Group-orthogonal OFDMA in fast time-varying frequency-selective fading environments
Bibliographic record
Abstract
This paper presents a group-orthogonal OFDMA (GO-OFDMA) suitable for broadband access systems in a fast time-varying frequency-selective fading environment when channel knowledge is not available at the transmitter. Subcarrier grouping to achieve the diversity gain of a time-domain Rake receiver is discussed and the closed-form expression of its bit-error-rate (BER) performance over a frequency-selective Rayleigh fading channel is derived. The proposed GO-OFDMA scheme uses a split-and-group structure and a maximum-likelihood (ML) multi-user detection (MUD) to increase the number of supportable active users and to reduce the peak-to-average ratio (PAR). Analytical and simulation results are in an excellent agreement. Performance evaluation indicates that the proposed GO-OFDMA provides a lower PAR and similar BER as compared with the group-orthogonal multi-carrier CDMA (GO-MC-CDMA), and outperforms the random-hopping (RH)-OFDMA and matched-filter based MC-CDMA.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".