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Record W2094513279 · doi:10.1109/ictta.2006.1684727

A Survey on Antenna Selection for MIMO Communication Systems

2006· article· en· W2094513279 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsConcordia University
Fundersnot available
KeywordsAntenna (radio)Selection (genetic algorithm)FadingMIMOBlock codeComputer scienceChannel capacity3G MIMOAntenna diversityDiversity gainTelecommunicationsChannel (broadcasting)Electronic engineeringAlgorithmMathematicsDecoding methodsEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

This paper serves as a tutorial on antenna selection for multiple-input multiple-output (MIMO) communication systems. We consider the impact of antenna selection on the system capacity, as well as on the performance of the space-time trellis codes (STTCs) and space-time block codes (STBCs). We consider various fading channel models, including fast, block and slow fading. We also consider two selection criteria, namely, the one that maximizes the channel capacity and the one that maximizes the instantaneous received signal-to-noise ratio (SNR). We show that little capacity loss is incurred with antenna selection. We also demonstrate that the diversity order is maintained with antenna selection for STTCs only for special cases, whereas the diversity order is maintained with antenna selection for orthogonal STBCs for all channel models. This makes OSTBCs very attractive when antenna selection is considered. We finally consider the effect of some system nonidealities on the performance with antenna selection

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.

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: none
Teacher disagreement score0.969
Threshold uncertainty score0.365

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.022
GPT teacher head0.263
Teacher spread0.241 · 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