Analysis of two-layered adaptive transmission systems
Bibliographic record
Abstract
A major challenge for personal communication systems is to meet the growing demand for various services when the frequency resources are increasingly scarce. Given the time varying nature of the radio channel, an efficient resource utilization calls for channel-adaptive transmission schemes. This paper integrates the two concepts of channels with side information and broadcast channels and introduces a model for flat Rayleigh fading channels with perfect interleaving and a single bit channel state information at the receiver. A true-level modulation constellation is deployed to send information to a two-state channel, where the state of the channel is determined by monitoring the received signal to noise ratio. The limited adaptability of the system helps gear up to a higher data rate as channel conditions improve, without any adjustment at the transmitter. A two-stage receiver, driven by the channel state estimation device, demodulates at full rate only if the channel signal to noise ratio is above a pre-set threshold. The average mutual information of the model as well as the bit probability expressions are derived for a non-uniform 8 PSK signal set. It is shown that the achievable rate is higher than that obtained using a uniform QPSK with only a negligible loss in error rate.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.005 | 0.001 |
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".