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Semi-Blind Estimation of FDD Massive MIMO Channels using Correlative Coded Analog Feedback

机译:使用相关编码模拟反馈的FDD大规模MIMO信道的半盲估计

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Knowledge of accurate channel state information (CSI) is crucial for Massive MIMO systems in order to unfold the full potential of spatial diversity. In TDD systems, uplink (UL) and downlink (DL) channels are estimated by transmitting pilots in the uplink and exploiting channel reciprocity. FDD systems are more complicated because they require a dedicated downlink training and corresponding CSI feedback in the UL. For the latter task, linear analog modulation has been proposed which avoids digitizing and coding the CSI (see e.g., Echo-MIMO). We investigate the possibility to utilize these feedback signals for the (blind) estimation of UL channels, making a separate UL training obsolete. The method requires the correlative coding of the feedback signals prior to transmission. As we will show, the blind channel estimation benefits from the large amount of DL CSI feedback that arises in Massive MIMO systems. Consequently, for sufficiently many base station antennas M (i.e., M > 32 with K = 4 terminals) and low SNR, our method exhibits larger coherent processing gains than the Echo-MIMO scheme which requires K additional uplink training symbols. On the other hand, employing Echo-MIMO with M/2 uplink training symbols is always superior to SBCE method.
机译:为了充分发挥空间分集的全部潜力,准确的信道状态信息(CSI)知识对于Massive MIMO系统至关重要。在TDD系统中,通过在上行链路中传输导频并利用信道互易性来估计上行链路(UL)和下行链路(DL)信道。 FDD系统更加复杂,因为它们需要在UL中进行专门的下行链路训练和相应的CSI反馈。对于后一项任务,已经提出了线性模拟调制,其避免了对CSI进行数字化和编码(例如,参见Echo-MIMO)。我们调查了将这些反馈信号用于UL信道的(盲)估计的可能性,从而使单独的UL训练过时了。该方法需要在传输之前对反馈信号进行相关编码。正如我们将显示的,盲信道估计受益于大规模MIMO系统中产生的大量DL CSI反馈。因此,对于足够多的基站天线M(即M> 32,其中K = 4个终端)和低SNR,与需要K个额外的上行链路训练符号的Echo-MIMO方案相比,我们的方法具有更大的相干处理增益。另一方面,采用具有M / 2个上行链路训练符号的Echo-MIMO总是优于SBCE方法。

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