Comparative evaluation of CDMA and FD-TDMA cellular system capacities with respect to radio link capacity
Bibliographic record
Abstract
This paper presents a comparative evaluation of code-division-multiple access (CDMA) and frequency-division time-division-multiple-access (FD-TDMA) system capacities as a function of the radio link capacity (i.e. Shannon bound). This bound is first evaluated over time-varying frequency-selective fading channels by treating this information theoretic value of the capacity as a random variable. The total system sum-of-rates capacity is then evaluated for both multiple-access schemes using a multi-cell simulator and the 99% reliability level of the radio link capacity. System capacity is compared as a function of the number of cells per cluster and the use of power control in the FD-TDMA system, the spreading gain in the CDMA system, the receiver space diversity level, the number of channel multipath components as well as large-scale propagation parameters such as the shadowing standard deviation and the path-loss exponent. According to this methodology, it is observed that CDMA system capacity can be but is not always superior to FD-TDMA capacity. The spectral efficiency advantage (in terms of capacity per unit bandwidth) of CDMA over FD-TDMA systems is however much larger for larger spreading gains.
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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 | 0.002 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".