arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1606.04022cs.ITcs.NAmath.ITmath.NA
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双向MIMO中继系统中的联合信道估计与训练信号设计

Joint Channel Estimation and Training Signal Design for Two-way MIMO Relay Systems

Huiming Chen, Xiaohan Zhong

AI总结:

本文提出了一种适用于单个中继天线的双向MIMO中继系统的两阶段信道估计方案,通过线性最小均方估计器估计后向信道,并设计最优训练信号,随后利用基于奇异值分解的极大似然方法估计前向信道,并提出相关训练信号设计,通过分析渐进贝叶斯CRB,以CRB为标准设计训练信号,最终通过数值结果表明所提训练信号能提升MSE性能。

摘要:

本文提出了一种适用于单个中继天线的双向MIMO中继系统的两阶段信道估计方案。第一阶段利用线性最小均方估计器(LMMSE)估计后向信道,其中设计了最优训练信号。随后主要通过基于奇异值分解(SVD)的极大似然方法估计前向信道,并提出相关训练信号。我们注意到前向信道估计器是非线性的,并通过分析渐进贝叶斯CRRLB,将CRRLB作为训练信号设计的标准。最后,数值结果表明所提出的训练信号能够提升MSE性能。

英文摘要:

In this paper, a two-stage channel estimation scheme for two-way MIMO relay systems with a single relay antenna is proposed. The backward channel is estimated by using linear minimum mean square estimator (LMMSE) at the first stage, where the optimal training signal is designed. We then mainly focus on the forward channel estimation by using singular value decomposition (SVD) based maximum likelihood method, and the related training signal is proposed. We note that the forward channel estimator is nonlinear and by analyzing the asymptotic Bayesian Cramer-rao Lower Bound (BCRLB), we seek BCRLB as the criterion for training signal design. Finally, the numerical results show that the proposed training signal can improve the MSE performance.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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