SIR-balanced macro power control for the reverse link of CDMA sectorized distributed antenna system
Bibliographic record
Abstract
The CDMA sectorized distributed antenna (SDA) is a novel antenna architecture which yields an increase in the reverse link capacity, in the order of the number of antenna elements used. In an SDA system, a power control algorithm that balances the SIR should be considered, since the conventional power-balanced power control algorithm results in considerable disparities among the SIR levels of different users. However, SIR-balancing for the SDA system is more complicated than that for the conventional central antenna systems due to macrodiversity. We use a power control algorithm which we refer to as SIR-balanced macro power control (SBMPC). SBMPC can be viewed as a special case of the power control algorithm introduced by Hanly (see IEEE Trans. Commun., vol.44, no.2, p.247-56, 1996) in the context of CDMA macrodiversity radio networks. In SBMPC, the set of equations to be solved are nonlinear (due to diversity) which makes the solutions for SIR-balancing algorithms, given in the literature, inapplicable. Therefore, we propose an iterative solution to the SBMPC algorithm which always converges. Because of the non-smooth convergence characteristics of the iterations, finding a suitable termination criterion for the iterations is a nontrivial problem. We suggest a multi-stage criterion which yields very low disparities among the SIR levels of different users for reasonably low number of iterations. Although the SBMPC algorithm and its iterative solution addressed in this paper are presented in the context of SDA systems, they may have wide applications. One such application is the power control problem in cellular systems employing macro diversity.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".