Low-Complexity Capacity Achieving Two-Stage Demodulation/Decoding for Random Matrix Channels
Bibliographic record
Abstract
Iterative processing for linear matrix channels, aka turbo equalization, turbo demodulation, or turbo CDMA, has traditionally been studied as the concatenation of conventional error control codes with the linear (matrix) channel. However, in several situations, such as CDMA, multiple-input multiple- output channels, OFDM, and intersymbol-interference channels, the channel itself either contains inherent signal redundancy or such redundancy can readily be introduced at the transmitter, for example, the direct-spread signature sequences of CDMA form inherent repetition codes. For such systems, iterative demodulation of the linear channel exploiting this redundancy using simple iterative cancellation demodulators, followed by conventional feed-forward error control decoding provides a low-complexity, but extremely efficient decoding alternative. It is shown that this two-stage demodulator/decoder, which outperforms more complex turbo CDMA methods for equal power modes (users), can support an arbitrary number of modes if an unequal power distribution is adopted, and that the capacity of the Gaussian multiple access channel can be approached to at least within less than one bit everywhere.
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How this classification was reachedexpand
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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".