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Record W1978954881 · doi:10.1109/tvt.2012.2203327

Joint Space-Time Parameter Estimation for Multicarrier CDMA Systems

2012· article· en· W1978954881 on OpenAlexaff
Jin He, Muneer Ahmad, M.N.S. Swamy

Bibliographic record

VenueIEEE Transactions on Vehicular Technology · 2012
Typearticle
Languageen
FieldComputer Science
TopicDirection-of-Arrival Estimation Techniques
Canadian institutionsConcordia University
Fundersnot available
KeywordsSmoothingSubcarrierMultipath propagationCovariance matrixCode division multiple accessAlgorithmComputer scienceDecorrelationJoint (building)Electronic engineeringOrthogonal frequency-division multiplexingEngineeringTelecommunications

Abstract

fetched live from OpenAlex

This paper addresses the problem of joint space-time parameter estimation for multicarrier code-division multiple-access (MC-CDMA) systems in the presence of multipath propagation. We propose a novel preprocessing technique termed as subcarrier smoothing (SCS) to decorrelate the coherency of the multipath signals. The basic idea behind the SCS is to restore the rank of the signal correlation matrix by averaging the space-time covariance matrices associated with each subcarrier. Unlike the other existing preprocessing techniques, such as spatial smoothing, the SCS preprocessing is not limited to any specific array geometry and does not decrease the array aperture.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.685
Threshold uncertainty score0.854

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.018
GPT teacher head0.258
Teacher spread0.240 · 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 designBench or experimental
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

Citations18
Published2012
Admission routes1
Has abstractyes

Explore more

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