Exploiting the Fast Spectral Roll-Off of CPM Sidelobes to Improve Bandwidth Efficiency in Satellite Communications
Bibliographic record
Abstract
Simple and efficient carrier-overlapping and interference-reduction techniques are addressed for frequency-division multiplexing-continuous phase modulation (FDM-CPM) schemes. CPM carriers are densely multiplexed (packed) in the frequency-domain, without leaving any guard bands, thus allowing frequency content in adjacent bands to overlap, so as to enhance the bandwidth efficiency. The intentional adjacent channel interference, introduced by carrier-overlapping during transmission, is combated at the receiver front-end using simple interference-reduction filters that are designed to exploit the fast roll-off of CPM spectral sidelobes. The receiver back-end is governed by a serially concatenated CPM iterative demodulation/decoding detector. Numerically optimal carrier-packing ratios are determined with respect to information-theoretic bounds. The presented method does not require cooperation among users, and is extended to QAM and PSK schemes as well. Bit error rate analyses show that the proposed non-cooperative receiver design facilitates bandwidth and energy-efficient communication for both the nonlinear and linear satellite channels, without resorting to multiuser detectors, and becomes an attractive solution when cooperation may not be feasible among users that are geographically spread-out.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".