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Record W2111789016 · doi:10.1109/ccece.2007.404

Application of Six-Port Receiver for OFDM Signals

2007· article· en· W2111789016 on OpenAlexaff
Munir Arshad, Jean‐François Frigon, Yanyang Zhao, R.G. Bosisio

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrowave and Dielectric Measurement Techniques
Canadian institutionsPolytechnique MontréalAdvanced Micro Devices (Canada)
Fundersnot available
KeywordsOrthogonal frequency-division multiplexingComputer scienceElectronic engineeringWirelessWidebandPort (circuit theory)Modulation (music)Frequency-division multiplexingSIGNAL (programming language)Communications systemTelecommunicationsComputer networkChannel (broadcasting)Engineering

Abstract

fetched live from OpenAlex

A significant amount of work has been carried out on the application of six-port receivers for single carrier communications and for the impulse ultra-wideband radio, however a small interest has been shown on the research of its use for orthogonal frequency division multiplexing (OFDM) communication systems. OFDM and its derived forms are now essential multi-carrier modulation techniques for various present and future high speed wireless communication systems. In this paper, we investigate the possible application of direct conversion six-port receiver for the OFDM signal. The application of six-port receiver for the OFDM signal proves its suitability for the present and future wireless communication systems based on standards such as IEEE 802.11x, 802.16x and 802.15.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.018
GPT teacher head0.249
Teacher spread0.230 · 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 designBench or experimental
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

Citations2
Published2007
Admission routes1
Has abstractyes

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