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Record W2760498114 · doi:10.48550/arxiv.1709.08085

Time-Reversal Routing for Dispersion Code Multiple Access (DCMA) Communications

2017· preprint· en· W2760498114 on OpenAlexaff
Lianfeng Zou, Christophe Caloz

Bibliographic record

VenuearXiv (Cornell University) · 2017
Typepreprint
Languageen
FieldEngineering
TopicMicrowave Imaging and Scattering Analysis
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsComputer scienceInterference (communication)Code (set theory)Communications systemRouting (electronic design automation)SIGNAL (programming language)Dispersion (optics)Bit error rateTransceiverElectronic engineeringComputer networkAlgorithmTelecommunicationsDecoding methodsWirelessEngineeringPhysicsChannel (broadcasting)

Abstract

fetched live from OpenAlex

We present the modeling and characterization of a time-reversal routing dispersion code multiple access (TR-DCMA) system. We show that this system maintains the low complexity advantage of DCMA transceivers while offering dynamic adaptivity for practial communication scenarios. We first derive the mathematical model and explain operation principles of the system, and then characterize its interference, signal to interference ratio, and bit error probability characteristics.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.407
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 science0.0020.001
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 head0.107
GPT teacher head0.232
Teacher spread0.125 · 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 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

Citations0
Published2017
Admission routes1
Has abstractyes

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