In this paper, we present a wideband subspace estimation method that characterizes the signal subspace through its orthogonal projection matrix at each frequency. Fundamentally, the method models this projection matrix as a function of frequency that can be approximated by a polynomial. It provides two improvements: a reduction in the number of parameters required to represent the signal subspace along a given frequency band and a quality improvement in wideband direction-of-arrival (DOA) estimators such as Incoherent Multiple Signal Classification (IC-MUSIC) and Modified Test of Orthogonality of Projected Subspaces (MTOPS). In rough terms, the method fits a polynomial to a set of projection matrix estimates, obtained at a set of frequencies, and then uses the polynomial as a representation of the signal subspace. The paper includes the derivation of asymptotic bounds for the bias and root-mean-square (RMS) error of the projection matrix estimate and a numerical assessment of the method and its combination with the previous two DOA estimators.
Channel Estimation for Wideband MmWave MIMO OFDM System Exploiting Block Sparsity
本文研究了宽带毫米波MIMO OFDM系统的时域信道估计问题。通过传输频域导频符号以及不同的波束成形向量，我们观察到时域毫米波MIMO信道表现出信道延迟稀疏性，特别是不同空间方向之间的块稀疏性。然后，我们提出了一个时域信道估计利用块稀疏性（TDCEBS）计划，它总是旨在找到最好的非零块实现最大的投影的残差在每次迭代。特别地，我们使用5G New Radio推荐的用于生成宽带毫米波MIMO信道的ADDRiGa来评估系统性能。仿真结果验证了所提出的TDCEBS方案的有效性，所提出的方案优于现有的方案。
