MétaCan
Menu
Back to cohort
Record W1483886976 · doi:10.1109/tbc.2015.2459662

Overview of Wireless Microphones—Part II: Frequency Bands, Interference, and Regulation

2015· article· en· W1483886976 on OpenAlexaffabout
Hong Liu, Donald McLachlan, Demin Wang

Bibliographic record

VenueIEEE Transactions on Broadcasting · 2015
Typearticle
Languageen
FieldEngineering
TopicPower Line Communications and Noise
Canadian institutionsCommunications Research Centre Canada
Fundersnot available
KeywordsTransmitterWirelessRadio spectrumTelecommunicationsFrequency bandBandwidth (computing)Interference (communication)Adjacent-channel interferenceComputer scienceMicrophoneElectrical engineeringElectronic engineeringChannel (broadcasting)Broadcasting (networking)EngineeringComputer network

Abstract

fetched live from OpenAlex

Most wireless microphones operate on vacant television broadcasting channels in the very high frequency and ultrahigh frequency bands, as secondary users operating on the no-interference and no-protection basis. Some wireless microphones share the 2.4 GHz band with other wireless devices. The 698-806 MHz band was repurposed when television broadcasting switched from analog to digital (and the 600 MHz band may be repurposed in the near future), resulting in less spectrum available for wireless microphone operations. To keep wireless microphones operating effective in this environment, engineers, researchers, and regulators require comprehensive knowledge of the spectrum, interference, and regulations regarding wireless microphones. This paper first presents the characteristics of the frequency bands currently allocated for wireless microphone operations. Next, interference that may be experienced by wireless microphones and frequency coordination required to allow multiple microphones to work together at the same site without interference are presented. Finally, it summarizes the regulations in Canada, United States of America, European Union, and Australia for wireless microphones regarding allowable transmitter frequency, power, bandwidth, channel masks, maximum frequency deviation for FM, and spurious emissions.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.533
Threshold uncertainty score0.536

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.063
GPT teacher head0.261
Teacher spread0.199 · 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 teacher head, 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

Citations1
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueIEEE Transactions on BroadcastingSame topicPower Line Communications and NoiseFrench-language works237,207