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Record W2593034648 · doi:10.1109/antem.2004.7860674

Time-domain channel estimation and performance evaluation of a MIMO-OFDM system

2004· article· en· W2593034648 on OpenAlexaff
Quazi Mehbubar Rahman, Mostafa Hefnawi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsOrthogonal frequency-division multiplexingPhase-shift keyingComputer scienceMIMO-OFDMMIMOElectronic engineeringChannel (broadcasting)Rayleigh fadingBit error rateQuadrature amplitude modulationFrequency domainTime domainFadingTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

This paper presents a simplified channel estimation technique for orthogonal frequency division multiplexing (OFDM) systems with multiple input, multiple output (MIMO) antenna structure. The estimation technique is presented both in the frequency and time domains. Quadrature phase shift keying (QPSK) modulation technique is used to modulate the transmitted data. To ensure low computational complexity, time domain estimated channel information is considered to evaluate the performance of the OFDM system in terms of symbol error rate (SER). For both channel estimation and performance evaluation, simulation results are presented for two-transmit and one-receive antenna configuration in the two-ray Rayleigh fading channel 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)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.251
Teacher spread0.236 · 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
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

Citations0
Published2004
Admission routes1
Has abstractyes

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