On the Capacity of the Two-User IM/DD Interference Channel
Bibliographic record
Abstract
In Visible Light Communications (VLC) with multiple transmitters sending information to multiple receivers simultaneously, the optical signals interfere due to the diffused light. The result is an Intensity-Modulation/Direct-Detection (IM/DD) Interference Channel (IC), whose capacity has not been investigated. The challenge in studying the capacity of the IM/DD IC is due to its non-negative inputs with mean optical power constraints on the one hand, and interference on the other hand. In this paper the capacity of the IM/DD IC is studied. Capacity inner and outer bounds are derived and evaluated. The inner bounds are based on treating interference as noise (TIN) and the Han-Kobayashi (HK) scheme. The outer bound is based on a Z-channel bound. The bounds are shown to coincide asymptotically at high signal-to-noise ratio (SNR) in the strong interference regime, leading to the characterization of the strong interference capacity at high SNR. The bounds are also compared numerically in the weak interference regime.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".