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cs.IT2026
Learning During Detection: Continual Learning for Neural OFDM Receivers via DMRS
Mohanad Obeed, Ming Jian
Deep neural networks (DNNs) have been increasingly explored for receiver design because they can handle complex environments without relying on explicit channel models. Nevertheles…
cs.IT2025
CoNet-Rx: Collaborative Neural Networks for OFDM Receivers
Mohanad Obeed, Ming Jian
Deep learning (DL) based methods for orthogonal frequency division multiplexing (OFDM) radio receivers demonstrated higher signal detection performance compared to the traditional…
cs.IT2025★ 1 cited
Hybrid Neural/Traditional OFDM Receiver with Learnable Decider
Mohanad Obeed, Ming Jian
Deep learning (DL) methods have emerged as promising solutions for enhancing receiver performance in wireless orthogonal frequency-division multiplexing (OFDM) systems, offering si…