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Window-based channel impulse response prediction for time-varying ultra-wideband channels

机译:时变超宽带信道的基于窗口的信道冲激响应预测

摘要

This work proposes channel impulse response (CIR) prediction for time-varying ultra-wideband (UWB) channels by exploiting the fast movement of channel taps within delay bins. Considering the sparsity of UWB channels, we introduce a window-based CIR (WB-CIR) to approximate the high temporal resolutions of UWB channels. A recursive least square (RLS) algorithm is adopted to predict the time evolution of the WB-CIR. For predicting the future WB-CIR tap of window wk, three RLS filter coefficients are computed from the observed WB-CIRs of the left wk-1, the current wk and the right wk+1 windows. The filter coefficient with the lowest RLS error is used to predict the future WB-CIR tap. To evaluate our proposed prediction method, UWB CIRs are collected through measurement campaigns in outdoor environments considering line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios. Under similar computational complexity, our proposed method provides an improvement in prediction errors of approximately 80% for LOS and 63% for NLOS scenarios compared with a conventional method.
机译:这项工作提出了时延超宽带(UWB)信道的信道冲激响应(CIR)预测,方法是利用延迟箱中信道抽头的快速移动。考虑到UWB信道的稀疏性,我们引入了基于窗口的CIR(WB-CIR)来近似UWB信道的高时间分辨率。采用递推最小二乘(RLS)算法预测WB-CIR的时间演化。为了预测窗口wk的未来WB-CIR抽头,从观察到的左wk-1,当前wk和右wk + ​​1的WB-CIR计算三个RLS滤波器系数。具有最低RLS误差的滤波器系数用于预测未来的WB-CIR抽头。为了评估我们提出的预测方法,考虑了视线(LOS)和非视线(NLOS)场景,通过在室外环境中进行测量活动收集了UWB CIR。在类似的计算复杂度下,与传统方法相比,我们提出的方法可将LOS的预测误差提高约80%,将NLOS场景的预测误差提高约63%。

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