Optimum scheduling for smart antenna systems in Rayleigh fading channel
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Bibliographic record
Abstract
Optimum and suboptimum scheduling schemes are proposed in the uplink of array antenna systems. We assume that once a user is permitted to transmit the data, the user transmits the data using the maximum power and adjusts the transmission bit rate so that the received SINR remains fixed. In this system model, we consider an optimization problem: how many and which users should be selected to transmit their data at a time in order to maximize the throughput? Based on the analysis on the complexity of the optimum scheme, we propose another optimum scheme having reduced complexity. In circular arrays, numerical results suggest that the maximum number of simultaneously transmitting users can be limited at the expense of small throughput penalty. Motivated by this result, we propose a suboptimum scheme to reduce the complexity further. Numerical results show that the suboptimum scheme provides almost the same performance as the optimum scheme with a dramatic decrease in the complexity.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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