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20202026
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9 papers · 1 filter

eess.SP2026

Common-Loss Parameter-Efficiency Analysis of MLP and KAN Neural Receivers for Digital Communications

Sude Ertan, Osman Tokluoglu, Enver Cavus

Classical coherent binary phase-shift keying (BPSK) reception over additive white Gaussian noise (AWGN) channels is analytically well understood, and the optimum hard-decision dete…

eess.SP2026

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…

eess.SP2026

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…

eess.SP2026

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…

eess.SP2026

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…

eess.SP2025

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…

eess.SP2025

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…

eess.SP2020

Low Complexity Lookup Table Aided Soft Output Semidefinite Relaxation based Faster-than-Nyquist Signaling Detector

Adem Cicek, Ian Marsland, Enver Cavus +2

Spectrum scarcity necessitates innovative, spectral-efficient strategies to meet the ever-growing demand for high data rates. Faster-than-Nyquist (FTN) signaling emerges as a compe…

eess.SP2020

Polar Coded Faster-than-Nyquist (FTN) Signaling with Symbol-by-Symbol Detection

Abdulsamet Caglan, Adem Cicek, Enver Cavus +2

Reduced complexity faster-than-Nyquist (FTN) signaling systems are gaining increased attention as they provide improved bandwidth utilization for an acceptable level of detection c…