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Record W2506403468 · doi:10.1002/wcm.2711

Cooperative amplify‐and‐forward partial relay selection with outdated channel information in spectrum‐sharing systems

2016· article· en· W2506403468 on OpenAlexaff
Jules Merlin Moualeu, Walaa Hamouda, Fambirai Takawira

Bibliographic record

VenueWireless Communications and Mobile Computing · 2016
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsConcordia University
Fundersnot available
KeywordsComputer scienceRayleigh fadingChannel state informationRelayChannel (broadcasting)Transmitter power outputCognitive radioInterference (communication)TransmitterSpectral efficiencyTelecommunicationsRelay channelBit error rateSignal-to-noise ratio (imaging)FadingComputer networkPower (physics)WirelessPhysics

Abstract

fetched live from OpenAlex

Abstract Recently, cooperative relaying techniques have been integrated into spectrum‐sharing systems in an effort to yield higher spectral efficiency. Many investigations on such systems have assumed that the channel state information between the secondary transmitter and primary receiver used to calculate the maximum allowable transmit secondary user transmit power to limit the interference is known to be perfect. However, because of feedback delay from the primary receiver or the time‐varying properties of the channel, the channel information may be outdated, which is an important scenario to cognitive radio systems. In this paper, we investigate the impact of outdated channel state information for relay selection on the performance of partial relay selection with amplify and forward in underlay spectrum‐sharing systems. We begin by deriving a closed‐form expression for the outage probability of the secondary network in a Rayleigh fading channel along with peak received interference power constraint and maximum allowable secondary user transmit power. We also provide a closed‐form expression for the average bit‐error rate of the underlying system. Moreover, we present asymptotic expressions for both the outage probability and average bit‐error rate in the high signal‐to‐noise ratio regime that reveal practical insights on the achievable diversity gain. Finally, we confirm our results through comparisons with computer simulations. Copyright © 2016 John Wiley & Sons, Ltd.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.961
Threshold uncertainty score0.545

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.022
GPT teacher head0.260
Teacher spread0.238 · 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
Published2016
Admission routes1
Has abstractyes

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