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ICD reciprocity calibration for distributed large-scale MIMO systems with BD precoding

机译:具有BD预编码的分布式大规模MIMO系统的ICD互易性校准

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Time division duplexing (TDD) operation is usually used for distributed large-scale multiple-input multiple-output (MIMO) systems to perform the downlink precoding by the uplink channel estimation due to the channel reciprocity. However, the channel reciprocity is often disabled by the non-symmetric transceiver radio frequency (RF) circuits at both sides of the link. This paper is focused on the reciprocity calibration for the distributed large-scale MIMO systems where both access points (APs) and user equipments (UEs) have multiple antennas. Theoretical analysis show that RF mismatches at the UEs still bring the inter-stream interference (ISI) and lead to a significant performance loss, although with the perfect partial calibration. Then, to avoid eigenvalue decomposition (EVD) operation of the total least squares (TLS) method, an iterative algorithm named as iterative coordinate descent (ICD) method is proposed to perform the full calibration, which significantly reduces the complexity and essentially achieves the performance of the TLS method.
机译:时分双工(TDD)操作通常用于分布式大规模多输入多输出(MIMO)系统,以通过信道互易性通过上行链路信道估计执行下行链路预编码。但是,通道互易性经常被链路两侧的非对称收发器射频(RF)电路禁用。本文着重于分布式大规模MIMO系统的互易性校准,其中接入点(AP)和用户设备(UE)均具有多个天线。理论分析表明,尽管具有完美的部分校准功能,但UE处的RF不匹配仍会带来流间干扰(ISI),并导致明显的性能损失。然后,为避免总最小二乘(TLS)方法的特征值分解(EVD)操作,提出了一种称为迭代坐标下降(ICD)方法的迭代算法来执行完整校准,这大大降低了复杂度并从本质上实现了性能TLS方法。

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