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Record W1516042150 · doi:10.1109/milcom.2005.1605828

Performance of a Decorrelator Based Successive Interference Cancellation Multiuser Receiver for Asynchronous Multirate DS-CDMA Systems

2006· article· en· W1516042150 on OpenAlex
Bin Yang, Florence Danilo-Lemoine

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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsCarleton University
Fundersnot available
KeywordsSingle antenna interference cancellationAsynchronous communicationCode division multiple accessComputer scienceMultipath propagationMultiuser detectionRayleigh fadingDecorrelationProcess gainChannel (broadcasting)Interference (communication)Electronic engineeringMatched filterMultipath interferenceFadingSpread spectrumAlgorithmTelecommunicationsEngineeringDetector

Abstract

fetched live from OpenAlex

In this paper we investigate the performance of a decorrelator based successive interference cancellation (DBSIC) multirate DS CDMA multiuser receiver over multipath Rayleigh fading channels with both perfect and imperfect channel side information. Variable processing gain (VPG) with various numbers of data rate classes is considered. The performance of DBSIC is presented using an analytical approach and simulations, and its improvement over other commonly-used suboptimum detection schemes such as the decorrelating, minimum mean square (MMSE), SIC, parallel interference cancellation (PIC) and decorrelating decision feedback (DF) receivers is demonstrated. In the case of imperfect channel estimates, it can be observed while all the receivers suffer degradation in performance, DBSIC still outperforms the other detection schemes

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.752
Threshold uncertainty score0.586

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 communication0.0000.001
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 head0.019
GPT teacher head0.263
Teacher spread0.244 · 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

Quick stats

Citations7
Published2006
Admission routes1
Has abstractyes

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