Parametric channel estimation for massive MIMO

TL;DR

This paper develops a parametric channel estimation method for massive MIMO systems, deriving bounds and proposing efficient algorithms tailored for sparse millimeter wave channels with hybrid architectures.

Contribution

It introduces a new analysis of the Cramér-Rao bound and interprets the Fisher Information Matrix to design optimal estimation algorithms for massive MIMO.

Findings

Derived the Cramér-Rao bound for sparse millimeter wave channels.

Analyzed Fisher Information Matrix to optimize system parameters.

Proposed asymptotically optimal and computationally efficient estimators.

Abstract

Channel state information is crucial to achieving the capacity of multi-antenna (MIMO) wireless communication systems. It requires estimating the channel matrix. This estimation task is studied, considering a sparse channel model particularly suited to millimeter wave propagation, as well as a general measurement model taking into account hybrid architectures. The contribution is twofold. First, the Cram{\'e}r-Rao bound in this context is derived. Second, interpretation of the Fisher Information Matrix structure allows to assess the role of system parameters, as well as to propose asymptotically optimal and computationally efficient estimation algorithms.