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Record W2077340013 · doi:10.1109/icc.2006.255490

Improved Pilot-Assisted Prediction of Unknown Time-Selective Rayleigh Channels

2006· article· en· W2077340013 on OpenAlexaff
Kareem E. Baddour, Norman C. Beaulieu

Bibliographic record

Venue2006 IEEE International Conference on Communications · 2006
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsUniversity of AlbertaQueen's University
Fundersnot available
KeywordsFadingRayleigh fadingComputer scienceChannel (broadcasting)TransmitterChannel state informationBlock (permutation group theory)AlgorithmElectronic engineeringWirelessTelecommunicationsEngineeringMathematics

Abstract

fetched live from OpenAlex

To enable closed-loop operation of high-mobility systems, reliable channel prediction is needed to prevent the obsolescence of channel information due to feedback and processing delays. In this paper, novel linear pilot symbol-aided techniques are proposed for block-adaptive prediction of flat time-selective Rayleigh fading channels. Unlike many previous investigations, which assume that the fading statistics are known, we focus on practical conditions where prediction must take place over short noisy windows of unknown channels. Significant performance gains are observed when the method is applied, for example, to a selection transmitter diversity system operating in a fast fading environment.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.054
GPT teacher head0.297
Teacher spread0.243 · 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 source (direct Gemma or distilled Codex), 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

Citations21
Published2006
Admission routes1
Has abstractyes

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