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Record W2370905461

Implementation of Multi-time Scale HF Channel Model in NS2

2014· article· en· W2370905461 on OpenAlexaff
Jiang Chua

Bibliographic record

VenueTelecommunication Engineering · 2014
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsUniversité du Québec
Fundersnot available
KeywordsFadingFading distributionChannel state informationRayleigh fadingChannel (broadcasting)Computer scienceElectronic engineeringTelecommunicationsEngineeringWireless
DOInot available

Abstract

fetched live from OpenAlex

In consideration of the complicated fading characteristics of high frequency( HF) channel and the difficulty of reappearing in simulation,a combined method of NS2( Network Simulation 2) and VOACAP( Voice of America Coverage Analysis Program) is proposed to simulate HF channel. Based on Walnut Street Model,the HF channel fading is divided into slow fading,mid-time scale fading and fast fading. In the fading model of HF propagation model,VOACAP is called in C++ to calculated slow fading on need, medium time scale fading is treated as log-normal distribution and fast fading is treated as Rayleigh distribution. The simulation results show that,this model can reveal the fading characteristics of HF channel, and the change of frequencies' fading with time of day is consistent with that of theory and experience. So this model may serve as the base of physical layer in HF network simulation. Meanwhile,the joint simulation method used in this paper avoids the complexity of calculation of channel fading before simulation,so it's more suitable for large scale HF network simulation.

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: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.782
Threshold uncertainty score0.521

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 studies0.0000.000
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 head0.021
GPT teacher head0.291
Teacher spread0.269 · 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
GenreMethods

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
Published2014
Admission routes1
Has abstractyes

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