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Record W2105832623 · doi:10.1109/icc.1996.542198

A block memory model for correlated Rayleigh fading channels

2002· article· en· W2105832623 on OpenAlex
Mahdi Sajadieh, Frank R. Kschischang, Alberto Leon‐Garcia

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced MIMO Systems Optimization
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFadingRayleigh fadingMarkov processChannel state informationFading distributionMarkov chainComputer scienceQuantization (signal processing)Statistical physicsAlgorithmChannel (broadcasting)MathematicsElectronic engineeringTelecommunicationsStatisticsEngineeringPhysicsWireless

Abstract

fetched live from OpenAlex

Channels with memory offer higher capacities provided that the system design can take advantage of this memory. In this paper, we study and characterize the dynamics of a correlated Rayleigh fading channel with known phase. The model follows a continuous-time Markov double-chain for the random fading process with the Markov states corresponding to the quantized amplitude levels. The analytical expression for the distribution of the state dwell times is derived. We also calculate the mean dwell times of the Markov states in terms of the fading properties and the quantization level. Observations from simulating a typical land-mobile channel verify that the Markovian dynamics are best represented through a finer quantization of the lower level fading amplitudes.

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.

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: Methods · Consensus signal: none
Teacher disagreement score0.959
Threshold uncertainty score0.495

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 head0.023
GPT teacher head0.210
Teacher spread0.187 · 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

Quick stats

Citations23
Published2002
Admission routes1
Has abstractyes

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