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Record W1995793510 · doi:10.1109/tap.2011.2173444

Multiple Element Antenna Efficiency and its Impact on Diversity and Capacity

2011· article· en· W1995793510 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

VenueIEEE Transactions on Antennas and Propagation · 2011
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsDiversity gainAntenna diversityContext (archaeology)Antenna (radio)Metric (unit)TelecommunicationsComputer scienceElectronic engineeringPerformance metricMIMOMathematicsTopology (electrical circuits)BeamformingEngineering

Abstract

fetched live from OpenAlex

A desirable characteristic of a multiple element antenna (MEA) is to be compact, but a smaller size tends to lead to higher ohmic and mutual coupling losses. A metric for the efficiency of the MEA would help clarify the tradeoffs between compactness and performance. In a MIMO/diversity antenna, the total efficiency seen at each port directly affects the signal-to-noise ratio (SNR) in the diversity branch. The SNR after diversity combining governs the performance of the diversity antenna system. In this paper, MEA efficiencies is therefore discussed and formulated in the context of mutual coupling and diversity combining. The impact of MEA efficiency on the diversity gain and the information theoretical capacity is also formulated and demonstrated using measurements of example MEAs. With these formulations, an equivalent number of idealized (lossless, uncorrelated, uncoupled, equal power) branches can be found for an MEA, and this defines the diversity order and the capacity order of the MEA. With this metric, the performance of different MEAs can be compared.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.943
Threshold uncertainty score0.553

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 head0.030
GPT teacher head0.216
Teacher spread0.186 · 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