A robust chaotic spread spectrum inter-vehicle communication scheme for ITS
Bibliographic record
Abstract
In this paper, an effective chaos based non-coherent spread spectrum communication scheme is proposed for inter-vehicle communication in intelligent transportation systems (ITS). The proposed spread spectrum scheme modulates the data to be broadcasted into the bifurcation parameter of the chaotic system and therefore the transmitted signal is broadband. By exploiting the ergodic property of chaotic signals, a simple non-coherent receiver is developed to demodulate the received signal. The new spread spectrum scheme can be implemented using simple hardware and with low manufacturing cost, which is one of the important considerations for communications in an ITS. It is shown here that the proposed chaotic spread spectrum system is highly robust against synchronization error and rapid multipath fading caused by vehicular mobility through computer simulations. Performance analysis illustrate the superior communication performance of the proposed chaotic spread spectrum over the conventional direct sequence spread spectrum scheme for collaborative driving in an ITS.
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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".