Abstract
This paper considers the channel modeling and prediction for ultra-wideband (UWB) channels. The sparse property of UWB channels is exploited, and an efficient prediction framework is developed by introducing two simplified UWB channel impulse response (CIR) models, namely, the windowing-based on window delay (WB-WD) and the windowing-based on bin delay (WB-BD). By adopting our proposed UWB windowing-based CIR models, the recursive least square (RLS) algorithm is used to predict the channel coefficients. By using real CIR coefficients generated from measurement campaign data conducted in outdoor environments, the modeling and prediction performance results and the statistical properties of the root mean square (RMS) delay spread values are presented. Our proposed framework improves the prediction performances with lower computational complexity compared with the performance of the recommended ITU-R UWB-CIR model. It is shown that our proposed framework can achieved 15% lower prediction error with a complexity reduction by a factor of 12.
Highlights
The Federal Communications Commission (FCC) defines ultra-wideband (UWB)communications [1,2] as systems that operate within the fractional bandwidth of B/ f c ≥ 20%, where B is the transmission bandwidth and f c is the center frequency of the band, or with a total bandwidth of more than 500 MHz [3,4]
We present the modeling and prediction mean square error (MSE) performances along with the statistical properties of the root mean square (RMS) delay spread for the proposed windowing-based channel impulse response (CIR) models
There are only 23 multipath components (MPCs), the prediction for CIR coefficients in the time slot must be performed within all 380 delay bins because the locations of these MPCs are random within the delay bins
Summary
Communications [1,2] as systems that operate within the fractional bandwidth of B/ f c ≥ 20%, where B is the transmission bandwidth and f c is the center frequency of the band, or with a total bandwidth of more than 500 MHz [3,4]. Extensive measurements were conducted to characterize and model UWB channels for the future 5G large bandwidth systems in different indoor [20,21,22] and outdoor environments [23,24]. The bins containing a single MPC are interspersed with empty bins, resulting in a sparse channel impulse response (CIR) for UWB systems [14] This sparse CIR property was found in future 5G wireless systems operating at mm-wave spectrum bands [14]. The modeling and prediction performance results and the statistical properties of the root mean square (RMS) delay spread are presented These results are generated by utilizing the proposed windowing-based models on the measured UWB-CIRs from an outdoor measurement campaign.
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