Eavesdropping-Resilient OFDM System Using CSI-Based Dynamic Subcarrier Allocation
Bibliographic record
Abstract
In this paper, we propose a simple and effective eavesdropping-resilient OFDM system achieved by dynamic subcarrier allocation, exploiting the independent frequency selectivities of different wireless channels. The transmitter utilizes the channel state information (CSI) between the legitimate receiver and itself for the OFDM subcarrier allocation. The highly faded subcarriers are dropped for the data transmission and the constellation size of subcarriers with excellent channel conditions is increased in order to retain the overall throughput. Based on channel reciprocity, the channel behaves in the same manner at each pair of users. The subcarrier allocation scheme is thus shared by the transmitter and the legitimate receiver without additional signaling. In contrast, with an independent multipath channel, the eavesdropper at a separate location cannot derive an identical subcarrier allocation scheme. Consequently, mismatched demodulation is carried out at the eavesdropper so that disrupts the information recovery for eavesdropping. Moreover, due to the time-varying nature of wireless channels, the subcarrier allocation is frequently updated which further enhances the security. Theoretical analysis and simulation results are provided to evaluate the performance of the proposed secure OFDM system. It is validated that the proposed system is much more resilient to eavesdropping compared to the conventional OFDM system.
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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".