A method for increasing downlink capacity by coded multiuser transmission with a base station diversity array
Bibliographic record
Abstract
In this paper, a simple structure is proposed for supporting multiple intracell users in the same time/frequency slot in the downlink using a transmit antenna array at the base station and joint detection at the single-antenna mobile receivers. To support multiple users, the system requires the simultaneous transmission of several successive code symbols from different diversity antennas. As a consequence, a single multi-antenna channel usage spans several trellis transitions - an unconventional situation which is handled with a novel merged trellis. Using the merged trellis, the optimal decoder is identified, and an analytical expression for the average bit-error rate is developed, based on soft-decision joint decoding at the mobiles. Unusual behaviour is demonstrated in terms of diversity order: as the number of transmit antennas increases due to an increasing number of users, the diversity order actually decreases due to the simultaneous transmission of successive code symbols. Even with the loss in diversity order, the method provides a major increase in downlink capacity while maintaining good performance for all users at low signal-to-noise ratios with moderate computational load.
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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) | 0.002 | 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".