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Record W2165816901 · doi:10.1109/glocom.2008.ecp.120

Channel Capacity and Second Order Statistics in Tactical Mobile Ad Hoc Networks

2008· article· en· W2165816901 on OpenAlexaff
Basile L. Agba, François Gagnon, Ammar B. Kouki

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicMobile Ad Hoc Networks
Canadian institutionsÉcole de Technologie SupérieureHydro-Québec
Fundersnot available
KeywordsComputer scienceWireless ad hoc networkChannel (broadcasting)Computer networkChannel capacityWirelessTelecommunications

Abstract

fetched live from OpenAlex

The channel capacity and the channel statistics are both important performance metrics to consider for appropriate design of wireless systems. In tactical mobile ad hoc networks environment, the capacity and the second order statistics are investigated based on an optimized physical layer simulation tool which includes tactical scenarios generator and propagation modeler. The possible link data rate is stemmed from the average channel capacity analysis between all pair of nodes. And based on the minimum data rate requirement for typical services (web, audio and video streaming, VoIP, videoconference), connectivity graphs are constructed. Moreover, level cross rate (ICR) and average duration of fade (ADF) are simulated as function of double mobility degree and the results show how the double mobility affects the second order channel statistics and the error probability.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.229
Teacher spread0.212 · 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 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

Citations0
Published2008
Admission routes1
Has abstractyes

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