Coherence signal impact on the performance of a spatio-temporal GSC receiver for CDMA applications
Bibliographic record
Abstract
The goal of adaptive beamforming is the reception of the desired signal in a specified direction and the cancellation of the interference signals without a priori knowledge of the interference environments. An efficient algorithm called generalized sidelobe canceller (GSC) was proposed (Rude, M.J. and Griffiths, L.J., Proc. IEEE ICASSP, p.968-71, 1989). However, one major problem is the desired signal cancellation that is caused by coherence between the desired signal and one or more interfering signals. We proposed a new spatio-temporal scheme based on GSC (Ghanem, K., Proc. IEEE Radio & Wireless Conf. p.119-22, 2003). The new receiver only prevents the desired signal cancellation but also provides robustness against channel variations. This paper presents the performance of the new efficient technique, combining spatial and temporal diversities, in coherent and non-coherent environments. Beamforming efficiency and convergence rates are investigated and presented. It is shown that the scheme performs well at higher interference levels, and, at the same time, the beamforming efficiency of the proposed technique presents a high robustness against signal coherence.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 source (direct Gemma or distilled Codex), 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".