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机构地区:[1]哈尔滨工程大学信息与通信工程学院,黑龙江哈尔滨150001
出 处:《系统工程与电子技术》2012年第7期1474-1478,共5页Systems Engineering and Electronics
基 金:国家自然科学基金(60772129)资助课题
摘 要:为了减轻脉冲无线超宽带(impulse radio ultra-wide band,IR-UWB)接收机高采样频率的负担,提出了基于压缩感知和递归最小二乘的低采样率信道估计算法。该算法先令接收到的训练符号通过随机滤波器,并对其欠采样,对采样到的信号进行递归最小二乘计算,最后利用压缩感知重构算法得到信道参数的估计值。提出的算法能够在低采样率的情况下对IR-UWB信道参数进行有效估计。该算法一方面降低了接收机对于模数转换器的要求;另一方面,低采样率产生较小的数据量,从而降低了估计算法的计算量。In order to reduce the burden of the high sample rate on the impulse radio ultra-wide band (IR- UWB) receiver, a channel estimation algorithm based on compressive sensing and recursive least squares is pro- posed. After passing through the stochastic filter, the received training symbols are sub-sampled. Then the re- cursive least square method is applied to calculate the sub-sampled signals. Finally, the estimated channel pa- rameters are achieved with the aid of the reconstruction algorithm in compressive sensing. The proposed algo- rithm can estimate the IR-UWB channel parameters effectively with a low sample rate. On one hand, the re- quirement on the ADC performance of the receiver is reduced. On the other hand, the smaller data quantity brought by the low sample rate can reduce the amount of calculation.
分 类 号:TN914.2[电子电信—通信与信息系统]
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