Investigating the effects of imperfect digital beamforming on cell capacity in a cellular CDMA communication system
Bibliographic record
Abstract
Cell capacity in a CDMA communication system can be increased through the use of base station antenna arrays and digital beamforming. It is necessary to estimate suitable beamforming weights from the received signal data which contains interference and noise. This imperfect beamforming produces corrupted weight values which affect the performance of the system. Due to the data coding methods used in IS-95, it is necessary to utilise an enhanced beamforming weight estimation technique which we present here. This permits significantly more accurate estimates of the beamforming coefficients to be made. A simplified method for cell capacity estimation based on the power control information is also included. Sample simulation results indicate that approximately a 50% increase in capacity is obtained when beamforming with two antenna elements is used instead of one element. Results obtained from the proposed imperfect beamforming and the power control capacity estimation technique agree with those obtained for the situation where perfect beamforming weights are need.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.007 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".