Queue-Aware Power Allocation for Space-Time Block Coded MIMO Systems
Bibliographic record
Abstract
A queue-aware power allocation scheme for multiple-output multiple-input (MIMO) system using space time block coding (STBC) is presented. In the the physical layer, along with space-time block coded MIMO, the authors consider adaptive modulation to enhance transmission rate and error performance. To improve data reliability, automatic request (ARQ) is used for retransmission of erroneous packets from the radio link level queue. The proposed power allocation scheme is designed to minimize the cost which is defined as a function of transmit power and packet dropping probability at the radio link level queue. The genetic algorithm is used to obtain the solutions for the optimal parameters of the queue-aware power allocation scheme to minimize radio resource usage while meeting the quality-of-service (QoS) requirements for data traffic. A queueing analytical model is presented to investigate the link level performances (e.g., average queue length, packet dropping probability, throughput, and average delay) under different physical layer parameter setting.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".