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Record W2095828264 · doi:10.1109/vetecf.2007.212

A Novel Chase Based Multiuser Detector for MIMO-CDMA Systems

2007· article· en· W2095828264 on OpenAlex
Feng Liu, M. Reza Soleymani

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 Vehicular Technology Conference · 2007
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsConcordia University
Fundersnot available
KeywordsDetectorMIMOChaseComputer scienceScheme (mathematics)Multiuser detectionCode division multiple accessElectronic engineeringAlgorithmTelecommunicationsMathematicsEngineeringChannel (broadcasting)

Abstract

fetched live from OpenAlex

This paper proposes a new chase based multiuser detection scheme for MIMO-CDMA systems. The proposed approach provides performance gain by concentrating on improving the detection accuracy of the weakest symbol. Compared to the layered space-time multiuser detector (LAST-MUD), the proposed scheme can achieve substantial performance improvement, especially, when the number of transmit antennas is equal to the number of receive antennas. The comparison between our scheme and another chase based scheme, the B-Chase detector, which was originally proposed for improving the performance of the vertical Bell Laboratories layered space-time (V-BLAST) system, is also presented. The problem existing in the B-Chase detector is the criterion for selecting the weakest symbol. In our scheme, a more reasonable selection criterion is proposed. We show that the proposed scheme has less complexity than the B-Chase detector but with the tendency of achieving better performance at high SNR.

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)0.001
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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.885
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0040.000
Research integrity0.0010.001
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 head0.048
GPT teacher head0.303
Teacher spread0.256 · 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