Leveraging the Restricted Isometry Property: Improved Low-Rank Subspace Decomposition for Hybrid Millimeter-Wave Systems
Leveraging the Restricted Isometry Property: Improved Low-Rank Subspace Decomposition for Hybrid Millimeter-Wave Systems
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DOI：
10.1109/tcomm.2018.2854779
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发表时间：
2018-07
影响因子：
8.3
通讯作者：
Wei Zhang;Taejoon Kim;D. Love;E. Perrins
中科院分区：
文献类型：
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作者：
Wei Zhang;Taejoon Kim;D. Love;E. Perrins
毫米波频率通信将是5G的基本新技术之一。获取准确的信道估计是推进先进的毫米波混合多输入多输出(MIMO)预编码技术的关键。然而，毫米波MIMO信道估计受到显著增加的信道使用开销的影响。发生这种情况的原因是射频(RF)链的数量有限，这些链阻止数字基带直接访问每个天线上的信号。为了解决这个问题，最近的研究集中在自适应闭环和双向信道估计技术上。与以往的方法不同，本文研究了一种非自适应的、简单的开环毫米波MIMO信道估计技术。提出了一种信道子空间采样信号的随机相位旋转设计，并证明了它们大概率地服从受限等距特性(RIP)。然后，我们将信道估计描述为一个低秩子空间分解问题，并基于RIP，证明了所提出的框架具有对低信噪比的恢复能力。结果表明，在保证有界估计误差与信道自由度成正比的情况下，所需的信道使用次数与信道自由度成正比，而如果射频链的数目可以与信道维度成比例地增长，同时保持信道等级不变，则所需的信道使用次数收敛到一个恒定值。特别地，我们证明了RIP描述越紧密，信道估计误差就越小。我们还设计了一种迭代技术，有效地找到了公式问题的次优但稳定的解。与以前的闭环和双向自适应技术相比，所提出的技术具有更高的信道估计精度和相当低的信道使用开销。
Communication at millimeter wave frequencies will be one of the essential new technologies in 5G. Acquiring an accurate channel estimate is the key to facilitate advanced millimeter wave hybrid multiple-input multiple-output (MIMO) precoding techniques. Millimeter wave MIMO channel estimation, however, suffers from a considerably increased channel use overhead. This happens due to the limited number of radio frequency (RF) chains that prevent the digital baseband from directly accessing the signal at each antenna. To address this issue, recent research has focused on adaptive closed-loop and two-way channel estimation techniques. In this paper, unlike the prior approaches, we study a non-adaptive, hence rather simple, open-loop millimeter wave MIMO channel estimation technique. We present a random phase rotation design of channel subspace sampling signals and show that they obey the restricted isometry property (RIP) with high probability. We then formulate the channel estimation as a low-rank subspace decomposition problem and, based on the RIP, show that the proposed framework reveals resilience to a low signal-to-noise ratio. It is revealed that the required number of channel uses ensuring a bounded estimation error is linearly proportional to the degrees of freedom of the channel, whereas it converges to a constant value if the number of RF chains can grow proportionally to the channel dimension while keeping the channel rank fixed. In particular, we show that the tighter the RIP characterization the lower the channel estimation error is. We also devise an iterative technique that effectively finds a suboptimal, but stationary, solution to the formulated problem. The proposed technique is shown to have improved channel estimation accuracy with a substantially low channel use overhead as compared to that of previous closed-loop and two-way adaptation techniques.