As an integral part of the electromagnetic system, antennas are becoming more advanced
and versatile than ever before, thus making it necessary to adopt new techniques to …

Metamaterials have unique physical properties. They are made of several elements and are
structured in repeating patterns at a smaller wavelength than the phenomena they affect …

In this paper, we propose a novel deep unsupervised learning-based approach that jointly
optimizes antenna selection and hybrid beamforming to improve the hardware and spectral …

In this paper, we study short-packet communications in multi-hop networks with wireless
energy transfer, where relay nodes harvest energy from power beacons to transmit short …

In this paper, we investigate the downlink robust precoding with imperfect channel state
information (CSI) for massive multiple-input-multiple-output (MIMO) communications. With …

Next-generation wireless networks strive for higher communication rates, ultra-low latency,
seamless connectivity, and high-resolution sensing capabilities. To meet these demands …

This paper proposes a deep learning approach to channel sensing and downlink hybrid
beamforming for massive multiple-input multiple-output systems operating in the time …

The popularity of mobile broadband connectivity continues to grow and thus, the future
wireless networks are expected to serve a very large number of users demanding a huge …

Graph neural networks (GNNs) can improve the efficiency of learning wireless policies by
leveraging their permutation properties and topology prior. While mismatched permutation …

Smart services based on the Internet of Things (IoT) are likely to grow in popularity in the
forthcoming years, necessitating the improvement of fifth-generation (5G) cellular networks …