Time-varying ultra-wideband channel modeling and prediction

摘要: This paper considers the channel modeling and prediction for ultra-wideband (UWB) channels. The sparse property of UWB channels is exploited, an efficient framework developed by introducing two simplified impulse response (CIR) models, namely, windowing-based on window delay (WB-WD) bin (WB-BD). By adopting our proposed CIR recursive least square (RLS) algorithm used to predict coefficients. using real coefficients generated from measurement campaign data conducted in outdoor environments, performance results statistical properties root mean (RMS) spread values are presented. Our improves performances with lower computational complexity compared recommended ITU-R UWB-CIR model. It shown that can achieved 15% error a reduction factor 12.