QoS-oriented packet scheduling for wireless multimedia CDMA communications
Bibliographic record
Abstract
In the third-generation (and beyond) wireless communication systems, there will be a mixture of different traffic classes, each having its own transmission rate characteristics and quality-of-service (QoS) requirements. In this paper, a QoS-oriented medium access control (MAC) protocol with fair packet loss sharing (FPLS) scheduling is proposed for wireless code-division multiple access (CDMA) communications. The QoS parameters under consideration are the transmission bit error rate (BER), packet loss, and delay requirements. The MAC protocol exploits both time-division and code-division statistical multiplexing. The BER requirements are guaranteed by properly arranging simultaneous packet transmissions and controlling there transmit power levels, whereas the packet loss and delay requirements are guaranteed by proper packet scheduling. The basic idea of FPLS is to schedule the transmission of multimedia packets in such a way that all the users have a fair share of packet loss according to their QoS requirements, which maximizes the number of the served users under the QoS constraints. Simulation results demonstrate effectiveness of the FPLS scheduler, in comparison with other previously proposed scheduling algorithms.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".