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Record W1916447172 · doi:10.48550/arxiv.1001.3403

Real Interference Alignment

2010· preprint· en· W1916447172 on OpenAlexaff
Seyed Abolfazl Motahari, Shahab Oveis Gharan, Mohammad Ali Maddah-Ali, Amir K. Khandani

Bibliographic record

VenuearXiv (Cornell University) · 2010
Typepreprint
Languageen
FieldEngineering
TopicWireless Communication Security Techniques
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsInterference alignmentDirty paper codingCoding (social sciences)Interference (communication)Computer scienceTopology (electrical circuits)GaussianMultiplexingDegenerate energy levelsData stream miningAlgorithmMathematicsChannel (broadcasting)TelecommunicationsPrecodingPhysicsCombinatoricsMIMO

Abstract

fetched live from OpenAlex

In this paper, we show that the total Degrees-Of-Freedoms (DOF) of the $K$-user Gaussian Interference Channel (GIC) can be achieved by incorporating a new alignment technique known as \emph{real interference alignment}. This technique compared to its ancestor \emph{vector interference alignment} performs on a single real line and exploits the properties of real numbers to provide optimal signaling. The real interference alignment relies on a new coding scheme in which several data streams having fractional multiplexing gains are sent by transmitters and interfering streams are aligned at receivers. The coding scheme is backed up by a recent result in the field of Diophantine approximation, which states that the convergence part of the Khintchine-Groshev theorem holds for points on non-degenerate manifolds.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.502
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.057
GPT teacher head0.194
Teacher spread0.137 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2010
Admission routes1
Has abstractyes

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