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Spatial Multipath Resolution for MIMO Systems

2011· article· en· W2028741922 on OpenAlexaff
Damith Senaratne, Chintha Tellambura

Bibliographic record

VenueIEEE Wireless Communications Letters · 2011
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsRake receiverMIMOMultipath propagationComputer scienceBeamformingNon-line-of-sight propagationTransmitterMulti-user MIMOSpatial multiplexingElectronic engineeringMultipath interference3G MIMOTransmission (telecommunications)Channel (broadcasting)WirelessTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

Wireless multiple-input multiple-output (MIMO) terminals with a large number of antennas are becoming a reality, increasing the spatial spatial degree of freedoms (DoFs) available at the terminals. This paper proposes exploiting the excess spatial DoFs available at the receiver for spatial multipath resolution. A rake-receiver structure, whose fingers are implemented through spatial signal processing, is introduced for that. The joint computation of beamforming matrices for the transmitter and each receiver finger to achieve single-carrier eigenmode transmission over a multipath MIMO channel is developed. Numerical results on the error performance are provided for a practical multipath MIMO channel based on the IEEE 802.15.3c NLOS (CM4) model.

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 score0.985
Threshold uncertainty score0.533

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 communication0.0000.000
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 head0.050
GPT teacher head0.236
Teacher spread0.186 · 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

Citations7
Published2011
Admission routes1
Has abstractyes

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