On the performance of polar codes for 5G eMBB control channel
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Bibliographic record
Abstract
Polar codes are a class of error-correcting codes which can provably achieve the capacity of a binary memoryless symmetric channel with low-complexity encoding and decoding algorithms. They have been selected for use in the next generation of wireless communications, as a coding scheme for the enhanced mobile broadband (eMBB) control channel, which requires codes with short lengths and low rates. Successive-cancellation (SC), SC list (SCL), and their modifications, are some of the most studied polar code decoding algorithms. In this paper, we study polar codes of short lengths and different code rates. We show that for a fixed target frame error rate (FER), there is an optimal code rate with which SC and SCL decoders can achieve it with maximum power efficiency. In addition, we study the effect of CRC on the error-correction performance of SCL decoders and show that there is an optimal CRC length with which the decoder achieves its best results. We further analyze the speed of polar code decoding by considering state-of-the-art fast SCL decoders available in literature, thus providing a survey of the decoder design space for eMBB, considering error-correction performance, achievable throughput, flexibility and estimated complexity.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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