Optimum Power Distribution for Uplink Channel in a Cooperative Wireless CDMA Network
Bibliographic record
Abstract
This paper studies power distribution in the uplink channel of a wireless CDMA network, where peer stations cooperatively relay traffic for each other, and the destination, i.e., the base station (BS), combines signals received from both the source station (SS) and the relay station (RS). Two different cooperative schemes are presented. In the first scheme, the SS transmits packets in all time slots, and two RSs forward received signals from the SS to the BS in odd and even time slots alternatively. In the second scheme, the SS transmits in the odd time slots, and a single RS receives from the SS in the odd time slots and forwards to the BS in the even time slots. Two forwarding techniques, i.e., decode-and- forward (DF) and amplify-and-forward (AF), are considered. For each of the cooperation scheme and forwarding technique combinations, an optimization problem is formulated with an objective to minimize the total transmission power subject to the average transmission rate and signal-to-interference-plus- noise ratio (SINR) requirement of the user traffic. Our results show that by appropriately selecting the RSs and forwarding techniques, cooperative communications in a CDMA network can significantly reduce the communication outage probability and save total transmission power.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".