BER analysis of BPSK signaling in Ricean-faded cochannel interference
Bibliographic record
Abstract
The bit error rate of a binary phase shift keying signal in Ricean-faded cochannel interference is studied. A precise bit error rate expression based on a characteristic function method is derived for a bandlimited binary phase shift keying signal corrupted by an arbitrary number of asynchronous Ricean-faded interfering signals. For the special case when there is one synchronous Ricean-faded interfering signal, a Chernoff bound analysis is performed and it predicts that the error floor of the desired user signal decreases with an increase of the Rice factor in the interfering user's fading channel. However, our precise bit error rate analysis results reveal that the opposite phenomenon can also happen, in particular when the signal-to-interference power ratio is low. A saddle-point approximation based error rate analysis is also provided. It is shown that this approximation is highly accurate. An asymptotic analysis based on the saddle-point approximation further reveals that a minimum signal-to-interference power ratio is required to have the desired user's error rate performance improved by a less-faded interfering signal.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".