Outage analysis and relay allocation for multi-stream OFDMA decode-and-forward Rayleigh fading networks
Bibliographic record
Abstract
In this paper, we study a clustered two-hop decode-and-forward (DF) network consisting of a set of source-destination pairs, and a cluster of relays. We consider the case where channels are Rayleigh frequency selective, orthogonal frequency division multiple access (OFDMA) is employed, and there is no line of sight (LOS) between source and destination clusters. Approximating the capacity of a single source-relay-destination link by a Gaussian random variable (RV), the global outage probability of this network is characterized allowing for correlated OFDM subcarrier gains and arbitrary number of bits on each subcarrier. The obtained global probability of outage is used as an objective function to formulate an optimization problem to allocate relays to source-destination pairs. The outage probability minimization problem through relay allocation then is converted to a standard assignment problem, for which a low complexity algorithm based on Hungarian method is proposed. The numerical results show the precision and effectiveness of our analysis and proposed relay allocation technique.
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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 | 0.005 |
| 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".