Rahim Tafazolli

On Deep Learning Solutions for Joint Transmitter and Noncoherent Receiver Design in MU-MIMO Systems

2020 · arXiv (Cornell University)

This paper aims to handle the joint transmitter and noncoherent receiver design for multiuser multiple-input multiple-output (MU-MIMO) systems through deep learning. Given the deep neural network (DNN) based noncoherent receiver, the novelty of this work …

Importance-Aware Source-Channel Coding for Multi-Modal Task-Oriented Semantic Communication

2025 · arXiv (Cornell University)

This paper explores the concept of information importance in multi-modal task-oriented semantic communication systems, emphasizing the need for high accuracy and efficiency to fulfill task-specific objectives. At the transmitter, generative AI (GenAI) is employed to …