A pilot‐aided detector for spectrum sensing of Digital Video Broadcasting—Terrestrial signals in cognitive radio networks
Bibliographic record
Abstract
ABSTRACT In this paper, the main properties of digital television broadcasting signals based on the Digital Video Broadcasting—Terrestrial (DVB‐T) standard are analyzed, and these properties are utilized to design a new pilot‐aided detector for spectrum sensing in cognitive radio networks. The proposed detector consists of a processing unit and a combination and decision unit. In the processing unit, multiple statistics that correspond to different enhanced pilot components are computed. In the combination and decision unit, three newly proposed combination schemes are adopted to combine these statistics, and then, a final decision on the presence or absence of the DVB‐T signals is made on the basis of the Neyman–Pearson criterion. The proposed pilot‐aided detector exploits both the periodic continual and scattered pilots that are intrinsic in the DVB‐T signals, processes the observed data timely, experiences short sensing duration, and requires no time synchronization information. Furthermore, the proposed pilot‐aided detector is able to distinguish DVB‐T signals from interference. Theoretical analysis and simulation results show that spectrum bands that are not currently occupied by the DVB‐T systems can be detected accurately by using the proposed pilot‐aided detector. Simulation results also demonstrate the significant performance gain of the proposed detector compared with the counterparts.Copyright © 2011 John Wiley & Sons, Ltd.
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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 | 0.001 |
| 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".