Blind channel estimation for MRC systems with maneuvering transmit/receive terminals
Bibliographic record
Abstract
This paper presents a new blind channel estimation technique for maximum-ratio combining systems where the relative speed of the transmit/receive terminals may change. This changing speed is called maneuvering. The proposed blind system has a hard decision switching block which selects between different speed modes of a maneuvering terminal. The speed can be therefore tracked in a mobile data communication link. This is accomplished based on only the received data information signal, i.e., no other information (for example from a speed sensor or radar, etc.) is required. The performance of the proposed technique is evaluated by simulation and comparison is made with optimal coherent detection. The importance of introducing the switching block can be demonstrated by disabling it in the algorithm, and this results in a large degradation in performance. To assess the direct impact of the proposed blind channel estimation on the error performance, a fair comparison with a known, blind technique based on Kalman filtering is also made, with the assumption of non-maneuvering terminals. Here, improved performance is observed.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".