Frequency selection strategies for hybrid TDD/FDD-CDMA cellular networks
Bibliographic record
Abstract
Hybrid TDD/FDD-CDMA is an attractive technique for third generation cellular networks, in which FDD-CDMA is used to provide wide area voice and low bit-rate data services, and TDD-CDMA with limited coverage is used to provide high bit-rate asymmetric data services. In this paper, we propose two new frequency selection strategies to select the FDD-CDMA channel (forward link f/sub F/ or reverse link f/sub R/) for TDD-CDMA picocell operation in a FDD-CDMA macrocellular network. One is random selection strategy (RSS) which chooses f/sub F/ or f/sub R/ in a random fashion, and the other one is distance based selection strategy (DBSS) which applies a cell partitioning structure to divide each macrocell into an inner tier and an outer tier. With two separated carrier frequencies (f/sub F/ and f/sub R/), the inner tier of each macrocell can use one of these two frequencies, while the outer tier can use the other one. The outage performance of the hybrid TDD/FDD-CDMA network employing the above strategies is studied through computer simulations.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 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".