Research

This research proposes a novel flexible hybrid beamforming scheme for spectrally efficient 6G joint radar-communications, enabling interference mitigation and improved system performance through reduced RF chain usage.

This paper develops a novel channel estimation method for lens-based hybrid MIMO systems using low-resolution ADCs, significantly improving performance and enabling practical mmWave applications.

This research introduces a novel subset selection-based RIS-aided beamforming approach that maximizes spectral efficiency in joint radar-communications systems, enabling more efficient use of RF resources.

Joint radar-communications (JRC) is considered to be a vital technology in deploying the next generation systems, since its useful in …

Joint radar-communications (JRC) benefits from multi-functionality of radar and communication operations using same hardware and radio …

This paper focuses on addressing the challenge of estimating multiple-input multiple-output (MIMO) channels for wireless communication …

This research develops quantum computing-assisted channel estimation techniques to significantly improve computational efficiency in massive MIMO mmWave systems.

The paper develops a novel channel estimation method for UAV-based mmWave massive MIMO systems with beam squint, improving accuracy by accounting for spatial selectivity in time-varying channels.

Researchers develop a distributed model predictive control approach to stabilize coupled motion and hybrid beam alignment in UAV networks.

This research presents a novel optimal sensor selection technique for mmwave-based bearing-only localization in smart environments, improving accuracy and reducing computational complexity.