ISI-Free Cochannel Interference Whitening for Bandlimited Fading Channels
Bibliographic record
Abstract
The problem of cochannel interference mitigation using interference-plus-noise whitening receiver design in the presence of intersymbol interference (ISI) is considered. The effect of ISI on the signal-to-interference-plus-noise ratio (SINR) of the interference whitening receiver is examined. Then, two methods are proposed to maximize the SINR without introducing ISI. In the first method, the transmitter and receiver filters are designed to maximize the SINR while their overall spectrum maintains a given Nyquist spectrum to avoid ISI. In the second method, the transmitter filter is assumed to be fixed and only the receiver filter is designed to achieve maximum SINR without introducing ISI. The SINR of the ISI-free SINR-maximizing filter is then analytically compared with that of the conventional matched filter receiver and the interference whitening receiver. Numerical results are presented for the cases when standard raised-cosine and Beaulieu-Tan-Damen pulses are used in the 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.004 | 0.002 |
| 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".