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Record W2139868601 · doi:10.1109/pacrim.2011.6032967

Performance analysis of relay-assisted mobile-to-mobile communication in double or cascaded Rayleigh fading

2011· article· en· W2139868601 on OpenAlexaff
Indrakshi Dey, R. Nagraj, Geoffrey G. Messier, Sebastian Magierowski

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsNon-line-of-sight propagationRayleigh fadingRayleigh scatteringRelayComputer scienceMobile stationChannel (broadcasting)Mobile radioElectronic engineeringAntenna (radio)FadingComputer networkTelecommunicationsWirelessBase stationEngineeringPhysicsOptics

Abstract

fetched live from OpenAlex

We consider a mobile-to-mobile (M2M) communication scenario in a crowded city or suburban area, where each mobile terminal is surrounded by a group of scatterers. The non-line of sight (NLOS) communication channel is modelled as non-frequency selective double or cascaded Rayleigh distributed. Cooperative relaying with amplify and forward (AF) protocol is used to improve the overall system performance. System performance is investigated in two sets. In the first case, the source (S) to destination (D) direct link is double Rayleigh distributed. The relay (R) or access point is assumed to be located above rooftop level and the cooperative links are flat Rayleigh faded. In the second case, both the direct and cooperative links are considered double Rayleigh faded. Modelling and simulations are used to evaluate overall performance in conditions, when the cooperative link is uncorrelated, partially correlated and completely correlated with the direct link.

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: Empirical
Teacher disagreement score0.781
Threshold uncertainty score0.433

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
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 head0.095
GPT teacher head0.311
Teacher spread0.216 · 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

Citations9
Published2011
Admission routes1
Has abstractyes

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