Research

Millimeter wave (mmWave) massive multiple input multiple output (MIMO) systems realizing directive beamforming require reliable …

Researchers develop an efficient graph-based approach to complete missing data in animated models, leveraging structural relationships between frames.

This study develops novel interference mitigation techniques for OFDM-based vehicular communications in 5G networks, enhancing the reliability of autonomous driving applications.

Automotive industry will be greatly benefited by the advent of 5G Networking and the huge boost in performance and coverage it will …

With the growing demand for easy and reliable generation of 3D models representing real-world or synthetic objects, new schemes for …

Recently, there has been increasing interest for easy and reliable generation of 3D animated models facilitating several real-time …

This research develops a model-based Bayesian learning approach to efficiently encode dense 3D meshes using compressed sensing, achieving higher compression ratios while preserving visual quality.

A novel supervised energy disaggregation method uses dictionary-based modelling of appliance states to accurately identify and quantify energy consumption patterns in real-world settings.

This research develops an adaptive completion algorithm for wireless sensor networks, preserving privacy while accurately estimating the full-rank correlation matrix.

This paper introduces a novel matrix completion-based approach to distributed beamforming, enabling efficient maximization of receiver SNR while minimizing transmit power and interference.