Research

A novel hybrid beamforming technique combining random analog sampling and matrix completion enables accurate wideband channel estimation in millimeter wave massive MIMO systems.

This research develops a novel approach to efficiently preserve privacy in Industrial IoT systems by leveraging correlation completion and tracking, enabling robust protection against sensitive information leakage.

This paper presents a robust estimator for lens-based hybrid MIMO systems using low-resolution ADCs, improving symbol estimation accuracy and enabling practical mmWave applications.

The paper presents novel signal processing techniques for static and dynamic 3D meshes, introducing sparse representations that enable efficient data compression and improved reconstruction accuracy.

A novel energy-efficient millimeter wave hybrid MIMO beamformer is proposed, maximizing energy efficiency by optimizing DAC resolution and selecting active RF chains using the Dinkelbach method and subset selection optimization.

This paper proposes a novel architecture with a framework that dynamically activates the optimal number of radio frequency (RF) chains …

This paper proposes an energy efficient millimeter wave (mmW ave) hybrid multiple-input multiple-output (MIMO) beamformer with low …

Low resolution analog-to-digital converters (ADCs) can be employed to improve the energy efficiency (EE) of a wireless receiver since …

Many mixed reality applications are b ased on the real-time compression and streaming of three-dimensional (3D) mod­ els. Thus, they …

Hybrid analog and digital BeamForming (HBF) transceiver architectures realizing directive communication over large bandwidths in …