Performance Analysis of CR-Enabled AmBC NOMA Under IQI and Sensitivity Constraints
Bibliographic record
Abstract
Considering tag sensitivity and in-phase and quadrature-phase imbalance (IQI), this paper investigates the reliability and security of a cognitive radio (CR)-aided ambient backscatter communication (AmBC) non-orthogonal multiple access (NOMA) system. Herein, the source communicates with its NOMA users in the presence of an eavesdropper, and to bolster security, artificial noise (AN) injection is introduced. The effects of non-ideal successive interference cancellation (SIC) and AN removal on system performance are also examined. Subsequently, outage probabilities (OPs) and interception probabilities (IPs) of the tag and NOMA signals are derived, with asymptotic results for further insights. Finally, simulation results are provided to validate the theoretical analysis. It is observed that both reliability and security remain stable even as interference or maximum transmission power increases up to a certain threshold. Furthermore, the reliability under NOMA mechanism outperforms that of orthogonal multiple access. Notably, IQI can consistently enhance the confidentiality of NOMA but selectively strengthen backscatter transmission, albeit at the expense of reliability. This paper comprehensively underscores the potential for real-world implementation by incorporating sensitivity constraints, IQI, AN, and imperfect SIC into the system model.
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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 | 0.000 |
| 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".