A PHASE algorithm for blind adaptive optimum diversity combining
Bibliographic record
Abstract
A new PHASE algorithm is proposed for blind adaptive extraction of signal in the presence of interference by cyclostationary signal processing using an antenna array. The algorithm operates in an interference-limited system in which the desired and interfering signals have equal symbol rates, but slightly different carrier frequencies. Compared to the SCORE algorithm and a modified version of SCORE, the new algorithm provides a simpler and faster converging means to estimate the channel phase for diversity combining. There is no need to solve eigenequations or to calculate the stochastic gradient. Analytical and simulation results are presented and performances are compared with DMI (direct matrix inversion), and SCORE algorithms in terms of their convergence rate, steady state SINR, and the computation complexity. This method is relatively simple and very promising in application to indoor wireless communication for its ability to reject heavy interference and increase the spectrum efficiency. Analysis and simulation results are presented to confirm this ability.
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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 | 0.001 | 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".