【摘要】 针对稀疏多径的频率选择性块传输信道,提出了基于叠加训练序列的新信道估计方法,在不占用额外信号带宽的情况下估计信道参数.利用叠加训练序列得到时域信道冲激响应的LS解,根据广义Akaike信息论准则得到信道的长度和具体多径的时延值,然后将时域信道冲激响应中非多径点的值置零,降低加性白噪声对信道估计的影响,提高信道估计的精度.通过仿真,在稀疏多径信道的条件下,与纯粹的叠加训练序列的信道估计方法相比,该方法较大程度地降低信道的估计误差,提高系统性能.更多还原

【Abstract】 A new channel estimation method based on superimposed training(ST) is proposed for the sparse frequency-selective multi-path block transmission channel,which can gain accurate channel parameters without any loss of bandwidth.With this method,first the LS solution of time domain channel impulse response(CIR) is obtained by using the superimposed training;then the channel length and the time delay of each path can be determined with the generalized Akaike information criterion(GAIC);finally the values of non multi-path position in CIR are set to zero.The new method reduces the effect of additive white noise on channel estimation and improves the precision of channel estimation.Through a series of simulations,we showed that,compared with the pure channel estimation based on ST,the proposed method reduces channel estimation error dramatically and improves the system performance.更多还原