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Record W2160853584 · doi:10.5539/mas.v8n5p56

Interference in Wireless Networks: Causes, Analyses and Practical Mitigating Techniques

2014· article· en· W2160853584 on OpenAlexvenueno aff
Atif Hameed, Ali A. Oudah

Bibliographic record

VenueModern Applied Science · 2014
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsnot available
FundersUniversiti Malaysia Pahang
KeywordsComputer scienceCode division multiple accessInterference (communication)WirelessWireless networkBase stationComputer networkWidebandTelecommunicationsDivision (mathematics)Key (lock)Radio resource managementCode (set theory)Electronic engineeringComputer securityChannel (broadcasting)Engineering

Abstract

fetched live from OpenAlex

This paper addresses the key characteristics of interference in wireless networks. Moreover, it considers the impact of interference from Code Division Multiple Access base station to Wideband-Code Division Multiple Access one. A detailed discussion of major interference mitigation techniques in wireless networks, in general, and CDMA and W-CDMA systems, in particular is also imparted on. The techniques and findings in this paper can be easily used in the analyses of other wireless technologies.

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)0.002
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: Methods · Consensus signal: none
Teacher disagreement score0.975
Threshold uncertainty score0.635

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0000.001
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 head0.064
GPT teacher head0.369
Teacher spread0.305 · 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
GenreMethods

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

Citations3
Published2014
Admission routes1
Has abstractyes

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