Broadcasting correlated Gaussian sources with bandwidth expansion
Bibliographic record
Abstract
We study hybrid digital-analog (HDA) joint source-channel coding schemes for the transmission of a bivariate Gaussian source S = (S <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> , S <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> ) across a power-limited two-user Gaussian broadcast channel. User i (i = 1, 2) observes the transmitted signal corrupted by Gaussian noise with power ¿ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> and wants to estimate the ith component of the source, S <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</sub> . We consider HDA coding schemes with bandwidth expansion and analyze the region of (squared-error) distortion pairs that are simultaneously achievable. We first adapt an HDA scheme proposed by Reznic, Feder and Zamir in for broadcasting a single common source and use it to provide an achievable distortion region for broadcasting correlated sources. We also consider a three-layered coding scheme, which we refer to by the HWZ scheme, and which consists of an analog layer and two layers each consisting of a Wyner-Ziv coder followed by a channel coder. We also examine numerical examples which indicate that the HWZ scheme performs similarly to the adapted Reznic-Feder-Zamir scheme. For comparison, we adapt the outer bound for the set of all achievable distortion pairs in broadcasting correlated Gaussian sources with matched source-channel bandwidth to the bandwidth expansion case.
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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".