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首页> 外文会议>IEEE International symposium on Personal, Indoor, and Mobile Radio Communications >A graphical model based frequency domain equalization for FTN signaling in doubly selective channels
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A graphical model based frequency domain equalization for FTN signaling in doubly selective channels

机译：双选择信道中FTN信令的基于图形模型的频域均衡

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摘要

Modern mobile communication applications raise the requirement of high quality support for high mobility users. In this paper, we present a Bayesian graphical model based frequency domain equalization method for faster-than-Nyquist (FTN) signaling in doubly selective channels. The conventional frequency domain minimum mean squared error (FD-MMSE) equalizer suffers high complexity due to the interferences induced by adjacent frequency symbols. To tackle this problem, a low complexity iterative message passing method namely, belief propagation is employed on the Bayesian graphical model to detect the FTN symbols. Compared to the low complexity variational inference method, the proposed algorithm considers the conditional dependencies between symbols and therefore can improve the performance. Simulation results show that the proposed equalization method has similar performance of the MMSE equalizer and outperforms the variational inference method.
机译：现代移动通信应用提出了对高移动性用户提供高质量支持的要求。在本文中，我们提出了一种基于贝叶斯图形模型的频域均衡方法，用于双选择信道中的比奈奎斯特（FTN）更快的信令。由于相邻频率符号引起的干扰，常规频域最小均方误差（FD-MMSE）均衡器遭受高复杂度。为了解决这个问题，在贝叶斯图形模型上采用了一种低复杂度的迭代消息传递方法，即置信传播来检测FTN符号。与低复杂度变异推理方法相比，该算法考虑了符号之间的条件相关性，从而可以提高性能。仿真结果表明，所提出的均衡方法具有与MMSE均衡器相似的性能，并且优于变分推理方法。

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