Adaptive Discrete-Rate MIMO Communications with Rate-Compatible LDPC Codes
Bibliographic record
Abstract
By using rate-compatible (RC) low density parity-check (LDPC) codes with adaptive modulation, we propose an adaptive, discrete-rate multiple-input multiple-output (MIMO) communications system. Given the high spectral efficiency of MIMO and the flexibility of an incremental redundancy (IR) protocol, combined with adaptive coding and modulation (ACM), the designed communications system is capable of achieving high data rates, for a low amount of overhead. A novel ACM power- and bit-allocation protocol is proposed to implement this system. We adapt the existing water-filling algorithm (WFA) to the discrete and finite bit rate constraints inherent in any communications system. This constrained WFA is shown to significantly improve the throughput performance of the communications system, over the case where a regular WFA is used. The results given in this paper show that the combination of IR and ACM with MIMO creates a wireless communications system that can easily adapt to channel fluctuations and provide high-data rates.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".