High throughput downlink cellular packet data access with multiple antennas and multiuser diversity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it