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首页> 外文期刊>Wireless personal communications: An Internaional Journal >Improved ML Channel Estimation for Uplink MC-CDMA Systems in Closely Spaced Multipath Channels
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Improved ML Channel Estimation for Uplink MC-CDMA Systems in Closely Spaced Multipath Channels

机译:在近距离多径信道中用于上行MC-CDMA系统的改进的ML信道估计

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摘要

In order to attain near-single user performance in uplink multicarrier code-division multiple-access (MC-CDMA) systems, multiuser detection (MUD) methods may be employed which rely on simultaneous estimation of the channel frequency responses of multiple users. Pilot symbol assisted (PSA) channel estimation is needed in fast fading channels and it can be performed either by applying maximum likelihood (ML) criterion or minimum mean-squared error (MMSE) criterion. The performance of ML estimation technique degrades significantly in the case of fractionally spaced (FS) multipath channels where dominant paths are closely spaced with respect to the time resolution of the system. In such situation, the number of effective paths (which contribute more towards signal power) becomes considerably less than the actual number of multipaths at low and moderate SNR values. We propose an improved ML estimation method which considers only effective paths during the estimation process. The proposed method performs nearly identical to the MMSE estimation method and it can also provide significant reduction in the computational complexity when a large number of users are accommodated in the system.
机译:为了在上行链路多载波码分多址(MC-CDMA)系统中获得近乎单一的用户性能,可以采用多用户检测(MUD)方法,该方法依赖于同时估计多个用户的信道频率响应。快速衰落信道中需要导频符号辅助(PSA)信道估计,并且可以通过应用最大似然(ML)标准或最小均方误差(MMSE)标准来执行。在分数间隔(FS)多径通道的情况下,ML估计技术的性能会大大降低,在该通道中,相对于系统的时间分辨率,主要路径之间的距离很近。在这种情况下,有效路径的数量(对信号功率有更大的贡献)变得比低和中等SNR值下实际的多路径数量要少得多。我们提出了一种改进的ML估计方法,该方法仅在估计过程中考虑有效路径。所提出的方法执行与MMSE估计方法几乎相同,并且当系统中容纳大量用户时,还可以显着降低计算复杂度。

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