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Record W2000029133 · doi:10.1109/icassp.2013.6638578

A balanced precoding scheme for the two-user SISO X channel with optimal DoF and a small power offset

2013· article· en· W2000029133 on OpenAlexaff
Ahmed Medra, Timothy N. Davidson

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced MIMO Systems Optimization
Canadian institutionsMcMaster University
Fundersnot available
KeywordsInterference alignmentPrecodingOffset (computer science)Control theory (sociology)Zero-forcing precodingComputer scienceChannel (broadcasting)AlgorithmTopology (electrical circuits)MathematicsTelecommunicationsMIMOCombinatorics

Abstract

fetched live from OpenAlex

In this paper we propose a structured low-latency interference alignment scheme for the two-user single-input single-output (SISO) time-invariant X channel. The scheme is based on asymmetric (non-circular) complex signals generated by linear precoders and linear zero-forcing receivers. In addition to achieving the optimal (sum) degrees of freedom (DoF) of 4/3, the precoders are balanced in the sense that for pairs of symbols the signal-to-noise ratio at the input to the decoder is the same. Furthermore, the sum rate is shown to have a small power offset-in one simple scenario that offset is at least 6 dB smaller than the offset of an existing scheme. The principles that underlie this scheme are extended to a time-varying channel with delayed feedback in which either asymmetric symmetric signalling is used.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.813
Threshold uncertainty score0.354

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 science0.0000.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.202
Teacher spread0.193 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

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

Citations1
Published2013
Admission routes1
Has abstractyes

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