Research

This research introduces a novel hybrid massive MIMO precoding architecture using random-resolution DACs and RF selection to maximize energy-efficiency while preserving spectral-efficiency.

Energy-efficiency (EE) is identified as a key 5G metric and will have a major impact on the hybrid beam- forming system design. The most …

In this article, we aim to design highly energy efficient end-to-end communication for millimeter wave multiple- input multiple-output …

This study develops a fast adaptive method for completing correlation matrices in industrial IoT networks, preserving privacy by adding noise that maximizes uncertainty while maintaining structural information.

Researchers develop an algorithm to optimize radio-frequency chain selection for efficient wireless transmission while minimizing hardware imperfections.

This research develops a novel joint localization and channel estimation framework for UAV-assisted mmWave communications, enabling accurate positioning and MIMO channel coefficient estimation through beam-space representation and matrix completion.

A novel energy-efficient beamformer maximizes millimeter wave hybrid MIMO system performance by optimizing DAC resolution and RF chain selection using Dinkelbach method and subset selection optimization.

A novel hardware architecture for reconfigurable intelligent surfaces minimizes active elements while enabling explicit channel estimation, a crucial step towards programmable wireless environments.

A novel matrix-completion-based approach enables efficient wideband channel tracking in millimeter wave massive MIMO systems with hybrid beamforming reception, reducing training periods while maintaining accurate estimation.

Intelligent surfaces comprising of cost effective, nearly pas- sive, and reconfigurable unit elements are lately gaining in- creasing …