5 papers
Pre-Whitening and BCJR Posterior Distillation for Bi-LSTM Detection in Faster-than-Nyquist Signaling
Nurettin Safak, Osman Tokluoglu, Enver Cavus
Recurrent detectors such as bidirectional long short-term memory (Bi-LSTM) networks are low-complexity alternatives to the optimal Bahl-Cocke-Jelinek-Raviv (BCJR) detector for fast…
Sub-6 GHz Over-the-Air AMC via Curriculum Fine-Tuned CNN-Transformers
Nurettin Safak, Muhammet Sefa Demirel, Alperen Marasli +3
Automatic modulation classification (AMC) models are frequently trained and validated on synthetic or channel-cabled data, leaving open the question of how they behave once path lo…
Low-Complexity Recurrent Neural Network Detector for Faster-than-Nyquist Signaling
Nurettin Safak, Osman Tokluoglu, Enver Cavus
This study proposes a low-complexity, bidirectional, single-pass Elman recurrent neural network detector for binary phase-shift keying signals transmitted with faster-than-Nyquist…
An Uncertainty-Driven Hybrid Deep Learning Approach for Broad-Coverage RF Modulation Recognition
Nurettin Safak, Durdu Can Yerdeyatar, Muhammet Sefa Demirel +3
Automatic RF modulation recognition is of critical importance in spectrum monitoring, electronic warfare, and cognitive radio applications, where low signal-to-noise ratio (SNR) co…
Self-Attention Transformer-Based Detector for Faster-than-Nyquist Signaling
Nurettin Safak, Osman Tokluoglu, Enver Cavus
In this study, a novel encoder-only Transformer-based receiver architecture is presented for BPSK signals transmitted over Faster-than-Nyquist (FTN) signaling channels that introdu…