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Record W2070045377 · doi:10.1109/bwcca.2012.15

Strength Based Receiver Architecture and Communication Range and Rate Dependent Signal Detection Characteristics of Concentration Encoded Molecular Communication

2012· article· en· W2070045377 on OpenAlexafffund
Mohammad Upal Mahfuz, Dimitrios Makrakis, Hussein T. Mouftah

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMolecular Communication and Nanonetworks
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMolecular communicationIntersymbol interferenceComputer scienceTransmission (telecommunications)UnicastEnergy (signal processing)Channel (broadcasting)Electronic engineeringSIGNAL (programming language)Bit error rateBinary numberCommunications systemDetection theoryPulse (music)Data transmissionPulse-amplitude modulationTelecommunicationsTransmitterComputer networkDetectorMathematicsEngineeringMulticastStatistics

Abstract

fetched live from OpenAlex

In this paper for the first time ever a strength (energy) based receiver architecture of binary pulse amplitude modulated (PAM) concentration-encoded molecular communication (CEMC) system between communicating nanomachines has been presented. We also analyze the communication range and data rate dependent signal detection characteristics of a PAM CEMC system in a three dimensional ideal (free) diffusion based unbounded propagation environment. A unicast CEMC channel with a single type of information molecules has been assumed to carry the information from the transmitting nanomachine (TN), through the propagation medium, to the receiving nanomachine (RN) in the form of received concentration of information molecules at the location of the receptor of the RN. We develop a mathematical model of strength based detection method for a PAM CEMC system, explain its dependence on communication range and transmission data rate, compare it with a single pulse transmission case, and determine the impacts of intersymbol interference (ISI) contributed by all the previous bits of information to the current bit duration.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.505
Threshold uncertainty score0.522

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 science0.0000.000
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 head0.007
GPT teacher head0.196
Teacher spread0.189 · 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.

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

Citations11
Published2012
Admission routes2
Has abstractyes

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