Optimal Power Allocation for Pilot Channel Assisted Multi-User CDMA
Bibliographic record
Abstract
This paper examines the performance of a conventional direct sequence-code division multiple access (DS-CDMA) receiver, a two-stage multi-user receiver that does not employ channel fading estimation in the interference cancellation process and a two-stage multi-user receiver that uses the channel fading estimation when cancelling the multiple access interference. The optimal power allocation to the pilot and data channels is also determined for different numbers of users, processing gains and signal-to-noise ratios by finding out the power ratio of the data bit to the pilot bit that minimizes the probability of error. It has been observed that the optimal power allocation to the pilot signal varies from 20 to 30% of the total power depending on the number of users, processing gain and signal-to-noise ratio. Increasing the power allocated to the pilot requires a corresponding decrease in power to the data channel. The bit error rate degradation caused by allocating more power to the pilot outweighs the benefits obtained by more accurate channel estimates when we attempt to allocate more than 30% of the power to the pilot stream. Simulations have also shown the two-stage multi-user receiver that employs the channel estimates for interference cancellation consistently outperforms the other two receivers.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".