Analysis of spectral efficiency for OFDM cooperative cognitive networks with non‐linear relay
Bibliographic record
Abstract
Abstract This paper analyzes the downlink achievable spectral efficiency of an orthogonal frequency‐division multiplexing (OFDM) cooperative cognitive network with a non‐linear relay. The analysis is carried out subject to the power amplifier's (PA) non‐linear effect on the relay node which operates in the amplify‐and‐forward (AF) mode. Specifically, an analytical expression for the power spectral density (PSD) of relay output in terms of its source power is derived. By using the obtained PSD, the power of relay's PA output is derived for each subcarrier and the 1 dB compression point is determined. Then, the adjacent channel power (ACP) of each subcarrier is analytically derived in terms of secondary user (SU) source input power. Next, the signal to interference and noise ratio (SINR) of each subcarrier at destination (SU receiver) is calculated by considering the non‐linear effect of PA at the relay. Having the SINRs of all subcarriers, a constrained optimization problem on the source's input power is formulated in which the achievable spectral efficiency is the objective function and all ACPs being less than the interference temperature limit are its constraints. Finally, we perform some simulations and show that the numerical results are consistent with the analytical findings.
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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 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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".