Source-Channel Coding for Fading Channels With Correlated Interference
Bibliographic record
Abstract
We consider the problem of sending a Gaussian source over a fading channel with Gaussian interference known to the transmitter. We study joint source-channel coding schemes for the case of unequal bandwidth between the source and the channel and when the source and the interference are correlated. An outer bound on the system's distortion is first derived by assuming additional information at the decoder side. We then propose layered coding schemes based on proper combination of power splitting, bandwidth splitting, Wyner-Ziv and hybrid coding. More precisely, a hybrid layer, that uses the source and the interference, is concatenated (superimposed) with a purely digital layer to achieve bandwidth expansion (reduction). The achievable (square error) distortion region of these schemes under matched and mismatched noise levels is then analyzed. Numerical results show that the proposed schemes perform close to the best derived bound and to be resilient to channel noise mismatch. As an application of the proposed schemes, we derive both inner and outer bounds on the source-channel-state distortion region for the fading channel with correlated interference; the receiver, in this case, aims to jointly estimate both the source signal as well as the channel-state (interference).
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".