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Record W4415707387 · doi:10.1109/lwc.2025.3627524

A Hyperbolic Secant-Based Pulse for Enhanced FTN Signaling in 5G/6G Systems

2025· article· W4415707387 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Wireless Communications Letters · 2025
Typearticle
Language
FieldEngineering
TopicPAPR reduction in OFDM
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsPulse shapingRobustness (evolution)Pulse compressionSpectral efficiencyPulse (music)Hyperbolic functionInterference (communication)Signal processing

Abstract

fetched live from OpenAlex

This paper investigates pulse shaping optimization in faster-than-Nyquist (FTN) signaling to enhance spectral efficiency and reduce inter-symbol interference (ISI). We propose a novel hyperbolic secant root-raised cosine (HS-RRC) pulse, obtained by multiplying the conventional RRC pulse with a hyperbolic secant function. The HS-RRC pulse exhibits improved time localization, reduced ISI, and enhanced bit-error-rate (BER) performance. Extensive simulations show that, compared to the standard RRC pulse, the HS-RRC achieves notable gains in time-bandwidth product and BER across various roll-off factors. Unlike prior hyperbolic-based approaches tyrovolas2022novel, our multiplicative shaping method offers both improved spectral containment and implementation simplicity. For selected temporal compression factors (τ), the HS-RRC achieves up to a 4 dB SNR improvement at τ=0.5 and 2 dB at τ=0.8, at BER levels of 10-1 and 10-4. These enhancements significantly boost system performance, demonstrating the pulse’s ability to reduce ISI and improve system robustness under varying compression conditions, with promising applications for next-generation 5G/6G networks.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.388
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0030.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.279
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it