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Record W2607843146 · doi:10.1109/tcsii.2017.2697456

Design and Performance Analysis of a Differentially Spatial Modulated Chaos Shift Keying Modulation System

2017· article· en· W2607843146 on OpenAlexaff
Wei Hu, Lin Wang, Georges Kaddoum

Bibliographic record

VenueIEEE Transactions on Circuits & Systems II Express Briefs · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicChaos control and synchronization
Canadian institutionsUniversité du Québec à Montréal
FundersNational Natural Science Foundation of China
KeywordsTransmitterKeyingSpatial modulationModulation (music)Amplitude and phase-shift keyingPhase-shift keyingComputer scienceElectronic engineeringBit error rateSpectral efficiencyTransceiverAlgorithmChannel state informationMinimum-shift keyingChannel (broadcasting)TelecommunicationsTopology (electrical circuits)MathematicsMIMOPhysicsWirelessEngineeringAcoustics

Abstract

fetched live from OpenAlex

In this brief, a new differentially spatial modulated chaos shift keying modulation communication system is proposed, in which the transceiver has not accessed channel state information. In the transmitter, the symbol can be mapped into the dependently selected antenna by the differential matrix in each interval. Meanwhile, in the receiver, the maximum received signal is used to retrieve the block of transmitted bits by the maximum likelihood estimation. By employing the spatial modulation, the proposed scheme offers a higher spectrum efficiency and the energy efficiency compared to the conventional multiple-input multiple-output differential chaos shift keying system. Lastly, the theoretical upper bounds on the average bit error probability, analyzed and derived, are in good agreement with the simulation results.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.221
Teacher spread0.204 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations27
Published2017
Admission routes1
Has abstractyes

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Same venueIEEE Transactions on Circuits & Systems II Express BriefsSame topicChaos control and synchronizationFrench-language works237,207