A method for increasing downlink capacity by coded multiuser transmission with a base station antenna array
Bibliographic record
Abstract
In this paper, a simple structure is proposed for accommodating reuse-within-cell in the downlink of a time-division multiple-access system using a transmit antenna array at the base station and joint detection of the cochannel signals at the single-antenna mobile receivers. The transmit array is used solely for system capacity increase; diversity is obtained in the traditional way through standard coding and interleaving. Due to the spatial formatting of the coded symbols prior to transmission, a single multiantenna channel usage spans several trellis transitions - an unconventional situation which is handled through a "merged trellis". Using the merged trellis, a combined joint detector/soft-decision decoder is constructed, and an analytical expression is derived for the coded bit-error rate based on the exact computation of pairwise error probabilities. It is shown that while the system suffers a reduction in diversity order as the number of intracell cochannel users increases, the reduction may be countered by increasing the constraint length of the code. Although this increases complexity, it is shown that multiple users may be supported, all enjoying good performance at low signal-to-noise ratios, while keeping the complexity in check.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".