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超宽带(UWB)以其隐蔽性好、传输速率高、抗多径和窄带干扰能力强等优点,在短距多址无线通信中良好的应用前景而引起广泛研究。以多带OFDM超宽带通信系统为背景,主要研究UWB系统室内密集多径信道的估计,提出两种基于训练比特的UWB信道估计算法——ML算法和IML算法。仿真结果表明:两种信道估计算法都能够有效估计信道参数,而IML算法在消除多径成分之间相互干扰方面更优越。
Ultra wideband (UWB) has attracted extensive attention due to its good concealment, high transmission rate, strong anti-multipath and narrowband interference ability, and its good application prospects in short-range multiple access wireless communications. Based on the multi-band OFDM ultra-wideband communication system, this paper focuses on the estimation of indoor dense multipath channels in UWB systems. Two training-based UWB channel estimation algorithms, ML and IML, are proposed. The simulation results show that both channel estimation algorithms can effectively estimate the channel parameters, while the IML algorithm is superior in eliminating the mutual interference between the multipath components.