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Record W4232845162 · doi:10.1109/glocom.2014.7417879

Irregular Multidimensional Constellations for Orthogonal STBCs

2014· article· en· W4232845162 on OpenAlexaff
Hossein Khoshnevis, Ian Marsland, Halim Yanıkömeroğlu

Bibliographic record

Venue2015 IEEE Global Communications Conference (GLOBECOM) · 2014
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsCarleton University
Fundersnot available
KeywordsConstellationBlock codeSpace–time block codeTransmitterComputer scienceAlgorithmDimension (graph theory)Antenna diversityConstellation diagramMIMOMathematicsBlock (permutation group theory)Block Error RateTransmit diversityReliability (semiconductor)Topology (electrical circuits)Theoretical computer scienceTelecommunicationsBit error rateDecoding methodsFadingAntenna (radio)BeamformingPure mathematicsCombinatorics

Abstract

fetched live from OpenAlex

Utilizing multiple antennas at the transmitter and receiver provides higher data rates and better reliability by exploiting spatial diversity. Space-time block codes (STBCs) is a simple approach for using multiple transmit and receive antennas that has been widely employed in standards. The STBCs introduced in the literature use independent two-dimensional constellations, while the performance of orthogonal STBCs may be improved with multidimensional constellations. These constellations are transmitted by combining multiple space-time resources to form a multidimensional signal space. In this paper, we propose a method for finding optimized multidimensional constellations for orthogonal STBCs. Optimization is performed by minimizing a novel bound on the block or symbol error rate. We show that a substantial improvement in the error probability can be achieved with these novel constellations.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.847
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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.039
GPT teacher head0.314
Teacher spread0.275 · 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 designTheoretical or conceptual
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

Citations1
Published2014
Admission routes1
Has abstractyes

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