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Record W2117402898 · doi:10.1109/tvt.2009.2039505

Performance Analysis of Joint Transmit and Receive Antenna Selection With Orthogonal Space-Time Coding

2010· article· en· W2117402898 on OpenAlexaff
W Zhang, Chintha Tellambura

Bibliographic record

VenueIEEE Transactions on Vehicular Technology · 2010
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsNakagami distributionMIMOBit error rateFadingJoint (building)Antenna (radio)AlgorithmSelection (genetic algorithm)Computer scienceCoding gainSignal-to-noise ratio (imaging)Electronic engineeringBlock codeCoding (social sciences)MathematicsTelecommunicationsControl theory (sociology)StatisticsDecoding methodsEngineeringBeamforming

Abstract

fetched live from OpenAlex

This paper analyzes the performance of multiple-input-multiple-output (MIMO) systems with transmit and receive antenna selection (T-RAS). The average bit error rate (BER) and the average symbol error rate (SER) are derived by utilizing the characteristic function (CF) of the joint output signal-to-noise ratios (SNRs). Our approach can be used over not only independent but also arbitrary correlated channels. For the sake of brevity, this paper focuses on Nakagami-m fading channels. The simulation results are provided to validate the numerical calculations.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.003
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.201
Teacher spread0.195 · 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 source (direct Gemma or distilled Codex), 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

Citations16
Published2010
Admission routes1
Has abstractyes

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