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Record W2340757643 · doi:10.1109/allerton.2015.7447185

Delay in cooperative communications: Higher multiplexing gain in Gaussian interference channels with full-duplex transmitters

2015· article· en· W2340757643 on OpenAlexaff
Ali Haghi, Neda Mohammadizadeh, Amir K. Khandani

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicWireless Communication Security Techniques
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsOrthogonal frequency-division multiplexingCyclic prefixComputer scienceTransmitterMultiplexingChannel (broadcasting)Interference (communication)Electronic engineeringTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

Delay, guaranteeing causality, is inevitable in cooperative communication systems. Traditionally, delay granularity has been limited to one symbol; however, channel delay is in fact governed by channel memory and can be shorter. For example, the delay requirement in orthogonal frequency-division multiplexing (OFDM), captured in the cyclic prefix, is typically much shorter than the OFDM symbol itself. This perspective is used to study the two-user Gaussian interference channel with full-duplex transmitters. By superimposing the signal from the other node on its own signal, each transmitter cancels the interference at its receiver. Among other results, it is shown that under a mild condition, the maximum multiplexing gain of this channel is in fact two, rather than the limit of one, previously proved under the traditional constraint of causal delay [1]. Further, the optimal power allocation among orthogonal sub-carriers, which maximizes the achievable sum-rate, is shown to be a generalization of the well-known water filling.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.360
Threshold uncertainty score0.735

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.055
GPT teacher head0.281
Teacher spread0.226 · 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
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

Citations1
Published2015
Admission routes1
Has abstractyes

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