Forward link interference suppression using multiple element adaptive array at mobile terminals
Bibliographic record
Abstract
The co-channel interference of the forward link of CDMA mobile systems results from two sources: the serving base station which also serves other users within the same cell and adjacent base stations. The former can be greatly reduced by using orthogonal spreading but the later has to be processed by other means. We study the application of multiple element arrays at mobile terminals for the purpose of suppressing interference from the other non-serving base stations. The adaptive array has the potential to enhance the SINR linearly proportional to the number of elements but other factors limit our choice of the maximal number of elements used. With such a limitation in mind we investigate the potential to process and cancel the effects of stronger interfering signals based on the knowledge of the spreading codes for all base stations and the estimates of the spatial signature vectors. We conclude that by processing the first two or three strangest interfering signals we achieve the substantial performance gain, hence we can reduce the total number of elements required by conventional adaptive beamforming techniques.
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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 | 0.000 | 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 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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 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".