Secondary system's scheduling using precoding-aided space shift keying for overlay cognitive radio
Bibliographic record
Abstract
In this paper, we consider an overlay cognitive radio (CR) scenario where the primary transmitter (PT) and the primary receiver (PR) communicate via the help of a secondary users' (SUs) system. Under a worst-case scenario, we assume that the link between the primary users (PUs) is broken and the help of a selected secondary transmitter (ST) is required. Taking advantage of this opportunity, this ST will be able to transmit its own data. The communications of the PUs and the SUs take place over two phases. In the first phase, receive space shift keying (R-SSK) is employed at the PT in order to activate one ST for reception. This ST is scheduled to transmit its own data during the second phase using conventional SSK, which also allows the PR to decode the PT's message. The proposed scheduling scheme is initiated by the PT based on its incoming bits which provides fairness among STs. The proposed system comes with other advantages including the low receivers' complexity and the improved energy efficiency (EE) all gained by the use of SSK. We analyze the performance of the proposed scheme in terms of the average bit error probability (ABEP). We finally provide comparisons to existing schemes and we generate numerical results through which we confirm the derived analysis and we demonstrate the effectiveness of the proposed overlay cognitive scheduling scheme.
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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".