An investigation of wireless personal communication systems: microcell co-channel interference modelling and outage probability analysis
Bibliographic record
Abstract
Cochannel interference in microcell radio systems is investigated. Two microcell cochannel interference models, at Rician/Rayleigh model and a Rician/Rayleigh-plus-log normal model, are presented. In the first model, the desired signal within a microcell experiences Rician fading while interfering signals from cochannel cells are subject to Rayleigh fading. In the second model, the cochannel interfering signals are subject to superimposed Rayleigh fading and log normal shadowing. Frequency selective multipath fading is considered in both models. The probability density function of the power ratio between the desired signal and composite interferers is derived. In evaluating the composite interference, both coherent and noncoherent interference addition are considered. Using the probability density function of the signal-to-interference ratio, expressions of the system outage probability are derived. Microcell systems are compared with medium/large cell systems in terms of the outage probability. It is shown that the former outperforms the latter. The effect of frequency selective multipath fading and that of shadowing on the outage probability are also observed.>
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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) | 0.001 | 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 | 0.001 | 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".