Stratified diagonal layered space-time architectures: signal processing and information theoretic aspects
Bibliographic record
Abstract
We consider a multielement antenna system that uses M transmit and N receive antennas [an (M,N) wireless link] impaired by additive white Gaussian noise in a quasistatic flat-fading channel environment. The transmitter, which is subject to a power constraint, does not know the random outcome of the matrix channel but does know the channel statistics. The link operates under a probability of outage constraint. We present a novel architecture using stratified space-time diagonals to express a message for efficient communications. The special message arrangement, which is termed stratified-diagonal-BLAST (SD-BLAST), enables receiver signal processing that substantially mutes self interference caused by multipath without incurring waste of space-time. We investigate the proposed communication structure in important downlink categories, showing that, in theory, the message architecture is optimally efficient for all (M, 1) systems and extremely efficient when M/spl Gt/N. We quantify the capacity performance of SD-BLAST using empirically generated complementary cumulative distribution functions (CCDFs) for (16, 5), (8, 3), and (4, 2) systems to exhibit near optimal performance most especially for the (16, 5) system.
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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) | 0.000 | 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 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".