Sublinear Capacity Scaling Laws for Sparse MIMO Channels
Sublinear Capacity Scaling Laws for Sparse MIMO Channels
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DOI：
10.1109/tit.2010.2090255
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发表时间：
2011
影响因子：
2.5
通讯作者：
V. Raghavan;A. Sayeed
中科院分区：
文献类型：
--
作者：
V. Raghavan;A. Sayeed
近年来，单用户多输入多输出（MIMO）系统的性能分析一直关注于空间相关模型对遍历容量的影响。在大多数这些工作中，它是假设的统计自由度（DoF）在信道中可以通过分解它沿着一个合适的本征基，并具有完美的知识的统计DoF的发射机。随着对最先进技术中的大天线系统的兴趣增加，必须重新审视文献中的这些隐式信道建模假设。特别是，多天线测量表明，大天线系统是稀疏的，只有几个自由度是占主导地位的，足以对容量的贡献。因此，在这项工作中，假设发射机只能学习信道中的主要统计DoF。重点是了解稀疏信道中的遍历容量标度律。与经典的结果，其中线性容量缩放是隐式的，稀疏的MIMO信道加上知识，只有占主导地位的自由度示出的结果在一个新的范例的次线性容量缩放，是一致的实验结果和物理参数。研究还表明，在所有天线维度上进行均匀功率信令是浪费的，并且可能会导致对响应于信道稀疏水平和传输SNR的天线间距进行最佳调整的显着损失。
Recent attention on performance analysis of single-user multiple-input-multiple-output (MIMO) systems has been on understanding the impact of the spatial correlation model on ergodic capacity. In most of these works, it is assumed that the statistical degrees of freedom (DoF) in the channel can be captured by decomposing it along a suitable eigenbasis and that the transmitter has perfect knowledge of the statistical DoF. With an increased interest in large-antenna systems in state-of-the-art technologies, these implicit channel modeling assumptions in the literature have to be revisited. In particular, multiantenna measurements have showed that large-antenna systems are sparse where only a few DoF are dominant enough to contribute towards capacity. Thus, in this work, it is assumed that the transmitter can only afford to learn the dominant statistical DoF in the channel. The focus is on understanding ergodic capacity scaling laws in sparse channels. Unlike classical results, where linear capacity scaling is implicit, sparsity of MIMO channels coupled with a knowledge of only the dominant DoF is shown to result in a new paradigm of sublinear capacity scaling that is consistent with experimental results and physical arguments. It is also shown that uniform-power signaling over all the antenna dimensions is wasteful and could result in a significant penalty over optimally adapting the antenna spacings in response to the sparsity level of the channel and transmit SNR.