MétaCan
Menu
Back to cohort
Record W2593492593

Smart antenna arrays — A geometrical explanation of how they work

2002· article· en· W2593492593 on OpenAlexaff
Peter F. Driessen

Bibliographic record

VenueInternational Symposium on Antenna Technology and Applied Electromagnetics · 2002
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Optimization
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsTransmitterBandwidth (computing)Directional antennaRayleigh scatteringChannel (broadcasting)PhysicsAntenna (radio)Topology (electrical circuits)Rayleigh fadingComputer scienceTelecommunicationsAcousticsOpticsElectrical engineeringFadingEngineering
DOInot available

Abstract

fetched live from OpenAlex

For fixed bandwidth and total radiated power, with Rayleigh fading, a wireless system with multiple antennas at both transmitter and receiver has a channel capacity which grows linearly (rather than logarithmically) with the number of antennas. This result, which assumes separate information is sent out of each transmit antenna, holds true even though the transmitter does not know the complex channel transfer characteristic. By explicitly spreading out the antennas well beyond a wavelength, we show that such capacities can be achieved not only on Rayleigh channels with many scatterers, but also on deterministic channels with direct line-of-sight (LOS) paths only and no scatterers. Roughly speaking, the wide spacing, replicates the effect of scatterers which create images and thus serves to spread out the apparent source of the signals over a wider angular range. In this way capacities on the order of C lin = nlog 2 (1 + ρ) bps/Hz can be obtained for LOS as well as Rayleigh channels when n transmit and n receive antennas are used. In contrast, when the transmit antennas are closely spaced, the number of degrees of freedom on a LOS channel degenerate, resulting in capacities of only C log = log 2 (1 + nρ).

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.859
Threshold uncertainty score0.871

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.007
GPT teacher head0.180
Teacher spread0.173 · 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 designBench or experimental
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

Citations0
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueInternational Symposium on Antenna Technology and Applied ElectromagneticsSame topicAntenna Design and OptimizationFrench-language works237,207