Information-Energy Capacity Region for SLIPT Systems Over Lognormal-Fading Channels
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this paper, we study the fundamental limits of simultaneous lightwave information and power transfer (SLIPT) systems over channels with path loss and lognormal fading conditions. We consider a system with a single transmitter transferring information to a photodiode-based receiver as well as transferring energy to a photovoltaic cell receiver. In particular, we study the information-energy capacity region and the optimal input distribution under (a) peak-power and average-power constraints at the transmitter, and (b) the minimum harvest energy at the energy harvesting receiver. To this end, an expression for the transition probability distribution function of the lognormal channel is derived. By extending Smith's framework and using Hermite polynomial bases, we prove that the optimal input distribution is discrete with a finite number of mass points. Information-energy capacity region for SLIPT over lognormal channel conditions is illustrated and compared with the case of additive white Gaussian noise channel.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.009 |
| 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