Energy Efficiency in Multipath Rayleigh Faded Wireless Sensor Networks Using Collaborative Communication
Bibliographic record
Abstract
Deployed in harsh or hostile environments, it is usually impossible to replace/recharge the power source of a sensor node in a wireless sensor network. Therefore, the only solution is an energy efficient communication system. This paper presents an energy efficient system based on multipath collaborative communication having noise and fading. The collaborative communication exploits spatial diversity to achieve high gain in received power, low bit error rate <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">(BER)</i> , and high energy savings even if the received signals are out-of-phase. The experimental results confirm that the benefits are further enhanced by the use of the multipath environment in combination with collaborative communication. For the trade-off analysis between energy consumption and transmission distances, the multipath collaborative communication is compared with the single-input-single-output ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SISO</i> ) system. Collaborative communication performs better over the long distance; however, the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SISO</i> is suitable for short distances. The proposed collaborative communication system can achieve 99% energy savings in comparison to the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SISO</i> system.
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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 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| 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".