Age and Energy Analysis in Code-Based Status Update System over 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
Energy efficiency and information freshness are two fundamentally critical performance metrics in real-time status update systems which can be measured by energy cost (EC) and age of information (AoI), respectively. This paper examines the AoI and EC performance of the hybrid automatic repeat request with incremental redundancy (HARQ-IR) scheme in code-based status update systems and presents unified results that can generally depict the average AoI and EC over block fading channels. First, we propose a practical code-based status update system that fully takes into account the impact of information processing and long-distance transmission in performance analysis. Then, we analyze and derive the average AoI/EC expressions for HARQ-IR scheme, which are unified results over block fading channels. The simulations of different transmission protocols validate our explicit results and show that there is a distance threshold on whether to retransmit the failed updates. Based on the simulation results, it appears that system AoI/EC demand will affect distance threshold values, which provide guidance for future designs of age-energy tradeoff transmission schemes.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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