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Record W2166165976 · doi:10.1109/pimrc.1992.279860

Suitability of MSK modulation in a direct-sequence spread spectrum system

2003· article· en· W2166165976 on OpenAlexaff
J.E. Salt, S. Kumar

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsPhase-shift keyingMinimum-shift keyingKeyingModulation (music)Frequency-shift keyingComputer scienceElectronic engineeringAmplifierTelecommunicationsAmplitude and phase-shift keyingSpread spectrumInterference (communication)Direct-sequence spread spectrumBit error rateEngineeringPhysicsCode division multiple accessChannel (broadcasting)Bandwidth (computing)AcousticsDemodulation

Abstract

fetched live from OpenAlex

Battery power efficiency of the portable unit is a major issue in the design of indoor radio telecommunication systems. The efficiency of the portables depends on the modulation method employed. Digital modulation methods with constant envelope signals are more battery efficient than those with modulated envelope signals since the latter require inefficient linear radio frequency amplifiers. The improvement in efficiency is very significant when the constant envelope modulation method is minimum shift keying and a directly modulated power radio frequency oscillator is used to generate the modulated signal. This paper compares the performance of binary phase shift keying (BPSK) and minimum frequency shift keying (MSK) in a spread spectrum code division multiple access setting. The BPSK system can support about 8 percent plus 0.5 more simultaneous users for a given carrier to interference ratio but the MSK system has the advantage of being more power efficient.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.916
Threshold uncertainty score0.303

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.041
GPT teacher head0.294
Teacher spread0.253 · 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 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

Citations1
Published2003
Admission routes1
Has abstractyes

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