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Orthogonal Transmissions for Spectrum Underlay MISO Cognitive Radio

2012· article· en· W2152124228 on OpenAlexaff
Hongbo Guo, Victor C. M. Leung

Bibliographic record

VenueIEEE Transactions on Wireless Communications · 2012
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCognitive radioRayleigh fadingComputer scienceInterference (communication)FadingWhite spacesUnderlayTransmission (telecommunications)TelecommunicationsChannel (broadcasting)Topology (electrical circuits)MathematicsWirelessSignal-to-noise ratio (imaging)

Abstract

fetched live from OpenAlex

This work studies a cognitive radio (CR) communication system in which multiple antennas assist the secondary user to achieve transmission diversity, while the constraint of zero interference to the primary user is satisfied. We show that due to the zero interference constraint, the secondary link may occasionally suffer from low signal levels, as if it is in deep fading. Employing space time coding for diversity does not help this situation. We show that a beamformer that is mutually orthogonal in time domain across the antennas is effective in mitigating the low signal effects. Further, N antennas provide an equivalent (N-1) x 1 Rayleigh channel due to the function of this beamformer. The effect of a non-orthogonal beamformer is also analyzed and shown by simulations.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.961
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.036
GPT teacher head0.296
Teacher spread0.260 · 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.

Study designOther design
Domainnot available
GenreMethods

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

Citations12
Published2012
Admission routes1
Has abstractyes

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