MétaCan
Menu
Back to cohort
Record W2109483103 · doi:10.1109/vetec.1992.245397

Bit error rate performance of a direct-sequence spread-spectrum multiple-access cellular system in urban multipath mobile radio environments

2003· article· en· W2109483103 on OpenAlexaff
Abraham O. Fapojuwo, Andy Shen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsNovAtel (Canada)
Fundersnot available
KeywordsMultipath propagationBit error rateComputer scienceSpread spectrumKeyingPhase-shift keyingElectronic engineeringModulation (music)Direct-sequence spread spectrumRake receiverWord error rateComputer networkTelecommunicationsChannel (broadcasting)Speech recognitionEngineeringPhysics

Abstract

fetched live from OpenAlex

The results of a comprehensive study of the bit error rate performance of a direct-sequence spread-spectrum multiple-access (DS-SSMA) cellular system with differential phase shift keying modulation in realistic urban and suburban multipath mobile radio propagation channels are presented. Sample simulation results show that multipath combining is more effective in an urban than in a suburban environment. The results show that the bit error rate can be reduced by up to an order of magnitude if a multipath combining receiver is used instead of a single-path receiver.< <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: Empirical
Teacher disagreement score0.643
Threshold uncertainty score0.969

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 communication0.0000.001
Open science0.0030.001
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 head0.034
GPT teacher head0.271
Teacher spread0.237 · 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

Explore more

Same topicWireless Communication Networks ResearchFrench-language works237,207