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Record W2115173428 · doi:10.1109/glocom.1998.775868

Performance of new adaptive combined space-time receiver for multiuser interference rejection in multipath slow fading CDMA channels

2002· article· en· W2115173428 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
KeywordsMultipath propagationCode division multiple accessFadingInterference (communication)Computer scienceElectronic engineeringMultipath interferenceSingle antenna interference cancellationMatched filterMultiuser detectionTelecommunicationsDetectorEngineeringChannel (broadcasting)

Abstract

fetched live from OpenAlex

A new adaptive combined array and multiuser detector (spatial and temporal) structure for direct sequence code division multiple access (DS-CDMA) has been proposed by Legnain, Falconer and Sheikh (see CCECE'98) to combat cochannel interference and increase the capacity for cellular CDMA. The structure uses a L-sensor (element) linear array. Each element is followed by a chip matched filter (CMF) and a fractionally spaced adaptive equalizer. The proposed structures combine the multipath component as well as suppressing interference. It outperforms the conventional receiver and the structures proposed by Abdulrahman, Sheikh and Falconer (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 capacity, near far resistance, multipath combining. The proposed structure can also operate in heavy traffic channels with many users having the same angle of arrival (AOA) as the desired user when the conventional array can not. The focus in this paper is the cochannel interference rejection and multipath combined capabilities of this structure. Analysis of the optimum tap weights and the minimum mean square error in multipath fading channels are provided, and comparison between this structure and the structures propose by Abdulrahman et al. and by Miller is 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: Empirical · Consensus signal: none
Teacher disagreement score0.818
Threshold uncertainty score0.598

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 head0.067
GPT teacher head0.276
Teacher spread0.209 · 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
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

Citations6
Published2002
Admission routes1
Has abstractyes

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