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Record W4415821327 · doi:10.1109/lwc.2025.3628136

Moments of the Bivariate Fox-H Function Fading Model and Applications to Wireless System Performance Evaluation

2025· article· W4415821327 on OpenAlexaff
Puspraj Singh Chauhan, Vimal Bhatia, Sonia Aı̈ssa, Ondřej Krejcar

Bibliographic record

VenueIEEE Wireless Communications Letters · 2025
Typearticle
Language
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsFadingMoment (physics)Moment-generating functionBivariate analysisProbability density functionWirelessErgodic theoryCumulative distribution functionBit error rate

Abstract

fetched live from OpenAlex

Performance analysis of wireless communication systems is generally based on statistical functions such as the probability density function, the cumulative density function, the moment-generating function, and the Mellin transform. This paper explores an alternative way based on the moment and truncated moment to assess the performance of wireless communication subjected to bivariate Fox H-function fading. First, novel expressions for the generalized moment and the truncated moment are derived. Subsequently, various system performance indicators, namely, amount of fading, channel quality estimation index, ergodic capacity, channel inversion with fixed inversion rate (CIFR) capacity, truncated CIFR capacity, and effective capacity, are obtained by considering the α-η-μ/Inverse-Gamma fading model as a typical representation of the bivariate Fox H-function model. The applicability of the truncated moment approach is further demonstrated via analysis of the block error rate and the delay outage rate performance of short-packet communication.

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 categoriesMeta-epidemiology (narrow), Science and technology studies
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 score0.648
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0040.001
Research integrity0.0000.001
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 head0.028
GPT teacher head0.284
Teacher spread0.256 · 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.

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
Published2025
Admission routes1
Has abstractyes

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