Enhancing Multiband OFDM Performance: Capacity-Approaching Codes and Bit Loading
Bibliographic record
Abstract
In this paper we consider turbo and repeat-accumulate (RA) codes as well as bit-loading as methods of enhancing the performance of multiband OFDM, a frequency-hopping orthogonal frequency-division multiplexing system which is a strong contender for the physical layer IEEE standard for high-rate wireless personal area networks (WPANs) based on ultra-wideband (UWB) transmission. Our methodology consists of (a) development and quantification of appropriate information-theoretic performance measures, and (b) comparison of these measures with simulation results for the multiband OFDM standard proposal as well as our proposed extensions. We find that the current multiband OFDM standard proposal sufficiently exploits the frequency selectivity of the UWB channel, and that the system performs in the vicinity of the channel cutoff rate. By applying turbo codes and a reduced-complexity clustered bit-loading algorithm the system power efficiency can be improved by over 6 dB at a data rate of 480 Mbps.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".