WLC04-1: A Distributed BER-Based Power Control Algorithm for WCDMA Systems
Bibliographic record
Abstract
Taking into consideration the dominance of the multiple access interference (MAI) in spread spectrum based CDMA systems, power control plays a vital role in reducing the system interference and helps in increasing the capacity of the system while maintaining the quality of the received signal. Closed loop power control is mainly used to mitigate the near-far effect in the uplink direction. In this paper, we propose a bit error rate (BER)-based first order distributed power control algorithm. Being distributed, the proposed algorithm has the flexibility of using the benefits of fast closed loop power control and thus can be used to update the transmit power of a single user at a time. Signal-to-interference ratio (SIR) based algorithms are in extensive use. But considering that the SIR is time variant, the BER would be a better quality of service (QoS) parameter because it can be easily measured using already known pilot bits. We analyze the convergence performance of the proposed algorithm and show that its convergence is always guaranteed. We demonstrate that a considerable improvement in the convergence speed along with the required average signal-to-noise ratio (SNR) is achieved as compared with other BER-based algorithms under comparison. We also show that the proposed algorithm performs well at different mobile speeds.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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".