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Record W1982695909 · doi:10.1049/iet-com.2013.1035

Iterative interference cancellation in multiuser relaying with fast frequency‐hopping modulation

2014· article· en· W1982695909 on OpenAlexaff
Tung Nguyen, Ha H. Nguyen, Tho Le‐Ngoc

Bibliographic record

VenueIET Communications · 2014
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsMcGill UniversityUniversity of Saskatchewan
Fundersnot available
KeywordsFrequency-hopping spread spectrumSingle antenna interference cancellationInterference (communication)Modulation (music)Computer scienceCo-channel interferenceTelecommunicationsElectronic engineeringPhysicsAcousticsDecoding methodsChannel (broadcasting)

Abstract

fetched live from OpenAlex

A novel iterative receiver is proposed for relay‐assisted multiuser communications in which multiple users transmit to a destination with the help of a relay and using fast frequency‐hopping modulation. Each user employs a channel encoder to protect its information and facilitate interference cancellation at the receiver. The signal received at the relay is either amplified, or partially decoded with a simple energy detector, before being forwarded to the destination. The proposed iterative receiver exploits the soft outputs of a channel decoder to successively extract the maximum‐likelihood symbols of the users and perform interference cancellation. Under the same spectral efficiency, simulation results demonstrate superior performance of the proposed receiver when compared to the performance of an interference cancellation scheme that was previously proposed for multiuser communications and is extended to multiuser amplify‐and‐forward relaying considered in this study, as well as performance of the maximum‐likelihood multiuser detection for uncoded transmission.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.942
Threshold uncertainty score0.594

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 communication0.0000.001
Open science0.0020.001
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 head0.048
GPT teacher head0.290
Teacher spread0.242 · 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 designSimulation or modeling
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

Citations5
Published2014
Admission routes1
Has abstractyes

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