MétaCan
Menu
Back to cohort
Record W2099054847 · doi:10.1109/icc.1999.765407

Adaptive multistage parallel interference cancellation for CDMA

2003· article· en· W2099054847 on OpenAlexaffabout
Guoqiang Xue, Jianfeng Weng, Tho Le‐Ngoc, Sofiène Tahar

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsConcordia University
Fundersnot available
KeywordsSingle antenna interference cancellationAdditive white Gaussian noiseComputer scienceFadingInterference (communication)Multipath propagationCode division multiple accessMultiuser detectionLeast mean squares filterAlgorithmWeightingChannel (broadcasting)Electronic engineeringAdaptive filterTelecommunicationsEngineeringPhysics

Abstract

fetched live from OpenAlex

An adaptive multistage parallel interference cancellation technique based on the partial interference cancellation (IC) approach of Divsalar and Simon (see Tech. Rep. 95-21, JPL Publication, 1995) was proposed by Xue, Weng, Le-Ngoc and Tahar (see Proc. of VTC'SS, Vancouver, Canada, 1999) for multipath fading channels. In this paper, the proposed technique is applied to develop a receiver structure in an AWGN environment. Unlike the scheme of Divsalar et al., the weighting factors in this proposed scheme are derived by minimizing the mean-square error between the received signal and its estimate through an LMS algorithm. Neither training sequence nor pilot signal is needed. The complexity of the proposed adaptive multistage PIC structure is much lower than that of linear multiuser detectors. Simulation results show the superior performance of the proposed receiver structure over an AWGN channel and in various conditions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.068
GPT teacher head0.316
Teacher spread0.248 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations33
Published2003
Admission routes2
Has abstractyes

Explore more

Same topicWireless Communication Networks ResearchFrench-language works237,207