 关键词:Zadoff-Chu Sequence; Discrete Cosine Transform (DCT); Peak-to-Average Power Ratio (PAPR); Vehicular Networks
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