Linear/Non-Linear Energy Harvesting Models via Multi-Antenna Relay Cooperation in V2V Communications
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
Vehicle-to-vehicle (V2V) communications is a part of next-generation wireless networks to create smart cities with the connectivity of intelligent transportation systems. Besides, green communications is considered in V2V communication systems for energy sustainability and carbon neutrality. In this scope, radio-frequency (RF) energy harvesting (EH) provides a battery-free energy source as a solution for the future of V2V communications. Herein, the employment of RF-EH in V2V communications is considered where the bit error probability (BEP) of a dual-hop decode-and-forward relaying system is obtained depending on the utilization of antennas at the relay. The multiple antenna power-constraint relay harvests its power by applying dedicated antenna (DA)/power splitting (PS) EH modes and linear (L)/nonlinear (NL) EH models. Moreover, the links between nodes are exposed to double-Rayleigh fading. Finally, the performance of different system parameters is compared using theoretical derivations of BEP. The results provide a comprehensive analysis of the proposed system considering PS/DA-EH modes and L/NL-EH models, as well as deterministic/uniformly distributed placement of nodes. It is observed that PS-EH outperforms DA-EH assuming a placement of an equal number of antennas and distances. Moreover, optimal performance of PS/DA-EH is achieved by allocating more power and increasing the number of antennas for EH, respectively.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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 it