Bibliographic record
Abstract
Orthogonal Frequency Division Multiplexing (OFDM) is a promising technology for high data rate transmission, that is widely used in modern wireless communication systems because of its suitability for frequency selective channels. However channel time variations destroy the orthogonality between sub-carriers resulting in Inter-Carrier Interference (ICI), that degrades performance in OFDM. Various techniques have been considered to mitigate the effects of ICI. In our work, we consider OFDM as a Multiple Input Multiple Output (MIMO) system in the frequency domain, and employ corresponding detection techniques that provide good performance despite the presence of ICI. As ICI is mainly contributed by a limited number of adjacent sub-carriers, the frequency domain channel matrix can be approximated as banded. This work introduces a reduced complexity Sphere Decoder (SD) for OFDM demodulation that is based on such banded matrix assumption. It is shown that the proposed algorithm provides performance and complexity advantages over competing detection techniques based on the Viterbi Algorithm (VA) operating in the frequency domain.
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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 | 0.002 |
| 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 | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".