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Low complexity minimum mean square error channel estimation for adaptive coding and modulation systems

机译:用于自适应编码和调制系统的低复杂度最小均方误差信道估计

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摘要

Performance of the Adaptive Coding and Modulation (ACM) strongly depends on the retrieved Channel State Information (CSI), which can be obtained using the channel estimation techniques relying on pilot symbol transmission. Earlier analysis of methods of pilot-aided channel estimation for ACM systems were relatively little. In this paper, we investigate the performance of CSI prediction using the Minimum Mean Square Error (MMSE) channel estimator for an ACM system. To solve the two problems of MMSE: high computational operations and oversimplified assumption, we then propose the Low-Complexity schemes (LC-MMSE and Recursion LC-MMSE (R-LC-MMSE)). Computational complexity and Mean Square Error (MSE) are presented to evaluate the efficiency of the proposed algorithm. Both analysis and numerical results show that LC-MMSE performs close to the well-known MMSE estimator with much lower complexity and R-LC-MMSE improves the application of MMSE estimation to specific circumstances.
机译:自适应编码和调制(ACM)的性能在很大程度上取决于所检索的信道状态信息(CSI),可以使用依赖于导频符号传输的信道估计技术来获得该信息。对ACM系统的导频辅助信道估计方法的早期分析相对较少。在本文中,我们使用ACM系统的最小均方误差(MMSE)信道估计器研究CSI预测的性能。为了解决MMSE的两个问题:计算量大和假设过于简单,我们然后提出了低复杂度方案(LC-MMSE和递归LC-MMSE(R-LC-MMSE))。提出了计算复杂度和均方误差(MSE)来评估所提出算法的效率。分析和数值结果均表明,LC-MMSE的性能接近众所周知的MMSE估计器,且复杂度低得多,R-LC-MMSE改进了MMSE估计在特定情况下的应用。

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