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Approximate Linear Minimum Mean Square Error estimation based on Channel Quality Indicator feedback in LTE systems

机译:基于LTE系统信道质量指示器反馈的近似线性最小均方误差估计

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The fast fading channel produced by the fast user mobility requires a powerful channel estimation to report the most accurate channel status. Such estimation techniques are usualy suffer from large number of computational processes, and thus, their complexity needs to be minimized. However, the calculation reliability of channel coefficients depends mainly on the accuracy of the channel estimation model. Therefore, obtaining a joint optimized solution for channel estimation error, feedback overhead, and complexity is very crucial. In this paper, two different channel estimation schemes; Linear Minimum Mean Square Error (LMMSE) and Approximate Linear Minimum Mean Square Error (ALMMSE) are used to calculate Channel Quality Indicator (CQI) and Precoding Matrix Indicator (PMI) in the 3GPP-LTE fast fading channel. It is found that, by using a low-complexity ALMMSE, the estimation error is reduced with relatively small reduction in throughput. Therefore, the proposed method is recommended to be used when the network is not fully loaded for better tradeoff concerning MSE and throughput taking into account the fixed and mobility scenarios, and thus, reliable transmission will be targeted.
机译:快速用户移动性产生的快速衰落信道需要强大的信道估计,以报告最准确的频道状态。这种估计技术是泛滥的遭受大量的计算过程,因此,需要最小化它们的复杂性。然而,信道系数的计算可靠性主要取决于信道估计模型的准确性。因此,获得用于信道估计误差,反馈开销和复杂性的联合优化解决方案非常至关重要。在本文中,两个不同的信道估计方案;线性最小均方误差(LMMSE)和近似线性最小均方误差(ALMMSE)用于计算3GPP-LTE快速衰落通道中的信道质量指示符(CQI)和预编码矩阵指示符(PMI)。发现,通过使用低复杂度ALMMSE,估计误差减小,吞吐量的相对较小。因此,建议所提出的方法在网络没有完全加载关于MSE更好的折衷和吞吐量考虑到固定和移动场景,因此,可靠的传输将有针对性地使用。

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