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Measured and estimated data of non-linear BRAN channels using HOS in 4G wireless communications

机译:在4G无线通信中使用HOS对非线性BRAN信道进行测量和估计的数据

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The aim of this research is to develop a non-linear blind estimator able to represents a Broadband Radio Access Networks (BRAN) channels. In the one hand, we have used Higher Order Statistics (HOS) theory to build our algorithm. Indeed, we develop a non-linear method based only on fourth order cumulants for identifying the diagonal parameters of quadratic systems. In the other hand, the developed approach is applied to estimate the experimental channels, BRAN A, C and E data normalized for MC-CDMA, in non-linear case. However, the estimated data will be used in the blind equalization. The simulation results in noisy environment and for different signal to noise ratio (SNR) show the accuracy of develop estimator blindly (i.e., without any information about the input) with non-Gaussian signal input. Furthermore, in part of blind equalization problem the obtained results, using Zero forcing (ZF) and Minimum Mean Square Error (MMSE) equalizers, demonstrate that the proposed algorithm is very adequate to correct channel distortion in term the Bit Error Rate (BER). Finally, these estimated data present a necessary asset for conducting validation experiments, and can be also used as a baseline.
机译:这项研究的目的是开发一种非线性盲估计器,该估计器能够代表宽带无线接入网(BRAN)信道。一方面,我们使用高阶统计(HOS)理论来构建算法。实际上,我们开发了一种仅基于四阶累积量的非线性方法来识别二次系统的对角线参数。另一方面,在非线性情况下,将开发的方法应用于估算实验信道,针对MC-CDMA标准化的BRAN A,C和E数据。但是,估计的数据将用于盲均衡。在嘈杂环境中以及针对不同信噪比(SNR)的仿真结果表明,使用非高斯信号输入时,盲目地开发估算器(即,没有任何有关输入的信息)的准确性。此外,在部分盲均衡问题中,使用零强迫(ZF)和最小均方误差(MMSE)均衡器获得的结果证明,所提出的算法非常适合根据误码率(BER)校正信道失真。最后,这些估计的数据为进行验证实验提供了必要的资产,也可以用作基准。

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