Cross Layer AMC Scheduling for a Cooperative Wireless Communication System over Nakagami-m Fading Channels
Bibliographic record
Abstract
We study a single-source single-destination cooperative wireless communication system with multiple relays operating in a modified decode-and-forward mode. Nakagami-m fading with additive white Gaussian noise is assumed for all inter-node channels. The bursty data packet arrival is modeled by a Markov-modulated Poisson process (MMPP). A packet feedback model is proposed to characterize packet loss in the wireless channel. An approximation to the steady state distribution of the proposed generalized discrete time M/G/1-type queue at the source is obtained by state truncation. Packet level performance of four transmission modes adopting different modulation and coding schemes is analyzed under a variety of channel and traffic conditions using the truncated queueing analysis. The network power is used as a criterion to find boundary curves of adaptive modulation and coding (AMC) scheduling for the cooperative wireless system. Two source node transmission protocols, namely the transmit-every-clock-tick (TREC) and the LAZY protocols, are examined for both the AMC scheduling and channel utilization analysis.
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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 | 0.001 | 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".