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Bi-LSTM networks enhanced for faster-than-Nyquist signaling

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new method for improving the bit error rate (BER) in faster-than-Nyquist (FTN) signaling using bidirectional long short-term memory (Bi-LSTM) networks. Their study found that while architectural changes like nested ISI windows did not significantly improve performance, pre-whitening the input and distilling BCJR soft posterior information into the Bi-LSTM did yield substantial gains. This approach, with a modest increase in parameters, achieved a notable BER reduction, particularly under challenging conditions with an ill-conditioned ISI matrix. AI

IMPACT This research could lead to more efficient data transmission in communication systems by improving the accuracy of signal detection.

RANK_REASON Academic paper detailing a new method for improving signal processing. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Bi-LSTM networks enhanced for faster-than-Nyquist signaling

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Academic paper detailing a new method for improving signal processing. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Nurettin Safak, Osman Tokluoglu, Enver Cavus ·

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

    arXiv:2609.07762v1 Announce Type: cross Abstract: 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 faster-than-Nyquist (FTN) signaling. Motivated by conv…

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