Research Topics

ISAC refers to the seamless integration of sensing and communication functionality into a system. ISAC is expected to improve spectral and energy efficiencies considerably while reducing both hardware and signaling costs. This integration increases awareness of surrounding conditions, enabling applications such as environmental monitoring, surveillance, medical monitoring, and smart infrastructure management.

RIS is a large 2D surface of metamaterial where each element can be controlled to change the electromagnetic properties such as phase shift of the reflection of incident signals to make better communication channels. RIS is a promising technology for future wireless communication systems due to its energy efficiency and various applications. Research about the RIS-assisted wireless communication system includes joint beamforming at base station and RIS, channel estimation of reflected signals, deploying multiple RISs, etc.

AI/ML-enabled wireless communication focuses on integrating machine learning and deep learning to create intelligent, data-driven network architectures. By shifting from traditional mathematical models to AI-native frameworks, this field optimizes complex processes such as physical layer signal processing and real-time resource allocation. These advancements enable networks to become highly adaptive and self-organizing, providing the necessary efficiency and reliability to support the demanding requirements of 6G and beyond.

Massive Multiple-Input Multiple-Output (MIMO) is a key enabling technology for modern wireless communication systems, particularly in mmWave communications in 5G and beyond. It involves the use of a large number of antennas at the base station (BS) to serve multiple users simultaneously in the same time-frequency resources. By leveraging spatial diversity and beamforming, massive MIMO significantly improves spectral efficiency, energy efficiency, and system reliability.