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Optimal Superimposed Training Design for Spatially Correlated Fading MIMO Channels

机译:空间相关衰落MIMO信道的最佳叠加训练设计

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摘要

The problem of channel estimation for spatially correlated fading multiple-input multiple-output (MIMO) systems is considered. Based on the channel驴s second order statistic, the minimum mean-square error (MMSE) channel estimator that works with the superimposed training signal is first developed. The problem of designing the optimal superimposed signal is then addressed and solved with an iterative optimization algorithm. Results show that under the constraint of equal training power and bandwidth efficiency, our optimal design of the superimposed training signal leads to a significant reduction in channel estimation error when compared to the conventional design of time-multiplexing training, especially for slowly timevarying channels with a large coherence time. The issue of power allocation between the information-bearing and training signals for detection enhancement is also investigated. Simulation results demonstrate excellent bit-error-rate performance of orthogonal space-time block codes with our proposed channel estimation.
机译:考虑了空间相关衰落多输入多输出(MIMO)系统的信道估计问题。基于channel驴的二阶统计量,首先开发了与叠加训练信号一起工作的最小均方误差(MMSE)信道估计器。然后,通过迭代优化算法解决并解决了设计最佳叠加信号的问题。结果表明,在训练功率和带宽效率相等的约束下,与传统的时分复用训练设计相比,叠加训练信号的最优设计可显着减少信道估计误差,尤其是对于时变慢的时变信道。相干时间长。还研究了用于增强检测的信息承载信号和训练信号之间的功率分配问题。仿真结果表明,利用我们提出的信道估计,正交空时分组码具有出色的误码率性能。

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