Distributed intercell coordination through time reuse partitioning in downlink CDMA
Bibliographic record
Abstract
Beyond 3G high speed cellular systems like HDR use a high speed downlink shared channel to provide users with services which are in many cases non real time. Each base station schedules transmissions to its users in a one by one fashion and transmits at its full power. In order to maintain an acceptable degree of fairness among users we should either assign more time slots to users at the cell boundary experiencing higher interference or use other means like intercell coordination to reduce users ' received interference. This paper proposes a fixed distributed intercell coordination method where base stations in a cluster of neighboring cells transmit one by one in a round-robin fashion and further shows that this intercell coordination scheme does not necessarily benefit all users of a cell especially when there is a maximum data rate limit for some users due to hardware limitations. Thus in order to increase the efficiency of our fixed intercell coordination scheme we propose a time reuse partitioning algorithm similar to the channel reuse partitioning in narrowband cellular systems.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".