This paper considers frequency division duplexing massive multiple-input multiple-output
systems in which the base station (BS) is equipped with either a uniform linear antenna …

This study considers the channel covariance conversion problem, which consists in
estimating the spatial covariance matrix of a wireless channel by exploiting measurements …

A large majority of cellular networks deployed today make use of Frequency Division
Duplexing (FDD) where, in contrast with Time Division Duplexing (TDD), the channel …

This paper addresses the problem of the angular power spectrum (APS) estimation in
massive multiple-input multiple-output (MIMO) systems. Estimating the APS is crucial, eg, for …

This paper addresses the problem of estimating and tracking the angular power spectrum
(APS) of MIMO channels. The APS displays properties such as invariance over a wide range …

We propose a novel algorithm to estimate the channel covariance matrix of a desired user in
multiuser massive MIMO systems. The algorithm uses only knowledge of the array response …

Mobile communications resources (spectrum and energy) are scarce. In addition, signals in
the real world are distorted by noise and interference while the statistics of wireless …

We propose two algorithms that use both models and datasets to estimate angular power
spectra from channel covariance matrices in massive MIMO systems. The first algorithm is …

This paper addresses the problem of estimating the angular power spectrum (APS) of
massive multiple input multiple output wireless channels. Estimating the APS is useful, for …

The Convergence of AI & Communications Page 1 Machine Learning for RAN: Delusion or
Salvation? Slawomir Stanczak Page 2 Why ML for Communications (=MLC)? • Entry points for …