A time spreaded quasi-orthogonal space-frequency coded scheme for OFDM systems
Bibliographic record
Abstract
A space-frequency (SF) coded orthogonal frequency division multiplexing (OFDM) system performs well in fast fading channels. The Hadamard time spreading offers additional time diversity gain with low complexity to SF-OFDM systems. Since quasi-orthogonal codes give higher data rate as compared to the orthogonal codes, this paper proposes a time spreaded quasi-orthogonal SF-OFDM system (called T-QOSF-OFDM) to achieve higher data rates with robust performance in fast fading channels. The proposed system performance is analyzed for different maximum Doppler frequency (fd) and time block spreading factor (M) via Monte-Carlo simulation. The T-QOSF-OFDM with 4 transmitter and 1 receiver antenna configuration offers 2 dB gain over orthogonal SF-OFDM system for fd= 300 Hz and M = 64 at BER of 10-4.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".