Modeling and delay analysis of wireless HANs in smart grids over fading channels subjected to multiple access schemes and interference
Bibliographic record
Abstract
Smart grids are comprised of several interconnected layers of networks. A set of Electrical Devices (EDs) in the lowest layer, the Home Area Network (HAN), communicates with the Mesh Client (MC). The HAN, in this paper, is modelled as a wireless network using Frequency Division Multiple Access (FDMA) and Time Division Multiple Access (TDMA) to facilitate communication between the EDs and their respective MCs. For these models, channel capacities over the Rayleigh and Nakagami fading channels are determined and delay analysis is presented. Upper and lower bound expressions for achievable delay, in closed-form, are derived as a function of Signal-to-Interference-plus-Noise Ratio (SINR), received power, number of EDs, number of channels, and Inter-channel Interference Range (ICR). Numerical simulations have been used to validate the analytical results. It is shown that transmission of packets using TDMA results in a shorter delay than by using FDMA.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 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".