Delay–Doppler Block Division Multiplexing: An Integrated Navigation and Communication Waveform for LEO PNT
Bibliographic record
Abstract
The recent rapid deployment of low-Earth-orbit (LEO) broadband constellations has positioned these systems as expected emerging navigation sources, thereby driving research interest in integrated navigation and communication (INAC) technologies. Existing INAC waveforms face various challenges in LEO environments, including limited ranging accuracy due to high mutual interference (MI) between signal components, a heavy signal processing burden for navigation users, or degraded data transmission reliability. We propose an INAC waveform named delay–Doppler block division multiplexing (DDBDM) in this work. MI is effectively reduced by modulating pseudo-random noise (PRN) codes and data separately on orthogonal delay–Doppler (DD) blocks. Navigation and communication signals in DDBDM can be separated in the frequency band, which allows the user to receive only the bandwidth occupied by the navigation subcarriers, reducing the signal processing overhead. Moreover, data transmission in the DD domain exhibits a low bit error rate in high-mobility channels, which enables fast and reliable navigation augmentation information for users. Simulation results demonstrate that DDBDM offers superior navigation performance and data transmission reliability compared to existing INAC schemes. The proposed waveform enhances the performance of the LEO INAC system and effectively extends the position, navigation, and timing (PNT) service capability.
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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 | 0.000 |
| 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 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".