Communications, Signal Processing, and Optimization
This axis constitutes the methodological core of INCT Signals, bringing together fundamental and applied research in statistical signal processing, wireless communications, artificial intelligence, and optimization. The goal is to develop new mathematical and computational models capable of addressing the challenges of future communication, sensing, and distributed computing infrastructures.
The research covers 5G/6G systems, wireless optical communications, ISAC (Integrated Sensing and Communications), machine learning, federated learning, tensor processing, Bayesian inference, convex and non-convex optimization, as well as emerging architectures based on reconfigurable intelligent surfaces and fluid antennas.
Scientific challenges include the efficient exploration of multidimensional data, the reduction of computational complexity, robustness in the face of uncertainty, and the integration of communication, sensing, and artificial intelligence. The results are expected to impact areas such as smart cities, Industry 4.0, the Internet of Things, autonomous systems, and defense.
Principal Investigators: André L. F. de Almeida, Tarcisio F. Maciel, Fazal-E-Asim, Yuri C. B. Silva
Institutions involved: UFC, ITA, UFRGS