Effects of Interference and Mitigation Using Notch Filter for the DVB-S2 Standard
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Bibliographic record
Abstract
The abundance of radio signals and their increasing number creates interferences on adjacent signals and sometimes, with co-channel communication. Jammers, which are operated by hackers or by military forces, are another source of smart and powerful interferences. This paper will discuss the effect of the continuous wave interference (CWI) on a radio communication receiver, specifically with the Digital Video Broadcasting for Satellite Second Generation (DVB-S2) communication standard. It investigates the general effect of the interference on a Quadrature Phase Shift Keying (QPSK) signal over each part of the DVB-S2 receiver. It also focuses on the impact of the center frequency and power of the interference on the critical blocks of a DVB-S2 receiver. This study also tries to determine the deviation from the normal operation in the format of mathematical expressions and simulation results. Based on the obtained results, there is a vulnerability in the chain of the receiver’s blocks that allows a smart jammer to affect the device with low power interference. The notch filter is utilized as a solution to mitigate the interference. In addition, the effects of this technique on the system’s performance are studied. The simulation results show that there is a great improvement after CWI removal according to the Jamming to Signal Ratio (JSR), the Signal-to-Noise Ratio (SNR), and the Bit Error Rate (BER). In some cases, the JSR was reduced by 15 dB, the SNR was improved by 10 dB and BER also improved by 7 dB. However, the notch filter deletes some information from the original signal. This study introduces new ways to clarify the tradeoff between the amount of interference power reduction and removed bandwidth from the signal with notch filtering.
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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 | 0.000 | 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 it