Off-Grid Aware Spatial Covariance Estimation in mmWave Communications

Abstract

This work investigates the problem of spatial covariance matrix estimation in a millimeter Wave (mmWave) hybrid multiple-input multiple-output (MIMO) system with an emphasis on the basis-mismatch effect. The basis mismatch is prevalent in the compressed sensing (CS) schemes which adopt discretization procedure. In such an approach, the algorithm yields a finite discrete point which is an approximation to the continuous parametric space. The quality of this approximation depends on the number of discretized points in the dictionary. Instead of increasing the number of discretized points to combat this off-grid effect, we propose an efficient parameter perturbed framework which uses a controlled perturbation mechanism in conjunction with the orthogonal matching pursuit (OMP) algorithm. Numerical results verify the performance improvement through our proposed algorithm in terms of relative efficiency metric, which is basically due to taking care of the off-grid effect carefully that is ignored in the conventional CS algorithms.

3D On and Off-Grid Dynamic Channel Tracking for Multiple UAVs and Satellite Communications

“…However, in the real world, the true angle is continuously distributed [22]. To solve the off-grid problem, [22] and [23] all proposed algorithms based on a two-dimensional (2D) flat environment. Hence, none of the mentioned work considered the 3D off-grid case of the channel model.…”

“…However, in practice, the true angle is continuously distributed. The channel with this kind of AoDs is named as off-grid channel [23]. Hence in this subsection, we present both on-gird and off-grid cases.…”