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Record W1965129975 · doi:10.1109/tcsi.2013.2285892

A Compact Architecture for Simulation of Spatio-Temporally Correlated MIMO Fading Channels

2014· article· en· W1965129975 on OpenAlexaff
Amirhossein Alimohammad, Saeed Fouladi Fard

Bibliographic record

VenueIEEE Transactions on Circuits and Systems I Regular Papers · 2014
Typearticle
Languageen
FieldEngineering
TopicAdvanced MIMO Systems Optimization
Canadian institutionsSierra Wireless (Canada)
Fundersnot available
KeywordsFadingBasebandMIMOComputer scienceChannel (broadcasting)Field-programmable gate arrayWirelessElectronic engineeringSoftware-defined radioPrecodingEngineeringComputer networkTelecommunicationsEmbedded systemBandwidth (computing)

Abstract

fetched live from OpenAlex

Radio channel impairments have a dramatic impact on the performance of wireless communication systems and hence, utilizing realistic radio channel models is crucial for the accurate performance validation of emerging wireless systems. However, faithful radio propagation channel models are computationally intensive for software-based simulations, especially for multiple antenna systems. This article presents the design and implementation of a multiple-input multiple-output (MIMO) baseband fading channel simulator on a field-programmable gate array (FPGA). In addition to the well-known independent and identically distributed channel model, the simulator supports three spatio-temporally correlated fading channel models which are commonly used for performance analysis. The implemented MIMO fading channel simulator is compact enough to be integrated with the baseband design under test on the same FPGA for accelerated performance validations.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.986
Threshold uncertainty score0.899

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 science0.0000.000
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 head0.014
GPT teacher head0.223
Teacher spread0.208 · 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

Citations10
Published2014
Admission routes1
Has abstractyes

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