Utilizing Multipath Clusters in Cognitive Radio Systems
Bibliographic record
Abstract
In this paper, we introduce a new technique that allows the coexistence of secondary users (SUs) with a primary user (PU), in the same frequency and time. The proposed technique (i.e., the cluster-based spatial opportunistic spectrum sharing (CB-SOSS) technique) exploits the spatial degrees of freedom resulting from the use of multiple antennas at both the secondary base station (SBS) and SUs; also it does not have any requirement regarding the number of antennas at the primary base station nor the PU. The CB-SOSS benefits from the fact that in wireless channels, the multipath components travel in clusters that are non-uniformly distributed in the spatio-temporal space. The key idea is to have the SBS become aware of the locations of the strong clusters in the surrounding environment and utilize them opportunistically for data transmission to the SUs, without causing a harmful interference at the PU receiver.
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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 | 0.000 |
| Open science | 0.000 | 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".