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Record W1634698960 · doi:10.1109/sarnof.2005.1426543

Selection diversity in non-identically distributed Nakagami fading channels

2006· article· en· W1634698960 on OpenAlexaff
Raymond Kwan, Cyril Leung

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsFadingIndependent and identically distributed random variablesNakagami distributionMoment-generating functionCumulative distribution functionProbability density functionComputer scienceDiversity schemeAlgorithmDiversity combiningTelecommunications linkClosed-form expressionChannel (broadcasting)MathematicsRandom variableStatisticsTelecommunicationsMathematical analysis

Abstract

fetched live from OpenAlex

The performance of selection diversity over independent but not necessarily identically distributed Nakagami fading channels is studied. An exact closed-form expression for the probability density function of the selected channel signal-to-noise ratio is derived. Exact closed-form expressions for the corresponding cumulative distribution function, moment generating function and moments are also obtained. The results are used to obtain outage probabilities and achievable bit rates for an adaptive modulation and coding scheme with multicode transmission as employed in systems similar to the high speed downlink packet access channel or the 3GPP cellular standard

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)0.000
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: Empirical · Consensus signal: none
Teacher disagreement score0.705
Threshold uncertainty score0.379

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.010
GPT teacher head0.227
Teacher spread0.217 · 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

Citations11
Published2006
Admission routes1
Has abstractyes

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