Multi-hop CDMA cellular networks with power control
Bibliographic record
Abstract
The concept of multi-hop CDMA cellular networks has been around for sometime now. It is a widely accepted assumption that using multi-hopping in cellular networks will increase the cellular capacity. This capacity increase has yet to be quantified. In this paper, this quantification is done, for the first time, for multi-hop CDMA cellular networks with power control. CDMA networks are interference limited. For this reason, interference is calculated at BSs and relaying MTs during an uplink slot, assuming power control is in use in all hops. The results for interference calculations show the possible increase in capacity, by increasing either the number of simultaneous calls or data rates. An increase of 23% in the number of supported simultaneous calls is shown to be possible even with relaying MTs being different than active MTs sending their own data. This paper derives formulas to calculate interference at BSs and MTs using power control in all hops. It also quantifies the potential capacity increase using multi-hopping with power control.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".