Analysis of the minimum Euclidean distance when doing faster than Nyquist signaling using different waveforms
Bibliographic record
Abstract
With the exploding demand for high data rate applications, the communication industry is faced with a necessity of exploiting the limited bandwidth available today.One promising area of research to exploit bandwidth more efficiently is Faster than Nyquist Transmission, when the transmitter is signaling at rates exceeding the channel Nyquist rate that is equal to twice the channel bandwidth.Although FTN signaling increases the transmit bit rates and does not increase the used signal bandwidth due to the time-shift property of the Fourier transform, it causes severe inter-symbol interference (ISI).However, Mazo has shown that one can transmit up to 25 percent faster than the channel Nyquist rate and minimum distance between transmitted waveforms is not affected.Furthermore, due to advances in equalization/coding techniques and silicon technology of signal processing units, FTN has been subject of intense research interest recently as severe ISI can be dealt with practically.This thesis studies the behavior of the minimum Euclidean distance for FTN signaling.We start with a literature review of previous work done in FTN research area and re-produce prior results regarding the analysis of the d min for Sinc and Raised Cosine modulating pulses.Next, we extend this study to eight more modulating pulses of interest, namely Half-Sine, Half-Cosine, Phydyas (for overlapping factors, K=2 and K=4), Hamming, Hanning, Blackman, Rectangular and the Gaussian pulse using binary and 4-PAM signaling.Finally, we determine the Mazo limit for each of these pulses as well as the exact error events that cause the d min degradation after signaling beyond the Mazo limit.For some of the studied modulation pulses, the Mazo limit is shown to be significantly larger (almost 3 times) than for the pulses previously analyzed in the literature.To the best of our knowledge, this result is novel in the FTN literature and has the potential of increasing practical data rates in the future communication systems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".