Space Shift Keying-Enabled ISAC for Efficient Debris Detection and Communication in LEO Satellite Networks
Bibliographic record
Abstract
The proliferation of space debris in low Earth orbit (LEO) presents critical challenges for orbital safety, particularly for satellite constellations. Integrated sensing and communication (ISAC) systems provide a promising dual-function solution by enabling both environmental sensing and data communication. This study explores the use of space shift keying (SSK) modulation within ISAC frameworks, evaluating its performance when combined with sinusoidal and chirp radar waveforms. SSK is particularly attractive due to its low hardware complexity and robust communication performance. Our results demonstrate that both waveforms achieve comparable bit error rate (BER) performance under SSK, validating its effectiveness for ISAC applications. However, waveform selection significantly affects sensing capability: while the sinusoidal waveform supports simpler implementation, its high ambiguity limits range detection. In contrast, the chirp waveform enables range estimation and provides a modest improvement in velocity detection accuracy. These findings highlight the strength of SSK as a modulation scheme for ISAC and emphasize the importance of selecting appropriate waveforms to optimize sensing accuracy without compromising communication performance. This insight supports the design of efficient and scalable ISAC systems for space applications, particularly in the context of orbital debris monitoring.
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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 | 0.001 | 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 | 0.000 |
| 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".