Université de Lille Massive MIMO Channel Characterization and Propagation-based Antenna Selection strategies: Application to 5G and Industry 4.0

In an attempt to understand the influence of the ignition source and the existence of a dead volume behind the electrodes on early stages of flame propagation, we varied both

Note that most classical massive MIMO channel estimation methods assume a similar physical model, but discretize a priori the DoDs and DoAs, so that the problem fits the framework

Considering the MIMO transmission channel, defined by the propagation channel (medium) and the antenna arrays at Tx and Rx, several parameters can be exploited as the eigenvalues

We study the analytical conditions of favorable propagation in DASs with two kinds of channels, namely, chan- nels with path loss and transmit and receive antennas in line of

maximum ratio combining (MRC) and zero-forcing (ZF) re- ceivers on the uplink (UL) in the large system limit. It has been shown in [1] that a linear receiver can be used to

LMS adaptive beamforming algorithm for planar antenna array configurations with 16, 64, 128, 256 and 1024 antenna elements was realized via simulation model so that to investigate

To reduce the amount of data, we propose to estimate the updated channel matrix from the knowledge of the full correlation matrix at the transmitter made during some initialization

Abstract—This paper presents a comprehensive performance analysis of a massive multiple-input multiple-output (MIMO) system using non-orthogonal multiple access (NOMA) in both