Effect of Intercell Interference on the SNIR of a Multihop Cellular Network
Bibliographic record
Abstract
In a multihop cellular network, the physical layer of mobile terminals is modified so that in addition to being able to transmit to base stations, mobile terminals are able to transmit directly to other mobile terminals. This allows mobile terminals to lower their maximum transmission power and use other terminals as repeaters to forward their packets to the base station. Multihop cellular networks may have a higher capacity than traditional cellular networks due to their potential of lower intercell interference. Intercell interference may be lower because the maximum transmission power of terminals is decreased. The effects of intercell interference in a multihop cellular network is investigated in this paper. Previous simulation results of a one-cell system show that the SNIR of a multihop cellular network is slightly lower than that of a traditional cellular network. However, our simulations of a network with many cells show that the overall SNIR of a multihop cellular network is in fact higher than in a traditional cellular network because of lower intercell interference. Previous simulation results of a one-cell system show that the total energy consumption of a multihop cellular network is lower than that of a traditional cellular network. Our simulations of a multihop cellular network show that the savings in energy consumption are even greater when a network with many cells is considered.
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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 | 0.001 | 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 | 0.001 | 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".