Traffic prediction based access control in wireless CDMA networks supporting integrated services
Bibliographic record
Abstract
In this paper an access control protocol is proposed and analyzed for an integrated video/voice/data DS-CDMA (direct-sequence code division multiple access) system. The protocol involves predicting the residual capacity available to non real-time data services in the reverse link (mobile to cell-site). Each real-time voice or video call is assumed to handle bursty traffic by utilizing one or more DS-CDMA channels, in parallel, as provisioned in IS-95-B and cdma2000 standards. The arrival of new calls well as the variations in the aggregate bit-rate of the existing real-time calls, and hence the number of occupied channels with respect to time, are modeled as a two-dimensional imbedded DTMC (discrete time Markov chain) process. The state of the Markov process is predicted to compute the residual capacity or the number of data packets that could be scheduled in the next time slot. Simulation results obtained, using synthetic data, are presented to demonstrate the viability of the approach. The main contribution of the paper is that it presents a simple yet effective application of the two-dimensional imbedded Markov chain model in the access control of integrated services in the reverse link of a CDMA cell.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".