Integrated Sensing and Communication Channel Modeling and Measurements: <i>Requirements and Methodologies Toward 6G Standardization</i>
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Bibliographic record
Abstract
Integrated sensing and communication (ISAC) has been defined as one of the major usage scenarios for 6G. When sensing and communication channels coexist in ISAC scenarios, neither conventional communication nor sensing channel models are applicable. As the foundation of ISAC studies, a new channel modeling methodology is required to characterize both sensing and communication channels and their correlations. This article introduces the framework of a general ISAC channel model, which integrates a deterministic multiscattering-center (MSC) model of sensing targets to the stochastic propagation channel model. Parameterizations of the proposed channel model rely on channel measurements. This article introduces two ISAC channel measurement methodologies based on the vector network analyzer (VNA) and a novel dual-sensor measurement system. The proposed methods can be applied in future 6G ISAC channel model standardization and system evaluations.
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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 it