Capacity analysis of an integrated voice/data DS-CDMA network
Bibliographic record
Abstract
This paper proposes a packetized direct sequence code division multiple access (DS-CDMA) system model that supports integrated voice and data traffic in a slowly Rayleigh fading environment and allows for seamless interfacing to an asynchronous transfer mode (ATM) broadband network. Forward error correction (FEC) coding and an automatic retransmission request (ARQ) protocol are applied to data packets. A queueing model is used for servicing data transmission requests. The reverse link power control utilizes a closed loop algorithm with channel estimation. A one-bit power control command is used for delay insensitive data packets and a two-bit command for delay sensitive voice packets. The cell capacity for data users is analyzed and is extended to include voice users by assigning a fixed number of DS-CDMA channels for data traffic and using all the remaining resources for voice traffic. It is shown that there is a linear relation between the capacity for data users and that for voice users.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".