论文标题
FDD巨大MIMO的基于部分互惠的渠道预测框架
A Partial Reciprocity-based Channel Prediction Framework for FDD Massive MIMO with High Mobility
论文作者
论文摘要
据信大量的多输入多输出（MIMO）可以为5G及以后提供无代表性的光谱效率提高。但是，在其商业部署期间出现了一个实际的挑战，这被称为``流动性的诅咒''。当用户的速度水平提高时，大量MIMO的性能会令人震惊。在本文中，我们通过新的通道状态信息（CSI）采集框架解决了频分化双工（FDD）中的问题。提出了一个宽带宽带预编码器（JADD）宽带预编码器进行通道训练。我们的想法包括对FDD的部分通道互惠的开发和Angle-Delay-Doppler通道结构。更确切地说，使用矩阵铅笔（MP）方法，基于UL通道的基础站（BS）估算UL通道的角度 - 划分多普勒信息。然后，它根据提取的参数计算宽带JADD预码器。之后，用户估算并馈回BS的一些标量系数，以重建预测的DL通道。渐近分析表明，当BS天线的数量和带宽增加时，CSI预测误差会收敛到零。工业通道模型的数值结果表明，我们的框架可以很好地适应高速（350 km/h），大CSI延迟（10 ms）和通道样品噪声。
Massive multiple-input multiple-output (MIMO) is believed to deliver unrepresented spectral efficiency gains for 5G and beyond. However, a practical challenge arises during its commercial deployment, which is known as the ``curse of mobility''. The performance of massive MIMO drops alarmingly when the velocity level of user increases. In this paper, we tackle the problem in frequency division duplex (FDD) massive MIMO with a novel Channel State Information (CSI) acquisition framework. A joint angle-delay-Doppler (JADD) wideband precoder is proposed for channel training. Our idea consists in the exploitation of the partial channel reciprocity of FDD and the angle-delay-Doppler channel structure. More precisely, the base station (BS) estimates the angle-delay-Doppler information of the UL channel based on UL pilots using Matrix Pencil (MP) method. It then computes the wideband JADD precoders according to the extracted parameters. Afterwards, the user estimates and feeds back some scalar coefficients for the BS to reconstruct the predicted DL channel. Asymptotic analysis shows that the CSI prediction error converges to zero when the number of BS antennas and the bandwidth increases. Numerical results with industrial channel model demonstrate that our framework can well adapt to high speed (350 km/h), large CSI delay (10 ms) and channel sample noise.
