Performance optimization of single frequency broadcast systems in FDD-CDMA cellular bands for wireless multimedia services
Bibliographic record
Abstract
We study performance optimization of single frequency broadcast systems (SFBSs) spectrally underlaid in an FDD-CDMA cellular network which operates in a high frequency band (HFB) for the forward link and a low frequency band (LFB) for the reverse link. Interference scenarios between the cellular network and the SFBSs in both HFB and LFB are identified, and an interference analysis is presented to evaluate the received bit-energy-to-noise ratio (E/sub b//N/sub o/). We also study a family of frequency allocation strategies for use by the SFBSs: (1) fixed channel allocation (FCA), (2) random channel allocation (RCA), and (3) distance based channel allocation (DBCA). The simulation results show that, in order to maximize the outage performance of the FDD-CDMA cellular network, and in the meantime to keep the outage performance of the SFBSs at an acceptable level, the DBCA with HFB as the inner tier and LFB as the outer tier should be adopted by the SFBSs given that D is properly adjusted. A good choice of D is to set D=0.76 at which acceptable outage performances of both FDD-CDMA cellular network and SFBSs can be achieved.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".