Research

Efficient Channel Estimation in Millimeter Wave Hybrid MIMO Systems with Low Resolution ADCs
This paper proposes an efficient channel estima- tion algorithm for millimeter wave (mmWave) systems with a hybrid analog-digital …
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Energy Efficient Transmitter with Low Resolution DACs for Massive MIMO with Partially Connected Hybrid Architecture
Millimeter wave (mmWave) multiple-input multiple- output (MIMO) systems have recently been proposed to meet the needs of the future …
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Massive MIMO Channel Estimation for Millimeter Wave Systems via Matrix Completion
Millimeter wave (mmWave) massive multiple input multiple output (MIMO) systems realizing directive beamforming require reliable …
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New Paper: Efficient graph-based matrix completion on incomplete animated models
Researchers develop an efficient graph-based approach to complete missing data in animated models, leveraging structural relationships between frames.
Jul 1, 2017 1 min read Paper
New Paper: Autonomous driving in 5G: Mitigating interference in OFDM-based vehicular communications
This study develops novel interference mitigation techniques for OFDM-based vehicular communications in 5G networks, enhancing the reliability of autonomous driving applications.
Jun 1, 2017 1 min read Paper
Autonomous driving in 5G: Mitigating interference in OFDM-based vehicular communications
Automotive industry will be greatly benefited by the advent of 5G Networking and the huge boost in performance and coverage it will …
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Compressed Sensing for Efficient Encoding of Dense 3D Meshes Using Model-Based Bayesian Learning
With the growing demand for easy and reliable generation of 3D models representing real-world or synthetic objects, new schemes for …
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Efficient graph-based matrix completion on incomplete animated models
Recently, there has been increasing interest for easy and reliable generation of 3D animated models facilitating several real-time …
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New Paper: Compressed sensing for efficient encoding of dense 3D meshes using model-based Bayesian learning
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.
Jan 1, 2017 1 min read Paper
New Paper: Supervised energy disaggregation using dictionary—based modelling of appliance states
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.
Oct 1, 2016 1 min read Paper