High throughput downlink cellular packet data access with multiple antennas and multiuser diversity
Bibliographic record
Abstract
This paper presents a discussion of MIMO (multiple-input multiple-output) system designed to exploit multiuser diversity, with the principal goal of increasing throughput of delay tolerant data services to nomadic and mobile users in cellular systems. We consider the downlink of a cellular packet data access scheme with a base station transmit antenna array and users equipped with a single receive antenna. We show that it can be preferable to transmit to several users simultaneously using the transmit antenna array even with sub-optimal signaling. This is in contrast to single antenna systems exploiting multiuser diversity and using link adaptation, in which the average throughput per sector is maximized, when in any packet time slot transmission occurs only to one user experiencing the best channel conditions at the time. We propose several scheduling algorithms and compare their performance to the throughput achievable with precoding and perfect channel state information at the transmitter. We show that the capacity scaling typical to MIMO systems can be achieved even with single-antenna mobile receivers, but only a fraction of that capacity can be achieved with limited channel knowledge at the transmitter, when multiuser diversity is exploited.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".