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Record W2125987894 · doi:10.1109/ccece.1998.682774

New adaptive combined space-time receiver for multiuser interference rejection in synchronous CDMA systems

2002· article· en· W2125987894 on OpenAlexaff
A.M. Legnain, D.D. Falconer, A.U.H. Sheikh

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicWireless Communication Networks Research
Canadian institutionsCarleton University
Fundersnot available
KeywordsCode division multiple accessSingle antenna interference cancellationComputer scienceInterference (communication)Electronic engineeringChannel (broadcasting)Multiuser detectionSpread spectrumMatched filterFilter (signal processing)ChipDetectorTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

New adaptive combined array and multiuser detector (spatial and temporal) structure for direct sequence code division multiple access (DS-CDMA) is proposed to combat co-channel interference and increase the capacity for cellular CDMA. The structure uses an L-sensor (element) linear array. Each element is followed by a chip matched filter (CMF) and a fractionally-spaced adaptive equalizer. The proposed structure outperforms the conventional receiver and the structures proposed by Abdulrahman, Sheikh and Falconer (see IEEE JSAC, vol.12, no.4, p.698-706, 1994) and by Miller (see IEEE Tran. Comm., vol.43, no.2/3/4, p.1746-55, 1995) in terms of the capacity and near far resistance. The proposed structure can also operate in heavy traffic channels with many users having the same angle of arrival (AOA) as the desired user, while the conventional array can not. Analysis of the optimum weights and the minimum mean square error in the synchronous DS-CDMA channel is provided, and comparison between this structure and the structures proposed by Abdulrahman et al. and by Miller are also provided.

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 score0.929
Threshold uncertainty score0.595

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 science0.0010.000
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 head0.043
GPT teacher head0.264
Teacher spread0.222 · 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

Citations6
Published2002
Admission routes1
Has abstractyes

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