In this tutorial paper, we look into the evolution and prospect of network architecture and
propose a novel conceptual architecture for the 6th generation (6G) networks. The proposed …

Over the last decade, transfer learning has attracted a great deal of attention as a new
learning paradigm, based on which fault diagnosis (FD) approaches have been intensively …

Many performance gains achieved by massive multiple-input and multiple-output depend on
the accuracy of the downlink channel state information (CSI) at the transmitter (base station) …

This two-part paper investigates the application of artificial intelligence (AI) and, in particular,
machine learning (ML) to the study of wireless propagation channels. In Part I of this article …

With outstanding features, machine learning (ML) has become the backbone of numerous
applications in wireless networks. However, the conventional ML approaches face many …

This article studies fast adaptive beamforming optimization for the signal-to-interference-plus-
noise ratio balancing problem in a multiuser multiple-input single-output downlink system …

Accurate downlink channel state information (CSI) is required to be fed back to the base
station (BS) in frequency division duplexing (FDD) massive multiple-input multiple-output …

In this paper, a channel state information (CSI) feedback method is proposed based on deep
transfer learning (DTL). The proposed method addresses the problem of high training cost of …

Massive multiple-input multiple-output can obtain more performance gain by exploiting the
downlink channel state information (CSI) at the base station (BS). Therefore, studying CSI …

The current wireless communication infrastructure has to face exponential development in
mobile traffic size, which demands high data rate, reliability, and low latency. MIMO systems …