Design of Energy Efficient Hybrid VLC/RF/PLC Communication System for Indoor Networks
Bibliographic record
Abstract
Integrating visible light communication (VLC) system with indoor radio frequency (RF) network is seen as a possible way of increasing the capacity and coverage of indoor networks. In such a hybrid network, the traffic generated at the indoor RF and VLC access points must be backhauled to the core network. Power line communication (PLC) technology is seen as a cost-effective backhaul (BH) solution due to its infrastructure availability in every home. In this letter, a novel system model that captures the joint effect of power and BH flow optimization for hybrid VLC/RF/PLC indoor communication network is proposed. For the proposed system model, the problem of energy efficiency (EE) maximization via power and BH flow optimization is formulated as a non-convex problem, and then transformed into a convex problem via the Dinkelbach's approach. An energy efficient algorithm is proposed to solve this joint problem with guaranteed optimality. Simulation results are used to verify the superiority of the proposed hybrid VLC/RF/PLC system and algorithm over a conventional indoor RF system and equal power allocation benchmark scheme, respectively, in terms of network throughput, power consumption, and EE.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".