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Record W2318276941 · doi:10.1109/tthz.2014.2331496

Design of a Reconfigurable MIMO System for THz Communications Based on Graphene Antennas

2014· article· en· W2318276941 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 Terahertz Science and Technology · 2014
Typearticle
Languageen
FieldEngineering
TopicMillimeter-Wave Propagation and Modeling
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsMIMOBeamwidthReconfigurable antennaTerahertz radiationComputer scienceGrapheneAntenna (radio)Smart antennaPath lossElectronic engineeringChannel (broadcasting)Radiation patternDirectional antennaPhysicsOptoelectronicsTelecommunicationsAntenna efficiencyEngineeringWireless

Abstract

fetched live from OpenAlex

Based on the properties of graphene nano-patch antennas, we propose a reconfigurable multiple-input multiple-output (MIMO) antenna system for Terahertz (THz) communications. First, the characteristics of the graphene are analyzed and a beam reconfigurable antenna is designed. The beamwidth and direction can be controlled by the states of each graphene patch in the antenna. Then the path loss and reflection models of the THz channel are discussed. We combine the graphene-based antenna and the THz channel model, and propose a new MIMO antenna design. The radiation directions of the transmit antennas can be programmed dynamically, leading to different channel state matrices. Finally, the path loss and the channel capacity are numerically calculated and compared with those of the Gigahertz (GHz) channel. The results show that for short range communications, the proposed MIMO antenna design can enlarge the channel capacity by both increasing the number of antennas and choosing the best channel state matrices.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.974
Threshold uncertainty score0.374

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 head0.028
GPT teacher head0.234
Teacher spread0.206 · 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