Delay limited optimal and suboptimal power and bit loading algorithms for OFDM systems over correlated fading channels
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper explores optimal and suboptimal power and bit loading algorithms for a multicarrier system. Specifically, we study the trade-offs between the total transmit power of an orthogonal frequency division multiplexing (OFDM) system and the buffering delay of the packets in a transmission buffer. The loading framework is formulated as a Markov decision process (MDP) and an optimal loading policy which minimizes the transmit power while meeting a target delay constraint is obtained via equivalent linear programming (LP) methodology. The complexity of finding the optimal loading policy and its' implementation issues are described. Since finding the optimal policies becomes complex and practically un-realizable for large number of carriers in the system, we offer a sub-optimal power and bit loading algorithm using the results of the single carrier system's power and rate adaptation policy and a greedy approach. Selected numerical examples show that the sub-optimal algorithm, which has reduced complexity, has performance close to the optimal one.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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