5 papers
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…
A Comparative Analysis of MLP and Kolmogorov-Arnold Networks (KAN) for Faster-than-Nyquist (FTN) Signaling Detection
Sude Ertan, Osman Tokluoglu, Enver Cavus
Faster-than-Nyquist signaling improves spectral ef- ficiency by deliberately introducing inter-symbol interference. Classical sequence detectors such as BCJR can approach optimal p…
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…
A Novel CNN Based Standalone Detector for Faster-than-Nyquist Signaling
Osman Tokluoglu, Enver Cavus, Ebrahim Bedeer +1
This paper presents a novel convolutional neural network (CNN)-based detector for faster-than-Nyquist (FTN) signaling, introducing structured fixed kernel layers with domain-inform…
A Novel Domain-Aware CNN Architecture for Faster-than-Nyquist Signaling Detection
Osman Tokluoglu, Enver Cavus, Ebrahim Bedeer +1
This paper proposes a convolutional neural network (CNN)-based detector for faster-than-Nyquist (FTN) signaling that employs structured fixed kernel layers with domain-informed mas…