Ambient Backscatter Communication Symbiotic Intelligent Transportation Systems: Covertness Performance Analysis and Optimization
Bibliographic record
Abstract
With the continuous integration of wireless communication and intelligent information technologies, Internet of Vehicles (IoV) technology has been widely used in Intelligent Transportation Systems (ITS). Unfortunately, it is still facing challenges such as spectrum scarcity, environmental restrict and transportation data leakage. Motivated by this, we propose an ambient backscatter communication (AmBC) symbiotic ITS. To evaluate the system performance, we derive the expressions in terms of detection error probability, outage probability (OP), effective covert rate (ECR) and energy efficiency (EE). In addition, the asymptotic analysis of the OPs in the high signal-to-noise ratio (SNR) is performed. Simulation results verify the analysis and prove that: i) increasing the number of transmitting antennas significantly reduces the OPs of vehicles and backscatter device; ii) the maximum ECR is obtained by optimizing the power allocation factor, and it first increases with the vehicle’s maximum transmit power, and then converges to a constant; iii) the multi-antenna selection scheme can significantly improve covertness performance and EE.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".