Intelligent solutions for self-interference cancellation and signal redefinition in integrated sensing and communications

This project targets solving challenges in integrated sensing and communication (ISAC) networks. Leveraging full-duplex (FD) and reconfigurable intelligent surface (RIS) technologies, we aim to establish analytical and algorithmic frameworks, shaping the next-generation 6G wireless communication standards. Our approach synthesizes collaboration across diverse communication systems within a large-scale dynamic network. Additionally, we strive to develop theoretical insights and computationally efficient algorithms, reducing processing delays and resource demands. In the project, incorporating machine learning (ML) techniques offers a promising avenue to obtain optimal waveform design, simplified RIS signal complexity, and enhanced efficiency of full-duplex systems by managing self-interference (SI).