The Effect of Imperfect Carrier Frequency Offset Estimation on OFDMA Uplink Transmission
Bibliographic record
Abstract
Since carrier frequency offset destroys user's signal orthogonality in orthogonal frequency-division multiplexing access (OFDMA) uplink transmission, resulting in an interference-limited system, its estimation/correction is very important. The residual carrier frequency offset of each user contributes inter-carrier-interference (ICI) and multiple-user-interference (MUI) to other users. In this paper, the effect of the carrier frequency offset on OFDMA uplink is analyzed. We first analyze the average uplink capacity losses as well as the signal-to-interference-and-noise ratio (SINR) reduction due to the carrier frequency offsets, and then discuss the capacity increases by using adaptive power allocation. The averaged bit error rate (BER) performance with the carrier frequency offsets on OFDMA uplink is also analyzed.
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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".