A reduced-complexity soft-input soft-output detection scheme for wideband MIMO channels
Bibliographic record
Abstract
This work presents a reduced-complexity soft-input soft-output detection scheme for wideband space-time bit-interleaved coded modulation (ST-BICM) MIMO systems. This scheme, which is referred to as iterative trellis search detection, is based in part on a reduced-complexity variant of the BCJR algorithm. It also uses signal sets with block partitioning labeling, called multilevel mapping constellations, in order to achieve further complexity reduction for higher-order QAM modulation formats. Results from computer simulations of an iterative ("turbo") MlMO receiver employing the new scheme have shown that it successfully eliminates the error floor that occurs if inter-symbol interference is not mitigated. It is also shown that the optimum choice of the number of fingers employed by the detector is not only dependent on the channel characteristics, but also by the fraction of states considered in the trellis search.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".