Receiver-Aided Spectrum Sensing Scheme with Spatial Differentiation in OFDM Based Cognitive Radio Networks
Bibliographic record
Abstract
In this paper, a novel spectrum sensing scheme, called receiver-aided spectrum sensing scheme with spatial differentiation (RaSSSD), is proposed for orthogonal frequency division multiplexing (OFDM) based cognitive radio networks. In RaSSSD, the deployed area of secondary users (SUs) is divided into two sub-areas. By determining which sub-area secondary user transmitter (SUT) and secondary user receiver (SUR) are located through measuring the received signal-to-noise radio (SNR) of primary signal, RaSSSD applies different strategies for channel sensing with the aid of SUR if feasible. Such aid from SUR is implemented through feeding back a state indicator, whose short length would not introduce high overhead and interference. In addition, the theory of partially observable Markov process (POMDP) is used to determine the optimal sub-channel for sensing and access. Numerical results demonstrate that with the proposed RaSSSD, the throughput of SUs can be significantly improved under the limitation of interference to the primary users.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".