ZC-OFDM-Aided Waveform Design for LEO Satellite Integrated Communication and Navigation
Bibliographic record
Abstract
In this letter, a novel Zadoff-Chu-orthogonal frequency division multiplexing (ZC-OFDM) waveform is designed for integrated communication and navigation (ICAN) in low Earth orbit (LEO) satellite systems. Firstly, the differential generalized ZC (DGZC) sequence is derived from the generalized ZC (GZC) sequence through differentially coherent processing to mitigate Doppler-induced ranging errors. Then, the DGZC sequence is integrated into ZC-OFDM to enable ICAN. Finally, an adaptive genetic algorithm (GA) is proposed for pilot assignment to obtain performance optimization with low complexity. Simulation results show that the proposed DGZC-OFDM system is capable of providing substantial performance gain over conventional ZC-OFDM counterpart in the terms of ranging accuracy and bit error ratio (BER).
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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 | 0.000 |
| 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) | 0.001 | 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".