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Record W2035512140 · doi:10.1109/ita.2009.5044978

Gaussian Z-interference channel with a relay link: Type II channel and sum capacity bound

2009· article· en· W2035512140 on OpenAlexaff
Wei Yu, Lei Zhou

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWireless Communication Security Techniques
Canadian institutionsUniversity of Toronto
FundersLG Electronics
KeywordsInterference (communication)Relay channelRelayChannel (broadcasting)Co-channel interferenceTopology (electrical circuits)Upper and lower boundsChannel capacityZero-forcing precodingAdjacent-channel interferenceSignal-to-noise ratio (imaging)Noise (video)TelecommunicationsComputer sciencePhysicsMathematicsMIMOPrecodingCombinatoricsMathematical analysisPower (physics)

Abstract

fetched live from OpenAlex

This paper studies the Gaussian Z-interference channel with a rate-limited digital relay link from one receiver to the other receiver. In a companion paper, we dealt with the Type I channel, where the relay link goes from the interference-free receiver to the interfered receiver. It was shown that in the weak interference regime, each relay bit can improve the sum capacity by up to one bit asymptotically in the high signal-to-noise-ratio and interference-to-noise-ratio limit. In this paper, we study the Type II channel where the relay link goes from the interfered receiver to the interference-free receiver. The capacity region for such a channel is established in the strong interference regime; achievable rate regions are established in the moderately strong and weak interference regimes. In the weak interference regime, we show that in contrast to the Type I channel, the sum capacity improvement due to relaying for the Type II channel is upper bounded by at most half a bit, even as the relay link rate goes to infinity.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.003
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.022
GPT teacher head0.231
Teacher spread0.209 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations8
Published2009
Admission routes1
Has abstractyes

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