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Performance Analysis of Space Shift Keying with Amplify and Forward Relaying

2011· article· en· W2066331953 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Communications Letters · 2011
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Technologies
Canadian institutionsInstitut National de la Recherche Scientifique
FundersUniversity of Tabuk
KeywordsTransmitterRelayComputer scienceAntenna (radio)Topology (electrical circuits)Monte Carlo methodAlgorithmKeyingUpper and lower boundsExpression (computer science)TelecommunicationsDetectorElectronic engineeringMathematicsStatisticsPhysicsPower (physics)EngineeringChannel (broadcasting)Combinatorics

Abstract

fetched live from OpenAlex

In this letter, dual-hop amplify and forward relaying using space shift keying (SSK) is introduced. In SSK, information bits are mapped into a spatial symbol. The spatial symbol is the index of the active transmit antenna, where a single antenna is activated at each time instance. The relay amplifies the data received from the transmitter and forwards it to the receiver without any further processing. The receiver applies optimum maximum-likelihood detector to retrieve the transmitted information bits. In particular, an exact closed-form expression for the average bit error probability is given for the case of two transmit antennas. In addition, an upper bound is derived for an arbitrary number of transmit antennas. The analytical results are validated through Monte Carlo 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.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.075
Threshold uncertainty score0.519

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.032
GPT teacher head0.230
Teacher spread0.198 · 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