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Record W2095962667 · doi:10.1109/vetecf.2007.293

OFDM with Cyclic-Pilot Time Diversity

2007· article· en· W2095962667 on OpenAlexaff
Ali Pour Yazdanpanah, Behrang Nosrat-Makouei, Rodney G. Vaughan

Bibliographic record

VenueIEEE Vehicular Technology Conference · 2007
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsOrthogonal frequency-division multiplexingComputer scienceOverhead (engineering)TransceiverMaximizationWirelessChannel (broadcasting)Electronic engineeringBandwidth (computing)MultiplexingReal-time computingTelecommunicationsEngineeringMathematicsMathematical optimization

Abstract

fetched live from OpenAlex

We present a novel transceiver design for orthogonal frequency-division multiplexing (OFDM) wireless systems employing pilot symbol aided channel estimation (PSACE). The design is based on the insertion of known pilots into the time- frequency OFDM grid in a controlled cyclic fashion to exploit time diversity in the pilot tones without consuming additional bandwidth resource. Semi-blind iterative detection based on the expectation-maximization algorithm along with optimum combining is employed at the receiver. Despite moderately increased transceiver complexity, simulations show that the proposed design has superior error rate performance compared to conventional PSACE methods for the same pilot overhead.

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)0.001
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: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.001

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 head0.013
GPT teacher head0.218
Teacher spread0.205 · 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

Citations3
Published2007
Admission routes1
Has abstractyes

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