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本文推导了DS-UWB信道估计中最大比合并(maximum ratio combining)结合滑动窗(sliding window)算法的理论公式,给出DS-UWB系统中最大似然(maximum likelyhood)算法公式并与之比较,经理论分析和计算机仿真证明,在没有码间干扰的条件下,MRC-SW算法等价于一阶ML算法,其性能随着输出端采样频率的提高逼近ML算法。在接收端采样频率一定的条件下,本文还提出了一种通过延迟重复发送导频信号等效提高采样频率的方法,可以在不改变接收端硬件电路的情况下,大幅提高算法性能。
This paper deduces the theoretical formula of the maximum ratio combining and sliding window algorithm in DS-UWB channel estimation, gives and compares the formula of the maximum likelihoodhood in DS-UWB system, Theoretical analysis and computer simulation show that the MRC-SW algorithm is equivalent to the first-order ML algorithm in the absence of inter-symbol interference, and its performance approaches the ML algorithm as the output sampling frequency increases. Under the condition that the sampling frequency of the receiving end is constant, this paper also presents a method of equivalently increasing the sampling frequency by delaying the repeated sending of the pilot signal, which can greatly improve the performance of the algorithm without changing the receiving end hardware circuit.