4 papers
Transformers as Implicit State Estimators: In-Context Learning in Dynamical Systems
Usman Akram, Haris Vikalo
Predicting the behavior of a dynamical system from noisy observations of its past outputs is a classical problem encountered across engineering and science. For linear systems with…
Robust Super-Capacity SRS Channel Inpainting via Diffusion Models
Usman Akram, Fan Zhang, Yang Li +1
Accurate channel state information (CSI) is essential for reliable multiuser MIMO operation. In 5G NR, reciprocity-based beamforming via uplink Sounding Reference Signals (SRS) fac…
Federated Self-Supervised Modulation Classification under Non-IID and Imbalanced Data
Usman Akram, Yiyue Chen, Haris Vikalo
Automatic modulation classification (AMC) is a core enabler of cognitive wireless systems, providing spectrum awareness and supporting adaptive communication at the network edge. H…
Fed-REACT: Federated Representation Learning for Heterogeneous and Evolving Data
Yiyue Chen, Usman Akram, Chianing Wang +1
Motivated by the high resource costs and privacy concerns associated with centralized machine learning, federated learning (FL) has emerged as an efficient alternative that enables…