Author

E. Çavuş

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Preprint Oct 2026

FTN Signaling: Spectral Efficiency from BPSK to 16-QAM

Faster-than-Nyquist (FTN) signaling can improve spectral efficiency by transmitting symbols closer together than the Nyquist limit, at the cost of additional inter-symbol interference (ISI). In this letter, we study the finite-alphabet symbol-wise achievable information rate (AIR) of FTN signaling for BPSK, QPSK, and 1...

Emre Çerçi, A. Çiçek, Melda Yuksel et al. · 0 citations

#software testing Preprint Sep 2026

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

This paper compares multi-layer perceptron (MLP) and Kolmogorov--Arnold Network (KAN) receivers using a multi-SNR Nyquist-rate BPSK dataset and shows that both MLP and KAN receivers reproduce the expected AWGN-BPSK detection trend, while a compact KAN configuration reaches a comparable operating region with substantial...

Sude Ertan, Osman Tokluoğlu, E. Çavuş · 0 citations

#machine learning Preprint Sep 2026

Pre-Whitening and BCJR Posterior Distillation for Bi-LSTM Detection in Faster-than-Nyquist Signaling

This work asks whether processing nested ISI windows in separate recurrent branches improves the bit error rate (BER) of a Bi-LSTM, and pre-whiten the input, restoring the conditional independence that colored matched-filter noise violates, and distill the BCJR soft posterior into the network.

Nurettin Şafak, Osman Tokluoğlu, E. Çavuş · 0 citations

Preprint Aug 2026

Low-Complexity Recurrent Neural Network Detector for Faster-than-Nyquist Signaling

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 signaling. Since the faster-than-Nyquist intersymbol interference has a short, finite memory, the classical Elman recurrent neural network,...

Nurettin Safak, Osman Tokluoğlu, E. Çavuş · 0 citations