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An Improved SRS Noise Estimation Algorithm Based on Interference Cancellation

机译:一种基于干扰消除的改进SRS噪声估计算法

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This thesis studies SRS noise estimation method with multi-users in the Long Term Evolution(LTE), and proposes a Discrete Fourier Transform (DFT) time-domain filtering algorithm based on interference cancellation. By calculating signal power in the system protecting band, decision threshold of time domain filtering can be denoted. Therefore, one can reduce the impact of noise on the useful signal within the window, and also obtain a more accurate noise estimation. Simulation results show that either in the case of single-user or multi-user, the proposed algorithm can get good performance. At the same time, the algorithm can accurately reflect the impact in neighborhood interference on each band channel quality, so as to achieve the frequency domain resource selective scheduling effectively.
机译:本文在长期演进(LTE)中具有多用户的SRS噪声估计方法,并提出了一种基于干扰消除的离散傅里叶变换(DFT)时域滤波算法。通过计算系统保护频带中的信号功率,可以表示时间域滤波的判定阈值。因此,可以减少噪声对窗口内有用信号的影响,并且还获得更准确的噪声估计。仿真结果表明,在单用户或多用户的情况下,所提出的算法可以获得良好的性能。同时,该算法可以准确反映对每个频带信道质量的邻域干扰的影响,以便有效地实现频域资源选择性调度。

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