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Record W2160817323 · doi:10.1109/ccece.2007.230

Closed-Form SER and Capacity Expressions for Receive Antenna Selection Using Orthogonal Space-Time Block Codes

2007· article· en· W2160817323 on OpenAlexaff
Khoa T. Phan, Chintha Tellambura, Duy T. Ngo

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMIMOBlock codeAntenna (radio)TransmitterRayleigh fadingSelection (genetic algorithm)Computer scienceAlgorithmMathematicsExpression (computer science)FadingTransmission (telecommunications)Topology (electrical circuits)Channel (broadcasting)TelecommunicationsDecoding methodsCombinatorics

Abstract

fetched live from OpenAlex

In multiple-input multiple-output (MIMO) systems, antenna selection where only a subset of antennas at the transmitter and/or receiver are activated for signal transmission is a practical technique for the realization of diversity benefits. Despite extensive research, closed-form symbol-error-rate (SER) and capacity expressions for MIMO systems employing receive antenna selection (RAS) and orthogonal space-time block codes (OSTBCs) are not available. We thus derive exact closed-form expressions for the SER and capacity of an OSTBC MIMO system when N receive antennas out of total Lrantennas are selected at the receiver. Our expressions are valid for a frequency-flat Rayleigh fading MIMO channel and avoid numerical integration methods.

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)0.006
metaresearch head score (Gemma)0.024
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 score0.008
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.024
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.003
Science and technology studies0.0010.002
Scholarly communication0.0030.004
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.004

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 head0.024
GPT teacher head0.272
Teacher spread0.248 · 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

Citations1
Published2007
Admission routes1
Has abstractyes

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