Energy Efficient Quality of Service Traffic Scheduler for MIMO Downlink SVD Channels
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Bibliographic record
Abstract
In this paper we focus on minimizing the long-term average power consumption of a single transmitter providing Quality of Service (QoS) enabled traffic to a single receiver. Both the transmitting and receiving stations are equipped with multiple antennas. First, we present a general {Kx M} system model where K is the number of independently buffered QoS streams and M is the number of parallel channels available through MIMO SVD eigenmode transmission. Through application of the constrained Markov decision process (MDP) framework combined with a novel MAC layer rate assignment scheme, a randomized per-buffer scheduling policy is obtained. The designed policy exploits queue state information to schedule traffic while meeting throughput, delay and loss constraints. Packets scheduled for transmission during each frame are mapped across the set eigenmode channels subject to available channel resources and the set of channel eigenvalues. Simulation results are provided for several scenarios. System drawbacks, limitations and extensions are also discussed.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it