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An Improved SLM Method Based on Split Preference and Four-Dimensional Hyper-Chaotic Sequences

机译:一种基于分裂偏好和四维超混沌序列的改进的SLM方法

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The traditional selective mapping method can be applied to the orthogonal frequency division multiplexing (OFDM) system to improve the peak-to-average power ratio (PAPR) reduction performance, which has to transmit plenty of side information and thus lead to the increase of complexity. To simplify and further improve the system, an improved SLM method is presented in this paper, which uses nonlinear four-dimensional hyper-chaotic phase sequence to transform the data into two segmented sequences respectively and then Hadamard transform is applied. Finally, the selected data with minimum PAPR will be transmitted after using IFFT transform to every row of the data. Simulation results show that the proposed scheme can significantly improve the PAPR reduction performance.
机译:传统的选择性映射方法可以应用于正交频分复用(OFDM)系统,以提高峰值平均功率比(PAPR)降低性能,这必须传输大量的侧面信息,从而导致复杂性的增加。为了简化和进一步改进系统,本文提出了一种改进的SLM方法,其使用非线性四维超混沌相序分别将数据转换为两个分段序列,然后施加Hadamard变换。最后,将在使用IFFT变换到数据的每一行之后传输具有最小PAPR的所选数据。仿真结果表明,该方案可显着提高PAPR降低性能。

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