Adaptive Modulation and Code Rate for Turbo Coded OFDM Transmissions
Bibliographic record
Abstract
This paper discusses the application of adaptive modulation and adaptive rate turbo-coding to OFDM (orthogonal frequency-division multiplexing), to enable a closer approach to the Shannon capacity of the time and frequency selective channel. The adaptive turbo-code scheme is based on a subband adaptive method, and compares two adaptation algorithms: a conventional, conservative approach where modulation and code rate is chosen based on the poorest subcarrier in a subband, and an optimal approach based on a prediction of the average BER over all sub-carriers. Four modulation schemes (BPSK, QPSK, \8AMPM and 16QAM) and four code rates (1/3, 1/2, 2/3 and uncoded) are employed. Systems employing different numbers of combinations of these schemes are compared. Simulation results for throughput and BER show that 8 schemes are sufficient to approach the maximum capacity: a small reduction in throughput occurs with only 4 schemes (all 1/2 rate coded). The optimal adaptation algorithm provides a significant improvement.
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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".