Adaptive beamforming in CDPD mobile end systems
Bibliographic record
Abstract
This paper addresses the application of antenna diversity in the Cellular Digital Packet Data (CDPD) Mobile End Systems (M-ESs) as a means to improve the performance of the CDPD forward channel and meet the tight requirements for mobile Internet access. The focal point is the construction of a maximal-ratio digital beamformer, which effectively exploits a periodic signal, transmitted in every CDPD cell. This signal serves as a reference temporal signal and it is used in the adaptive calculation of the complex weights of the beamformer. The paper presents the design and the operation of the adaptive beamformer, it demonstrates its performance through simulation results and additionally it discusses its significance and its applications. It is argued that even for relatively small spacing between the antenna elements the considered beamforming scheme has the potential to provide significant improvements in the performance of the CDPD forward channel.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".