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Record W1181605978 · doi:10.1049/iet-com.2014.0720

Performance analysis of orthogonal space–time block coding with antenna selection

2015· article· en· W1181605978 on OpenAlexaff
Mohammad Torabi, Jean Conan

Bibliographic record

VenueIET Communications · 2015
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsTransmitterCoding gainBlock codeBit error rateQuadrature amplitude modulationAntenna (radio)Computer scienceAlgorithmCoding (social sciences)MathematicsQuadrature (astronomy)Phase-shift keyingQAMSelection (genetic algorithm)TelecommunicationsTopology (electrical circuits)Electronic engineeringStatisticsDecoding methodsChannel (broadcasting)CombinatoricsArtificial intelligence

Abstract

fetched live from OpenAlex

A new approach for performance analysis of orthogonal space–time block coding systems with antenna selection is presented. Antenna selection has been performed at the transmitter and/or at the receiver sides. Closed‐form expressions are derived for the approximate average bit error rate (BER) of the considered system for M ‐ary quadrature amplitude modulation and phase‐shift keying schemes. Different from other approaches presented in the literature, analytical expressions are derived for the average signal‐to‐noise ratio (SNR) gain obtained from each antenna selection scheme, and then using those SNR gains closed‐form expressions are obtained for the approximate average BER performance. The system performances of several forms of the presented scheme are evaluated and compared. It is shown that the results obtained from the mathematical expressions match closely with simulation results.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.179
Threshold uncertainty score0.492

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.025
GPT teacher head0.259
Teacher spread0.234 · 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

Citations5
Published2015
Admission routes1
Has abstractyes

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