Secure Transmission for MISO Wiretap Channels Using General Multi-Fractional Fourier Transform: An Approach in Signal Domain
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, we propose a physical layer secure transmission technology based on multi-components for multiple-input single-output (MISO) systems. The scheme mainly realizes physical layer security (PLS) in General Multi-Fractional Fourier Transform (GMFRFT) signal domain, which is different from traditional schemes that rely on the spatial domain. Different GMFRFT components are transmitted by multiple antennas at the transmitter, then the legitimate receiver and the eavesdropper receive the superposition of multiple non-orthogonal components. The resulting mutual interference will reduce the signal-to-interference and noise (SINR) at the eavesdropper, but without affecting the legitimate receiver. Because the legitimate receiver receives the non-contaminated GMFRFT signal due to designing multi-components at the transmitter, while the eavesdropper receives the signal whose constraint relations in the GMFRFT signal domain are destroyed, which will cause the energy loss of the information bearing signal. Furthermore, in order to achieve the maximum secrecy capacity, the selection method of GMFRFT transform order is given to adjust the power allocation among GMFRFT components. Compared with the scheme based on artificial noise (AN), the advantages of our scheme are: 1) our scheme can further reduce the capacity of wiretap channel while not requiring the transmitter to use partial power to transmit meaningless artificial noise signals; 2) our scheme outperforms AN-based schemes when the available spatial degrees of freedom are limited. Simulation results are provided to demonstrate the secrecy performance of the proposed scheme.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it