Soft capacity analysis of TDMA systems with slow-frequency hopping and multiple-beam smart antennas
Why this work is in the frame
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Bibliographic record
Abstract
Smart antenna is considered as one of the most effective means for enhancing wireless system capacity. When fractional loading is accompanied with slow-frequency hopping (SFH), soft capacity can be realized in time-division multiple access (TDMA) wireless networks. Then, the interference reduction due to smart antennas, power control, and discontinuous transmission can be directly translated into capacity gain. This paper addresses the capacity gain due to multiple-beam (MB) smart antennas in TDMA wireless systems with soft capacity. The system capacity is determined analytically and by simulation. MB smart antennas with practical antenna pattern are used in this study. Perfect power control and discontinuous transmission are assumed in the simulation and the theoretical analysis. A novel call admission control algorithm is proposed to enhance the system capacity without degrading the signal quality. The TDMA system is assumed to be global system for mobile communications (GSM)-like, however, the analysis can be extended and applied to other TDMA systems.
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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 | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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