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Joint CSIT Acquisition Based on Low-Rank Matrix Completion for FDD Massive MIMO Systems

机译:FDD大规模MIMO系统中基于低秩矩阵完成的联合CSIT采集

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Channel state information at the transmitter (CSIT) is essential for frequency-division duplexing (FDD) massive MIMO systems, but conventional solutions involve overwhelming overhead both for downlink channel training and uplink channel feedback. In this letter, we propose a joint CSIT acquisition scheme to reduce the overhead. Particularly, unlike conventional schemes where each user individually estimates its own channel and then feed it back to the base station (BS), we propose that all scheduled users directly feed back the pilot observation to the BS, and then joint CSIT recovery can be realized at the BS. We further formulate the joint CSIT recovery problem as a low-rank matrix completion problem by utilizing the low-rank property of the massive MIMO channel matrix, which is caused by the correlation among users. Finally, we propose a hybrid low-rank matrix completion algorithm based on the singular value projection to solve this problem. Simulations demonstrate that the proposed scheme can provide accurate CSIT with lower overhead than conventional schemes.
机译:发射机(CSIT)的信道状态信息对于频分双工(FDD)大规模MIMO系统是必不可少的,但是传统解决方案涉及下行链路信道训练和上行链路信道反馈的压倒性开销。在这封信中,我们提出了一个联合CSIT采购方案以减少开销。特别是,与常规方案不同,在常规方案中,每个用户分别估计自己的信道,然后将其反馈给基站(BS),我们建议所有调度的用户直接将导频观测反馈给BS,然后可以实现联合CSIT恢复在BS。我们利用用户之间的相关性导致的大规模MIMO信道矩阵的低秩特性,将联合CSIT恢复问题表述为低秩矩阵完成问题。最后,我们提出了一种基于奇异值投影的混合低秩矩阵完成算法,以解决该问题。仿真表明,所提出的方案可以提供比传统方案更低的开销的精确CSIT。

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