MétaCan
Menu
Back to cohort
Record W2167895949 · doi:10.1109/issse.2007.4294443

A Study on the Channel and Signal Cross Correlation of UHF DTV Channels

2007· article· en· W2167895949 on OpenAlexaff
Viet-Ha Pham, Jean‐Yves Chouinard

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTelecommunications and Broadcasting Technologies
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsUltra high frequencyChannel (broadcasting)Digital televisionComputer scienceSIGNAL (programming language)AutocorrelationElectronic engineeringDigital broadcastingWirelessWidebandBroadcasting (networking)TelecommunicationsDigital Video BroadcastingEnvelope (radar)Frequency bandElectrical engineeringEngineeringBandwidth (computing)Computer networkMathematicsStatistics

Abstract

fetched live from OpenAlex

UHF channels are traditionally used for television broadcasting where the channels can be regarded static or slowly-varying. Since the advent of the unlicensed and cognitive radio, there is a need of re-evaluation the channels in UHF frequency band under the new application environments. In this paper, new results on the temporal and spatial characteristics of the wideband UHF mobile wireless signals and channels in the digital television (DTV) broadcasting UHF frequency bands are presented. Our analysis of DTV mobile field measurements shows that the complex channel correlation magnitude depends on the channel phase correlation and is considerably different from the channel envelope correlation. Furthermore, the transmitted signal autocorrelation is embedded in the received signal correlation and makes it different from the channel correlation.

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: Empirical · Consensus signal: none
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.038
GPT teacher head0.274
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

Citations4
Published2007
Admission routes1
Has abstractyes

Explore more

Same topicTelecommunications and Broadcasting TechnologiesFrench-language works237,207