Achievable sum-rate of the two-user Gaussian interference channel through rate-splitting and successive decoding
Bibliographic record
Abstract
Most coding schemes, proposed for the interference channel, take advantage of joint decoding to achieve a larger rate region. However, joint decoding significantly increases decoding complexity. This paper investigates the achievable sum-rate of the two-user Gaussian interference channel when successive decoding is employed instead of joint decoding. First, this study proves that when interference is strong and the powers of the transmitters satisfy certain conditions, the sum-capacity can be achieved by successive decoding. The number of the required splits, the amount of power allocated to each split, and the order of decoding at receivers are explicitly determined. Moreover, the maximum sum-rate loss when simultaneous non-unique decoding is replaced by successive decoding is characterized. Second, it is proved that successive decoding achieves the sum-rate of simultaneous non-unique decoding, when interference is weak and the powers of the transmitters satisfy certain conditions. Rate-splitting is shown to be beneficial, if the powers of the transmitters are greater than a threshold. However, when the powers are below the threshold, still single-split successive decoding can achieve the sum-capacity.
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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".