Bibliographic record
Abstract
We consider the sequential transmission of a stream of messages over a block-fading multi-input-multi-output channel. A new message arrives at the beginning of each coherence block, and the decoder is required to output each message sequentially, after a delay of T coherence blocks. In the special case when T = 1, the setup reduces to the quasi-static fading channel. We establish the optimal diversity-multiplexing tradeoff (DMT) in the high signal-to-noise-ratio (SNR) regime, and show that it equals T times the DMT of the quasi-static channel. The converse is based on utilizing the delay constraint to amplify a local outage event associated with a message, globally across all the coherence blocks. This approach appears to be new. We propose two coding schemes that achieve the optimal DMT. The first scheme involves interleaving of messages, such that each message is transmitted across T consecutive coherence blocks. This scheme requires the knowledge of the delay constraint at both the encoder and decoder. Our second coding scheme involves a sequential tree code and is delay universal, i.e., the knowledge of the decoding delay is not required by the encoder. However, in this scheme, we require the coherence block length to increase as log (SNR), in order to attain the optimal DMT. Finally, we discuss the case when multiple messages arrive at uniform intervals within each coherence period. Through a simple example, we exhibit the suboptimality of interleaving and propose another scheme that achieves the optimal DMT.
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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 | 0.001 | 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 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".