On the Effect of Oscillator Phase Noise on the Performance of OFDM Systems in Sub-THz Band
Bibliographic record
Abstract
This paper presents an in-depth analysis of effect of oscillator phase noise (PN) on the performance of orthogonal frequency division multiplexing (OFDM) systems in sub-terahertz (Sub-THz) band. We use the empirical PN measurement of current Sub-THz signal sources to propose a two-part PN model that captures the unique characteristics of PN in Sub-THz band. Subsequently, the proposed model is used to analyze the performance of OFDM systems affected by PN. Our analysis reveals some key distinctions between the effect of PN on the OFDM systems operating at Sub-THz and the same systems operating at conventional microwave frequency bands. In particular, we show that in these systems: 1) the PN floor has a significant effect on the performance degradation, 2) the assumption of PN being a low-pass process is inaccurate, and 3) the existing OFDM PN mitigation schemes are less effective. To verify our analysis the upper bound on the signal-to-interference-and-noise ratio (SINR) after using the existing PN mitigation schemes under limited computational complexity constraint is derived and the effect of PN floor on the SINR is analytically calculated.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".