Reducing the probability of detection, improving jamming resistance and security for broadband wireless systems
Bibliographic record
Abstract
Commercial radio systems, including the broadband wireless communications systems based on OFDM technology such as those of the IEEE standard 802.16, are designed from the outset to operate in protected spectrum channels with low interference and noise. This paper outlines some techniques whereby the commercial radio signal waveform may be modified to reduce its probability of detection, the communication is made more robust to jamming, and the signalling and control information is protected against eavesdropping. The techniques applied include reduction of the spectral signature through changes in the data and pilot signals and the symbol timing. The modulation of the data and pilot/guard sub-carriers is also modified to disguise the signal characteristics. Protection techniques are also applied to the signalling information flows used to administer the radio operations and to prevent the identity of terminals from being revealed to hostile receivers. There are advantages to developing radio systems based on commercially derived systems that are also suitable for communications use in hostile environments. The use of commercially based systems provides the opportunity to lower costs for the military and public safety users through the economies of manufacturing scale that are applied to the commercial systems and terminals. The use of systems with a commercial base also facilitates interworking between the military/public-safety radio systems and commercial devices and networks. The modifications to the commercial waveform discussed in this paper have the advantage that they may be added as functional blocks to the standard chip-sets for processing the commercial waveforms.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".