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Record W2143118552 · doi:10.1109/icc.1995.524282

A reduced dimensionality propagation model for frequency selective Rayleigh fading channels

2002· article· en· W2143118552 on OpenAlexaff
Deng Guanghua, J.K. Cavers, P. Ho

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsViterbi algorithmFadingRayleigh fadingComputer scienceChannel (broadcasting)Delay spreadAlgorithmViterbi decoderElectronic engineeringImpulse responseTelecommunicationsMathematicsEngineeringDecoding methods

Abstract

fetched live from OpenAlex

Presents a new model for the frequency selective Rayleigh fading channel, based on a Taylor expansion of the transmitted signal. Because only a few derivatives are required, the discrete time channel impulse response (CIR), which normally spans many symbols, can be described by only a few parameters. Consequently, both channel estimation and channel simulation become simpler. The authors assess the accuracy of the model and demonstrate its effectiveness by the BER performance of a Viterbi receiver that uses the reduced dimensionality CIR. For channels with a rms delay spread not exceeding a quarter of a symbol duration, the receiver performs as well as a Viterbi receiver with access to the true CIR. For greater delay spreads, higher derivatives can be employed.

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: Methods · Consensus signal: none
Teacher disagreement score0.833
Threshold uncertainty score0.503

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 head0.043
GPT teacher head0.267
Teacher spread0.223 · 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

Citations17
Published2002
Admission routes1
Has abstractyes

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