Layered interference alignment: Achieving the total DOF of MIMO X-channels
Bibliographic record
Abstract
The K × 2 multiple input multiple output (MIMO) X-channel with constant channel coefficients available at all transmitters and receivers is considered. A new alignment scheme, named layered interference alignment, is proposed in which both vector and real interference alignment techniques are exploited together with joint processing at receiver sides. Data streams, having fractional multiplexing gains, in the desired directions are sent by transmitters to align the interfering signals at receivers efficiently. To decode the intended messages at receivers, a new number theoretic joint processing technique which exploits the availability of several received antennas, is proposed. This processing is backed up by a recent result in the field of Simultaneous Diophantine Approximation, which is introduced in this paper for the firs time. It is shown that incorporating the layered interference alignment is essential to characterize the total DOF of 2 km/ k+1, in the k × 2 m-antenna X-channel.
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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 | 0.000 | 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".